WO2017070497A1 - Methods and compositions for use of driver mutations in cll - Google Patents

Abstract

Applicants identified (44) recurrently mutated genes and (11) recurrent somatic copy number variations (CNV) through whole-exome sequencing of 538 chronic lymphocytic leukemia (CLL) and matched germline DNA samples, 278 of which were collected in a prospective clinical trial. These include previously unrecognized cancer drivers (RPS15, IKZF3) and collectively identify RNA processing and export, MYC activity and MAPK signaling as central pathways involved in CLL. Clonality analysis of this large dataset further enabled reconstruction of temporal relationships between driver events. Direct comparison between matched pretreatment and relapse samples from 59 patients demonstrated highly frequent clonal evolution. The discovery of novel cancer genes and the network of relationships between the driver events and their impact on disease relapse and clinical outcome provide novel treatment options.

Description

METHODS AND COMPOSITIONS FOR USE OF DRIVER MUTATIONS IN CLL

RELATED APPLICATIONS AND INCORPORATION BY REFERENCE

[0001] This application claims priority and benefit of U.S. provisional application serial number 62/244,533, filed October 21, 2015.

[0002] Reference is made to U.S. provisional patent application Serial No. 62/,053,697 filed September 22, 2014 and U.S. provisional patent application Serial No. 62/181,715, filed June 18, 2015. Reference is also made to International patent application serial numbers PCT/US2012/068633, filed December 7, 2012 and PCT/US2015/051340, filed September 22, 2015.

[0003] The foregoing applications, and all documents cited therein or during their prosecution ("appln cited documents") and all documents cited or referenced in the appln cited documents, and all documents cited or referenced herein ("herein cited documents"), and all documents cited or referenced in herein cited documents, together with any manufacturer's instructions, descriptions, product specifications, and product sheets for any products mentioned herein or in any document incorporated by reference herein, are hereby incorporated herein by reference, and may be employed in the practice of the invention. More specifically, all referenced documents are incorporated by reference to the same extent as if each individual document was specifically and individually indicated to be incorporated by reference.

FEDERAL FUNDING LEGEND

[0004] This invention was made with government support under grant numbers CA182461 , CA184922, and CA180861 awarded by the National Institutes of Health. The government has certain rights in the invention.

FIELD OF THE INVENTION

[0005] The present invention provides methods for treatment and prognosis of chronic lymphocytic leukemia (CLL) using novel cancer driver mutations.

B ACKGROUND OF THE INVENTION

[0006] In recent years, unbiased massively parallel sequencing of whole exomes (WES) in chronic lymphocytic leukemia (CLL) has yielded fresh insights into the genetic basis of this disease^1"4. Two important constraints have limited previous WES analyses. First, cohort size is critical for statistical inference of cancer drivers⁵, and prior CLL WES series³ had a power of only 68%, 23% and 7%, to detect putative CLL genes mutated in 5%, 3% and 2% of patients, respectively (www.tumorportal.org/power)⁵. Limited cohort size has also curtailed the ability to effectively learn the relationships between CLL driver events, such as their co-occurrence and the temporal order of their acquisition. Second, the composition of the cohort of prior WES studies has limited the ability to accurately determine the impact of drivers and clonal heterogeneity on clinical outcome since they included samples collected at variable times from subjects exposed to a variety of therapies. Understanding the genetic alterations that drive tumorigenesis and how they evolve over the course of disease and therapy are central questions in cancer biology. Thus, identifying novel cancer drivers is necessary to improve treatment and diagnosis of CLL.

[0007] Citation or identification of any document in this application is not an admission that such document is available as prior art to the present invention.

SUMMARY OF THE INVENTION

[0008] It is an objective of the present invention to provide novel cancer driver alterations for use in improved treatment of patients suffering from CLL. Applicants identified 44 recurrently mutated genes and 11 recurrent somatic copy number variations through whole-e ome sequencing of 538 chronic lymphocytic leukemia (CLL) and matched germline DNA samples, 278 of which were collected in a prospective clinical trial. These include previously unrecognized cancer drivers (RPS15, IKZF3) and collectively identify RNA processing and export, MYC activity and MAPK signaling as central pathways involved in CLL. Clonality analysis of this large dataset further enabled reconstruction of temporal relationships between driver events. Direct comparison between matched pre-treatment and relapse samples from 59 patients demonstrated highly frequent clonal evolution.

[0009] Specifically, Applicants analyzed WES data from 538 CLLs, including 278 pre- treatment samples collected from subjects enrolled on the phase III CLL8 study¹³. This trial established the combination of fludarabine (F), cyclophosphamide (C) and rituximab (R) as the current standard-of-care first-line treatment for patients of good physical fitness, with a median of >6 years of follow-up. Applicants discovered novel CLL cancer genes, performed a comprehensive genetic characterization of samples from patients prior to exposure to a uniform and contemporary treatment, and uncovered features contributing to relapse from this therapy.

[0010] In a first aspect the present invention provides for a method of treating chronic lymphocytic leukemia (CLL) in a subject in need thereof comprising identifying the presence of gene mutations and somatic copy number variations (CNV) in a genomic DNA sample obtained from the subject, wherein the mutated genes and somatic copy number variations (CNV) comprise del(13q), SF3B1, A TM, del(llq), tril2, TP53, NOTCH 1, POT1, amp(2p), del(17p), CHD2, XPOl, RPS15, BIRC3, BRAF, IGLL5, d l(8p), MGA, MYD88, del(6q21), EGR2, FBXW7, ampfSq), DDX3X, KRAS, BCOR, IKZF3, MAP2K1, ZMYM3, IRF4, SAMHD1, BAZ2A, CARD! I, FUBP1, HIST1H1E, MED12, NRAS, NXF1, del (18p), DYRK1A, PTPNll, del(20p), ELF 4, TRAF2, XP04, tril9, BRCC3, Erf SRI, FAM50A, TRAF3, ASXL!, CHEK2, GNB1, HISTIHIB, and PIMI, wherein the subject is treated if the presence of a mutated gene and/or somatic copy number variation (CNV) is identified. The patient may have stage 0, 1, II, III, or IV CLL. Preferably, the method is performed before a patient has symptoms. The method may be performed before treatment, during treatment, or after treatment. The method may be performed when the patient is in remission. The presence of mutations in NRAS, KRAS, BRAF, and/or MAP2K1 may indicate treating with an inhibitor of the MAPK-ERK pathway. The mutation in BRjiF may be a mutation that is not the canonical V600E mutation. In this instance the treatment may include a MEK inhibitor and would not indicate the use of a BRAF inhibitor. The presence of mutations in RPS15 may indicate an adverse outcome and the subject is treated with an alternative treatment regimen. The presence of mutations in IKZF3 may indicate an adverse outcome and the subject is treated with an alternative treatment regimen. The mutation in IKZF3 may be an L162R substitution. The presence of mutations in delflSq), MYD88, and/ or ( 7/7/2 may indicate decreased clinical aggressiveness. The presence of mutations in TP53, SF3B1 and/or XPOl may indicate shorter progression-free survival (PFS) and overall survival (OS).

[0011] The genomic DNA sample may be obtained prior to treatment by any methods known in the art. Not being bound by a theory, obtaining the sample prior to treatment allows the detection of the mutations or alterations in copy number of the present invention in clonal and subclonal populations of cells present in a cancer cell fraction (CCF) before treatment. Identification of mutations or alterations in copy number can be used to predict resistence to a treatment and efficacy of a treatment. [0012] The method may further comprising determining mutations in IGHV, wherein the presence of unmutated IGHV indicates increased clinical aggressiveness and the presence of mutated IGHV indicates decreased clinical aggressiveness.

[0013] In another aspect, the present invention provides for a method of determining whether a subject having chronic lymphocytic leukemia (CLL) would derive a clinical benefit of early treatment comprising determining the presence of gene mutations and somatic copy number variations (CNV) in a genomic DNA sample obtained from the subject, wherein the mutated genes and somatic copy number variations (CNV) comprise del(13q), SF3B1, ATM, del(llq), trill, TPS 3, NOTCH 1, POT1, amp(2p), del(17p), CHD2, XPOl, RPS15, BIRC3, BRAF, IGLL5, del(8p), MGA, MYD88, del(6q21), EGR2, FBXW7, amp(8q), DDX3X, KRAS, BCOIi IKZF3, MAP2K1, 7MYM3, IRF4, SAMHD!, BAZ2A, CARDIl, FUBP1, HISTIH!E, MED 12, NRAS, NXFI, del (18p), DYRK1A, PTPNll, delQOp), ELF 4, TRAF2, XP04, in 19. BRCC3, EWSR1, FAM50A, TRAF3, ASXL1, CHEK2, GNBl, HISTIHIB, and P!Ml, wherein the presence of a mutated gene and/or somatic copy number variation (CNV) indicates that the subject would derive a clinical benefit of early treatment,

[0014] In another aspect, the present invention provides for a method of predicting survivability of a subject having chronic lymphocytic leukemia (CLL) comprising determining the presence of gene mutations and somatic copy number variations (CN V) in a genomic DN A sample obtained from the subject, wherein the mutated genes and somatic copy number variations (CNV) co pnsQdeI(I3q), SF3B1, ATM, del(l lq), trill, TP53, NOTCH!, POT1, amp(2p), del(17p), CIID2, XPOl, RPS15, BIRC3, BRAF, IGLL5, del(8p), MGA, MYD88, del(6q21), EGR2, FBXW7, amp(8q), DDX3X, KRAS, BCOR, IKZF3, MAP2K1, 7MYM3, IRF4, SAMHD!, BAZ2A, CARDIl, FlJBPl, HISTIHIE, MED12, NRAS, NXFI, del (18p), DYRK1A, PTPNll, del(20p), ELF 4, TRAF2, XP04, tril9, BRCC3, EWSRl, FAM50A, TRAP 3, ASXL1, CHEK2, GNBl, HISTIHIB, and PIM1, wherein the presence of a mutated gene and/or somatic copy number variation (CNV) indicates that the subject is less likely to survive.

[0015] In another aspect, the present invention provides for a method of identifying a candidate subject for a clinical trial for a treatment protocol for chronic lymphocytic leukemia (CLL) comprising determining the presence of gene mutations and somatic copy number variations (CNV) in a genomic DNA sample obtained from the subject, wherein the mutated genes and somatic copy number variations (CNV) comprise del(13q), SF3B1, ATM, del/1 Iq), trill, TP 53, NOTCH!, POT I, amp(lp), deI(T7p), CHD2, XPOl, RPS15, B1RC3, BRAF, IGLL5, del(8p), MGA, MYD88, deMqll), EGR2, FBXW7, mpfSq), DDX3X, KRAS, BCOR, IKZF3, MAP1K1, ZMYM3, IRF4, SAMHD1, BAZ1A, CARDll, FUBPl, H1ST1H1E, MED 12, NRAS, NXFI, del (18p), DYRKIA, PTPNII, del(20p), ELF 4, TRAF2, XP04, tnl9, BRCC3, EWSRI, FAS 150 1. TRAF3, ASXLl, CHEK2, GNB1, HISTIHIB, and PIML wherein the presence of a mutated gene and/or somatic copy number variation (CNV) indicates that the subject is a candidate for the clinical trial.

[0016] In another aspect, the present invention provides for a method of detecting chronic lymphocytic leukemia (CLL) in a subject comprising determining the presence of gene mutations and somatic copy number variations (CNV) in a genomic DNA sample obtained from the subject, wherein the mutated genes and somatic copy number variations (CNV) comprised?/^), SF3B1, Am, del/1 Iq), tnl2, TP 53, NOTCH 1, POT1, amp(2p), del(17p), CHD2, XPOl, RPSI5, BIRC3, BRAF, IGLL5, del(8p), MGA, MYD88, del(6q2l), EGR2, FBXW7, αηιρβ , DDX3X, KRAS, BCOR, IKZF3, MAP2K1, ZMYM3, IRF4, SAMHD1, BAZ2A, CARDll, FUBPl, HISTIHIE, MED 12, NRAS, NXFI, del (18p), DYRKIA, PTPNII, del (20p), ELF 4, TRAF2, XP04, tril9, BRCC3, EWSRI, FAM50A, TRAF3, ASXI !. CHEK2, GNB1, HISTIHIB, and P!Ml , whereby the presence of one or more mutations and/or CNV indicates that the subject has a greater than 90% probability of having CLL.

[0017] In another aspect, the present invention provides for a method of identifying a subject at elevated risk of having CLL with rapid disease progression comprising: (a) analyzing genomic DNA in a sample obtained from a subject having or suspected of having chronic lymphocytic leukemia (CLL) for the presence of gene mutations and somatic copy number variations (CNV), wherein the mutated genes and somatic copy number variations (CNV) comprise£fe/{73¾), .SV-^'.?/>7, A TM, del(llq), tril2, TP53, NOTCH 1, POT I, amp(lp), del(l7p), CHDl, XPOl, RPS15, BIRC3, BRAF, IGLL5, del(8p), MGA, MYD88, deUfiqll), EGRl, FBXW7, amp(8q), DDX3X, KRAS, BCOR, IKZF3, MA 2 h i, ZMYM3, TRF4, SAMHDl, BAZIA, CARDll, FUBPl, HISTIHIE, MED 12. NRAS, NXFI, del (I8p), DYRKIA, PTPNII, del(20p), ELF 4, TRAF2, XP04, tril9, BRCC3, EWSRI, FAM50A, TRAF3, ASXLl, CHEK2, GNBl, HISTIHIB, and PIM1; (b)determining whether the mutations and/or somatic copy number variations are clonal or subclonal, and (c) identifying the subject as a subject at elevated risk of having CLL with rapid disease progression if at least one mutation and/or somatic copy number variation is subdorsal. The method may further comprise treating a subject for CLL identified as a subject at elevated risk of having CLL with rapid disease progression.

[0018] Any of the methods may include determining mutations in more than one risk allele. Any of the methods may be repeated every month, 2 months, 3 months, 4 months, five months, 6 months 8 months, or one year or at any time where there is a change in clinical status. The genomic DNA sample may be obtained from peripheral blood, bone marrow, or lymph node tissue. The genomic DNA may be analyzed using whole genome sequencing (WGS), whole exome sequencing (WES), single nucleotide polymorphism (SNP) analysis, deep sequencing, targeted gene sequencing, hybridization to an array, or any combination thereof. Clonal or subdorsal mutations, CNV's and/or populations of cells may be detected using whole genome sequencing (WGS), whole exome sequencing (WES), single nucleotide polymorphism (SNP) analysis, deep sequencing, targeted gene sequencing, hybridization to an array, or any combination thereof The gene mutation may be a missense mutation, frameshift indel, inframe indel, splice site mutation, or nonsense mutation.

[0019] Accordingly, it is an object of the invention to not encompass within the invention any previously known product, process of making the product, or method of using the product such that Applicants reserve the right and hereby disclose a disclaimer of any previously known product, process, or method. It is further noted that the invention does not intend to encompass within the scope of the invention any product, process, or making of the product or method of using the product, which does not meet the written description and enablement requirements of the USPTO (35 I. S C. § 112, first paragraph) or the EPO (Article 83 of the EPC), such that Applicants reserve the right and hereby disclose a disclaimer of any previously described product, process of making the product, or method of using the product.

[0020] It is noted that in this disclosure and particularly in the claims and/or paragraphs, terms such as "comprises", "comprised", "comprising" and the like can have the meaning attributed to it in U. S. Patent law; e.g., they can mean "includes", "included", "including", and the like; and that terms such as "consisting essentially of and "consists essentially of have the meaning ascribed to them in U.S. Patent law, e.g., they allow for elements not explicitly recited, but exclude elements that are found in the prior art or that affect a basic or novel characteristic of the invention. Nothing herein is intended as a promise. [0021] These and other embodiments are disclosed or are obvious from and encompassed by, the following Detailed Description.

BRIEF DESCRIPTION OF THE DRAWINGS

[0022] The patent or application file contains at least one drawing executed in color. Copies of this patent or patent application publication with color drawing(s) will be provided by the Office upon request and payment of the necessary fee.

[0023] The following detailed description, given by way of example, but not intended to limit the invention solely to the specific embodiments described, may best be understood in conjunction with the accompanying drawings.

[0024] Figure 1 : The landscape of putative driver gene mutations and recurrent somatic copy number variations in CLL. Somatic mutation information is shown across the 55 putative driver genes and recurrent sCNVs (rows) for 538 primary patient samples (from CLL8 [green], Spanish ICGC [red], DFCI/Broad [blue]) that underwent WES (columns). Blue labels- recurrent sCNVs; Bold labels- putative CLL cancer genes previously identified in Landau et al.³); asterisked labels- additional cancer genes identified in this study. Samples were annotated for IGHV status (black-mutated, white-unmutated; red-unknown), and for exposure to therapy prior to sampling (black-prior therapy; white - no prior therapy; red-unknown prior treatment status).

[0025] Figure 2: Selected novel putative driver gene maps. Individual gene mutation maps for select putative drivers, showing mutation subtype (e.g., missense), position and evidence of mutational hotspots, based on COSMIC database information (remaining gene maps shown in Extended Data Fig. 4).

[0026] Figure 3A-3B: Inferred evolutionary history of CLL. A. The proportion in which a recurrent driver is found as clonal or subclonal across the 538 samples is provided (top), along with the individual cancer cell fraction (CCF) values for each sample affected by a driver (tested for each driver with a Fisher's exact test, comparing to the cumulative proportions of clonal and subclonal drivers excluding the driver evaluated). Median CCF values are shown (bottom, bars represent the median and IQR for each driver), B. Temporally direct edges are drawn when two drivers are found in the same sample, one in clonal and the other in subclonal frequency. These edges are used to infer the temporal sequences in CLL evolution, leading from early, through intermediate to late drivers. Note that only driver pairs with at least 5 connecting edges were tested for statistical significance and only drivers connected by at least one statistically significant edge are displayed (see Methods, and Supplementary Table 7).

[0027] Figure 4A-4B. Associations of CLL drivers with cli ical outcome. A, Kaplan- Meier analysis (with logrank values) for putative drivers with associated impact on progression free survival (PFS) or overall survival (OS) in the cohort of 278 patients that were treated as part of the CLLS trial. For candidate CLL genes tested here for the first time regarding impact on outcome, a Bonferroni Q value is also shown. B. Presence of a subclonal driver is associated with shorter PFS, in both the FC and FCR arms, and a trend towards shorter OS.

[0028] Figure 5A-5C: Matched pre-treatment and relapse samples reveal patterns of clo al evolution in relation to therapy, A. The number and proportion of the patterns of clonal evolution of CLLs studied at pre-treatment and at relapse. B. Selected plots of 2D clustering of pre-treatment and relapse cancer cell fraction (CCF) demonstrating clonal stability of tri(12) (CLL case: GCLL115), concordant increase in CCFs of TP53 and del(ll^) (GCLL27), clonal shifts in ATM sSNVs in a sample with clonally stable monoallelic deletion of A TM (GCLL307). Red coloring was added when greater than half of the CCF probability indicated >0.1 increase in CCF at relapse. C. Clonal evolution of CLL drivers. Left panel - for each driver with at least 4 instances detected across the 59 CLLs, the proportion of instances where the CCF increased (red), decreased (blue) or remained stable (grey) over time is shown (see Methods for details of the statistical analysis). The driver events were distributed to three main groups: predominately stable events (top); predominately increasing CCF (middle), and all other patterns (bottom). Right panel - Comparison (modal CCF with 95%CI) between pre-treatment and relapse samples for select CLL drivers (see Extended Data Fig. 10 for the remaining driver events from the cohort of 59 CLLs).

[0029] Extended Data Figure I : Candidate CLL cancer genes discovered in the combined cohort of 538 primary CLL samples. Significantly mutated genes identified in 538 primary CLL. Top panel: the rate of coding mutations (mutations per megabase) per sample. Center panel: Detection of individual gene found to be mutated (sSNVs or sINDELs) in each of the 538 patient samples (columns), color-coded by type of mutation. Only one mutation per gene is shown if multiple mutations from the same gene were found in a sample. Right panel: Q- values (red: Q<0.1; purple dashed: Q<0.05) and Hugo Symbol gene identification. New candidate CLL genes are marked with asterisks (*) Left panel: The percentages of samples affected with mutations (sSNVs and sINDELs) in each gene. Bottom panel: plots showing allelic fractions and the spectrum of mutations (sSNVs and sINDELs) for each sample.

[0030] Extended Data Figure 2: Cellular networks and processes affected by putative CLL drivers. Putative CLL cancer genes cluster in pathways that are central to CLL biology such as Notch signaling, inflammatory response and B cell receptor signaling. In addition, proteins that participate in central cellular processes such as DNA damage repair, chromatin modification and mRNA processing, export and translation are also recurrently affected. Boxed in yellow— new CLL subpathways highlighted by the current driver discovery effort. Red circles- putative driver genes previously identified³ , purple circles- newly identified in the current study,

[0031] Extended Data Figure 3A-3B: RNAseq expression data for candidate CLL genes and targeted candidate driver validation. A. Matched RNAseq and WES data were available for 156 CLLs (103 CLLs previously reported in Landau et al.³ and 53 CLLs from the ICGC studies¹). From the WES of these 156 cases, Applicants identified 318 driver mutations (sSNVs and sINDELs). For each site, Applicants quantified the number of alternate reads corresponding to the somatic mutation in matched RNAseq data. Applicants subsequently counted the number of instances in which a mutation was detected {'detected') and compared it to the number of instances in which mutation detection had >90% power based on the allelic fraction in the WES and the read depth in the RNAseq data powered'). Overall, Applicants detected 78.1% of putative CLL gene mutations at sites that had >90% power for detection in RNAseq data B. Targeted orthogonal validation (Access Array System, Fluidigm) was performed for 71 mutations (sSNVs and sINDELs) in putative CLL genes, affecting 47 CLLs from the CLLS cohort (selected based on sample availability). With a mean depth of coverage of 7472X, 65 of the 71 mutations (91.55%) validated, with a higher variant allele fraction compared with normal sample DNA (binomial P <0.01).

[0032] Extended Data Figure 4A-4V: Gene mutation maps for candidate CLL genes. Individual gene mutation maps are shown for all newly identified candidate CLL cancer genes not included in Fig. 2, The plots show mutation subtype (e.g., missense, nonsense etc) and position along the gene. [0033] Extended Data Figure 5: CLL copy number profiles. Copy number profile across 538 CLLs detected from WES data from primary samples (see Methods).

[0034] Extended Data Figure 6A-6D: Annotation of drivers based on clinical characteristics and co-occurrence patterns. A, Putative drivers affecting greater than 10 patients were assessed for enrichment in IGHV mutated vs. unmutated CLL subtype (Fisher's exact test, magenta line denotes P = 0.05). B. Putative drivers affecting greater than 10 patients were assessed for enrichment in samples that received therapy prior to sampling (Fisher's exact test). Putative drivers affecting greater than 10 patients were tested for co-occurrence. Significantly high (C) or low (D) co-occurrences are shown (Q<0. \, Fisher's exact test with BH FDR, after accounting for pri or therapy and IGHV mutation status, see Methods).

[0035] Extended Data Figure 7: Mutation spectrum analysis, clonal vs. subclonal sSNVs, The spectrum of mutation is shown for the clonal and subclonal subsets of coding somatic sSNVs across WES of 538 samples. The rate is calculated by dividing the number of trinucleotides with the specified sSNVs by the covered territory containing the specified trinucleotide. Both clonal and subclonal sSNVs were similarly dominated by C>T transitions at C*pG sites. Thus, this mutational process that was previously associated with aging³⁹, not only predates oncogenic transformation (since clonal mutations will be highly enriched in mutations that precede the malignant transformation⁴⁰), but also is the dominant mechanism of malignant diversification after transformation in CLL.

[0036] Extended Data Figure 8: The CLL driver landscape in the CLL8 cohort. Somatic mutation information shown across the 55 candidate CLL cancer genes and recurrent sCNVs (rows) for 278 CLL samples collected from patients enrolled on the CLLS clinical trial primary that underwent WES (columns). Recurrent sCNA labels are listed in blue, and candidate CLL cancer genes are listed in bold if previously identified in Landau et &\. and with an asterisk (*) if newly identified in the current study.

[0037] Extended Data Figure 9: CLLS patient cohort clinical outcome (from 278 patients) information by CLL cancer gene. Kaplan-Meier analysis (with logrank P values) for putative drivers not associated with significant impact on progression free survival (PFS) or overall survival (OS) in the cohort of 278 patients that were treated as part of the CLLS trial . For candidate CLL genes tested here for the first time regarding impact on outcome, a Bonferroni P value is also shown. [0038] Extended Data Figure 10: Comparison of pre-treatment and relapse cancer cell fraction (CCF) for non-silent mutations in candidate CLL genes across 59 CLLs. For each CLL gene mutated across the 59 CLLs that were sampled longitudinally, the modal CCF is compared between the pre-treatment and relapse samples. CCF increases (red), decreases (blue) or stable (grey) over time are shown (in addition to CLL genes shown in Figure 6). A significant change in CCF over time (red or blue) was determined if the 95%CI of the CCF in the pre-treatment and relapse samples did not overlap.

DETAILED DESCRIPTION OF THE INVENTION

[0039] The term "therapeutic effect" refers to some extent of relief of one or more of the symptoms of a disorder (e.g., a neoplasia or tumor) or its associated pathology. "Therapeutically effective amount" as used herein refers to an amount of an agent which is effective, upon single or multiple dose administration to the cell or subject, in prolonging the survivability of the patient with such a disorder, reducing one or more signs or symptoms of the disorder, preventing or delaying, and the like beyond that expected in the absence of such treatment. "Therapeutically effective amount" is intended to qualify the amount required to achieve a therapeutic effect. A physician or veterinarian having ordinary skill in the art can readily determine and prescribe the "therapeutically effective amount" (e.g., ED50) of the pharmaceutical composition required. For example, the physician or veterinarian could start doses of the compounds of the invention employed in a pharmaceutical composition at levels lower than that required in order to achieve the desired therapeutic effect and gradually increase the dosage until the desired effect is achieved.

[0040] The term "clinical aggressiveness" refers to the average aggressiveness of a cancer. Increased clinical aggressiveness refers to a cancer that is more aggressive as compared to the average.

[0041] A "CLL driver" is any mutation, chromosomal abnormality, or altered gene expression, that contributes to the etiology, progression, severity, aggressiveness, or prognosis of CLL. In some aspects, a CLL driver is a mutation that provides a selectable fitness advantage to a CLL cell and facilitates its clonal expansion in the population. CLL driver may be used interchangeably with CLL driver event and CLL driver mutation. CLL driver mutations occur in genes, genetic loci, or chromosomal regions which may be referred to herein interchangeably as CLL risk alleles, CLL alleles, CLL risk genes, CLL genes, CLL-associated genes and the like.

[0042] In one embodiment, staging of chronic lymphocytic leukemia (CLL) is used to determine treatment of a subject in need thereof. Any CLL staging system may be used. The Rai staging system and the Binet classification are exemplary systems that may be used in the present invention (Rai KR, et al.: Clinical staging of chronic lymphocytic leukemia. Blood 46 (2): 219-34, 1975; Binet JL, et al. : A new prognostic classification of chronic lymphocytic leukemia derived from a multivariate survival analysis. Cancer 48 (1): 198-206, 1981). Additionally, a National Cancer institute (NCI)-sponsored working group has formulated standardized guidelines for criteria related to eligibility, response, and toxic effects to be used in future clinical trials in CLL (Hallek M, et al. : Guidelines for the diagnosis and treatment of chronic lymphocytic leukemia: a report from the International Workshop on Chronic Lymphocytic Leukemia updating the National Cancer Institute-Working Group 1996 guidelines. Blood 1 1 1 (12): 5446-56, 2008).

[0043] The Binet classification integrates the number of nodal groups involved with the disease with bone marrow failure. Its major benefit derives from the recognition of a predominantly splenic form of the disease, which may have a better prognosis than in the Rai staging, and from recognition that the presence of anemia or thrombocytopenia has a similar prognosis and does not merit a separate stage. Neither system separates immune from nonimmune causes of cytopenia. Patients with thrombocytopenia or anemia or both, which is caused by extensive marrow infiltration and impaired production (Rai i ii/iV. Binet C) have a poorer prognosis than patients with immune cytopenias. The International Workshop on CLL has recommended integrating the Rai and Binet systems as follows: A(0), A (I), A(II); B(I), B(II); and C(III), C^'i lY) The NCI-sponsored working group has published guidelines for the diagnosis and treatment of CLL in both clinical trial and general practice settings. Use of these systems allows comparison of clinical results and establishment of therapeutic guidelines. In preferred embodiments any of these classification systems may be used with the methods of the present invention.

[0044] Treatments or therapeutic agents contemplated by the present disclosure include but are not limited to immunotherapy, chemotherapy, bone marrow and stem cell transplantation, and others known in the art. In one embodiment, the treatment described herein is based upon current treatments and clinical trials of treatments used to treat a patient in need thereof suffering from CLL. Doses and administration of treatments may be any regimen used. The treatment may be based on age, health, weight, sex, or ethnicity. The standard of care for the most common cancers can be found on the website of National Cancer Institute (www.cancer.gov/cancertopics). Alternative treatments of leukemia can be found at www.cancer.gov/types/leukemia/hp. The standard of care is the current treatment that is accepted by medical experts as a proper treatment for a certain type of disease and that is widely used by healthcare professionals. Standard or care is also called best practice, standard medical care, and standard therapy. Standards of Care for cancer generally include surgery, lymph node removal, radiation, chemotherapy, targeted therapies, antibodies targeting the tumor, and immunotherapy. Immunotherapy can include checkpoint blockers (CBP), chimeric antigen receptors (CARs), and adoptive T-cell therapy.

[0045] In one embodiment, patients diagnosed with stage 0, I, II, III, and IV Chronic Lymphocytic Leukemia are treated with the current standard-of-care first-line treatment. This treatment may be a combination of fludarabine (F), cyclophosphamide (C) and rituximab (R). In one embodiment, alternative treatment options tested in clinical trials are used. In one embodiment, an alternative treatment of stage 0 CLL is any treatment described herein, not limited to standard treatments for stage 0 CLL. Not being bound by a theory, the present invention provides for novel stratification of patients suffering from CLL and the stratification may indicate early treatment or observation. Early treatment may be before the appearance of symptoms. The present invention may provide for delaying treatment of patients determined to have CLL. Not being bound by a theory, the absence of cancer drivers may indicate a less aggressive CLL.

[0046] In one embodiment, the methods of the present invention indicate a subject is treated with a specific treatment. The treatment may be different than current treatments. The treatments may be the same as current treatments, but administered to a specific population identified with the methods of the present invention. Not being bound by a theory, patients having different mutations or alterations may have a different response to a specific treatment. Not being bound by a theory, the identification of novel cancer drivers or alterations allows a more informed treatment choice. Not being bound by a theory, incorporation of the methods of the present invention allows for delaying treatment or providing earlier treatment as compared to the previous standard of care. Not being bound by a theory the identification of a novel cancer driver or alteration may indicate increased aggressiveness of a cancer. The subject may have stage 0 CLL or have no symptoms, but have a mutation or alteration of the present invention, such that treatment is indicated. Early treatment of the cancer may lead to longer progression free survival and overall survival. The treatment may be any treatment regimen approved or in clinical trials.

[0047] Standard treatments of chronic lymphocytic leukemia (CLL) ranges from periodic observation with treatment of infectious, hemorrhagic, or immunologic complications to a variety of therapeutic options, including steroids, alkylating agents, purine analogs, combination chemotherapy, monoclonal antibodies, and transplant options. CLL is most often treated in a conservative fashion.(Gribben JG, et al . J Clin Oncol 29 (5): 544-50, 2011), In asymptomatic patients, treatment may be deferred until the patient becomes symptomatic as the disease progresses. Since the rate of progression may vary from patient to patient, with long periods of stability and sometimes spontaneous regressions, frequent and careful observation is required to monitor the clinical course (Del Giudice I, et al., Blood 114 (3): 638-46, 2009). The methods of the present invention may be used to monitor such patients. In one embodiment, the driver mutations of the present invention are used to determine if a patient should be treated. Not being bound by a theory, monitoring of driver mutation presence can predict spontaneous regressions.

[0048] In one embodiment, the methods of the present invention allow an alternative treatment to the current standard of care for Stage 0 CLL. Prior to the present invention, treatment for patients grouped as Stage 0 is no treatment. The French Cooperative Group on CLL randomly assigned 1,535 patients with previously untreated stage A disease to receive either chlorambucil or no immediate treatment and found no survival advantage for immediate treatment with chlorambucil. (Dighiero G, et al., N Engl J Med 338 (21): 1506-14, 1998). A meta-analysis of six trials of immediate versus deferred therapy with chlorambucil (including the aforementioned trial by the French Cooperative Group) showed no difference in overall survival at 10 years. (CLL Trialists' Collaborative Group. J Natl Cancer Inst 91 (10): 861-8, 1999). Not being bound by a theory, a therapeutic effect may be achieved using the present invention to stratify patients in the clinical trial based upon the presence of cancer drivers. The invention provided herein is useful in determining whether and when to start treatment.

[0049] In other embodiments, treatments used to treat Stage I, II, III, and IV CLL are used to treat patients based on identification of the mutations or alterations of the present invention. Several decades of large, randomized, prospective trials of previously untreated patients have demonstrated statistically significant improvements in response rates, event-free survival (EFS), and progression-free survival (PFS) with comparison of combinations of drugs versus single- agent alkyiators, (Clin Adv Hematol Oncol 5 (3 Suppl 5): 1-14; quiz 15-6, 2007; and Montserrat E, et al. Blood 107 (4): 1276-83, 2006), Three trials have shown statistically significant improvement in overall survival (OS) (Rai KR, et al., Blood 14 (22): A-536, 2009; Hallek M, et al., Lancet 376 (9747): 1 164-74, 2010, and Byrd JC, et al., N Engl J Med 371 (3): 213-23, 2014).

[0050] The first trial, a comparison of chlorambucil versus fludarabine for untreated chronic lymphocytic leukemia (CLL), after 15 years of median follow-up, showed improved median OS for patients on the fludarabine regimen at 63 months versus 59 months (P ^:=: .04), and an improved percentage of patients were alive at 8 years (31% vs. 19%, P = .04) (Rai KR, et al., Blood 114 (22): A-536, 2009, and Rai KR, et al,, N Engl J Med 343 (24): 1750-7, 2000).

[0051] The second trial, which had 817 untreated patients, compared FCR (fludarabine + cyclophosphamide + rituximab) versus FC (fludarabine + cyclophosphamide) with a median follow-up of 38 months and showed improved OS at 3 years for the rituxirnab combination (i.e., 87% vs. 83%, P = .01 (Haliek M, et al., Lancet 376 (9747): 64-74, 2010).

[0052] A prospective randomized trial of 391 patients with relapsed or refractor}' CLL and small lymphocytic lymphoma (SLL) compared ibrutinib with ofatumumab. With a median follow-up of 9.4 months, the 12-month OS favored ibrutinib (90% to 81%, HR, 0.43; P = .005) (Byrd JC, et al, N Engl J Med 371 (3): 213-23, 2014).

[0053] In the absence of a clinical trial, the standard therapy begins when patients develop profound cytopenias, which are consistently indicative of advanced-stage disease, or when they become symptomatic enough that quality of life is substantially impacted, such as with enlarging bulky lymphadenopathy or debilitating symptoms. The methods of the present invention allow prediction and early treatment of patients before having advanced-stage disease,

[0054] In one embodiment, a patient is treated with a maximal cytoreduction strategy. In one embodiment an alternative treatment of a CLL indicated as having an adverse outcome is treated with this strategy. This strategy involves using a combination regimen to achieve a durable complete remission. On the basis of previously described randomized clinical trial, FCR is a popular choice for induction therapy (Haliek M, et al. : Lancet 376 (9747): 1164-74, 2010). The combination of BR (bendamustine + rituxirnab) is another regimen used for this strategy (Fischer K, et al.: J Clin Oncol 29 (26): 3559-66, 2011; and lannitto E, et al : Br J Haematol 153 (3): 351 - 7, 201 1). Other combinations include R-CHOP (rituxirnab + cyclophosphamide + doxorubicin + vincristine plus prednisone) and R-CVP (eliminating doxorubicin from R-CHOP).

[0055] In one embodiment, a patient is treated with an avoidance of alkylators and purine analogues strategy. The goal of this strategy is to minimize the possibility that subclones with deleterious mutations, which are subsequently resistant to further therapy, will emerge. In one embodiment, the presence of subclones having any of the driver mutations of the present invention are treated with this alternative strategy. This strategy also avoids prolonged cytopenias and the recurrent, long-lasting, sometimes fatal, infections seen after therapy with these agents. Initial therapy with a monoclonal antibody, such as rituxirnab (in high doses or more frequent scheduling) with or without maintenance rituxirnab, is consistent with this strategy. The subsequent use of a B-cell receptor inhibitor, such as ibrutinib or idelalisib at relapse, is consistent with this approach. (Furman RR, et al. : N Engl J Med 370 (1 1): 997-1007, 2014, and Byrd JC, et al. : N Engl J Med 369 (1): 32-42, 2013), Avoidance of alkylators or purine analogues might be particularly advantageous for younger patients, who must reduce the risk of toxicities for many future years. This strategy is also used to prevent the harmful side effects of alkylator or purine analogue-based therapy in patients of advanced age and with significant comorbidities. In one embodiment, an alternative treatment of a CLL indicated as having an adverse outcome is treated with this strategy.

[0056] In one embodiment, a patient is treated with a risk-adapted therapy. Prior to the present invention prognostic factors, such as the mutational immunoglobulin variable region heavy chain (IgVH), 17p~, or HQ-status, were used to help inform the choice of therapy. Patients with a better prognosis might receive more gentle therapy with fewer short-term and long-term side effects. This approach might also be applicable for older patients with multiple comorbidities. Patients with a worse prognosis might receive combination regimens that are used for maximal cytoreduction. The methods of the present invention may be used to further determine a prognosis,

[0057] Standard options for CLL treatment are roughly ordered by level of toxic effects, starting with the least toxic options. In one embodiment, the present invention provides for treating a patient in need thereof based on identification of cancer drivers that indicate an adverse outcome. In one embodiment, treatment is with a more toxic option. The standard options include the following:

1. Observation. Outside of the context of a clinical trial, treatment for asymptomatic or minimally affected patients with chronic lymphocytic leukemia (CLL) is observation. Because the rate of progression may vary from patient to patient, with long periods of stability and sometimes spontaneous regressions, frequent and careful observation is required to monitor the clinical course.

2. Rituximab. Rituximab is a murine anti-CD20 monoclonal antibody (Mavromatis B, et ai. : J Clin Oncol 21 (9): 1874-81, 2003; O'Brien SM, et al. : J Clin Oncol 19 (8): 2165-70, 2001; Byrd JC, et al. : J Clin Oncol 19 (8): 2153-64, 2001.; Hainsworth ID, et al.: J Clin Oncol 21 (9): 1746-51 , 2003; and Castro JE, et al. : Leukemia 22 (11): 2048-53, 2008), When used alone, higher doses of rituximab or increased frequency or duration of therapy is required for comparable responses to those seen for other indolent lymphomas,

3. Ofatumomab. Ofatumomab is a human anti-CD20 monoclonal antibody (Wierda WG, et al. : J Clin Oncol 28 (10): 1749-55, 2010). A trial of 138 patients, who were previously treated with fludarabine and alerntuzumab, showed overall response rates around 50% in patients refractory to fludarabine and with previous exposure to rituximab (Wierda WG, et al.: J Clin Oncol 28 (10): 1749-55, 2010; and Wierda WG, et ai.: Blood 118 (19): 5126-9, 2011).

Obinutuzumab. Obinutuzumab is a human anti-CD20 monoclonal antibody. In a randomized prospective trial (NCT01010061), 781 previously untreated patients with coexisting medical problems were randomly assigned to chlorambucil and obinutuzumab versus chlorambucil and rituximab versus chlorambucil alone (Goede V, et al. : N Engl J Med 370 (12): 1101-10, 2014). The median PFS was best for the obinutuzumab arm (26.7 months) versus the rituximab arm (16.3 months) versus chlorambucil alone (1 1.1 months ) (hazard ratio [HR], 0.18; 95% confidence interval [CI], 0, 13-0.24; P < .001) for obinutuzumab and chlorambucil versus chlorambucil alone; for rituximab and chlorambucil versus chlorambucil alone [HR, 0,44; 95% CI, 0.34-0.57; P < .001 ]. The 2- year OS was significantly improved for the obinutuzumab arm (91%) versus chlorambucil alone (80%) (HR, 0.41; 95% CI, 0.23-0.74, P = .002). Patients who received obinutuzumab did not have improved survival compared with those who received rituximab alone (Goede V, et al. : N Engl J Med 370 (12): 1101-10, 2014), Idelalisib. Idelalisib is an oral inhibitor of the delta isoform of the phosphatidylinositol 3- kinase, which is located in the B-cell receptor-signaling cascade. In a randomized, double-blind, prospective trial (NCT01539512), 220 patients treated mainly with fludarabine-based regimens and who had coexisting medical problems, such as renal dysfunction, received rituximab and idelalisib versus rituximab and placebo (Furman RR, et al: N Engl J Med 370 (11): 997-1007, 2014). With a median follow-up of less than 1 year, the PFS rate at 24 weeks favored the rituximab and idelalisib arm (93%) versus the rituximab and placebo arm (46%) (HR, 0.15; 95% CI, 0.08-0.28; P < .001), and the OS rate at I year was significantly better for the rituximab and idelalisib ami (92%) versus the rituximab and placebo arm (80%) (HR, 0.28, 95% CI, 0.09-0.86; P = ,02) (Furman RR, et al.: N Engl J Med 370 (1 1): 997-1007, 2014). A median PFS of 16 months was observed in a phase I trial of patients with heavily pretreated relapsed or refractory disease (Brown JR, et al.: Blood 123 (22): 3390-7, 2014). 6. Ibrutinib. Ibrutinib is a selective irreversible inhibitor of Bruton tyrosine kinase, a signaling molecule located upstream in the B-eell receptor-signaling cascade. Trials of previously untreated patients and of patients with relapsed or refractory CLL showed durable responses to the oral agent in phase I and II studies (Advani RH, et al. : J Clin Oncol 31 (1): 88-94, 2013; and O'Brien S, et al : Lancet Oncol 15 (1): 48-58, 2014). A phase fb -II trial (NCT01 105247) of 85 patients with relapsed or refractory CLL showed a 26-month PFS rate of 75% and included patients with 17p- or unmutated IgVH FISH testing. [ 12.Byrd JC, Furman RR, Coutre SE, et al.: Targeting BT with ibrutinib in relapsed chronic lymphocytic leukemia. N Engl J Med 369 (1): 32-42, 2013] Patients who discontinued ibrutinib early because of disease progression or drug intolerance had very poor outcomes, which were mainly attributable to very poor preexisting prognostic factors (Jain P, et al.: Blood 125 (13): 2062-7, 2015; and Maddocks KJ, et al.: JAMA Oncology 1 (1 ): 80-7, 2015).

[0058] A prospective randomized trial of 391 patients with relapsed or refractory CLL/SLL compared ibrutinib with ofatumumab. With a median follow-up of 9.4 months, the 12-month OS favored ibrutinib (90% to 81%, HR, 0.43; P = .005) (Byrd JC, et al. : N Engl J Med 371 (3): 213- 23, 2014). Similar outcomes were seen for patients whose disease was resistant to purine analogues or who had a chromosome 17p deletion.

7. Oral alkylating agents with or without corticosteroids. The French Cooperative Group on CLL randomly assigned 1 ,535 patients with previously untreated stage A disease to receive either chlorambucil or no immediate treatment and found no survival advantage for chlorambucil (Dighiero G, et al. : N Engl J Med 338 (21 ): 1506-14, 1998). A metaanalysis of six trials of immediate versus deferred therapy with chlorambucil (including the aforementioned trial by the French Cooperative Group) showed no difference in OS at 10 years (J Natl Cancer Inst 91 (10): 861-8, 3999).

8. Purine analogs. Several randomized trials have compared the purine analogs with chlorambucil; with cyclophosphamide, doxorubicin, and prednisone; or with cyclophosphamide, doxorubicin, vincristine, and prednisone (CHOP) in previously untreated patients. All of these trials showed higher or equivalent response rates for the purine analog, and most showed an improvement in PFS; one reached significance in OS favoring f!udarabine (Rai KR, et al .: Blood 1 14 (22): A-536, 2009; Rai KR, et al : N Engl J Med 343 (24): 1750-7, 2000; Robak T, Blood 96 (8): 2723-9, 2000; Johnson S, et al., Lancet 347 (9013): 1432-8, 1996; Leporrier M, et al. : Blood 98 (8): 2319-25, 2001 ; Eichhorst BF, et al. : Blood 1 14 (16): 3382-91, 2009; and Steurer M, et al. : Cochrane Database Syst Rev 3 : CD004270, 2006).

9. Bendamustine. Bendamustine is a cytotoxic agent with bifunctional properties of an alkylator and a purine analog (Leoni LM, et al. : Clin Cancer Res 14 (1): 309-17, 2008). In previously treated and untreated patients, bendamustine with rituximab has shown response rates around 70% to 90% (Fischer K, et al. : J Clin Oncol 29 (26): 3559-66, 2011; and lannitto E, et al: Br J Haematol 153 (3): 351-7, 201 1).

[0059] In a randomized comparison with chlorambucil in 319 previously treated patients, bendamustine showed a better response rate (68% vs. 31%, P < .0001) and PFS (21 .6 months vs. 8 months) with a median follow-up of 35 months (Knauf WU, et al. : J Clin Oncol 27 (26): 4378- 84, 2009). The German CLL Study Group compared bendamustine plus rituximab versus FCR as first-line therapy in patients with CLL who require therapy (Fischer K, et al. : J Clin Oncol 29 (26): 3559-66, 201 1).

10. Lenalidomide. Lenalidomide is an oral immunomodulatory agent with response rates over 50%, with or without rituximab, for patients with previously treated and untreated disease. Prolonged, lower-dose approaches and attention to prevention of tumor lysis syndrome are suggested with this agent (Chen CI, et al. : J Clin Oncol 29 (9): 1175-81, 201 1 ; Chanan-Khan A, et al.: J Clin Oncol 24 (34): 5343-9, 2006, Ferrajoli A, et al : Blood 111 (11): 5291-7, 2008; Strati P, et al. : Blood 122 (5): 734-7, 2013; Wendtner CM, et al : Leuk Lymphoma 53 (3): 417-23, 2012; Badoux XC, et al . : J Clin Oncol 31 (5): 584-91, 2013; and Moutouh-de Parseval LA, et al. : J Clin Oncol 25 (31): 5047, 2007).

1 1. Combination chemotherapy.

[0060] Other combination chemotherapy regimens include the following:

o Fludarabine plus cyclophosphamide plus rituximab (Lamanna N, et al. : J Clin Oncol 27 (4): 491-7, 2009, Foon KA, et al .: J Clin Oncol 27 (4): 498-503, 2009; Tarn CS, et al : Blood 1 12 (4): 975-80, 2008; and Badoux XC, et al.: Blood 117 (11): 3016-24, 2011),

o Fludarabine plus rituximab as seen in the CLB-9712 and CLB-901 1 trials (Woyach J A, et al.: J Clin Oncol 29 (10): 1349-55, 201 1). o Fludarabine plus cyclophosphamide versus fludarabine plus cyclophosphamide plus rituximab (Robak T, et al . : J Clin Oncol 28 (10): 1756-65, 2010).

o Pentostatin plus cyclophosphamide plus rituximab as seen in the MAYO-MC0183 trial, for example (Kay NE, et al.: Blood 109 (2): 405-1 1, 2007, and Shanafelt

TD, et al.: Cancer 109 (1 1): 2291-8, 2007).

o Ofatumumab plus fludarabine plus cyclophosphamide (Wierda WG, et al. : Blood

117 (24): 6450-8, 2011).

o CVP: cyclophosphamide plus vincristine plus prednisone (Raphael B, et al. : J

Clin Oncol 9 (5): 770-6, 1991).

o CHOP: cyclophosphamide plus doxorubicin plus vincristine plus prednisone

(French Cooperative Group on Chrome Lymphocytic Leukemia. Leuk

Lymphoma 13 (5-6): 449-56, 1994).

o Fludarabine plus cyclophosphamide versus fludarabine as seen in the E2997 trial

[NCT00003764] and the LRF-CLL4 trial, for example (Flinn IW, et al.: J Clin

Oncol 25 (7): 793-8, 2007, Catovsky D, et al : Lancet 370 (9583): 230-9, 2007). o Fludarabine plus chlorambucil as seen in the CLB-90H trial, for example.

(Morrison VA, et al.: J Clin Oncol 20 (18): 3878-84, 2002).

Involved-field radiation therapy. Relatively low doses of radiation therapy will affect an excellent response for months or years. Sometimes radiation therapy to one nodal area or the spleen will result in abscopal effect (i.e., the shrinkage of lymph node tumors in untreated sites).

Alemtuzumab. Alemtuzumab, the monoclonal antibody directed at CD52, shows activity in the setting of chemotherapy-resistant disease or high-risk untreated patients with 17p deletion or p53 mutation (Moreton P, et al. : J Clin Oncol 23 (13): 2971 -9, 2005; Parikh SA, et al.: Blood 118 (8): 2062-8, 2011; Pettitt AR, et al. : J Clin Oncol 30 (14): 1647-55, 2012). In one embodiment, patients are treated if a cancer driver of the present invention is identified. As a single agent, the subcutaneous route of delivery for alemtuzumab is preferred to the intravenous route in patients because of the similar efficacy and decreased adverse effects, including less acute allergic reactions that were shown in some nonrandomized reports (Pettitt AR, et al. : J Clin Oncol 30 (14): 1647-55, 2012; Stilgenbauer S, et al. : J Clin Oncol 27 (24): 3994-4001 , 2009; Cortelezzi A, et al. : Leukemia 23 (11): 2027-33, 2009; Osterborg A, et al.: Leukemia 23 (11): 1980-8, 2009, and Gritti G, et al.: Leuk Lymphoma 53 (3): 424-9, 2012).

[0061] In a randomized prospective study, 335 previously treated patients received intravenous alemtuzumab plus fiudarabine versus fiudarabine alone. With a median follow-up of 30 months, the combination of fiudarabine plus intravenous alemtuzumab had better PFS, with a median of 23.7 months versus 16.5 months (HR, 0.61; 95% CI, 0.47-0.80; P ------- .0003); and better

OS, with a median not reached, versus 52.9 months (HR, 0.65; 95% CI, 0.45-0.94; P = .021) (Elter T, et al. : Lancet Oncol 12 (13): 1204-13, 201 1).

14. Bone marrow and peripheral stem cell transplantations. Bone marrow and peripheral stem cell transplantations are alternative treatment options (Doney KC, et al.: Bone Marrow Transplant 29 (10): 817-23, 2002; Schetelig J, et al .: J Clin Oncol 21 (14): 2747- 53, 2003; Ritgen M, et al. : Blood 104 (8): 2600-2, 2004; Moreno C, et al.: J Clin Oncol 23 (15): 3433-8, 2005; houri IF, et al. : Cytotherapy 4 (3): 217-21 , 2002; Pavletic SZ, et al : J Clin Oncol 23 (24): 5788-94, 2005; and Dreger P, et al.: Blood 1 19 (21): 4851-9, 2012). In a prospective randomized trial, 241 previously untreated patients younger than 66 years with advanced-stage disease received induction therapy with a CHOP -based regimen followed by fiudarabine (Sutton L, et al.: Blood 117 (23): 6109-19, 2011). Complete responders (105 patients) were randomly assigned to undergo autologous stem cell transplantation (ASCT) or observation, while the other 136 patients were randomly assigned to receive dexamethasone, high-dose aracytin, and cisplatin reinduction followed by either ASCT or fiudarabine plus cyclophosphamide. Although the 3 -year EFS favored ASCT in complete responders, there was no difference in OS in any of the randomized comparisons.

15. Autologous T-cells directed at specific antigen targets. Autologous T-cells were modified by a ientiviral vector to incorporate antigen receptor specificity for the B-cell antigen CD19 and then infused into a previously treated patient (Porter DL, et al. : N Engl J Med 365 (8): 725-33, 2011). A dramatic response lasting 6 months has prompted larger trials of this concept. Ongoing clinical trials are testing the concept of T-cells directed at specific antigen targets with engineered chimeric-antigen receptors (termed CARs (Maus MV, et al. : Blood 123 (17): 2625-35, 2014). [0062] In one embodiment, the present invention provides for treatment with a MEK inhibitor. A MEK inhibitor is a chemical or drug that inhibits the mitogen-activated protein kinase kinase enzymes MEK1 and/or MEK2. They can be used to affect the MAPK/ERK pathway which is often overactive in some cancers. The present invention provides for identification of CLL driver mutations indicating that treatment with MEK inhibitors should be performed. MEK inhibitors may be Trametinib (GSK1 120212), Selumetinib (Janne, Pasi A, et al. (2013). The Lancet Oncology 14 (1): 38-47) and is in phase III development in KRAS mutation positive NSCLC (SELECT-1,NCT01933932), Binimetinib (MEK 162), PD-325901, Cobimetinib or XLS 18, CI- 1040, or PD035901.

[0063] In another aspect, the present invention provides for novel targets for therapeutic intervention. Cancer drivers may be targeted with any agent that modulates the activity or expression of the target. The agent may be an antibody, a soluble polypeptide, a polypeptide agent, a peptide agent, a nucleic acid agent, a nucleic acid ligand, or a small molecule agent. The agent may target any of the genes or CNV's described herein. The nucleic acid agent may encode for RNAi, a Zinc finger nuclease (ZFN), a Transcription Activator-Like Effector Nuclease (TALEN), or a CRISPR/Cas system.

[0064] The present invention advantageously utilized large sequencing datasets of clinically informative samples to enable the discovery of novel cancer drivers and the network of relationships between the driver events and their impact on disease relapse and clinical outcome. Thus, the present advantageously allows improved clinical outcomes for patients suffering with

CLL,

[0065] Although the present invention and its advantages have been described in detail, it should be understood that various changes, substitutions and alterations can be made herein without departing from the spirit and scope of the invention as defined in the appended claims.

[0066] The present invention will be further illustrated in the following Examples which are given for illustration purposes only and are not intended to limit the invention in any way.

Examples

Example 1

[0067] Unbiased candidate CLL genes discovery. Applicants performed WES of CLL and matched germline samples, collected from 278 subjects enrolled on the CLL8 trial, with mean read depth of 95.0 and 95.7, respectively {Supplementary Table 1). Consistent with previous CLL WES studies, Applicants detected a mean+/-SD rate of 21.5+/-7.9 silent and non-silent single nucleotide variants [sSNVs] and somatic insertions and deletions [sINDELs] per exome

1,3

[0068] Applicants inferred candidate cancer genes in CLL through implementation of MutSig2CV⁵'' . To maximize statistical sensitivity for driver detection⁵ Applicants combined the CLL8 cohort with two previously reported and non-overlapping WES cohorts¹'', thereby increasing the size of the cohort to 538 CLLs. This cohort size is expected to saturate candidate CLL gene discovery for genes mutated in 5% of patients, and provides 94% and 61% power to detect genes mutated in 3% and 2% of patients, respectively⁵.

[0069] Applicants detected 44 putative CLL. driver genes, including 18 CLL mutated drivers that Applicants previously identified³, as well as 26 additional putative CLL genes {Fig. 1-2, Extended Data Fig. 1-2). In total, 33.5% of CLLs harbored mutation in at least one of these 26 additional genes. Targeted DNA sequencing as well as variant allele expression by RNAseq demonstrated high rates of orthogonal validation (Extended Data Fig. 3),

[0070] Of the newly identified putative cancer genes, some were previously suggested as CLL drivers in studies using other detection platforms. For example, the suppressor of MYC MGA (n=17, 3.2%), which Applicants detected as recurrently inactivated by insertions and nonsense mutations, was previously found to be inactivated through deletions⁸ and truncating mutations^8,9 in high-risk CLL (Extended Data Fig. 4). A gene set enrichment analysis of matched RNAseq data revealed down-regulation of genes that are suppressed upon MYC activation in B-cells^l0. In addition to MGA, Applicants report two additional candidate driver genes that likely modulate MYC activity (PTPNll¹¹ [n=7, 1.3%] and FUBP1¹² [n=9, 1.7%]), highlighting MYC-related proteins as drivers of CLL.

[0071] Another cellular process affected by novel CLL drivers is the MAPK-ERK pathway, with 8.7% of patients harboring at least one mutation in CLL genes in this pathway. These included mutations in RAS genes (NBAS, n 9 and KRAS n 14, totaling 4. 1 %); BRAF in 2 1 , 3.7%); or the novel putative driver MAP2K1 (n=12, 2%). This finding suggests therapeutic options including MAPK-ERK. pathway inhi bitors in CLL. Intriguingly, BRAF mutations in CLL did not involve the canonical hotspot (V600E) seen in other malignancies^5,1 '¹⁴, but rather clustered heavily around the activation segment of the kinase domain (Fig. 2). This may hint at a different mechanism of activity¹⁵'¹", and has clinical implications, as BRAF inhibitors are thought to be less effective for non-canonical BRAF mutations' ^7,18 and may be more effectively targeted by MEK inhibitors (Pratilas, C. A. et al. Genetic predictors of MEK dependence in non- small cell lung cancer. Cancer Res 68, 9375-9383, doi : 10.1 158/0008-5472.CAN-08-2223 (2008))..

[0072] In addition to highlighting novel cellular processes and pathways affected in CLL, many of the 26 additional CLL genes more densely annotated pathways or functional categories previously identified in CLL¹⁹, including R A processing and export (FUBPI, XP04, ESWR1, NXFI), DNA damage (CHEK2, BRCC3, ELF4²⁰ and DYRK1A²¹), chromatin modification (ASXLI, HIST1H IB, BAZ2B, FKZF3) and B cell activity related pathways (TRAF2, TRAF3, CARD11).

[0073] Applicants discovered a number of putative CLL drivers previously unrecognized in human cancer. In a first example. Applicants found that RPS15 was recurrently mutated (n==^:23, 4.3%), with mutations localized to the C -terminal region (Fig. 2) at highly conserved sites (median conservation score of 94/100). This component of the S40 ribosomal sub unit, has not been extensively studied in cancer, although rare mutations have been identified in Diamond- Blackfan anemia²². A gene set enrichment analysis revealed upregulation of gene sets related to adverse outcome in CLL as well as immune response gene sets. In another example of a previously unrecognized cancer gene, Applicants identified recurrent L162R substitutions (n=l l , 2.0%) in IKZF3, targeting a highly conserved amino acid (93/100 conservation score). This gene is a key transcription factor in B cell development^'3, and its upregulation has been associated with adverse outcome^24,25.

[0074] In addition to sSNVs and sINDELs, Applicants characterized somatic copy number variations (sCNVs) directly from the WES data (Extended Data Fig. 5, Supplementary Table 5). When Applicants accounted for all 55 identified driver events - including non-silent sSNVs and sINDELs in putative CLL genes (n=44), and recurrent sCNVs (n=l 1)— 91.1% of CLLs contained at least one driver. Moreover, 65.4% of CLLs now harbor at least 2 drivers, and 44.4% at least 3 drivers, compared with 55.9% and 3 1.8% were Applicants to exclude the 26 additional CLL genes. Supplementary Table 1: Patients characteristics ©f the 278 patients that rovided s m les m part of GCLLSG-CLL8 trial.

Respoader versus non-response/missmg S«p|>!e#*etttary Tafeie 5: (.^'¾>?«ρ, trfcon between $os« c copy

deiee k i with WES vs. ISH _* oge.»efks

Example 2

[0075] Drivers and CLL characteristics. The larger cohort size also provided statistical power to examine associations between genetic alterations and key CLL features. First, Applicants examined whether mutations differed between IGHV mutated and unmutated subtypes, the two main subtypes of CLL. In agreement with the relative clinical aggressiveness of IGHV unmutated CLL, most drivers were found in a higher proportion in this subtype (Extended Data Fig. 6 A). Only three driver genes were enriched in the IGHV mutated CLL (iii?/(13q), MYD88, ( 7/7⁾2), suggesting a role for these specific alterations within the oncogenic process of this subtype.

[0076] Second, since therapy could lead to selection of particular driver events, Applicants examined the 33 samples (6.2%, none enrolled on CLL8) that had received therapy prior to sampling. Prior treatment was associated with enrichment in TP53 and BIRC3 mutations, del(np) and de!(l lq) as previously indicated²⁶, as well as in mutated DDX3X and MAP2K1, suggesting their selection by therapeutic interventions (Extended. Dat Fig. 6B).

[0077] Third, Applicants examined whether coherent patterns of co-occurrence of driver events were evident, limiting our analysis to the 31 drivers with >10 affected patients. Of 465 possible pairs, 1 1 combinations had statistically significant high or low co-occurrence (Extended Data Fig. 6C-D). As expected, a high degree of co-occurrence was found between mutated TP53 and (. ('/( 1 7p). and between mutated AIM. and dei(l lq). Both mutated AIM and de!(l lq) significantly co-occurred with amp(2p), and associations between presence of tri(\2) with mutated BIRC3 and with mutated BCOR were also found. A significantly low rate of cooccurrence was seen between tfe/(13q) and /·/^'{ 12).

[0078] Fourth, Applicants examined the temporal sequence of driver acquisition in the evolutionary history of CLL, To do this, Applicants computed the cancer-cell fraction (CCF) of each mutation across the 538 samples, and identified mutations as either clonal or subcional^{2 '} (58.1% of mutations classified as subcional). Both clonal and subcional sSNVs were similarly dominated by C>T transitions at C*pG sites {Extended Data Fig. 7).

[0079] Applicants first classified driver events likely acquired earlier or later in the disease course based on the proportion of cases in which the driver was found as clonal {Fig. 3Λ). This large dataset further enabled the inference of temporal relationships between pairs of drivers. Applicants systematically identified instances in which a clonal driver was found together with a subcional driver within the same sample, as these pairs reflect the acquisition of one lesion (clonal) followed by another (subcional), providing a temporal 'edge' leading from the former to the latter^2,8'²⁹. For each driver, Applicants calculated the relative enrichment of out-going edges compared to in-going edges to define early, late and intermediary drivers (Supplementary Table 7). For 23 pairs connected by at least 5 edges. Applicants further established the temporal relationship between the two drivers in each pair, and thereby constructed a temporal map of the evolutionary trajectories of CLL {Supplementary Table 8, Fig. 3B)^" . This network highlights sCNVs as the earliest events with two distinct points of departure involving del(\3q) and //· ( 12). It further demonstrates an early convergence towards de!(l lq) and substantial diversity in late drivers. Finally, this analysis suggests that in the case of the tumor suppressor genes ^ Z and BIRC3, copy loss precedes sSNVs and sINDELs in bialleiic inactivation.

Su plementar Table 7; Temporal order of somatic mutation acquisitions -^■ clas»ifyi»g drivers as ea ly vs. late.

These table includes all driver events (recurrent sCNVs and candidate CLL gene non-silent mutations), classifying the driver events based on the relative enrichment of out-degrees vs. in- degrees as early (O<0.2 and number of out-degrees > in-degrees). late {Q<Q,2 and number of out-degrees < in-degrees) and intermediate or not powered (£>>0.2. Inter./not powered). Out- degrees are defined as instances in which the driver event is clonal and found in the same CLL with another driver event that is subclonal. in-degrees are defined as instances in which the driver event is subclonal and found in the same CLL with another driver event that is clonal.

Table 7 a: Results in n = 501 treatment naive patients (4 patients with unknown status of prior therapy were excluded from the analysis as well):

Driver O-value occurin-degrees out-degrees classification

event rences

del 13q L22E-23 233 35 1 83 Early

tri12 9.44E-22 67 i 81 Early

ATM 2.94E-13 76 89 14 Late

BI. C3 2.05E-07 15 27 0 Late

dell I q 3.93E-04 103 42 90 Early

del20p 2.24E-03 6 0 1 Early

FBXW7 1.53E-02 10 10 0 Late

MAP2K1 2.39E-02 8 9 0 Late

NRAS 2.39E-02 8 9 0 Late

KRAS 3.49E-02 14 1 1 1 Late

BAZ2A 3.58E-02 9 8 0 Late

MYD88 3.58E-02 14 0 8 Early

CARD! 1 4.64E-02 7 10 1 Late

Mi A 4.64E-02 15 16 4 Late

ΖΜΎΜ3 4.74E-02 10 12 Late

TP53 6.90E-02 29 26 1 1 Late

amp2p 9.54E-02 45 44 25 Late

del6q2.1 L60E-01 16 1 6 Late

DYR 1 A 1 .93E-01 7 7 I. Late

FAM50A 1.93E-01 5 7 1 Late

CHEK2 3.12E-01 5 1 6 Inter . not powered

TRAF3 3.12E-01 4 4 0 Inter./not powered

BRAF 3.35E-01 19 12 5 inter./not powered

1RF4 3.35E-01 10 9 3 Inter./not powered

NOTCH 1 3.38E-01 37 25 15 Inter . not powered

ampSq 3.531.-01 12 10 4 1 nter . not powered MED 12 3.53E- I "7 "7 2 I liter .n ot powered

TRAF2 3.53E-01 6 7 · Inier./not powered

ΡΪΡΝΠ 4.15E-01 6 5 1 Inter .not powered

ΡΪΜΙ 4.44E-01 3 0 i ter, /not powered tril 4.44E-01 6 0 3 Inter./not powered

ASXLi 4.82E-01 5 6 2 1 nter. /not powered

EL.F4 4.82E- 1 7 6 Inter./not powered

RPS15 5.29E-01 21 16 1 Inier./not powered

SF3B1 5.32E-01 103 72 60 Inter./not powered

NXFI 5.G7E-01 7 4 1 inier./not powered

POTl 5.67E-01 33 20 27 Inter./not powered

GNB1 6.56E-0I 5 5 2 Inter./not powered

HISTIH!E 7.16E-01 7 3 6 Inter./not powered

BRCC3 7.55E-01 5 7 4 1 nter ./n ot powered

IKZF3 7.79E-01 ii 5 S Inter./not powered dell 8p 8.24Ε-0Ϊ 12 10 7 Inter./not powered

EGR2 8.67Ε-ΘΙ 16 10 13 Inter./not powered dell7p 9.10E-01 24 15 18 Inter./not powered

FUB 1 9. EE-0I 9 8 6 inter./not powered

CHD2 9.61E-01 23 9 7 I nter in ot poweed

XPOI 9.95E-01 22 13 15 inter./not powered

BCOR L OE+00 10 7 6 Inter./not powered

IGLL5 LOOE+00 11 6 7 Inter./not powered

DDX3X 1. OE+00 10 4 4 Inter./not powered delSp LOOE+00 16 10 10 Inter, /n ot pow ered

EWSRJ 1.OOE+00 4 1 I nter ./not powered

MIST 1 Ml B LOOE+00 4 2 Inier./not powered

SA.M.HD 1 1.OOE+00 10 6 6 Inter./not powered

X.P04 LOOE+00 7 5 5 Inter./not powered

Table 7b: Results in n = 229 treatment naive patients with IGHV unmntated CLL:

TRAF3 6.67E-01 .> 0 Inter, n ot powered

EGR.2 8.54E-01 14 9 12 inter./not powered

XPO i 8.54E-01 20 10 13 inter./not powered

RPS I 5 8.54E-01 1.9 14 1 1 Inter ./not powered

BRCC3 8.79E-01 4 5 3 inter./not powered

J.KZF3 8.9 ! E-01 8 4 6 Inter./not powered

DDX3.X l .OOE+OO 8 3 4 Inter./not powered

SAMHD S L00E÷00 7 3 4 Inter./not powered

SF3B I 1..00F 00 60 41 42 Inter./not powered

BCOR 1 .OOE+00 8 7 6 Inter./not powered amp8q LOOE+00 5 1 2 Inter./not powered

FAM50A :i .ooE+oo ! 0 1 Inter./not powered

FUBPl i .OOE+00 6 5 5 inter./not powered

TRAF2 1 .OOE+00 4 3 - Inter./not powered

Table 7c: Results in n ^~ 245 treatment naive patients with IGHV mutated CLL:

Supplementary Table 8: Temporal order of so a tie oMsteikso acquisitions ~ pair fee data.

These tables includes all pairs of driver events (dl, d2) that had at least 5 cases in which the two drivers were detected in the same CLL sample, but one of the drivers is clonal and the other is subclonal. A two-tailed binomial test is performed to test whether the pairings are found to be in one order more frequently than the other (i.e., dl c!2 > d2 dl ). A multi-hypothesis correction is then applied and the table lists all hypotheses tested.

Table 8a: Pairing in a = 501 treatment naive patients ( 4 patients with unknown status of prior therapy were excluded f om the analysis as well):

Ordering P- value £?-value No. orderings No. opposite

(clonal - orderings

subclonal) (subclonal

clonal)

dell3q->ATM 1.54E-08 3.53E-07 31 1

dell1q->ATM 2.10E-05 2.41E-04 20 1

del Bq->auip2p 6.10E-05 4.68E-04 15 0

dell3q->SP3Bl 3.24E-04 1.86E-03 27 6

dell lq~>amp2p 9.77E-04 4.49E-G3 14 1

tril2~>BlRC3 3.91E-03 E50E-02 9 0

tril2->delllq 3.12E-02 1.03E-01 6 0

de!llq->BlRC3 6.25E-02 1.20 !.-⁽)! 5 0

dell3q->del6cj21 6.25E-02 1.20E-01 5 0

dell3q->MGA 6.25E-02 1.20E-01 5 0

trii2->FBXW7 6.25E-02 1.20E-01 5 0

tril2-> RAS 6.25E-02 1.20E-01 5 0

amp2p- ATM 7.03E-02 1.24E-01 1

dell q->de!11q 9.31E-02 1.53E-01 16

dell3q->POTl 1.25E-01 L80E-01 6 1

deil3q->TP53 1.25E-01 1.SOE-01 6 1

dell!q->SF3Bl 2.67E-01 3.61E-01 9 4

de113q-X_el17p 3.75E-01 4.54E-01 4 1

delI3q->NOTCHl 3.75E-01 4.54E-01 4 1

SF3BI->ATM 5.08E-01 5.S4E-01 6 3

deU7p->TP53 6.88E-01 7.53E-01 4

XP01->ddl3q 1.00E+(M) LOOE+OO 4 3

POTl->deiiiq LOOE+OO 1.00E+00 3 Table 8b: Pairing in n - 229 treatment naive patients with /GHFunmutated CLL, Patients with unknown IGHV status were excluded from the analysis:

Table 8c: Pairings in n = 245 treatment naive patients with IGHV mutated CLL. Patients with unknown IGHV ^" status were excluded from the analysis:

Example 3

[0080] Impact of presence and clonality of CLL drivers on clinical outcome. Applicants examined whether presence of any of the drivers detected in at least 10 of the 278 pre-treatment CLL8 samples was associated with impact on clinical outcome (Fig. 4A, Extended Data Fig. 8- 9; the genomics analysis team was blinded to the clinical outcome data). Previous investigations suggested an impact for 7 CLL genes (SF3HI. A TM, TPS ^'3, XPOl, EGR2, POTl and BIRC3)^30'33. Applicants found shorter progression-free survival (PFS) associated only with TP53 and SF3B1 mutations. Of the newly identified recurrent lesions evaluated (MGA, BRAF and RPS15), Applicants observed a shorter PFS with mutated RPS15 (Bonferroni P = 0.024).

[0081] Presence of a detectable pre-treatment subclonal driver has been previously associated with shorter remissions in patients treated with heterogeneous therapies³. In the CLLS cohort, Applicants again found that the presence of a pre-treatment subclonal driver was associated with a significantly shorter PFS (hazard ratio (HR) 1.6 [95%CI 1.2-2.2, P = 0.004). This association remained significant in both the FC and FCR treatment arms (Fig. ¥11), with a non-significant trend when IGHV mutation status was added to a muitivariable model in addition to the treatment arm (1.3 [0,9-1 ,9], P=0.102). Applicants also note a trend towards shorter OS in CLLs with a subclonal driver (P = 0.151 ).

Example 4

[0082] Clonal evolution at disease relapse.

[0083] To define clonal evolution in disease relapse, Applicants performed WES on matched samples collected at the time of relapse from 59 of 278 CLL8 subjects (Supplementary Table 9), Applicants observed large clonal shifts between pre-treatment and relapse samples in the majority of cases (57 of 59), thus demonstrating that CLL evolution after therapy is the rule rather than the exception (Fig. 5A). The relapse clone was already detectable in pre-treatment WES in 18 of 59 (30%) cases, demonstrating that the study of pre-treatment diversity anticipates the future evolutionary trajectories of the relapsed disease³⁴. By targeted deep sequencing, Applicants detected relapse drivers in 1. 1 of the 41 of pre-treatment samples in which WES did not detect the relapse driver. In 7 of these 1 1 CLLs, at least one relapse driver was detected in the pretreatment sample.

[0084] Applicants further compared the pre-treatment and relapse CCF for each driver, and observed three general patterns. First, //· ( ! 2), d.el(\3q) and afe/fl l q), suggested as early drivers (Fig. SB), tended to remain stably clonal despite marked, often branched, evolution (Fig. SB [CLL cases: GCLL-1 15, 307], Fig. 5C-top; Extended Data Fig. 10). This confirms that these are indeed early events likely shared by the entire malignant population . Second, TP53 mutations and dei(l7p) demonstrated increases in CCF upon relapse, suggesting a fitness advantage under therapeutic selection (Fig. SB [GCLL-27, Fig. SC-middle\). The novel driver 1KZF3 increased in CCF in 3 of 4 relapse cases (and remained clonal in the fourth), supporting that these mutations likely enhance fitness. Third, mutations in SF3B1 and ATM, identified as a temporally intermediate or late drivers, seemed just as likely to fall in CCF as they were to rise (Fig. 5C- Bottom). These results suggest that within this therapeutic context such mutations do not provide as strong of a fitness advantage as TP53 disruption. In addition, Applicants observed 9 instances each of multiple distinct alleles of Λ ΊΜ and SF3BI mutations within the same CLL, (e.g., GCLL-307 in Fig. SB), indicating convergent evolution of these late-occurring CLL drivers.

[0085] This series also informs us regarding the mutagenesis of the tumor suppressor genes TP53 and ATM, where biallelic inactivation is common. In the case of ATM, Applicants typically find a fixed clonal dei(l lq223) and subclones harboring sSNVs affecting the other allele that shift in CCF over time (e.g., GCLL -307). Applicants confirmed that the breakpoints of sCNVs in matched relapse and pre-treatment samples were highly consistent, likely representing the same deletion event. These data thus suggest that mono-allelic ATM deletion provides a fitness advantage that enables the expansion of the malignant population with subsequent growth of multiple co-existing clones that harbor a second hit in the remaining allele. Thus while a biallelic lesion is clearly selected for (Extended Dat Fig. 6C), the longitudinal data support the temporal analysis (Fig. 3B) in which del(l lq) precedes AIM. mutations, reflecting the higher likelihood of a focal copy number loss compared with a deleterious point mutation^''^3,36. In contrast, Applicants consistently observed a concordant rise of <afe/(17p) and ΊΡ53 mutations in all 12 CLLs harboring both of these events, and none of these cases exhibited multiple shifting TP53 sSNVs/sINDELs. These observations suggest that a true biallelic inactivation of ΊΡ53 is required, and indeed, across the 538 CLL samples, the odds ratio for co-occurrence of i¾?/(17p) and TP53 mutation was far greater than the odds ratio for co-occurrence of del(\ lq) and ATM mutation (97.22 vs. 10.99, respectively). These observations are in agreement with a recent analysis that suggested that with the exception of a few genes such as TP53, tumor suppressor genes in sporadic cancers are haploinsufficient to begin with, and that the second hit only further builds on this fitness advantage'⁷. Supplementa Table 9: Beseriptio.® o.f patients for whkh matched pre-breateeat ami rela se sampler were an lyze ..

Example 5

[0086] CONCLUSIONS. This study of WES in CLL enabled a comprehensive identification of putative cancer genes in CLL, generating novel hypotheses regarding the biology of this disease, and identifying previously unrecognized putative CLL drivers such as RPS15 and IKZF3, The detailed characterization of the compendium of driver lesions in cancer is of particular importance as Applicants strive to develop personalized medicine, as driver genes may inform prognosis (e.g., RPS15 mutations) and identify lesions that may be targeted by therapeutic intervention (e.g., MAPK pathway mutations and specifically the unexpected enrichment for non-canonical BRAF mutations). Through the inclusion of samples collected within a landmark clinical trial with mature outcome data. Applicants could further study of the impact of genetic alterations in the context of the current standard-of-care front line therapy. As targeted therapy is rapidly transforming the treatment algorithms for CLL, future studies will be required to reexamine these associations in this context³⁸.

[0087] An important benefit of the larger cohort size is the enhanced ability to explore relationships between driver lesions based on patterns of their co-occurrence. Focusing on temporal patterns of driver acquisition - based on the distinction between clonal versus subclonal alterations in a cross-sectional analysis - Applicants derived a temporal map for the evolutionary history of CLL. In the context of relapse after first-line fludarabine based therapy, Applicants note highly frequent clonal evolution, and that the future evolutionary trajectories were already anticipated in the pre-treatment sample in one third of cases with WES.

[0088] This study provides a glimpse of some of the anticipated fruits of the application of novel genomic technologies to growing cohort sizes across ieukemias: the continued discovery of novel candidate cancer genes, the deeper integration of genetic analysis with standardized clinical information (collected within clinical trials) to inform prognosis and therapy, and the ability to delineate the complex network of relationships between cancer drivers in the history and progression of the malignant process.

References

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Methods

[0089] Human samples: Heparinized blood was obtained from patients enrolled on the prospective, randomized, open-label CLL8 trial¹ before the first cycle of treatment. Sample selection was based on availability, and the baseline characteristics of the cohort of patients studied with WES are largely reflective of the baseline characteristics of the entire CLL8 cohort {Supplementary Table 1). All patients had a diagnosed CLL according to WHO criteria confirmed by flow cytometry and were in Binet Stage C or Binet A or B with need for treatment as defined by the study inclusion criteria¹. Peripheral blood mononuclear cells (PBMC) from patients were isolated by Ficoll density gradient centrifugation. Immuno-magnetic tumor cell enrichment via CD 19 was performed on all baseline pretreatment samples (Midi MACS, Miltenyi Biotec, Bergisch Gladbach, Germany) achieving a separation of PBMCs into a CD19- positive tumor sample and a CD19-negative normal sample with a purity of >95% by flow cytometry. For some samples, the source of matched normal tissue was PBMC collected following chemoimmunotherapy when the samples were evaluated by flow cytometry as minimal residual disease-negative (Kiel Laboratory, Germany). Samples were used fresh or cryopreserved (with FBS with 10% DMSO) and stored in vapor-phase liquid nitrogen until the time of analysis.

[0090] Established CLL prognostic factor analysis: Analyses of genomic aberrations and immunoglobulin heavy-chain variable (IGHV) homology were performed in the central reference laboratory of the German CLL Study Group (GCLLSG) in Ulm, Germany. Unmutated IGHV was defined as greater than or equal to 98% homology to the closest germline match analyzed via DNA sequencing. Greater than 20% ZAP-70 expression was considered positive (high-risk)². Cytogenetics were evaluated by FISH for the most common CLL abnormalities (tfe/(1.3q), tri(\2), del{\ \q), (Ιβί(Πρ), rearrangements of chromosome 14) (probes from Vysis, Des Plaines, IL). Samples were scored positive for a chromosomal aberration based on consensus cytogenetic scoring³. Statistical analysis considered the hierarchical Doehner classification \

[0091] DNA quality control: Applicants used standard Broad Institute protocols as previously described^5,6. Tumor and normal DNA concentration were measured using PicoGreen® dsDNA Quantitation Reagent (Invitrogen, Carlsbad, CA). A minimum DNA concentration of 5 ng/μΐ was required for sequencing. All Illumina sequencing libraries were created with the native DNA. The identities of ail tumor and normal DNA samples were confirmed by mass spectrometric fingerprint genotyping of 95 common SNPs by Fluidigm Genotyping (Fluidigm, San Francisco, CA).

[0092] Whole exome sequencing (WES): Informed consent for genomic analyses of patients' samples was obtained prior to the initiation of sequencing studies. The study was approved by the Ulm University Ethics Committee, IRC/EC number 138/03. DNA was extracted and purified from CD 19+ and CD 19- fractions of PBMC for tumor and matched germline DNA, respectively, using the Qiagen all-prep kit (Quiagen, Hilden, Germany) according to its unmodified protocol. Libraries for whole exome sequencing were constructed and sequenced on either an Illumina HiSeq 2000 or Illumina HiSeq 2500 using 76 bp paired-end reads. Details of whole-exome library construction have been described elsewhere '. Standard quality control metrics, including error rates, percentage-passing filter reads, and total Gb produced, were used to characterize process performance before downstream analysis. Note that due to a change in the Agilent capture bait set, the NOTCH 1 hotspot was not covered in samples GCLL-199 through GCLL-313, which included 10 samples with NOTCH! c.7544_7545delCT deletions by Sanger sequencing⁸. CLL samples found to harbor NOTCH! mutations by Sanger sequencing were subsequently submitted to targeted sequencing with Illumina TruSeq Custom Amplicon library, and sequenced on an Illumina MiSeq with a mean coverage depth of 1332X. In the relapse samples, samples with NOTCH 1 mutations by Sanger sequencing (GCLL-0146-T-02, GCLL-0192-T-02, GCLL-0049-T-02, GCLL-0208-T-02) were also submitted to targeted sequencing. In addition to samples from patients included in the CLL8 clinical trial, Applicants have analyzed 157 WES samples from the cohort Applicants have previously published⁵'. The sequencing reads were realigned to hgl9 and all downstream analysis was done using the same methods as with the sequencing data for the CLL8 cohort. Finally, previously published WES data for 103 matched CLL and germline DNA samples were downloaded with permission from the European Genome-Phenome Archive¹⁰, The raw sequencing reads were processed in identical fashion to the in house produced WES libraries. New WES data is deposited in dbGaP (phs000922.vl .pl).

[0093] Identification of somatic mutations: Output from Iflumina software was processed by the "Pi card" data processing pipeline to yield BAM files containing aligned reads (bwa version 0,5.9, to the NCBI Human Reference Genome Build hgl 9) with well-calibrated quality scores 5, 11. From the sequencing data, somatic alterations were identified using a set of tools within the "Firehose" pipeline, developed at the Broad Institute (www.broadinstitute.org/cancer/cga). The details of the sequencing data processing have been described elsewhere^5,6. Somatic single nucleotide variations (sSNVs) were detected using MuTect (Firehose version vl3112); somatic small insertions and deletions were detected using an improved version (manuscript in preparation, Cibulskis et al.,) of Indelocator^J. The primary improvement is implementation of local reassembly, which results in more accurate allele fraction estimation. Following our standard procedure, Applicants filter sSNVs and sINDELs by removing events seen in sequencing data of a large panel of normal samples. Overall, this filtering removed -35% of all candidate somatic mutations, mostly ones with very low allelic fraction. In order to ensure that no candidate driver mutation were mistakenly removed by the filter, after completing the MutSig process, all filtered events in candidate CLL genes were also manually reviewed using the integrated genome viewer (IGV)!3. In addition all mutations in candidate CLL genes were confirmed by manual inspection as well. The Oncotator tool was used to annotate mutations¹⁴. Conservation across 46 vertebrate species was performed and scored as previously described⁹. Sample contamination by DNA originating from a different individual was assessed using ContEst ^l5. Median contamination value was 0.1% [inter-quartile range 0.1- 0.3%]. Ig loci mutations were not included in this analysis,

[0094] In the 59 longitudinal samples, Applicants utilized "forced calling" to quantify the number of alternate and reference alleles at sites with somatic mutation detected in a different sample from the same patient which was taken at a different time point, using the Sam tools suite. Reads were considered if they were not marked as duplicate reads, had a base quality score at the site of interest > 20 and alignment quality score > 5, based on GATK BQSR base quality recalibration¹¹.

[0095] Estimation of and correction for tumor in normal content: For samples from the CLL8 trial, the majority of matched germline DNA samples were obtained from the CD Infraction of PBMC. Applicants found that some of these germline samples contained substantial proportions of tumor DNA, which could significantly decrease the ability to detect somatic mutations with high sensitivity using MuTect. Applicants thus applied deTiN (manuscript in preparation, Taylor-Weiner et a!,), a method for estimating the level of tumor cells in the normal paired sample and recovering somatic mutations that would otherwise be filtered out due to evidence of the mutation in the normal. In brief, Applicants estimate the level of tumor-in- normal (TiN) using two complementary approaches: (i) for tumors with a sufficient number of somatic mutations (total number of sSNVs and sFNDELs >5), Applicants use a linear fit of the respective tumor and normal allele fractions of candidate somatic mutations, and (ii) for tumors with sufficiently large sCNVs, Applicants fit the allele frequency shift of germline heterozygous SNPs to a mixture of tumor and nonnal which provides an independent estimate for TiN. Next Applicants use the TiN estimate to recover sSNVs and sINDELs that are at least a 1000 times more likely to be a somatic mutation than a germline event.

[0096] Significance analysis for recurrently mutated genes: Applicants used MutSig2CV16 to detect candidate cancer genes using three signals of positive selection: (i) increased mutation burden as compared to a background model; (ii) clustering of mutations along the gene; and (iii) enrichment of mutations at likely functional sites.

[0097] Genome-wide copy number analysis: Genome-wide copy number profiles of the CLL samples and their patient-matched germline DNA were estimated directly from the WES data, based on the ratio of CLL sample read-depth to the average read-depth observed in normal samples for that region. Applicants observed a high level of agreement between sCNV detection by exome and standard FISH cytogenetics, with the exception of smaller deletions in the region of chromosome 13ql 4, where 14.5% of cases were missed by WES {Supplementary Table 5). Allelic copy number analysis was then performed by examination of alternate and reference read counts at heterozygous SNP positions (as determined by analysis of the matched normal sample). These counts were used to infer the contribution of the two homologous chromosomes to the observed copy-ratio in each segment. Further analysis of change-points in these ailelic-ratios was performed using PSCBS17, refining the segmentation. Finally, for each segment, Applicants combined the copy-ratio and allelic data to derive allelic copy-ratios.

[0098] Significant recurrent chromosomal abnormalities were identified using the GISTIC2.0 algorithm¹⁸ (v87). Regions with germline copy number variants were excluded from the analysis. Arm level and focal deletion and amplifications filtered by FDR Q<0.01 for significance. Applicants identified 8 recurrent somatic arm level events in 157 of 538 patients (Fig. 1). GISTIC2.0^|l analysis yielded 4 significant arm level amplifications, including the previously described amplification of chromosome 8q (n=15) and trisomies of chromosomes 12 (n^:==72), 2p in 47 ), and 19 in 6) '^!i ' \ Applicants also identified a significant focal amplification peak at 2pl5 with 16 genes, which includes the CLL driver gene XPOl. Applicants noted that XPOl mutations and amplifications involving the 2p arm were mutually exclusive in our cohort. Recurrent arm level deletions included deifllp) (n=34), del(%p) (n 10} , <ie/(18p) (n=13) and ¾/(20p) (n^::=7) as previously described^20'"^'2. Focal deletions included the canonical fife/(13ql4.2) (n=255, containing mir-15a and mir-16-1), del(l lq22.3) (n=118, containing ATM), a large deletion in 6q21 (n=18) (with a peak region spanning 72MB)23, as well as expected deletions in the immunoglobulin (Ig) loci.

[0099] RNA sequencing and data analysis: RNA sequencing (RNAseq) was performed as previously described²⁴. In addition, previously published RNAseq data for additional CLL RNA samples were downloaded with permission from the European Genome-Phenome Archive²⁵, and processed in an identical fashion to the in-house produced libraries. In total, matching WES and RNAseq data were available for 156 samples including 103 samples collected at the DFCI and 53 samples collected by the ICGC. RNAseq BAMs were aligned to the hg!9 genome using the TopHat suite. Each somatic base substitution detected by WES was compared to reads at the same location in RNAseq. Based on the number of alternate and reference reads, a power calculation was obtained with beta-binomial distribution (power threshold used was greater than 90%). A mutation call was deemed negative if no alternate allele reads were observed in RNASeq at the site, as long as RN Aseq was powered to detect an event at the specified location. Differential gene expression analysis was performed for the novel two driver gene mutations which affect at least 5 samples with matched RNAseq and WES data (RPSJ5 [3 DFCI samples and 2 ICGC samples] and MGA [4 DFCI samples and 2 ICGC samples). Gene expression in transcripts per million (TPM) was quantified using the RSEM algorithm²⁶ (v 1.2.19). Significant batch effects were seen between the DFCI and ICGC samples and were addressed as described herein. After filtering non-expressed genes, gene expression was compared between samples with mutations in one of the studied driver genes and samples that are wild type for this gene. To address the significant batch affected, a generalized linear model (glm) was applied that includes both the mutation status and the batch information; and the P values for the mutation status coefficients were subjected to FDR correction (Q<0.1). Gene set enrichment analysis was performed using the GSEA software^{"' 7} (V2.2.0), with the pre-ranked list option. Genes were ranked based on the log transformed P values of the glm mutation coefficients.

[00100] Co-occurrence analysis: First, Applicants considered two potential important confounders: prior therapy and IGIiV mutation status, which may affect the proportion of patients affected by specific drivers (Extended Data Fig. 6A-B) resulting in spurious instances of significant low or high co-occurrence. Indeed, despite similar average numbers of coding mutations per sample (24.3 +/- 11.2 versus 23,0 +/- 13.4 in IGIiV mutated vs. unmutated samples, =0.246), the median number of driver mutations per sample was higher in the unmutated IGIIV subtype (3 [IQR 2-4] vs. 1 driver per sample [IQR 1-2], rank sum ^><0.00001, note that these do not include IGHV as a driver, as IGHV mutations may represent a physiologic process in B cells). Similarly, compared to treatment-nai^'ve cases, prior exposure to treatment was associated with an increased average number of coding sSNVs and slNDELs (34.9 +/- 22.7 vs. 23.0 +/- 1 1.4, P = 1.16 x 10^"'), and a higher median number of drivers (4 vs. 2, P = 3.55 x 10^{" 9}), Of note, to examine the explanation that higher number of mutations simply reflects a longer time from diagnosis to sampling of patients with prior therapy, linear regression model analysis to evaluate the impact of the time between diagnosis and sample acquisition on the association between prior therapy and the number of mutations and drivers was performed. Applicants found that in a model that included both time from diagnosis to sampling and prior therapy, only prior therapy retained significance in terms of a positive association with the number of mutations (P = 0,27147 and =0.00634, respectively) and in terms of a positive association with the number of drivers (P ^zzz: 0.201 and P^zzz 1.66e-10, respectively). Therefore, to address the effect of IGHV and prior therapy status, significant low or high co-occurrence patterns were retained if the combined P value²⁸ for the tests in the two subsets after multi-hypotheses correction was significant at Q< .1.

[00101] Estimation of mutation cancer cell fraction using ABSOLUTE: Applicants used the ABSOLUTE algorithm (vl . l.) to calculate the purity, ploidy, and absolute DNA copy- numbers of each sample²⁹, as previously described⁹. sCNVs were classified as clonal if the modal CCF estimate exceeded 0.85. Modifications were made to the algorithm for the purpose of assessing the clonaiity of sSNVs and sINDELs as follows. For each mutation, the CCF probability density is estimated based on the mutation reference and alternate allele counts (t_ref_count and t_alt_count, respectively), the tumor purity, and local copy number for each homologous allele. The first step is to calculate the allele fraction probability distribution for the tumor alone, excluding the contribution from the normal fraction of cells. The proportion of tumor DNA at a site is:

Tumor DNA fraction -(purity · CN_T)/( purity · CN_T + CN^ (I -purity))

Where CN_T is the local copy number in the tumor cell and CN_N is the local copy number in the normal cells (2 in the autosome, and 1 or 2 on the X chromosome depending on gender). The allele fraction probability density in the tumor is estimated from the binomial probability density "binopdf over the range of reference allele counts in the tumor "t ref between 0 and t_ref_count:

w(t ref) hiiiofkifii ref i alt count ref count +t alt count, Tumor DNA fraction) [00102] The probability distribution for the allele fraction in the tumor is then:

p(AF_T) =∑_t reffwft ref) · betapdffAFr alt count+l,i <_ref+l))/Z

[00103] Where AF_T is the full range of allele fractions from 0 to 1 and Z is set such that p(AFY) is normalized to 1.

[00104] At this point, ρ(Α1⁷τ) no longer contains the normal cell component, which simplifies the remaining steps to estimate the mutation cancer cell fraction (CCF). The CCF estimate is integrated over all possible mutation multiplicities "m", the number of mutations per tumor cell. The multiplicity m can range from 1 to q hat I or q hat2 (the local somatic absolute copy numbers of each homologous allele in the tumor). Applicants assume that the mutation occurred before or after any local copy number change and each possible multiplicity is given equal weight w_m such that the w's are normalized to 1. AF_T is transformed to CCF coordinates by CCF- AFfCNj/m and the probability density for CCF's ranging from 0 to 1 : p(CCF) -∑_m (w_si *p(AF_T)) foi- AFr* CN_T/m < 1 and iotAFr* CNt/m > 1, the probability density was accumulated at C F=/: piCCF^l) =∑_m (w_m * p(AFr'CNv'm)) for AFj'CNFm >--- 1

[00105] Clonal mutations were defined as sSNVs or sINDELs with p(CC7' 0,85)>0.5 (ie. median CCF. greater than 0.85).

[00106] Clustering analysis of sSNVs and sINDELs ie 59 CLL sample pairs: Applicants performed WES on matched samples collected at the time of first progression following therapy from 59 of 278 CLL8 subjects (Supplementary Table 9). The median time to progression was 35.1 months (range 5.9-75.5), with relapse samples collected at a median of 7.6 months following documented progression, ail before receipt of subsequent therapy. The two time point CCF clustering procedure was performed as previously described⁹. Clonal evolution between pretreatment and relapse samples was defined based on the presence of mutations with a P{ CCF > 0.1)>0.5. Branched evolution was classified when a dominant clone in the pre-treatment sample was replaced by sibling dominant clone. This pattern was indicated by a CCF decrease of the mutations in the pre-treatment dominant clone co-occurring with a CCF increase of mutations in the relapse dominant clone. In contrast, linear evolution (replacement of a parent clone by its progeny) was indicated when the increase in CCF of the relapse dominant clone was not ccompanied by a decrease in CCF of the pre-treatment dominant clone,

[00107] For the CLL driver analysis (Fig. SO), a significant change in CCF over time (red or blue) was determined if the 95% CIs of the CCF in the pre-treatment and relapse sample did not overlap. For each driver, a binomial test was performed to assess whether the proportion of instances within each category (increases, decreases, stable) significantly exceeded 0.5 (with a BH FDR correction, QO. l).

[00108] Deep sequencing of somatic single nucleotide variants Targeted deep sequencing was performed using microfluidic PGR (Access Array System, Fluidigm). Six unmatched saliva samples were included in this analysis to assist with the quantification of background sequencing error noise. Target-specific primers were designed to flank sites of interest and produce amplicons of 200 bp ± 20 bp. Per well, molecularly barcoded, lilumina-compatible specific oligonucleotides containing sequences complementary to the primer tails were added to the Fluidigm Access Array chip together with genomic DNA samples (20-50 ng of input) such that all amplicons for a given DNA sample shared the same index, and PGR was performed according to the manufacturer's instructions. From each individual collection well from the Fluidigm chip, indexed libraries were recovered for each sample, quantified using picogreen, and then normalized for uniformity across libraries. Resulting normalized libraries were loaded on the MiSeq instrument and sequenced using paired-end 150 bp sequencing reads³⁰. Applicants confinned the presence of a mutation in a sample if the fraction of alternate reads exceeded that in the normal control samples (beta binomial test, FDR Q<0.1).

[00109] Order of mutations analysis: To investigate the question of temporal ordering of driver appearance in CLL, the driver clonality patterns in the 501 of 538 samples which were treatment na^'ive were studied using the following approach: Whenever a driver event dl is clonal and another driver event d2 is subclonal in the same sample, this pattern indicates that dl was acquired before d2 (denoted by dl →d2), and allow us to draw an edge between these two drivers (out-going for dl, and in-going for d2). Assuming the temporal ordering of a driver pair is random, Applicants can apply hypothesis testing to find significant temporal orderings among drivers in this data set³¹. Applicants classified driver events as early, late or intermediary/not powered by counting the in-degrees and out-degrees of each driver event across the 501 samples and applying a two-tailed binomial test to quantify whether a driver event has a significantly greater number of out-degrees (early), a significantly greater number of in-degrees (late) or no significant preference (intermediary/not powered). To account for multiple hypothesis testing, Applicants additionally calculate the corresponding q-values as a measure of significance in terms of the false discovery rate³².

[00110] To infer a temporal order between any two pairs of drivers, all known CLL driver pairs were considered for which at least 5 clonal -subclonal orderings were observed, as this was the minimal number of observations powered for statistical significance (P<0.1) to detect a completel unidirectional relationship (i.e., d__l is clonal and d_2 is subclonal in all five pairing). Two-tailed binomial tests were used to quantify the confidence in the temporal ordering of each pair of driver mutations. To account for multiple hypothesis testing, the corresponding q-values were further calculated as a measure of significance in terms of the false discovery rate³². [00111] Statistical methods Statistical analysis was performed with MATLAB (MathWorks, Natiek, MA), R version 2.1 1.1 and SPSS version 21 (IBM, NYC, NY). Categorical variables were compared using the Pearson Chi-square test or Fisher Exact test as appropriate, and continuous variables were compared using non-parametric rank-sum tests. Statistical analyses of data from the CLL8 clinical trial were performed on an intention-to-treat basis meaning that all eligible subjects with available samples were analyzed as randomized. Time to event analyses were done for progression free survival (PFS), which was defined as the time from randomization to disease progression or death, and for overall survival (OS), which was understood as the time between randomization and death. Time to event data were estimated by the Kaplan-Meier method, and differences between groups were assessed using two-sided non- stratified log-rank tests. Additionally, hazard ratios (HR) and 95% confidence intervals (CI) were calculated using unadjusted and adjusted Cox regression modeling. Independent factors for PFS and OS were identified by multivariable analysis using Cox proportional hazards regression models.

Materials References

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* * *

[00112] Having thus described in detail preferred embodiments of the present invention, it is to be understood that the invention defined by the above paragraphs is not to be limited to particular details set forth in the above description as many apparent variations thereof are possible without departing from the spirit or scope of the present invention.

Claims

WHAT IS CLAIMED IS:

1. A method of treating chronic lymphocytic leukemia (CLL) in a subject in need thereof comprising identifying the presence of gene mutations and somatic copy number variations (CNV) in a genomic DNA sample obtained from the subject, wherein the mutated genes and somatic copy number variations (CNV) comprise del(13q), SF3B1, ATM, del(llq), tril2, TPS 3, NOTCH!, POT I, amp(2p), dei(17p), CHD2, XPOI, RPS15, BIRC3, BRAF, IGLL5, del(8p), MGA, MYD88, del(6q21), EGR2, FBXW7, amp(8q), DDX3X, KRAS, BCOR, 1KZF3, MAP2K1, ZMYM3, IRF4, SAMHD1, BAZ2A, CARD J 1, FUBPl, HIST1H1E, MED12, NRAS, NXFl, del (18p), DYRK1A, PTPNU, del(20p), ELF 4, TRAP 2, XP04, triI9, BRCC3, EWSR1, FAM50A, TRAP 3, ASXL1, CHEK.2, GNB1, HIST1H1B, and PIMJ, wherein the subject is treated if the presence of a mutated gene and/or somatic copy number variation (CNV) is identified.

2. The method according to claim 1, wherein the patient has stage 0 CLL.

3. The method according to claims 1 or 2, wherein the presence of mutations in NRAS, KRAS, BRAF^', and/or MAP2K1 indicate treating with an inhibitor of the MAPK-ERK pathway.

4. The method according to claim 3, wherein the mutation in BRAF is not V600E and wherein the treatment includes a MEK inhibitor and not a BRAF^' inhibitor.

5. The method according to claims 1 or 2, wherein the presence of mutations in RPS15 indicate an adverse outcome and the subject is treated with an alternative treatment regimen.

6. The method according to claims 1 or 2, wherein the presence of mutations in IKZF3 indicate an adverse outcome and the subject is treated with an alternative treatment regimen.

7. The method according to claim 6, wherein the mutation in IKZP3 is an L162R substitution.

8. The method according to claims 1 or 2, wherein the presence of mutations in deli^' !3q) . MYD88, and/or CFLD2 indicate decreased clinical aggressiveness.

9. The method according to claims 1 or 2, wherein the presence of mutations in TP53, SF3B1 and/or XPOI indicate shorter progression-free survival (PFS) and overall survival (OS),

10. The method according to any of claims 1 to 9, wherein the sample is obtained prior to treatment.

11. The method according to any of claims 1 to 10, further comprising determining mutations in /(;/// wherein the presence of unmutated IGHV indicates increased clinical aggressiveness and the presence of mutated IGHV indicates decreased clinical aggressiveness.

12. A method of determining whether a subject having chronic lymphocytic leukemia (CLL) would derive a clinical benefit of early treatment comprising determining the presence of gene mutations and somatic copy number variations (CNV) in a genomic DNA sample obtained from the subject, wherein the mutated genes and somatic copy number variations (CNV) comprise del/13q), SF3B1, A TM, del(llq), in 12, Ί 53, NOTCH 1, POT1, amp(2p), del(17p), CHD2, XPOl, RPS15, BIRC3, BRAF, IGLL5, del(8p), MGA, MYD88, del(6q21), EGR2, FBXW7, amp(8q), DDX3X, KRAS, BCOR, IKZF3, MAP2K1, ZMYM3, IRF4, SAMHDJ, BAZ2A, CARDll, FlJBPl, HISTTHIE, MED 12, NRAS, NXFl, del (18p), DYRK1A, PTPN! I, del(20p), ELF4, TRAF2, XP04, tril9, BRCC3, EWSRI, FAM50A, TRAF3, ASXLI, CHEK2, GNBl, HISTIHIB, and PIMI, wherein the presence of a mutated gene and/or somatic copy number variation (CNV) indicates that the subject would derive a clinical benefit of early treatment.

13. A method of predicting survivability of a subject having chronic lymphocytic leukemia (CLL) comprising determining the presence of gene mutations and somatic copy number variations (CNV) in a genomic DNA sample obtained from the subject, wherein the mutated genes and somatic copy number variations (CNV) comprise<3k/(73¾ , SF3BI, A TM,^' del/1 Iq), tril2, TPS 3, NOTCH 1, POT1, amp(2p), del/Up), CHD2, XPOl, RPS15, BIRC3, BMP, IGLL5, del(8p), MGA, MYD88, del(6q21), EGR2, FBXW7, amp(8q), DDX3X, KRAS, BCOR, IKZF3, MAP2K1, ZMYM3, IRF4, SAMHDl, BAZ2A, CARDll, FlJBPl, HISTIHIE, MED12, NRAS, NXFL del (18p), DYRK1A, PTPNll, delQQp), ELF 4, TRAF2, XP04, tril9, BRCC3, EWSRI, FAM50A, TRAF3, ASXLI, CHEK2, GNBl, HISTIHIB, and PIMI, wherein the presence of a mutated gene and/or somatic copy number variation (CNV) indicates that the subject is less likely to survive.

14. A method of identifying a candidate subject for a clinical trial for a treatment protocol for chronic lymphocytic leukemia (CLL) comprising determining the presence of gene mutations and somatic copy number variations (CNV) in a genomic DNA sample obtained from the subject, wherein the mutated genes and somatic copy number variations (CNV) comprise del(13q), SI- 311 !. AIM., del(llq), trill, TP 53, NOTCH!, POTl, amp(2p), del(17p), CHDl, XPOl, RI^JS15, BIRC3, BMP, IGLL5, del(8p), MGA, MYP 88, del(6q21), EGR2, FBXW7, ampfiq), DDX3X, KRAS, BCOR, IKZF3, MAP1K1, ZMYM3, IRF4, SAMHD1, BAZ2A, CARDll, FlJBPl, HIST1H1E, MED 12, NRAS, NXF1, del (I8p), DYRKIA, PTPN11, del(20p), ELF4, TRAF2, XP04, tril9, BRCC3, EWSR1, FAM50A, TRAF3, ASXL1, CHEK2, GNB1, HIST IE IB, and PIML wherein the presence of a mutated gene and/or somatic copy number variation (CNV) indicates that the subject is a candidate for the clinical trial.

15. A method of detecting chronic lymphocytic leukemia (CLL) in a subject comprising determining the presence of gene mutations and somatic copy number variations (CNV) in a genomic DNA sample obtained from the subject, wherein the mutated genes and somatic copy number variations (CNV) compri sodelf I3q), SF3B1, ATM, del(llq), trill, TP 53, NOTCH 1, POTl, amp(2p), del(17p), CHD2, XPOl, RPS15, BIRC3, BRAF, IGLL5, del(8p), MGA, MYD88, del(6q21), EGR2, FBXW7, amp(8q), DDX3X, KRAS, BCOR IKZF3, MAP2K1, ZMYM3, IRF4, SAMHD1, BAZ2A, CARDll, FlJBPl, HISTIHIE, MFD 12. NRAS, NXF1, del (18p), DYRKIA, PTPN11, del (20p), ELF 4, TRAFl, XP04, tril9, BRCC3, EWSRl, FAM50A, TRAF3, ASXIA, CHEK1, GNB1, HIST1H1B, and PIM1, whereby the presence of one or more mutations and/or CNV indicates that the subject has a greater than 90% probability of having CLL.

16. A method of identifying a subject at elevated risk of having CLL with rapid disease progression comprising:

(a) analyzing genomic DNA in a sample obtained from a subject having or suspected of having chronic lymphocytic leukemia (CLL.) for the presence of gene mutations and somatic copy number variations (CNV), wherein the mutated genes and somatic copy number variations (CNV) comynsodel/lSq), SF3B1, AIM, del(llq), iril2, TPS 3, NOTCH I POTl, amp(lp), del(17p), CHDl, XPOl, RPS15, BIRC3, BR iF, IGLL5, del(8p), MGA, MYD88, del(6qll), EGRl, FBXW7, amp(8q), DDX3X, KRAS, BCOR, 1KZF3, MAP IK 1, ZMYM3, 1RF4, SAMHDl, BAZIA, CARDll, FUBPl, HISTIHIE, MED 12, NRAS, NXF1, del (18p), DYRKIA, PTPNll, del(lOp), ELF4, TRAFl, XP04, tril9, BRCC3, EWSR1, FAM50A, TRAF3, ASXL1, CHEK1, GNB1, HIST1H1B, and TI I :

(b) determining whether the mutations and/or somatic copy number variations are clonal or subclonal, and (c) identifying the subject as a subject at elevated risk of having CLL with rapid disease progression if at least one mutation and/or somatic copy number variation is sub clonal.

17. The method according to claim 16, further comprising treating a subject identified as a subject at elevated risk of having CLL with rapid disease progression.

18. The method according to any one of claims 1 to 17, wherein mutations in more than one risk allele are analyzed.

19. The method according to any one of claims 1 to 18, wherein the method is performed before treatment.

20. The method according to any one of claims 1 to 18, wherein the method is performed after treatment.

21. The method according to any one of claims 1 to 20, further comprising repeating the method every 6 months or if there is a change in clinical status.

22. The method according to any one of claims 1 to 21, wherein the genomic DNA sample is obtained from peripheral blood, bone marrow, or lymph node tissue.

23. The method according to any one of claims 1 to 22, wherein the genomic DNA is analyzed using whole genome sequencing (WGS), whole exome sequencing (WES), single nucleotide polymorphism (SNP) analysis, deep sequencing, targeted gene sequencing, hybridization to an array, or any combination thereof.

24. The method according to any one of claims 16 to 23, wherein clonal or subclonal mutations, CNV's and/or populations of cells are detected using whole genome sequencing (WGS), whole exome sequencing (WES), single nucleotide polymorphism (SNP) analysis, deep sequencing, targeted gene sequencing, hybridization to an array, or any combination thereof.

25. The method according to any one of claims 1-24, wherein the gene mutation is a missense mutation, frameshift indel, inframe indel, splice site mutation, or nonsense mutation.