CN114736966A - Combined preparation for reversing breast cancer drug resistance and marker application - Google Patents
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- CN114736966A CN114736966A CN202210493537.0A CN202210493537A CN114736966A CN 114736966 A CN114736966 A CN 114736966A CN 202210493537 A CN202210493537 A CN 202210493537A CN 114736966 A CN114736966 A CN 114736966A
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Abstract
The invention discloses a combined preparation for reversing breast cancer drug resistance and a marker application. The invention determines that FGFR4 is an important driving gene for treating drug resistance of breast cancer HER2 by in vitro and in vivo whole genome CRISPR/Cas9 library screening. Inhibition of FGFR4 can significantly enhance the sensitivity of breast cancer to anti-HER2 therapy. Mechanistically, the level of RNA m6A hypomethylation modification in breast cancer drug-resistant cells mediates FGFR4 up-regulation, and FGFR4 drives the drug resistance of breast cancer to anti-HER2 treatment by phosphorylating GSK-3 beta and activating beta-catenin/TCF 4 signals. Furthermore, we found that anti-FGFR 4 and anti-HER2 had a synergistic effect in the treatment of drug-resistant breast cancer by patient-derived xenografts and organoid susceptibility testing. These results define the mechanism of resistance to anti-HER2 therapy and provide a novel strategy for overcoming resistance to anti-HER2 therapy in breast cancer by inhibiting FGFR 4.
Description
Technical Field
The invention relates to the field of breast cancer treatment, and in particular relates to a combined preparation for reversing breast cancer drug resistance and a marker application.
Background
Amplification and/or overexpression of human epidermal growth factor receptor 2(HER2) occurs in 14-30% of breast cancer cases, which are defined as HER2 positive breast cancers; this subtype is associated with poor survival outcomes. Trastuzumab (also known as Herceptin), the first human monoclonal antibody against HER2, significantly extended survival in patients with early or metastatic HER2 positive breast cancer. Despite the significant efficacy of trastuzumab, anti-HER2 resistance has become a major cause of treatment failure in HER2 positive breast cancer patients. Trastuzumab resistance is common in HER2 positive breast cancer patients receiving adjuvant therapy, with a 1-year recurrence rate of approximately 15% and a 10-year recurrence rate of over 31% after trastuzumab treatment in HERA trials. Median progression-free survival for advanced breast cancer patients treated with trastuzumab is approximately 11 months, with the majority of patients developing secondary resistance within one year after receiving trastuzumab therapy. Although a range of anti-HER2 drugs have been developed and put into clinical use, resistance remains in some patients. There is an urgent need to elucidate the underlying molecular mechanisms of resistance to HER2 and to develop new therapeutic strategies to overcome resistance.
Previous studies have revealed several molecular mechanisms of anti-HER2 resistance in HER2 positive breast cancer. First, loss of trastuzumab binding site on the extracellular domain of HER 2. For example, p95 HER2 truncated protein or MUC4 overexpression, respectively, resulted in loss of trastuzumab binding site and subsequently protected HER2 from being blocked from binding outside the membrane. Secondly, persistent activation of the HER2 downstream pathway is caused by dysregulation of downstream signaling components in breast cancer cells, including PIK3CA mutations or PTEN loss. Third, enhanced expression of Receptor Tyrosine Kinases (RTKs) results in compensatory activation of alternative signaling pathways. For example, IGF1R expression is upregulated in anti-HER2 resistant breast cancer and maintains intracellular signaling pathway activation following HER2 blockade. Fourth, tumor immune infiltration (TIL), including lymphocytes, dendritic cells and natural killer cells, is also involved in the resistance of anti-HER2 therapy. For example, endocytosis reduces the response to trastuzumab blockade by reducing ADCC mediation. Nevertheless, the complete picture of the molecular mechanisms underlying resistance to HER2 in breast cancer remains unclear. Most inhibitors developed against these targets failed to overcome anti-HER2 resistance in clinical trials. In addition, there is a lack of biomarkers that accurately predict patient response to treatment and risk of relapse following neoadjuvant and adjuvant anti-HER2 treatment. Therefore, identification of new effective drug resistance targets at the genome wide level, and providing new therapeutic strategies for HER2 resistant patients is an urgent task.
Disclosure of Invention
In the invention, in vitro and in vivo screening is carried out on a whole genome level by using a CRISPR/Cas9 library containing 123411 sgRNAs and targeting 20914 human genes, so as to search a target for overcoming the anti-HER2 drug resistance of breast cancer. By analyzing the screening results, we found a series of genes mediating breast cancer resistance to HER 2. Among these candidate genes and related proteins, fibroblast growth factor receptor 4(FGFR4) ranked high in the results of in vitro and in vivo screening. FGFR4, a receptor tyrosine kinase, plays an important role in promoting metastasis of various digestive system tumors, angiogenesis, chemotherapy resistance, dryness of cancer cells, and the like. Although FGFR4 is one of the aggregated genes contained in the 50 gene intrinsic subtype predictor (PAM50), little is known about the potential role of FGFR4 in breast cancer. Other FGFR family members are reported to be important mediators of resistance to HER 2. FGFR1 confers resistance to lapatinib, trastuzumab and TDM-1 to breast cancer. FGFR2 signaling serves as an escape pathway responsible for resistance to anti-HER2 therapy in breast cancer. An autocrine loop driven by FGFR3 maintains acquired trastuzumab resistance in HER2 positive gastric cancer. However, there is a lack of research to investigate the function of FGFR4 in anti-HER2 resistance. In our study, FGFR4 was found to be significantly upregulated in drug-resistant breast cancer, and patient-derived xenograft and organoid models revealed that Roblitinib (a selective inhibitor of FGFR 4; also known as FGF-401) was significantly effective in the treatment of endogenous and acquired anti-HER2 drug-resistant breast cancer. Thus, this study reveals a mechanism of breast cancer resistance to HER2 and provides a novel strategy to overcome this resistance by inhibiting FGFR4 in HER2 positive breast cancer.
Inhibition of FGFR4 enhances the sensitivity of breast cancer patients to anti-HER2 treatment. In mechanism, the RNA m6A hypomethylation level in drug-resistant cells regulates the FGFR4 to be up-regulated, the FGFR4 phosphorylates GSK-3 beta and activates beta-catenin/TCF 4 signals, and thus, the drug resistance of the anti-HER2 is driven. Notably, inhibition of FGFR4 significantly reduced glutathione synthesisAnd Fe passing through the beta-catenin/TCF 4-SLC7A11/FPN1 axis2+Efflux efficiency, leading to excessive production of ROS and accumulation of unstable iron pools. Iron death is a unique iron-dependent form of oxidative cell death that is triggered after FGFR4 is inhibited. Through patient-derived xenografts and organoid experiments, we found that anti-FGFR 4 and anti-HER2 have synergistic effects on the treatment of breast cancer with intrinsic or acquired resistance.
Drawings
Figure 1 is a genome-wide CRISPR screen identifying FGFR4 as a key gene for anti-HER2 resistance in breast cancer.
(a) A flow chart for screening HER2 resistance-related genes using geckov2.0 whole genome lentivirus sgRNA library. (b) Function and pathway enrichment analysis of the anti-HER2 drug resistance-related genes performed using Metascape. (c) A rank aggregation score (RRA) revealed background-dependent vulnerability in anti-HER2 resistant breast cancer. The blue dots represent the anti-HER2 resistance gene that has been reported in previous studies. (d) FGFR4 is highly expressed in HER2 positive breast cancers in the METABRIC database. Normal (n-140), lumen a (n-679), lumen B (n-461), HER2 positive (n-220), substrate-like (n-199). (e) Representative IHC staining images showed high or low expression of FGFR4 in 322 HER2 positive breast cancer tissues from SYSUCC. Scale bar 200 μm (low magnification) and 100 μm (high magnification). (f) Kaplan-Meier analysis of overall and recurrence-free survival of HER2 positive breast cancer patients in a SYSUCC cohort with high or low FGFR4 expression. (g) The IHC H score expresses FGFR4 in HER2 positive breast cancer specimens from (n ═ 80) or no (n ═ 252) relapsed patients. (h-1) representative images and h-scores of FGFR4 expression in different metastases of breast cancer after IHC staining. Scale bar 200 μm (low magnification) and 100 μm (high magnification). (j) Representative images of FGFR4 IHC staining in non-pCR and pCR breast cancer tissues after neoadjuvant therapy based on anti-HER 2. Samples were collected by core needle biopsy prior to treatment. Scale bar 200 μm (low magnification) and 100 μm (high magnification). (k) IHC H score of FGFR4 in non-pCR (n ═ 16) and pCR (n ═ 19) breast cancer samples. Data are expressed as mean ± s.d. (l) expression of FGFR4 in HER2 positive breast cancer samples from patients with (n ═ 19) or without pCR (n ═ 16). (m) receiver operating characteristic curve (ROC) depicts the accuracy in predicting pCR by detecting the expression level of FGFR4 prior to neoadjuvant therapy based on anti-HER 2.
Fig. 2 is a graph demonstrating the establishment and validation of an anti-HER2 resistant breast cancer cell line.
(a) A parent anti-HER2 sensitive HER2 positive breast cancer cell line was exposed to trastuzumab continuously for three months to establish anti-HER2 resistant cells. (b) Dose-response curves of parental (SKBR3, BT474 and AU565) and drug-resistant cells (rSKBR3, rBT474 and rAU565) after treatment with trastuzumab. Cell viability was measured using absorbance values at 450nm as determined by the CCK-8 assay. The group treated with vehicle (control) was defined as 100% relative survival. (c) Brightfield micrographs of cultured parental cells (SKBR3, BT474, and AU565) and cultured drug-resistant cells (rSKBR3, rBT474, and rAU565) treated with vehicle or trastuzumab (0.1 μ M) for 24 hours. Drug resistant cells were removed from trastuzumab for 4 weeks prior to the experiment. Scale bar 200 μm. (d) Trastuzumab inhibition of parental cells (SKBR3, BT474 and AU565) and drug-resistant cells (rSKBR3, rBT474 and rAU565) was evaluated for hours after 72 hours of treatment with trastuzumab (0.1 μm). Drug resistant cells were removed from trastuzumab for 4 weeks prior to the experiment. CCK-8 assays were performed to assess cell viability. (e-g) tumor-bearing mice established from parental (SKBR3, BT474 and AU565) and drug-resistant cells (rSKBR3, rBT474 and rAU565) were treated with vehicle or trastuzumab (20mg/kg, administered intraperitoneally). Tumor volumes were recorded every 7 days and tumor growth curves were plotted. Tumors were excised and weighed at the end of the experiment.
Figure 3 is a high expression of FGFR4 in HER2 positive breast cancer and correlated with poorer survival outcomes.
(a) Expression levels of FGFR family members in different molecular subtype breast cancers in the TCGA cohort. In addition to the high expression of FGFR4 in HER2 positive breast cancer, the expression level of FGFR family members in breast cancer was very low. (b) FGFR4 mRNA expression in HER 2-positive (TCGA n-78, METABRIC n-220) and non-HER 2-positive (TCGA n-867, METABRIC n-1538) breast cancers. (c) FGFR4 expression in HER2 positive breast cancer patients enrolled in the FinHER trial (panel n-102) and the che-LOB trial (panel n-88). FGFR4 expression was analyzed from tumors prior to treatment. (d) Expression of FGFR4 in a SYSUCC cohort in HER2 positive breast cancer samples with (n ═ 80) or without (n ═ 252) recurrence. Data were analyzed by log rank test. (e) Recipient operating characteristics plots the accuracy of FGFR4 expression in predicting recurrence following trastuzumab-based adjuvant therapy. (f) The proportion of FGFR4 that was highly expressed in various samples of breast cancer.
Figure 4 is that inhibition of FGFR4 enhanced the sensitivity of endogenous and acquired drug resistant HER2 positive breast cancer cell line to anti-HER2 treatment.
(a) Expression of FGFR4 was detected by qPCR in normal breast cell lines and breast cancer cell lines with different subtypes. (b) Expression of FGFR4 in parental (SKBR3, BT474 and AU565) and trastuzumab-resistant (rSKBR3, rBT474 and rAU565) cell lines. (c) Cells resistant to lapatinib, an anti-HER2 inhibitor, had higher levels of FGFR4 expression according to the CTRP database. Sensitive n 305. And the drug resistance n is 298. (d) The efficiency of FGFR4 overexpression was examined by qPCR. (e) Schematic representation of CRISPRi method for inhibiting FGFR4 expression. (f) The inhibitory efficiency of the three most effective sgrnas was verified by qPCR analysis. (g) FGFR4 protein was detected after transcriptional repression and observed under a confocal microscope. Scale bar 20 μm. (h-i) dose-response curves of trastuzumab-resistant cells (rSKBR3 and MDA-MB-361) carrying sg-NC or sg-FGFR4 constructs after treatment with trastuzumab. Cell viability was measured using absorbance values at 450nm as determined by the CCK-8 assay. The group treated with vehicle (control) was defined as 100% relative survival. (i) Dose-response curves of trastuzumab-sensitive cells (SKBR3 and BT474) carrying either an empty vector or FGFR4 overexpression vector construct following trastuzumab treatment. (j) Cell viability was measured in trastuzumab-resistant cells treated with vehicle (Veh), 0.5 μ M trastuzumab (Traz) and/or 0.5 μ M moblitinib (Rob, FGFR4 inhibitor). Synergy of anti-FGFR 4 with anti-HER2 therapy was assessed by combination index. (k) Real-time monitoring of viable cells was performed to assess the efficacy of trastuzumab and robinib in trastuzumab-resistant cells. (l) Colony formation assay of rSKBR3, MDA-MB-361 and MDA-MB-453 cells treated with vehicle or trastuzumab (0.5. mu.M) with increasing concentrations of Roblitinib. (m) the Mammosphere formation assay reveals the effect of an agent on inhibiting HER2 positive breast cancer stem cells. Scale bar 100 μm.
Figure 5 is FGFR4 inhibition conferring sensitivity of endogenous and acquired drug resistant cells to anti-HER2 treatment.
(a) Dose-response curves for trastuzumab-resistant cells (MDA-MB-453) carrying sg-NC or sg-FGFR4 constructs after treatment with trastuzumab. (b) Molecular structure of a highly selective FGFR4 inhibitor Roblitinib (also known as FGF-401). (c) Cell viability was measured in trastuzumab-sensitive cells treated with vehicle (Veh), 0.5 μ M trastuzumab (Traz) and/or 0.5 μ M mrobilitinib (Rob, FGFR4 inhibitor), respectively. Cell viability was measured using absorbance values at 450nm as determined by the CCK-8 assay. The group treated with vehicle (control) on day 0 was defined as 1 relative cell viability. Data were analyzed by one-way analysis of variance and multiple comparisons were performed. (d) Real-time monitoring of viable cells was performed to assess the efficacy of trastuzumab and robitinib in trastuzumab-resistant MDA-MB-453 cells. (e) The Mammosphere formation assay revealed a role for FGFR4 in protecting HER2 positive breast cancer stem cells from trastuzumab inhibition. Scale bar 100 μm. (f) Dose-response curves of sensitive cells (SKBR3) carrying either vector or FGFR4 overexpression construct after treatment with TDM-1 (left). Dose-response curves of resistant cells (rSKBR3) carrying sg-NC or sg-FGFR4 constructs after treatment with TDM-1 (right). (g) Dose-response curves (left) for sensitive cells carrying the vector or FGFR4 overexpression construct (SKBR3) after treatment with trastuzumab and pertuzumab in combination at a molar ratio of 1: 1. Dose-response curves (right) for drug-resistant cells carrying sg-NC or sg-FGFR4 constructs (rSKBR3) after treatment with trastuzumab and pertuzumab in combination at a molar ratio of 1: 1. (h) Dose-response curves (left) for sensitive cells carrying the vector or FGFR4 overexpression construct (SKBR3) after treatment with trastuzumab and tucatenib in combination at a molar ratio of 10: 1. Dose-response curves of drug-resistant cells carrying sg-NC or sg-FGFR4 constructs (rSKBR3) after treatment with trastuzumab and tucatenib in combination at a molar ratio of 10:1 (right). Cell viability was measured using absorbance values at 450nm as determined by the CCK-8 assay. The group treated with vehicle (control) was defined as 100% relative survival.
Figure 6 is a patient derived model revealing the efficacy of FGFR4 inhibitors in endogenous and acquired anti-HER2 resistant breast cancer.
(a-h) tumor-bearing mice established with rSKBR3 and MDA-MB-361 anti-HER2 resistant cells were treated with control vehicle, trastuzumab (20mg/kg, administered intraperitoneally), Roblitinib (30mg/kg, oral). Or a combination of both agents. a-b) photographs of the primary tumors harvested. c-d) recording the tumor volume every 3 days and plotting the tumor growth curve. e-f) representative bioluminescence of mice taken on day 36. g-h) weight of harvested xenograft tumors. Data are expressed as mean ± s.d., with each set of n-5. (i) Representative H & E and IHC stained images of MDA-MB-361 cell based tumors from the control vehicle and apotinib groups. (j) Schematic representation of the establishment of patient-derived xenografts (PDX) and patient-derived organoids (PDO) from endogenous and acquired trastuzumab-resistant breast cancer tissue in SYSUCC. (k-p) in vivo experiments in PDX models treated with vehicle, trastuzumab (20mg/kg, administered intraperitoneally), robitinib (30mg/kg, administered orally) or a combination of both agents. k-l) photographs of harvested PDX tumors. m-n) tumor volumes were recorded every 9 days and tumor growth curves were plotted. o-p) weight of harvested PDX tumors. Data are expressed as mean ± s.d., with n-3 for each group. (q) representative images of patient-derived organoids treated with a control vehicle, trastuzumab, apocynib, or a combination of both agents. (r) an established histological image of a patient-derived organoid. Scale bar 50 μm. (s) cell viability assay of patient-derived organoids treated with the corresponding agents.
Figure 7 is a patient derived model demonstrating the potent efficacy of the FGFR4 inhibitor apocynib for safety in trastuzumab-resistant HER2 positive breast cancer.
(a) Representative H & E and IHC stained images of rSKBR3 cell-based tumors from the control vehicle and apotinib groups. (b-c) quantifying IHC staining by H-scoring in vehicle and Apocyntinib groups. Data are expressed as mean ± s.d., with each set of n-5. (d-e) Roblitinib did not have significant toxicity to liver at this dose as detected by Tunel and H & e staining, indicating safety of clinical application. (f) HER2 expression was verified by IHC staining to confirm the origin of HER2 positive breast cancer organoids. Scale bar 20 μm.
Detailed Description
In order to make the present invention more clear and intuitive for those skilled in the art, the present invention will be further described with reference to the accompanying drawings.
Research method
Patient sample collection
The study was approved by the institutional research ethics committee at the center of tumor prevention and treatment, university of zhongshan and was conducted under the guidance of the declaration of helsinki. Retrospective analysis the center collected HER2 positive primary infiltrating breast cancer samples from 332 patients during 2010 to 2020 using anti-HER2 drug adjuvant therapy. After surgical acquisition of the tissue samples, formalin fixation and paraffin embedding were performed using standard methods. Breast tumor tissue cores were collected from each patient and used to construct tissue chips for further validation. Molecular subtypes were determined by Immunohistochemistry (IHC), and if the IHC result was moderately positive, HER2 status was further confirmed by Fluorescence In Situ Hybridization (FISH). Patients with no detailed active follow-up were excluded. Overall Survival (OS) is defined as the time from the date of diagnosis to the day of death for any cause or last follow-up. Recurrence-free survival (RFS) is defined as the time from the date of diagnosis to the date of first recurrence or last follow-up. For specimens from neoadjuvant patients, HER2 positive tumor samples were obtained from 36 breast cancer patients, followed by pre-operative neoadjuvant chemotherapy using trastuzumab-based protocols and taxanes according to NCCN guidelines. Pathologically complete response (pCR) is defined as the absence of infiltrating tumor cells when the primary tumor is microscopically examined during surgery. The response assessment criteria in solid tumor version 1.1(RECIST 1.1) were used as criteria for assessing tumor response to treatment regimens. Informed consent was obtained from all subjects.
Cell lines and reagents
Human breast cancer cell lines (MDA-MB-453, MDA-MB-361, SKBR3, BT474, AU565, MCF-7, T47D, ZR-75-1, MDA-MB-231, BT549, MDA-MB-468 and SUM-159), normal breast epithelial MCF-10A cell lines and HEK293T cell lines were purchased from American Type Culture Collection and cultured according to the manufacturer's instructions. rSKBR3, rBT474 and rAU565 cells were developed by three months of exposure and selection with 1 μ M trastuzumab. The obtained trastuzumab-resistant cell lines were continuously cultured in a conventional medium containing trastuzumab, which was removed four weeks before the experiment. Cell lines were passaged for no more than six months and identified by STR analysis. No mycoplasma infection was found in any cell lines. Trastuzumab, pertuzumab, TDM-1 was obtained from Roche (Basel, Switzerland). Tucotinib (T2364) was purchased from TOPSCIENCE. The FGFR4 selective inhibitor, robitinib (Roblitinib/FGF-401, HY-101568), was purchased from MedChemexpress.
In vitro and in vivo screening of drug-resistant genes by CRISPR/Cas9 library
A total of 2.4 million trastuzumab-resistant rSKBR3 cells were seeded into 20 15cm plates and infected with a geckov2.0 lentivirus library. Human lentivirus library with MOI of 0.3 (coverage over 300-fold) to ensure that most cells take up only one stable short guide rna (sgrna). Puromycin (1. mu.g/ml) was added to the cells 24 hours post infection and maintained in culture for 4 days. Then, the cells were divided into four groups at the same density. Of these four groups, two were used for in vitro screening and two for in vivo screening. Mutant trastuzumab-resistant rSKBR3 cells were treated with vehicle or trastuzumab (1 μ M for in vitro screening; 20mg/kg for in vivo screening) for 2 weeks. After drug selection, cells and tumors were collected from each group, and genomic DNA was isolated using a DNA extraction kit (Omega, D3396). The sequence of the sgRNA was amplified by PCR and the product was purified prior to sequencing. Drug-resistant genes were identified from sgRNA screening sequencing results using MAGeCK analysis. The MAGeCK algorithm can prioritize drug resistance genes by comparing sgrnas in trastuzumab-treated cells/tumors to sgrnas in vector-treated cells/tumors. Briefly, read counts for each sgRNA from different samples were normalized to adjust the effect of library size and read count distribution. Drug-resistant genes were subsequently identified by finding genes with sgrnas consistently ranked higher using Robust Rank Aggregation (RRA). Genes with smaller RRA values ranked higher in the knockout screen.
RNA isolation, quantitative real-time PCR (qPCR) and sequencing analysis
TRIzol reagent (Invitrogen) was used to extract total RNA from cells and tissues. After completion of reverse transcription, RNA expression levels were checked by qPCR in triplicate on Bio-Rad CFX96 using SYBR Green kit (Takara, RR 420A). rSKBR3 breast cancer cells (2X 10) from sg-NC or sg-FGFR4 group using TRIzol reagent (Invitrogen)6) Total RNA was extracted for sequencing analysis. After assessing RNA integrity, mRNA libraries were generated by CapitalBio Technology (beijing, china) and sequenced. NEB Next Ultra RNA library preparation kit (NEB) for Illumina was used to construct libraries for sequencing. All next generation sequencing experiments were performed on an Illumina NovaSeq sequencer (Illumina). The Differentially Expressed Genes (DEG) were then screened and Y cells were generated using | log2FC>1 and FDR<The 0.05 standard was used for identification. The DAVID tool was used to perform Gene Ontology (GO) and kyoto gene and genome encyclopedia (KEGG) pathway enrichment analyses. Using the GSEA4.1.0 desktop application, a Gene Set Enrichment Analysis (GSEA) was applied to identify pathways significantly enriched between the two groups.
Immunohistochemistry (IHC) and hematoxylin-eosin (H & E) staining
IHC staining was performed using paraffin embedded tissue as described previously. Section slides with tissue were dewaxed in xylene and rehydrated by gradient ethanol (100%, 95%, 85% and 75% dilutions). Blocking of endogenous peroxidase activity and antigen retrieval was performed prior to overnight incubation with primary antibody at 4 ℃. After incubation with secondary antibody (HRP conjugated) for 20 min at room temperature, staining was performed with Diaminobenzidine (DAB) substrate (Dako). Sections were stained with hematoxylin after DAB treatment. The antibodies used are listed in supplementary table 6. The staining intensity of each section was scored as 0 (no staining), 1+ (weak staining), 2+ (moderate staining) or 3+ (strong staining), and the percentage of positive cells was determined from five different random areas. Expression was quantified using H-scoring (score range, 0 to 300). H-score from 0 to 200 was considered low expression, and H-score from 201 to 300 was designated high expression. For H & E staining, sections were immersed in hematoxylin for 3 minutes, washed with water for 30 minutes, and stained with eosin for 3 minutes. After dehydration in ethanol at various concentrations, the slides were covered with coverslips. Stained slides were imaged under light microscopy (NIKON ECLIPSE80 i).
Cell viability and colony formation assays
Cell viability was assessed using the Cell Counting Kit-8 Kit (Dojindo, Japan). Briefly, 1X 103Individual cells were seeded into 96-well plates. A CCK-8 solution (10. mu.L) mixed with medium was added to each well on a specific day. After incubation for 2 hours at 37 ℃, the absorbance at 450nm was measured using a microtiter plate reader. The CompuSyn software was used to assess the synergy of FGFR4 and HER2 inhibition. Synthetic lethal effects are indicated if the Combination Index (CI) is below the value 1. For colony formation assays, 1X 103Individual cells were seeded in 24-well plates. After 24 hours, different concentrations of drug were added to specific wells to test the sensitivity of the cells. The cell colonies were fixed with methanol and stained with 0.3% crystal violet before photographing.
Breast cancer stem cell globulogenesis assay
Balloon formation assays were performed as previously described. Will be 5X 10 in total3The cells were resuspended in DMEM/F-12 medium (Gibco) containing B27 supplement (Gibco), basic fibroblast growth factor (bFGF) (Invitrogen), EGF (Invitrogen), and insulin (Sigma) and plated in ultra-low adhesion 6-well plates. Cells were cultured for 7 days and the diameter counted>100 μ M mammosphere.
Construction and transfection of vectors
For CRISPRi inhibition of FGFR4, we constructed sgrnas targeting the FGFR4 promoter sequence and dCas9-KRAB fusion protein using a lentivirus-based plasmid (Addgene, # 71236). The sequences of all vectors were verified by Sanger sequencing. Cells were transfected using Lipofectamine 3000 (Invitrogen).
Patient-derived organoid (PDO) culture and drug sensitivity assays
Fresh breast cancer tissue was excised and digested with 2mg/ml collagenase (Sigma) on an orbital shaker at 37 ℃ for 2-6 hours. After centrifugation and resuspension of the cells, they were seeded in Matrigel (Corning, 356255). Into 24-well plates and supplemented with advanced DMEM/F12(Gibco), B27 supplement (Gibco), hepes (Sigma), Glutamax (Gibco), Nicotinamide (Sigma), Y-27632(Abmole), N-acetylcysteine (Sigma), A83-01(Tocris), SB202190(Sigma), R-spondin 1(R & D), basic fibroblast growth factor (bFGF) (Invitrogen), EGF (Invitrogen), Noggin (R & D) and penicillin/streptomycin (Gibco). After 1-3 weeks of culture, the number of breast cancer organoids was counted and passaged. For drug sensitivity assays, ATP was measured as a representative of viable cells using CellTiter-Glo 3D reagent (Promega, G9682). After lysing the cells with 3D reagents, the plates were shaken at room temperature for 30 minutes and the luminescence detected.
Drug sensitivity test for animals
Four week old female BALB/c nude mice and NOD-SCID mice were purchased from Beijing vitamin River Laboratories Animal Technology. Luciferase-tagged rSKBR3 and MDA-MB-361 cells (1X 10) mixed with 1:1 matrigel (Corning, 356237)7Individual cells) were injected subcutaneously into the fat pad of mice. After palpable tumors, mice were randomized into four groups (five mice per group) and treated with control vehicle, trastuzumab (20mg/kg, administered intraperitoneally), Roblitinib (30mg/kg, administered orally) or a combination of both drugs. Tumor volume was measured every 3 days, and according to the formula, the volume is length x width2The volume is estimated 2. To visualize tumor size, 150mg/kg D-fluorescein potassium salt (ATT Bioquest) was injected intraperitoneally into mice 10 minutes prior to imaging. Mice were sacrificed at the end of the experiment, xenografts excised, weighed and photographed. To construct the PDX model, fresh breast cancer samples from patients were subcutaneously inoculated into NOD-SCID mice. When the PDX built up reaches about 500mm3At that time, the tumor was transplanted to other mice. After tumors were palpable, mice were randomized to test the efficacy of treatment with trastuzumab and Roblitinib, alone or in combination. All mice were kept under specific pathogen free conditions in the animal facility at the center of tumor control at the university of zhongshan. They were kept in an animal chamber with a 12 hour light and dark cycle at a temperature of 20-22 deg.C and humidity40-70 percent. The maximum allowed tumor diameter was 15 mm. The tumor weight was no more than 10% of the mouse body weight. All animal procedures were approved by the Institutional Animal Care and Use Committee (IACUC) at the center for tumor control at the university of zhongshan.
Statistical method
All experiments were performed at least three times for immunofluorescence staining, immunohistochemical staining, mammosphere formation assay, western blot assay and DNA agarose gel blot showing representative images. Data were analyzed using SPSS 25.0 software. Unpaired student t-test was used to analyze the differences between the two groups. Comparisons between groups were analyzed using one-way ANOVA. Survival curves are described by Kaplan-Meier plots and compared to the log rank test. Results are expressed as mean ± standard deviation. All box plots represent the median, 25 th and 75 th percentiles, and the minimum and maximum values. P <0.05 was considered statistically significant.
Results of the study
First, genome-wide CRISPR screening identifies FGFR4 as a key gene for anti-HER2 drug resistance in breast cancer
Trastuzumab-based anti-HER2 regimen is the standard treatment modality for HER2 positive breast cancer treatment. Therefore, we generated anti-HER2 resistant cells by exposing trastuzumab-sensitive HER2 positive breast cancer cell lines SKBR3, BT474 and AU565 to trastuzumab continuously for 3 months in vitro (fig. 2 a). The anti-HER2 resistant cell lines rSKBR3, rBT474 and rAU565 showed higher IC 50 values for trastuzumab and undisturbed proliferation than their respective parental cell lines (fig. 2 b). Bright field micrographs of cultured parental cells and resistant cells treated with vehicle or trastuzumab are shown in fig. 2 c. After four weeks of trastuzumab withdrawal, the resulting rSKBR3, rBT474, and rAU565 cells maintained stable resistance to HER2 (fig. 2 d). In addition, in vivo experiments demonstrated that the drug-resistant cell line was significantly resistant to trastuzumab treatment (fig. 2 e-g). To identify the vulnerability of trastuzumab-resistant breast cancer cells, we performed a whole genome CRISPR screen of rSKBR3 cells with a sgRNA lentiviral library containing 123411 sgrnas targeting 20914 individual genes (fig. 1 a). To ensure accuracy of the loss-of-function genetic screen, in vitro and in vivo selection was performed. In this screening strategy, cells carrying sgRNA-targeted genes critical for viability will be depleted under trastuzumab therapeutic conditions (i.e., drug resistance genes). After high throughput screening, 1052 genes and 1032 genes were identified after in vitro and in vivo selection, respectively. Among them, several identified genes have been reported (IGF1R, SRC, PIK3CA, CTNNB1, CCNE1, FOXM1, CDK12, etc.). The applicability of our screening method was demonstrated in previous studies as a robust anti-HER2 drug resistance gene. The functional and pathway enrichment analysis of these resistance genes was further performed in Metascape, where FGFR signaling is one of the most important pathways involved in resistance to HER2 (fig. 1 b). FGFR4 is highly ranked in both in vitro and in vivo screens as one of the core family members of the FGFR signaling pathway (fig. 1 c). FGFR4 is a druggable target; the first highly selective and potent inhibitor developed for this protein is Roblitinib (FGF-401). Roblitinib showed promising clinical efficacy and favorable safety profile in phase II clinical trials for the treatment of hepatocellular carcinomas and solid tumors with high FGFR4 expression. Therefore, we selected FGFR4 for further study to verify whether it could be a target to overcome anti-HER2 resistance in breast cancer. FGFR4 mRNA was highly overexpressed in HER2 positive breast cancers according to the TCGA and METABRIC databases (fig. 1d and fig. 3 a-b). FGFR4 was highly expressed in the relapsed group (FinHER trial) and the non-pathological complete remission (non-pCR) group (CHER-LOB trial) after anti-HER2 adjuvant therapy and neoadjuvant therapy (fig. 3 c)). FGFR4 expression was detected in 332 HER2 positive breast cancers that received adjuvant anti-HER2 treatment in the SYSUCC cohort (fig. 1 e). In the SYSUCC cohort, high expression of FGFR4 was associated with poor relapse-free survival and overall survival (fig. 1 f). Patients with high FGFR4 tumors had a higher postoperative recurrence rate (fig. 1g and fig. 3 d-e). Further univariate and multivariate Cox regression analyses showed FGFR4 expression to be an independent risk factor for HER2 positive breast cancer patients. To verify the expression level of FGFR4 in advanced breast cancer, we collected specimens from different recurrent or metastatic sites. Metastatic tumors showed higher FGFR4 expression compared to primary breast cancer, especially brain metastases of breast cancer (fig. 1h-i and fig. 3 f). To examine whether FGFR4 expression correlates with intrinsic anti-HER2 resistance, we performed IHC staining using 36 HER2 positive breast cancer biopsies obtained prior to administration of anti-HER 2-based neoadjuvant therapy (fig. 1 j). FGFR4 expression was higher in non-pCR tumor patients than in pCR tumor patients (FIG. 1 k-l). In addition, the recipient operational profile indicated that FGFR4 expression could be used as a predictor of pCR prior to neoadjuvant anti-HER2 treatment (fig. 1 m).
Second, inhibition of FGFR4 enhances the sensitivity of drug-resistant HER2 positive breast cancer cell lines to anti-HER2 treatment
FGFR4 mRNA was expressed at low levels in normal breast epithelial cells (MCF-10A) and triple negative breast cancer cell lines (FIG. 4 a). Essentially anti-HER2 drug-resistant HER2 positive cell lines (MDA-MB-453 and MDA-MB-361) had higher FGFR4 expression levels compared to HER2 positive cell lines (SKBR3, BT474 and AU565) that were resistant to HER2 (fig. 4 a). Consistently, FGFR4 mRNA levels were significantly higher in the obtained anti-HER2 drug-resistant HER2 positive cell lines (rSKBR3, rBT474 and rAU565) than in their corresponding parental cell lines (fig. 4 b). Cells with resistance to lapatinib (an anti-HER2 inhibitor) had higher levels of FGFR4 expression according to the Cancer Treatment Response Portal (CTRP) database (fig. 4 c). To explore the role of FGFR4 in driving anti-HER2 resistance, we established a FGFR4 overexpression model in anti-HER2 sensitive breast cancer cells (fig. 4 d). To better mimic the effect of small molecule inhibitors, FGFR4 expression was inhibited in anti-HER2 resistant cells using the dCas9-KRAB CRISPRi technique (fig. 4 e). The transcriptional inhibition of CRISPRi was shown to have a very high efficiency in inhibiting FGFR4 expression by qPCR and immunofluorescence analysis (fig. 4 f-g). Trastuzumab sensitivity was assessed following FGFR4 intervention as a basis for anti-HER2 regimens. Trastuzumab resistance reversed significantly after inhibition of FGFR4 in cells with intrinsic (MDA-MB-453 and MDA-MB-361) or acquired (rSKBR3) resistance (FIGS. 4h and 5 a). Furthermore, exogenous overexpression of FGFR4 conferred resistance to trastuzumab by SKBR3 and BT474 cell lines (fig. 4 i). Roblitinib is an FGFR4 selective inhibitor for further evaluation (fig. 5 b). Roblitinib showed potent antitumor effects on trastuzumab-resistant cells (fig. 4j and fig. 5 c). In addition, the combination of trastuzumab and robitinib showed a synergistic effect in trastuzumab-resistant cells with a combination index below the value 1 (fig. 4 j). Real-time monitoring further confirmed the combined effect of trastuzumab and Roblitinib in the treatment of trastuzumab-resistant HER2 positive breast cancer cells (fig. 4k and fig. 5 d). Co-treatment with trastuzumab and Roblitinib resulted in a significant reduction of colony formation in cells with intrinsic or acquired resistance in a concentration-dependent manner (FIG. 4 l). This combination decreased the characteristics of the stem cells, the ability to form mammospheres, suggesting that it decreased stem cells, which is associated with relapse/metastasis. (FIG. 4m and FIG. 5 e). Next, we further investigated the effect of FGFR4 on the sensitivity of other anti-HER2 drugs currently used in the clinic. Trastuzumab emtansine (TDM-1) is an antibody-drug conjugate (ADC) approved as the second line therapy for HER2 positive metastatic breast cancer. Exogenous overexpression of FGFR4 reduced the sensitivity of SKBR3 cell line to TDM-1, while FGFR4 inhibition increased the sensitivity of rSKBR3 cell line to TDM-1 treatment (FIG. 5 f). Trastuzumab plus pertuzumab strategy is the current standard of care for HER2 positive breast cancer adjuvant therapy, neoadjuvant therapy and metastatic therapy. As a tyrosine kinase inhibitor targeting HER2, tucatenib was used with trastuzumab for metastatic HER2 positive breast cancer. We found that FGFR4 reduced the sensitivity of HER2 positive breast cancers to trastuzumab plus pertuzumab or tucatenib (fig. 5 g-h). Therefore, inhibition of FGFR4 may be a strategy to increase sensitivity to various anti-HER2 strategies in breast cancer.
Thirdly, the patient-derived model discloses the curative effect of the FGFR4 inhibitor in endogenous and acquired anti-HER2 drug-resistant breast cancer
The antitumor efficacy of the FGFR4 inhibitor Roblitinib was further verified in endogenous and acquired trastuzumab-resistant breast cancer models. First, mice bearing rSKBR3 and MDA-MB-361 tumors were treated with vehicle, trastuzumab, Roblitinib or combination agents (FIGS. 6 a-b). The robitinib-treated group had a reduced tumor volume compared to the trastuzumab-treated group. The combination of trastuzumab and robitinib showed synergistic antitumor effect in trastuzumab-resistant breast cancer (fig. 6 c-h). As shown by IHC staining, FGFR4 inhibition significantly reduced the levels of p-GSK-3 β, active β -catenin, SLC7A11, FPN1 and the cell proliferation marker Ki67 (FIG. 6i and FIGS. 7 a-c). To better validate the efficacy of Roblitinib, patient-derived xenograft (PDX) and organoid (PDO) models were established (fig. 6 j). One successful culture model among these is derived from non-pCR breast cancer tissue specimens obtained after trastuzumab-based neoadjuvant therapy, which reflects the biological characteristics of intrinsic anti-HER2 resistant breast cancer. Another model representative of acquired anti-HER2 resistant breast cancer was established in patients with liver metastases found 18 months after adjuvant trastuzumab treatment. The tumor volume and weight of the tissues from the group of combination treatments (trastuzumab and Roblitinib) were significantly reduced compared to the vehicle, trastuzumab and Roblitinib groups (FIG. 6 k-n). In addition, we examined the toxicity of the drug to mouse liver (FIG. 7 d-e). Next, we evaluated the effect of Roblitinib in overcoming anti-HER2 resistance in organoids (FIG. 6 q-r). To rule out the possibility of contamination with hepatocytes and normal mammary epithelial cells, patient-derived organoids were validated as HER2 overexpressing breast cancer organoids prior to the experiment (fig. 7 f). The combination of trastuzumab and robitinib significantly attenuated the growth of established trastuzumab-resistant breast cancer organoids (FIG. 6 s). Taken together, these findings indicate that FGFR4 inhibition can restore sensitivity of drug-resistant breast cancer cells to anti-HER 2. The combination of anti-HER2 and anti-FGFR 4 may be a broadly effective therapy against both intrinsic and acquired resistant breast cancer.
Conclusion
1. Full-genome CRISPR screening for determining that FGFR4 is key drug resistance gene for resisting HER2 drug resistance in breast cancer
Detecting the expression level of FGFR4 in a tissue after operation, and predicting the recurrence risk and the total survival time of a patient after anti-HER2 adjuvant therapy;
the tissue FGFR4 expression quantity is detected before operation, and the complete remission rate of a patient after anti-HER2 new adjuvant therapy can be predicted.
2. Inhibition of FGFR4 can enhance the sensitivity of drug-resistant HER2 positive breast cancer cell lines to anti-HER2 treatment
FGFR4 is knocked down in drug-resistant breast cancer cells, so that drug resistance can be reversed, and the sensitivity of the drug-resistant breast cancer cells to anti-HER2 treatment is recovered;
with FGFR4 inhibitors (Roblitinib), drug resistance can be reversed, restoring sensitivity to anti-HER2 treatment.
M6A hypomethylation mediates upregulation of FGFR4 in anti-HER2 resistant breast cancer
It was found that a decrease in the methylation level of m6A in drug-resistant cells resulted in an increase in the stability of FGFR4 mRNA and an upregulation in the expression level of FGFR 4.
FGFR4 phosphorylation of GSK-3 to modulate beta-catenin/TCF signaling and drive anti-HER2 drug resistance
5. Patient derived models show that the use of the FGFR4 inhibitor Roblitinib can increase the sensitivity of anti-HER2 resistant breast cancer to HER2 inhibitors
(by PDX, organoid model, it was demonstrated that FGFR4 inhibitor (Roblitinib) can reverse drug resistance and restore sensitivity to anti-HER2 treatment).
The embodiments described above are presented to enable those skilled in the art to make and use the invention. It will be readily apparent to those skilled in the art that various modifications to these embodiments may be made, and the generic principles described herein may be applied to other embodiments without the use of the inventive faculty. Therefore, the present invention is not limited to the embodiments described herein, and those skilled in the art should make improvements and modifications to the present invention based on the disclosure of the present invention within the protection scope of the present invention.
Claims (8)
- Application of FGFR4 as a HER2 positive breast cancer drug resistance marker.
- 2. The application of the reagent for detecting the content of FGFR4 or the expression level of FGFR4 gene in tissues in preparing a product for evaluating the prognosis condition of a HER2 positive breast cancer patient.
- The application of an FGFR4 inhibitor or an FGFR4 gene expression inhibitor in a product for reversing or eliminating drug resistance of HER2 positive breast cancer patients.
- Application of an FGFR4 inhibitor or an FGFR4 gene expression inhibitor in preparation of a product for improving prognosis of HER2 positive breast cancer patients.
- 5. The use of claim 2 or 4, wherein the prognostic profile includes risk of recurrence and overall survival of HER2 positive breast cancer patients.
- 6. A preparation composition for reversing breast cancer drug resistance is characterized by comprising an anti-HER2 drug and an FGFR4 inhibitor or an FGFR4 gene expression inhibitor.
- 7. The formulation composition of claim 6, wherein the anti-HER2 drug is selected from at least one of Trastuzumab (Trastuzumab), Pertuzumab (Pertuzumab), Enmetuzumab (TDM-1), Lapatinib (Lapatinib), and Tucatinib (Tucatiniib).
- 8. The formulation composition of claim 6 or 7, wherein the FGFR4 inhibitor is robitinib (Roblitinib).
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