CN105243293A - Prostate related cancer gene information collection and analysis method - Google Patents
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Abstract
The invention relates to a prostate related cancer gene information collection and analysis method. The invention provides a prostate related cancer gene information collection and analysis system. Through collecting all the data related to the prostate cancer in the existing database, a bioinformatics method is utilized to carry out confluence analysis on the prostate cancer mRNA and miRNA high-throughput transcriptome data, and a prostate cancer diagnostic marker suitable for clinic application is obtained on the basis of large-sample big data processing.
Description
Technical field
The present invention relates to B ioinformation data management field, be specifically related to prostate Related oncogene information and analytical approach.
Background technology
Prostate cancer (prostatecancer) is common male genitourinary tract infections tumour.Up to now, the mechanism that prostate cancer occurs to develop it be unclear that.High-throughput techniques is that the research of disease pathogenesis provides more comprehensively and analysis means fast, therefore a large amount of scholar utilizes genetic chip or mRNA and the miRNA transcript profile of high throughput sequencing technologies to prostate cancer to study, but, each researchist or laboratory are due to limited material or the limited sequencing analysis that only can complete small sample of funds, but in the pathogenic process of cancer, cancer cell obtains the accumulation of survival advantage, continuous amplification, surrounding tissue environment is produced and infiltrates, the genetic structure that the process need series of genes of diffusion occurs changes, and need the process of large sample data greatly to obtain more accurately to researchs of these changes.
The present invention is by collecting data relating to prostate cancer all in existing database, mRNA and the miRNA high flux transcript profile data of bioinformatics method to the prostate cancer of collecting are utilized to carry out confluence analysis, thus the pathogenesis of prostate cancer is probed into, for its Diagnosis and Treat provides certain Research foundation.For the exploitation of later stage drug target provides reference.
Summary of the invention
The object of the present invention is to provide a kind of prostate Related oncogene information and analytic system, comprise data acquisition module, data analysis module and data disaply moudle, data acquisition module sends data analysis module to after collecting data, data analysis module is shown by data disaply moudle after carrying out Machining Analysis to data, and described data acquisition module comprises DNA data acquisition module, RNA data acquisition module and protein data acquisition module.
Further, described DNA data are genomic data, and described RNA data are transcript profile data, and described protein data is proteomic data.Data are high-flux sequence data, comprise chip order-checking and the order-checking of two generations.
Further, described DNA data acquisition module comprises mutational site acquisition module, methylation sites acquisition module, SNP site acquisition module; Described RNA data acquisition module comprises mrna expression acquisition module, miRNA expresses acquisition module, lncRNA expresses acquisition module; Protein data acquisition module comprises protein expression profiling data acquisition module.
Described sudden change comprises the point mutation caused by single sequence change, or the disappearance of multiple base, repetition and insertion.
Further, described data analysis module comprises difference expression gene analysis module, prediction target spot analysis module, biological information net analysis module, GO analysis module, pathway analysis module.
Further, the analysis of described biological information net comprises biological information network, the biological information network between gene and gene, the biological information network between gene and albumen of differential expression miRNA and target gene foundation.
Further, described prediction target spot analysis and utilization comprises DIANAmT, the target spot of these algorithm predicts differential expressions of miRanda, miRDB, miRWalk, PICTAR5 and Targetscan miRNA, preferably >=4 algorithm predicts target spot out.
Further, from data with existing storehouse, download mutational site data, methylation sites data, SNP site data, mrna expression data, miRNA expression data, lncRNA expression data, protein expression profiling data that prostate cancer is relevant.
Further, data acquisition module downloads sequencing data from GEO database, SRA database, ICGC database.
Further, described prostate Related oncogene information and analytic system also comprise data preprocessing module, and data acquisition module sends data analysis module to after carrying out background correction and standardization by data preprocessing module after collecting data.
The object of the present invention is to provide a kind of prostate Related oncogene information and analytical approach, comprising:
(1) from data with existing storehouse, download prostate cancer sample order-checking raw data and check sample order-checking raw data;
(2) background correction and standardization are carried out to the raw data downloaded;
(3) to data analysis;
(4) display analysis result.
Further, the analysis of difference expression gene prediction target spot, the analysis of biological information net, GO analysis, pathway analysis are carried out to data.
Further, the analysis of described biological information net comprises biological information network, the biological information network between gene and gene, the biological information network between gene and albumen of differential expression miRNA and target gene foundation.
Further, described prediction target spot analysis and utilization comprises DIANAmT, the target spot of these algorithm predicts differential expressions of miRanda, miRDB, miRWalk, PICTAR5 and Targetscan miRNA, preferably >=4 algorithm predicts target spot out.
Preferred employing R software carries out transcript profile data analysis.
Further, from data with existing storehouse, download mutational site data, methylation sites data, SNP site data, mrna expression data, miRNA expression data, lncRNA expression data, protein expression profiling data that prostate cancer is relevant.
Further, from GEO database, SRA database, ICGC database, sequencing data is downloaded.
The object of the present invention is to provide one group of prostate cancer diagnosis and treatment mark, comprise miRNA:hsa-miR-183, hsa-miR-153, hsa-miR-96, hsa-miR-25, hsa-miR-93, hsa-miR-182, hsa-miR-663, hsa-miR-106b, hsa-miR-130b, hsa-miR-18a; And/or mRNA:SIM2, HPN, AMACR, MYC, OR51E2, BICD1, DNAH5, PCA3, ARHGEF38, TRIB1, REPS2, GJB1, EPCAM, PCSK6, CAMKK2, STIL, SLC12A8, GNPNAT1, PVT1, TMTC4; Rise and the positive correlation of trouble prostate cancer risk of said gene.
The object of the present invention is to provide one group of prostate cancer marker, comprise miRNA:hsa-miR-222, hsa-miR-224, hsa-miR-99b, hsa-miR-221, hsa-miR-204, hsa-miR-181c, hsa-miR-378, hsa-miR-452, hsa-miR-378, hsa-miR-31, hsa-miR-139-5p, hsa-miR-505, hsa-miR-133a, hsa-miR-328, hsa-miR-27b, hsa-miR-154, hsa-miR-324-5p, hsa-miR-487b, hsa-miR-502-5p; And/or mRNA:TCEAL2, CPA6, C15orf41, VSNL1, KANK1, NYNRIN, NAV2, ZNF185, STARD5, GSTP1, ROR2, DUOX1, ALAD, ST5, DBNDD2, SEMA6D, BCL2, DOK4, ST6GALNAC2, ACACB; Downward and the positive correlation of trouble prostate cancer risk of said gene.
Accompanying drawing explanation
Fig. 1 prostate Related oncogene information analytic system sketch
Fig. 2 prostate Related oncogene information data collection module map
Fig. 3 prostate Related oncogene information data analysis module figure
Fig. 4 prostate Related oncogene information analytic system figure
Fig. 5 prostate Related oncogene information analytic system detail drawing
Embodiment
Below in conjunction with specific embodiment, setting forth the present invention further, only for explaining the present invention, and can not limitation of the present invention be interpreted as.Those having ordinary skill in the art will appreciate that: can carry out multiple change, amendment, replacement and modification to these embodiments when not departing from principle of the present invention and aim, scope of the present invention is by claim and equivalents thereof.The experimental technique of unreceipted actual conditions in the following example, the usually conveniently conditioned disjunction condition examinations of advising according to manufacturer.
Embodiment 1
A kind of prostate Related oncogene information analytic system (see Fig. 1), comprise data acquisition module, data analysis module and data disaply moudle, data acquisition module sends data analysis module to after collecting data, data analysis module is shown by data disaply moudle after carrying out Machining Analysis to data, wherein, data acquisition module comprises DNA data acquisition module, RNA data acquisition module and protein data acquisition module.
Embodiment 2
Data collection module (see Fig. 2) in a kind of prostate Related oncogene information analytic system, comprise DNA data acquisition module, RNA data acquisition module and protein data acquisition module, wherein, DNA data acquisition module comprises mutational site acquisition module, methylation sites acquisition module, SNP site acquisition module; RNA data acquisition module comprises mrna expression acquisition module, miRNA expresses acquisition module, lncRNA expresses acquisition module; Protein data acquisition module comprises protein expression profiling data acquisition module.
Embodiment 3
In a kind of prostate Related oncogene information analytic system data analysis module (see Fig. 3), comprise difference expression gene analysis module, prediction target spot analysis module, biological information net analysis module, GO analysis module, pathway analysis module.
Embodiment 4
A kind of prostate Related oncogene information analytic system (see Fig. 4), comprise data acquisition module, data preprocessing module, data analysis module and data disaply moudle, data acquisition module sends data analysis module to after carrying out background correction and standardization by data preprocessing module after collecting data, data analysis module is shown by data disaply moudle after carrying out Machining Analysis to data, wherein, data acquisition module comprises DNA data acquisition module, RNA data acquisition module and protein data acquisition module.
Embodiment 5
A kind of prostate Related oncogene information analytic system (see Fig. 5), comprise data acquisition module, data preprocessing module, data analysis module and data disaply moudle, data acquisition module sends data analysis module to after carrying out background correction and standardization by data preprocessing module after collecting data, data analysis module is shown by data disaply moudle after carrying out Machining Analysis to data, wherein, data acquisition module comprises DNA data acquisition module, RNA data acquisition module and protein data acquisition module.Wherein, DNA data acquisition module comprises mutational site acquisition module, methylation sites acquisition module, SNP site acquisition module; RNA data acquisition module comprises mrna expression acquisition module, miRNA expresses acquisition module, lncRNA expresses acquisition module; Protein data acquisition module comprises protein expression profiling data acquisition module.Data analysis module comprises difference expression gene analysis module, prediction target spot analysis module, biological information net analysis module, GO analysis module, pathway analysis module.
The collection of embodiment 6 data
Collect part prostate cancer data in GEO database, concrete data are shown in Table 1.
Table 1.3 overlaps the basic condition of prostate cancer high flux mRNA and miRNA data set
The process of embodiment 7 data
Carry out t-test after background correction and standardization being carried out to 3 cover miRNA and mRNA raw data by transcript profile data analysis software and obtain P value, calculate effect quantity, then utilize Fisher to check and merge P value, random-effect model is adopted to merge effect quantity, screening differential expression miRNA and mRNA, setting P value < 0.01, effect quantity > 0.8, filter out 29 miRNA altogether, the gene 10 of wherein expression rise, the gene 19 that expression is lowered.As shown in table 2, wherein left side is the miRNA of up-regulated, and right side is the miRNA of down-regulated expression.P value < 0.01 is set in analytic process, effect quantity > 1, filter out 946 mRNA altogether, the wherein gene 17 7 of expression rise, the gene 769 that expression is lowered, enumerates it and raises or lower the mRNA (see table 3) of before rank 20.
Table 2. prostate cancer expresses the miRNA significantly raising and lower
Table 3. prostate cancer expresses the mRNA (front 20) significantly raising and lower
The identification of the miRNA target gene of embodiment 8 prostate cancer differential expression
Identify that miRNA target gene is the very important step of research particular organization and cell miRNA function.Utilization comprises DIANAmT, miRanda, miRDB, miRWalk, the target gene of these algorithm predicts differential expressions of PICTAR5 and Targetscan miRNA, choose >=4 algorithm predicts target gene out, and the target gene of the miRNA of the differential expression verified at miRWalk database lookup, then the gene of expressing negative correlation in all target genes and mRNA chip with miRNA is carried out confluence analysis, we obtain 751 target genes altogether, the target gene that 574 are raised miRNA is obtained by prediction, the target gene of 128 downward miRNA, and the target gene of the miRNA of the up-regulated that 24 have been verified is obtained by miRWalk database, the target gene of the miRNA of 35 down-regulated expressions verified.
The biological information network chart of the target gene composition of embodiment 9 prostate cancer differential expression miRNA and differential expression
Utilize the biological information network chart that Cytoscape software building is made up of the target gene of prostate cancer differential expression miRNA and differential expression.MiRNAs and mRNAs shown in figure be differential expression in prostate cancer all.If central point is the miRNAs significantly raised, around central point is the mRNAs significantly lowered, if central point is the miRNAs significantly lowered, around central point is the mRNAs significantly raised.
The functional annotation of the target gene of embodiment 10 prostate cancer differential expression
In order to better study the function of differential expression target gene, we carry out the enrichment of GO function and the enrichment of KEGG path by DAVID to the gene of differential expression, and the GO function of front 15 significant enrichments and KEGG path are in table 4 and table 5.The target gene that the result of KEGG path enrichment shows 188 differential expressions can sift out in KEGG storehouse, concentrate on cancer path, talin, melanogenesis, glutamatergic synaptic, Wnt signal path, small-cell carcinoma of the lung, purine metabolism, axon guidance, pentose phosphate pathway, 30 signal paths such as actin cytoskeleton adjustment.
The GO function of front 15 the differential expression target gene significant enrichments of table 4.
The signal path of front 15 the differential expression target gene significant enrichments of table 5.
Claims (10)
1. a prostate Related oncogene information and analytic system, it is characterized in that, comprise data acquisition module, data analysis module and data disaply moudle, data acquisition module sends data analysis module to after collecting data, data analysis module is shown by data disaply moudle after carrying out Machining Analysis to data, and described data acquisition module comprises DNA data acquisition module, RNA data acquisition module and protein data acquisition module.
2. system according to claim 1, is characterized in that, described DNA data acquisition module comprises mutational site acquisition module, methylation sites acquisition module, SNP site acquisition module; Described RNA data acquisition module comprises mrna expression acquisition module, miRNA expresses acquisition module, lncRNA expresses acquisition module; Protein data acquisition module comprises protein expression profiling data acquisition module.
3. system according to claim 1, is characterized in that, described data analysis module comprises difference expression gene analysis module, prediction target spot analysis module, biological information net analysis module, GO analysis module, pathway analysis module.
4. system according to claim 1, it is characterized in that, described prostate Related oncogene information and analytic system also comprise data preprocessing module, and data acquisition module sends data analysis module to after carrying out background correction and standardization by data preprocessing module after collecting data.
5. prostate Related oncogene information and an analytical approach, comprising:
(1) from data with existing storehouse, download prostate cancer sample order-checking raw data and check sample order-checking raw data;
(2) background correction and standardization are carried out to the raw data downloaded;
(3) to data analysis;
(4) display analysis result.
6. the method according to right 5, is characterized in that, carries out the analysis of difference expression gene prediction target spot, the analysis of biological information net, GO analysis, pathway analysis to data.
7. the method according to right 6, is characterized in that, the analysis of described biological information net comprises biological information network, the biological information network between gene and gene, the biological information network between gene and albumen of differential expression miRNA and target gene foundation; Described prediction target spot analysis and utilization comprises DIANAmT, the target spot of these algorithm predicts differential expressions of miRanda, miRDB, miRWalk, PICTAR5 and Targetscan miRNA, preferably >=4 algorithm predicts target spot out.
8. the method according to right 5, it is characterized in that, from data with existing storehouse, download mutational site data, methylation sites data, SNP site data, mrna expression data, miRNA expression data, lncRNA expression data, protein expression profiling data that prostate cancer is relevant.
9. one group of prostate cancer diagnosis and treatment mark, comprises miRNA:hsa-miR-183, hsa-miR-153, hsa-miR-96, hsa-miR-25, hsa-miR-93, hsa-miR-182, hsa-miR-663, hsa-miR-106b, hsa-miR-130b, hsa-miR-18a; And/or mRNA:SIM2, HPN, AMACR, MYC, OR51E2, BICD1, DNAH5, PCA3, ARHGEF38, TRIB1, REPS2, GJB1, EPCAM, PCSK6, CAMKK2, STIL, SLC12A8, GNPNAT1, PVT1, TMTC4; It is characterized in that, rise and the positive correlation of trouble prostate cancer risk of said gene.
10. one group of prostate cancer marker, comprises miRNA:hsa-miR-222, hsa-miR-224, hsa-miR-99b, hsa-miR-221, hsa-miR-204, hsa-miR-181c, hsa-miR-378, hsa-miR-452, hsa-miR-378, hsa-miR-31, hsa-miR-139-5p, hsa-miR-505, hsa-miR-133a, hsa-miR-328, hsa-miR-27b, hsa-miR-154, hsa-miR-324-5p, hsa-miR-487b, hsa-miR-502-5p; And/or mRNA:TCEAL2, CPA6, C15orf41, VSNL1, KANK1, NYNRIN, NAV2, ZNF185, STARD5, GSTP1, ROR2, DUOX1, ALAD, ST5, DBNDD2, SEMA6D, BCL2, DOK4, ST6GALNAC2, ACACB; It is characterized in that, downward and the positive correlation of trouble prostate cancer risk of said gene.
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| CN107630092A (en) * | 2017-10-23 | 2018-01-26 | 广州医科大学附属第二医院 | The 3p of miR 505 are applied to diagnosis, prognosis and the treatment of prostate cancer with osseous metastasis |
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| CN114333992A (en) * | 2020-09-30 | 2022-04-12 | 北京瑷格干细胞科技有限公司 | System and method for collecting and analyzing skin aging related gene information |
| CN114628022A (en) * | 2020-12-14 | 2022-06-14 | 北京致成生物医学科技有限公司 | Osteoporosis related gene screening and function analysis method and system |
| CN117831624A (en) * | 2023-12-15 | 2024-04-05 | 江苏和福生物科技有限公司 | Tumor mutation analysis method based on tumor molecular diagnosis knowledge base |
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