Construction Of The Recurrence Risk Signature Of Prostate Cancer After Resection And Subtype Characteristics Analysis

Background:Prostate cancer(PCa)is the second highest proportion cancer among male patients,especially,its mortality is the highestin the developed countries.In China,the discovery rate of prostate cancer increases year by year due to aging and the development of detection technology.Patients are usually recommended for active surveillance or surgical resection based on the pathologist’s diagnosis of magnetic resonance imaging and biopsy samples.About 20%-40%prostate cancer patients who receive surgical resection undergo biochemical recurrence in tenyears.Gleason grade is a widely used index of histological grade for PCa.However,it is uncertain to evaluatethe recurrence risk due to sampling location or pathologist’s subjective judgment.The specificity and sensitivity of other clinical indexes,such as prostate specific antigen and tumor stage,are not high.Hence,accurate assessment of the recurrence risk in PCa patients after resection is important to decide treatment regimen and improve survival.Methods:The within-sample relative expression orderings(REOs)of gene expression is robust to the experimental batch effect and the quality of clinical samples.Based on the within-sample REOs of gene expression profile for 56 PCa patients were used to construct a signature to evaluate the recurrence risk of PCa patients after surgical resection.First,based on Student’s t-test,differentially expressed genes(DEGs)were screened between patients with gleason>=8 and gleason<=6.Candidate gene pairs,which are significantly associated with the biochemical recurrence time of PCa patients,were selected from the combination of DEGs.According to the sequential forward selection algorithm,the gene pairs with the highest C-index in the training dataset is selected as the recurrence risk signature and validated in multiple independent datasets.Then the functional enrichment analysis,cell proliferation ability analysis,immune infiltration analysis and multi-omics analysis were carried out to find the different subtype characteristics between the high-risk and low-risk samples predicted by the signature.Results:This study developed a recurrence risksignature for PCa paitents in the training dataset,which were consistedof 14 gene pairs(14-GPS).When more than 7gene pairs vote a patient as the high-risk,it is assigned as the high-risk group;otherwise,the patient is assigned as the low-risk group.The 14-GPS were validated in a total of 888 patients from six independent datasets,and the survival analysis showed that BCR time of patients in the high-risk group are significant shorter than that in the low risk-group.Transcriptome analysis showed that the number of DEGs between the high-risk group and the low-risk group reclassified by 14-GPS is more than that two subgroups classifiedby the gleasongrade,and enriched more pathways related to tumor proliferation.Epigenomic and genomics analysis showed that differential hypomethylated genes and differential overexpressed genes are significantly overlapped.Protein-protein interaction analysis showed that differentially expressed genes that altered in omics may regulate the expressions of hub genes which were associated with the development of prostate cancer in the network to influence the recurrence.Meanwhile,the proliferation ability of tumor cells is significantly higher in the high-risk group than that in the low-risk group.The tumor cell immune infiltration analysis revealed that the infiltration degree of memory B cells,regulatory T cells,activated NK cells,CD4~+naive cell and CD8~+cell are deeper in the high-risk group than in the low-risk group.The survival analysis showed that BCR time difference among patients in the three groups are more significant than that in the two groups.Conclusion:Based on within-sample REOs of gene expression,this study developed a qualitative transcriptional signature with 14 gene pairs to predict the recurrence risk of PCa patients after resection.The multi-omics analyses between samples in the high-risk group and the low-risk group classified by 14-GPS were helpful to understand the mechanism of recurrence.The combination of 14-GPS and gleason grade could more accurately predict the recurrence risk of PCa patients,which could provide important guides for individualized treatment.