Multi-omics reveals novel prognostic implication of SRC protein expression in bladder cancer and its correlation with immunotherapy response
| العنوان: | Multi-omics reveals novel prognostic implication of SRC protein expression in bladder cancer and its correlation with immunotherapy response |
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| المؤلفون: | Aihetaimujiang Anwaier, Yuan-Yuan Qu, Wenhao Xu, Hailiang Zhang, Xiaoxin Hu, Chunguang Ma, Dingwei Ye, Maierdan Palihati, Xi Tian, Wangrui Liu |
| المصدر: | Annals of Medicine article-version (VoR) Version of Record |
| بيانات النشر: | Informa UK Limited, 2021. |
| سنة النشر: | 2021 |
| مصطلحات موضوعية: | medicine.medical_treatment, Gene Expression, Adaptive Immunity, 030204 cardiovascular system & hematology, Protein expression, Machine Learning, 0302 clinical medicine, Risk Factors, Databases, Genetic, 030212 general & internal medicine, skin and connective tissue diseases, Annexin A1, Bladder cancer, Genomics, General Medicine, Prognosis, immune checkpoint therapy, prediction model, ErbB Receptors, Genes, src, Oncology, Area Under Curve, biomarker, Biomarker (medicine), Beclin-1, Immunotherapy, Research Article, SRC, Proto-oncogene tyrosine-protein kinase Src, Protein Kinase C-alpha, 03 medical and health sciences, Predictive Value of Tests, Proto-Oncogene Proteins, Biomarkers, Tumor, medicine, Humans, Proportional Hazards Models, business.industry, Patient Selection, Receptor Protein-Tyrosine Kinases, multi-omics, medicine.disease, Survival Analysis, Axl Receptor Tyrosine Kinase, Urinary Bladder Neoplasms, Cancer research, Multi omics, business |
| الوصف: | Purpose This study aims to identify potential prognostic biomarkers of bladder cancer (BCa) based on large-scale multi-omics data and investigate the role of SRC in improving predictive outcomes for BCa patients and those receiving immune checkpoint therapies (ICTs). Methods Large-scale multi-comic data were enrolled from the Cancer Proteome Atlas, the Cancer Genome Atlas and gene expression omnibus based on machining-learning methods. Immune infiltration, survival and other statistical analyses were implemented using R software in cancers (n = 12,452). The predictive value of SRC was performed in 81 BCa patients receiving ICT from aa validation cohort (n = 81). Results Landscape of novel candidate prognostic protein signatures of BCa patients was identified. Differential BECLIN, EGFR, PKCALPHA, ANNEXIN1, AXL and SRC expression significantly correlated with the outcomes for BCa patients from multiply cohorts (n = 906). Notably, risk score of the integrated prognosis-related proteins (IPRPs) model exhibited high diagnostic accuracy and consistent predictive ability (AUC = 0.714). Besides, we tested the clinical relevance of baseline SRC protein and mRNA expression in two independent confirmatory cohorts (n = 566) and the prognostic value in pan-cancers. Then, we found that elevated SRC expression contributed to immunosuppressive microenvironment mediated by immune checkpoint molecules of BCa and other cancers. Next, we validated SRC expression as a potential biomarker in predicting response to ICT in 81 BCa patient from FUSCC cohort, and found that expression of SRC in the baseline tumour tissues correlated with improved survival benefits, but predicts worse ICT response. Conclusion This study first performed the large-scale multi-omics analysis, distinguished the IPRPs (BECLIN, EGFR, PKCALPHA, SRC, ANNEXIN1 and AXL) and revealed novel prediction model, outperforming the currently traditional prognostic indicators for anticipating BCa progression and better clinical strategies. Additionally, this study provided insight into the importance of biomarker SRC for better prognosis, which may inversely improve predictive outcomes for patients receiving ICT and enable patient selection for future clinical treatment. |
| تدمد: | 1365-2060 0785-3890 |
| الوصول الحر: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::977d775444b179e0b4dd0bb2d47900faTest https://doi.org/10.1080/07853890.2021.1908588Test |
| حقوق: | OPEN |
| رقم الانضمام: | edsair.doi.dedup.....977d775444b179e0b4dd0bb2d47900fa |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 13652060 07853890 |
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