Identification of biomarkers for immunotherapy response in prostate cancer and potential drugs to alleviate immunosuppression

Abstract

Background: Immunotherapy has a significant effect on the treatment of many tumor types. However, prostate cancers generally fail to show significant responses to immunotherapy owing to their immunosuppressive microenvironments. To sustain progress towards more effective immunotherapy for prostate cancer, comprehensive analyses of the genetic characteristics of the immune microenvironment and novel therapeutic strategies are required. Methods: The transcriptome profiles of patients with prostate cancer were obtained from GEO and processed with the TIDE algorithm to predict their responses to immunotherapy. Next, the significant differentially expressed genes (DEGs) between the responder and non-responder groups were identified and used to compute the co-expression modules by WGCNA. Then, co-expression networks were constructed and survival analysis was applied to hub genes. Finally, drug candidates to alleviate immunosuppression were filtered in prostate cancer using GSEA based on hub genes. Results: In total, we identified 2758 significant DEGs and constructed 16 co-expression modules, seven of which were significantly correlated with the immune response score. In total, 133 hub genes were identified, of which 13 were significantly associated with prostate cancer prognosis. Co-expression networks of hub genes were constructed with KMT2B at the center. Finally, six candidate drugs for prostate cancer immunotherapy were identified in PC3 and LNCaP cell lines. Conclusions: We obtained datasets from multiple platforms, performed integrated bioinformatic analysis to identify 133 hub genes and 13 biomarkers of an immunotherapy response, and six candidate drugs were filtered to inhibit the immunosuppressive tumor microenvironment, to ultimately improve patient responses to immunotherapy in prostate cancer.

Drug repositioning for immunotherapy in breast cancer using single-cell analysis

“…The application of the LINCS L1000 project 31 in drug repositioning for immunotherapy has been previously explored 50 , 51 . While various studies have attempted to repurpose non-human immunomodulatory peptides 52 and immunomodulatory drugs for different disorders 53 .…”

Drug repositioning for immunotherapy in breast cancer using single-cell analysis

“…The use of LINCS L1000 project [41] in drug repositioning for immunotherapy has been already addressed [58,59]. Besides, several studies attempt to repurpose the non-human immunomodulatory peptides [60] and immunomodulatory drugs against different disorders [61].…”

A Blood-Based Immune Gene Signature with Prognostic Significance in Localized Prostate Cancer

“…Intriguingly, a growing body of evidence associates these eight genes with a spectrum of immune responses, including regulation of tumor-infiltrating immune cell populations, and many studies have highlighted them as predictors of immunotherapy outcomes in distinct tumors, as described above [38,[50][51][52]56]. Importantly, immune evasion predominates among the responsible mechanisms for PCa unresponsiveness to immunomodulatory therapeutic regimes [57,58], which is orchestrated by the presence of low numbers of infiltrating lymphocytes, high densities of intra-tumoral suppressive cells, and indolent antigen-presenting cells in the tumor microenvironment that deregulate the balance between the immune mechanisms structuring a robust anti-tumor immune response [59,60].…”