Identification of immune cell infiltration pattern and related critical genes in metastatic castration-resistant prostate cancer by bioinformatics analysis

Article type: Research Article

Authors: Fan, Caibin^{a; 1} | Lu, Wei^{b; 1} | Li, Kai^{a; 1} | Zhao, Chunchun^a | Wang, Fei^a | Ding, Guanxiong^{c; *} | Wang, Jianqing^{a; *}

Affiliations: [a] Department of Urology, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, Jiangsu, China | [b] School of Nursing, Suzhou Vocational Health College, Suzhou, Jiangsu, China | [c] Department of Urology, Huashan Hospital, Fudan University, Shanghai, China

Correspondence: [*] Corresponding authors: Jianqing Wang, Department of Urology, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, 26 Daoqian Rd, Suzhou, Jiangsu 215000, China. Tel.: +86 512 623 62011; E-mail: [email protected] and Jianqing Wang, Department of Urology, Huashan Hospital, Fudan University, Shanghai, China. E-mail: [email protected].

Note: [1] Equal first contributors for this work.

Abstract: BACKGROUND: Metastatic castration-resistant prostate cancer (mCRPC) is the lethal stage of prostate cancer and the main cause of morbidity and mortality, which is also a potential target for immunotherapy. METHOD: In this study, using the Approximate Relative Subset of RNA Transcripts (CIBERSORT) online method, we analysed the immune cell abundance ratio of each sample in the mCRPC dataset. The EdgeR (an R package) was used to classify differentially expressed genes (DEGs). Using the Database for annotation, visualisation and interactive exploration (DAVID) online method, we performed functional enrichment analyses. STRING online database and Cytoscape tools have been used to analyse protein-protein interaction (PPI) and classify hub genes. RESULTS: The profiles of immune infiltration in mCRPC showed that Macrophages M2, Macrophages M0, T cells CD4 memory resting, T cells CD8 and Plasma cells were the main infiltration cell types in mCRPC samples. Macrophage M0 and T cell CD4 memory resting abundance ratios were correlated with clinical outcomes. We identified 1102 differentially expressed genes (DEGs) associated with the above two immune cells to further explore the underlying mechanisms. Enrichment analysis found that DEGs were substantially enriched in immune response, cell metastasis, and metabolism related categories. We identified 20 hub genes by the protein-protein interaction network analysis. Further analysis showed that three critical hub genes, CCR5, COL1A1 and CXCR3, were significantly associated with prostate cancer prognosis. CONCLUSION: Our findings revealed the pattern of immune cell infiltration in mCRPC, and identified the types and genes of immune cells correlated with clinical outcomes. A new theoretical basis for immunotherapy may be given by our results.

Keywords: Immune infiltration, metastatic castration resistant prostate cancer (mCRPC), RNA sequencing, bioinformatics analysis, immunotherapy

DOI: 10.3233/CBM-203222

Journal: Cancer Biomarkers, vol. 32, no. 3, pp. 363-377, 2021