A novel immune-related gene-based prognostic signature to predict biochemical recurrence in patients with prostate cancer after radical prostatectomy

Abstract

Accumulating evidences indicates that the immune landscape signature dramatically correlates with tumorigenesis and prognosis of prostate cancer (PCa). Here, we identified a novel immune-related gene-based prognostic signature (IRGPS) to predict biochemical recurrence (BCR) after radical prostatectomy. We also explored the correlation between IRGPS and tumor microenvironment. We identified an IRGPS consisting of seven immune-related genes (PPARGC1A, AKR1C2, COMP, EEF1A2, IRF5, NTM, and TPX2) that were related to the BCR-free survival of PCa patients. The high-risk patients exhibited a higher fraction of regulatory T cells and M2 macrophages than the low-risk BCR patients (P < 0.05) as well as a lower fraction of resting memory CD4 T cells and resting mast cells. These high-risk patients also had higher expression levels of CTLA4, TIGIT, PDCD1, LAG3, and TIM3. Finally, a strong correlation was detected between IRGPS and specific clinicopathological features, including Gleason scores and tumor stage. In conclusion, our study reveals the clinical significance and potential functions of the IRGPS, provides more data for predicting outcomes, and suggests more effective immunotherapeutic target strategies for PCa.

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Data availability

All data generated or analyzed during this study are included in this published article.

Code availability

The data of this study are freely available from TCGA database (https://cancergenome.nih.gov/), GEO database (https://www.ncbi.nlm.nih.gov/geo/). The authors did not have special access privileges.

Abbreviations

BCR:

Biochemical recurrence

DEIRGs:

Differentially expressed immune-related genes

IRGPS:

Immune-related gene-based prognostic signature

mCRPC:

Metastatic castration-resistant PCa

TIL:

Tumor-infiltrating lymphocyte

TMB:

Tumor mutation burden

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Acknowledgements

We are grateful to the TCGA database, GEO database, and ICGC database for the data provided for this study.

Funding

This study was funded by grants from the Guangdong Basic and Applied Basic Research Foundation (Grant No. 2019A1515110033), China Postdoctoral Science Foundation (Grant No. 2019M662865), Distinguished Young Talents in Higher Education Foundation of Guangdong Province (Grant No. 2019KQNCX115 and 2020KZDZX1168), Achievement cultivation and clinical transformation application cultivation projects of the First Affiliated Hospital of Guangzhou Medical University (Grant No. ZH201908), the National Natural Science Foundation of China (No. 81670643 and 81870483), the Collaborative Innovation Project of Guangzhou Education Bureau (No. 1201620011), the Guangzhou Science Technology and Innovation Commission (No. 201704020193), and the Science and Technology Planning Project of Guangdong Province (No. 2017B030314108).

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All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Lv DJ, Wu XK and Chen X. Yang SX, Chen WZ and Wang M assisted in collecting data. The first draft of the manuscript was written by DJL and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. Zeng GH, Liu YD and Gu D supervised the study.

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Correspondence to Yongda Liu or Di Gu or Guohua Zeng.

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Daojun Lv, Xiangkun Wu and Xi Chen are co-first authors.

Yongda Liu, Di Gu, Guohua Zeng jointly supervised this work.

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Lv, D., Wu, X., Chen, X. et al. A novel immune-related gene-based prognostic signature to predict biochemical recurrence in patients with prostate cancer after radical prostatectomy. Cancer Immunol Immunother (2021). https://doi.org/10.1007/s00262-021-02923-6

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Keywords

  • Biochemical recurrence
  • Prognosis
  • Prostate cancer
  • Immunotherapy