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Transcriptome subtyping of metastatic Castration Resistance Prostate Cancer (mCRPC) for the precision therapeutics: an in silico analysis

Prostate Cancer and Prostatic Diseases volume 25, pages 327–335 (2022)Cite this article

Subjects

Abstract

Background

Men with metastatic prostate cancer who are treated with androgen deprivation therapy (ADT) typically develop therapeutic resistance eventually and have a dismal outcome. Moreover, the limited survival benefit observed in only a proportion of patients receiving novel therapeutics including immune checkpoint blockade and PARP inhibitors suggests the biological heterogeneity of mCRPCs.

Methods

To understand the heterogeneity of mCRPC, we analyzed the transcriptome of 231 mCRPCs and identified four disparate biological subtypes (Basal, Homologous Recombination Repair (HRR), Neuroendocrine and Luminal). The package “randomForest” was used to construct a Random Forest model. Circular plots were used for visualization of TMPRSS2-ERG fusion in each subtype.

Results

The Luminal subtype of mCRPCs has higher Androgen Receptor (AR) expression and copy number alterations as compared with the other subtypes. Genes in HRR pathway are relatively downregulated in most subtypes regardless of the genetic alterations, except for the HRR and NE subtypes, suggesting potential resistance of the HRR and NE mCRPCs to PARP inhibitor treatment. The HRR subtype has relatively more immune cell infiltration and higher expression of immune checkpoints, highlighting that the efficacy of immunotherapy should be evaluated in this particular subtype. TMPRSS2-ERG fusion is the most frequent gene fusion in all mCRPCs, and the Basal subtype has a higher frequency of this fusion than the other subtypes.

Conclusions

Our results reveal that the stratification of mCRPC according to transcriptome is informative of personalized therapeutics in the treatment of mCRPCs. The predictive capacity of the transcriptome subtyping of mCRPC warrants further exploration in the future.

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Fig. 1: Unsupervised clustering of mCRPC reflects the heterogeneity.
Fig. 2: Genomics and transcriptome of HR pathway in each subtype.
Fig. 3: Landscape of immune cell infiltration and regulation in each subtype.
Fig. 4: Subtyping of mCRPC is validated via Random Forest.
Fig. 5: Fusion genes in each subtype.

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Data availability

The data that support the findings of this study are available in GEO, reference number GSE31528, GSE50630, GSE70285. Data was running in this study will be provided upon the reasonable request.

Code availability

The code is available on: https://figshare.com/s/cbe2398424066f8e2a14.

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Funding

This research was funded by National Natural Science Foundation of China, grant number 81803900.

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Author notes

  1. These authors contributed equally: Yingchun Liang, Enlin Rong.

Authors and Affiliations

  1. Departments of Urology, Huashan Hospital, Fudan University, No. 12 WuLuMuQi Middle Road, 200040, Shanghai, China

    Yingchun Liang & Jimeng Hu

  2. Fudan Institute of Urology, Huashan Hospital, Fudan University, Shanghai, China

    Yingchun Liang & Jimeng Hu

  3. Departments of Nursing, Huashan Hospital, Fudan University, No. 12 WuLuMuQi Middle Road, 200040, Shanghai, China

    Enlin Rong

  4. Department of Radiation Oncology, Stanford University, Stanford, CA, 94305, USA

    Jin Qian

  5. Molecular Diagnostic Solution, Nutrition and Health, Health and Biosecurity, CSIRO, Canberra, Australia

    Chenkai Ma

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  1. Yingchun Liang
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Contributions

YL collected data, analyzed data, and wrote the manuscript; ER analyzed data and edited the manuscript; JQ wrote and edited the manuscript; CM drafted the study, wrote and edited the manuscript; HJ edited the manuscript, and supervised the project. All authors gave final approval of the manuscript.

Corresponding authors

Correspondence to Jin Qian, Chenkai Ma or Jimeng Hu.

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The authors declare no competing interests.

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Liang, Y., Rong, E., Qian, J. et al. Transcriptome subtyping of metastatic Castration Resistance Prostate Cancer (mCRPC) for the precision therapeutics: an in silico analysis. Prostate Cancer Prostatic Dis 25, 327–335 (2022). https://doi.org/10.1038/s41391-022-00495-9

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