Immunogenomic analyses associate immunological alterations with mismatch repair defects in prostate cancer
Daniel Nava Rodrigues, et al.
Daniel Nava Rodrigues, et al.
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Clinical Research and Public Health Genetics Oncology

Immunogenomic analyses associate immunological alterations with mismatch repair defects in prostate cancer

Abstract

BACKGROUND. Understanding the integrated immunogenomic landscape of advanced prostate cancer (APC) could impact stratified treatment selection. METHODS. Defective mismatch repair (dMMR) status was determined by either loss of mismatch repair protein expression on IHC or microsatellite instability (MSI) by PCR in 127 APC biopsies from 124 patients (Royal Marsden [RMH] cohort); MSI by targeted panel next-generation sequencing (MSINGS) was then evaluated in the same cohort and in 254 APC samples from the Stand Up To Cancer/Prostate Cancer Foundation (SU2C/PCF). Whole exome sequencing (WES) data from this latter cohort were analyzed for pathogenic MMR gene variants, mutational load, and mutational signatures. Transcriptomic data, available for 168 samples, was also performed. RESULTS. Overall, 8.1% of patients in the RMH cohort had some evidence of dMMR, which associated with decreased overall survival. Higher MSINGS scores associated with dMMR, and these APCs were enriched for higher T cell infiltration and PD-L1 protein expression. Exome MSINGS scores strongly correlated with targeted panel MSINGS scores (r = 0.73, P < 0.0001), and higher MSINGS scores associated with dMMR mutational signatures in APC exomes. dMMR mutational signatures also associated with MMR gene mutations and increased immune cell, immune checkpoint, and T cell–associated transcripts. APC with dMMR mutational signatures overexpressed a variety of immune transcripts, including CD200R1, BTLA, PD-L1, PD-L2, ADORA2A, PIK3CG, and TIGIT. CONCLUSION. These data could impact immune target selection, combination therapeutic strategy selection, and selection of predictive biomarkers for immunotherapy in APC. FUNDING. We acknowledge funding support from Movember, Prostate Cancer UK, The Prostate Cancer Foundation, SU2C, and Cancer Research UK.

Authors

Daniel Nava Rodrigues, Pasquale Rescigno, David Liu, Wei Yuan, Suzanne Carreira, Maryou B. Lambros, George Seed, Joaquin Mateo, Ruth Riisnaes, Stephanie Mullane, Claire Margolis, Diana Miao, Susana Miranda, David Dolling, Matthew Clarke, Claudia Bertan, Mateus Crespo, Gunther Boysen, Ana Ferreira, Adam Sharp, Ines Figueiredo, Daniel Keliher, Saud Aldubayan, Kelly P. Burke, Semini Sumanasuriya, Mariane Sousa Fontes, Diletta Bianchini, Zafeiris Zafeiriou, Larissa Sena Teixeira Mendes, Kent Mouw, Michael T. Schweizer, Colin C. Pritchard, Stephen Salipante, Mary-Ellen Taplin, Himisha Beltran, Mark A. Rubin, Marcin Cieslik, Dan Robinson, Elizabeth Heath, Nikolaus Schultz, Joshua Armenia, Wassim Abida, Howard Scher, Christopher Lord, Alan D’Andrea, Charles L. Sawyers, Arul M. Chinnaiyan, Andrea Alimonti, Peter S. Nelson, Charles G. Drake, Eliezer M. Van Allen, Johann S. de Bono

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Figure 3

Tumor-infiltrating lymphocytes, molecular features, and PD-L1 expression of CRPC samples from RMH cohort.

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Tumor-infiltrating lymphocytes, molecular features, and PD-L1 expression...
(A) Tumor-infiltrating T lymphocyte quantitation in 50 mCRPC biopsies, with MMR status according to the different orthogonal assays (MSI_MUT; MSI_IHC; MSI_MSINGS; mutation load), ordered from left to right by T cell infiltration score. A sample from 1 dMMR patient was not used for this analysis since it was a TURP sample taken at time of CRPC. Blue squares mark altered biomarker. (B) Stacked bar chart depicts proportion of PD-L1 immunohistochemical positivity (e.g., Supplemental Figure 3A) in samples reviewed by pathologists blinded to dMMR results in 51 mCRPC samples (n = 10 dMMR, n = 41 pMMR). (C) Dot plot showing the correlation between PD-L1 expression and T cell infiltration in mCRPC biopsies (n = 29). The y axis depicts total T cell infiltration defined as n of T cells/mm2 using a negative binomial regression model; there was an IRR of 3.91 (95% CI, 1.45–10.53; P = 0.007) for patients with PD-L1 > 0. Filled circles represent pMMR; open circles represent dMMR.