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Immunogenomic analyses associate immunological alterations with mismatch repair defects in prostate cancer
Daniel Nava Rodrigues, … , Eliezer M. Van Allen, Johann S. de Bono
Daniel Nava Rodrigues, … , Eliezer M. Van Allen, Johann S. de Bono
Published September 4, 2018
Citation Information: J Clin Invest. 2018;128(10):4441-4453. https://doi.org/10.1172/JCI121924.
View: Text | PDF | Corrigendum
Clinical Medicine Genetics Oncology

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

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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 1

Consort diagram.

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Consort diagram.
Assays performed on 2 different cohorts of sample patie...
Assays performed on 2 different cohorts of sample patients from the Royal Marsden Hospital (RMH) and the Stand Up To Cancer/Prostate Cancer Foundation (SU2C/PCF) database. ML, mutational load; QC, quality control.
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