Genotype-to-Phenotype Associations in the Aggressive Variant Prostate Cancer Molecular Profile (AVPC-m) Components.

Abstract

The aggressive variant prostate cancer molecular profile (AVPC-m), composed of combined defects in TP53, RB1 and PTEN, characterizes a subset of prostate cancers linked to androgen indifference and platinum sensitivity. To contribute to the optimization of the AVPC-m assessment for inclusion in prospective clinical trials, we investigated the status of the AVPC-m components in 28 patient tumor-derived xenografts (PDXs) developed at MDACC. We subjected single formalin-fixed, paraffin-embedded (FFPE) blocks from each PDX to immunohistochemistry (IHC), targeted next-generation genomic sequencing (NGS) and Clariom-S Affymetrix human microarray expression profiling. Standard validated IHC assays and a 10% labeling index cutoff resulted in high reproducibility across three separate laboratories and three independent readers for all tumor suppressors, as well as strong correlations with loss-of-function transcriptional scores (LOF-TS). Adding intensity assessment to labeling indices strengthened the association between IHC results and LOF-TS for TP53 and RB1, but not for PTEN. For TP53, genomic alterations determined by NGS had slightly higher agreement scores with LOF-TS than aberrant IHC, while for RB1 and PTEN, NGS and IHC determinations resulted in similar agreement scores with LOF-TS. Nonetheless, our results indicate that the AVPC-m components can be assessed reproducibly by IHC using various widely available standardized assays.

• Authors: Rama Soundararajan, Paul Viscuse, Patrick Pilie, Jingjing Liu, Souzana Logotheti, Caddie Laberiano Fernández, Daniele Lorenzini, Anh Hoang, Wei Lu, Luisa Maren Solis Soto, Ignacio I Wistuba, Mingchu Xu, Xingzhi Song, Peter D A Shepherd, Nora M Navone, Rebecca S S Tidwell, Guillermina Lozano, Christopher Logothetis, Jianhua Zhang, James P Long, Marcos R Estecio, Vasiliki Tzelepi, Ana M Aparicio
• Journal: Cancers (Cancers (Basel)) Vol. 14 Issue 13 (Jun 30 2022) ISSN: 2072-6694 [Print] Switzerland
• PMID: 35805010 (Publication Type: Journal Article)