Integrative clinical genomics of advanced prostate cancer

Dan Robinson, Eliezer M Van Allen, Yi-Mi Wu, Nikolaus Schultz, Robert J Lonigro, Juan-Miguel Mosquera, Bruce Montgomery, Mary-Ellen Taplin, Colin C Pritchard, Gerhardt Attard, Himisha Beltran, Wassim Abida, Robert K Bradley, Jake Vinson, Xuhong Cao, Pankaj Vats, Lakshmi P Kunju, Maha Hussain, Felix Y Feng, Scott A Tomlins, Kathleen A Cooney, David C Smith, Christine Brennan, Javed Siddiqui, Rohit Mehra, Yu Chen, Dana E Rathkopf, Michael J Morris, Stephen B Solomon, Jeremy C Durack, Victor E Reuter, Anuradha Gopalan, Jianjiong Gao, Massimo Loda, Rosina T Lis, Michaela Bowden, Stephen P Balk, Glenn Gaviola, Carrie Sougnez, Manaswi Gupta, Evan Y Yu, Elahe A Mostaghel, Heather H Cheng, Hyojeong Mulcahy, Lawrence D True, Stephen R Plymate, Heidi Dvinge, Roberta Ferraldeschi, Penny Flohr, Susana Miranda, Zafeiris Zafeiriou, Nina Tunariu, Joaquin Mateo, Raquel Perez-Lopez, Francesca Demichelis, Brian D Robinson, Marc Schiffman, David M Nanus, Scott T Tagawa, Alexandros Sigaras, Kenneth W Eng, Olivier Elemento, Andrea Sboner, Elisabeth I Heath, Howard I Scher, Kenneth J Pienta, Philip Kantoff, Johann S de Bono, Mark A Rubin, Peter S Nelson, Levi A Garraway, Charles L Sawyers, Arul M Chinnaiyan, Dan Robinson, Eliezer M Van Allen, Yi-Mi Wu, Nikolaus Schultz, Robert J Lonigro, Juan-Miguel Mosquera, Bruce Montgomery, Mary-Ellen Taplin, Colin C Pritchard, Gerhardt Attard, Himisha Beltran, Wassim Abida, Robert K Bradley, Jake Vinson, Xuhong Cao, Pankaj Vats, Lakshmi P Kunju, Maha Hussain, Felix Y Feng, Scott A Tomlins, Kathleen A Cooney, David C Smith, Christine Brennan, Javed Siddiqui, Rohit Mehra, Yu Chen, Dana E Rathkopf, Michael J Morris, Stephen B Solomon, Jeremy C Durack, Victor E Reuter, Anuradha Gopalan, Jianjiong Gao, Massimo Loda, Rosina T Lis, Michaela Bowden, Stephen P Balk, Glenn Gaviola, Carrie Sougnez, Manaswi Gupta, Evan Y Yu, Elahe A Mostaghel, Heather H Cheng, Hyojeong Mulcahy, Lawrence D True, Stephen R Plymate, Heidi Dvinge, Roberta Ferraldeschi, Penny Flohr, Susana Miranda, Zafeiris Zafeiriou, Nina Tunariu, Joaquin Mateo, Raquel Perez-Lopez, Francesca Demichelis, Brian D Robinson, Marc Schiffman, David M Nanus, Scott T Tagawa, Alexandros Sigaras, Kenneth W Eng, Olivier Elemento, Andrea Sboner, Elisabeth I Heath, Howard I Scher, Kenneth J Pienta, Philip Kantoff, Johann S de Bono, Mark A Rubin, Peter S Nelson, Levi A Garraway, Charles L Sawyers, Arul M Chinnaiyan

Abstract

Toward development of a precision medicine framework for metastatic, castration-resistant prostate cancer (mCRPC), we established a multi-institutional clinical sequencing infrastructure to conduct prospective whole-exome and transcriptome sequencing of bone or soft tissue tumor biopsies from a cohort of 150 mCRPC affected individuals. Aberrations of AR, ETS genes, TP53, and PTEN were frequent (40%-60% of cases), with TP53 and AR alterations enriched in mCRPC compared to primary prostate cancer. We identified new genomic alterations in PIK3CA/B, R-spondin, BRAF/RAF1, APC, β-catenin, and ZBTB16/PLZF. Moreover, aberrations of BRCA2, BRCA1, and ATM were observed at substantially higher frequencies (19.3% overall) compared to those in primary prostate cancers. 89% of affected individuals harbored a clinically actionable aberration, including 62.7% with aberrations in AR, 65% in other cancer-related genes, and 8% with actionable pathogenic germline alterations. This cohort study provides clinically actionable information that could impact treatment decisions for these affected individuals.

Copyright © 2015 Elsevier Inc. All rights reserved.

Figures

Figure 1. Overview of the SU2C-PCF IDT…
Figure 1. Overview of the SU2C-PCF IDT multi-institutional clinical sequencing of mCRPC project
A, Schema of multi-institutional clinical sequencing project work flow. B, Clinical trials associated with the SU2C-PCF mCRPC project. C, Biopsy sites of the samples used for clinical sequencing. D, Histopathology of the cohort. Representative images of morphological analysis of mCRPC are shown along with prevalence in our cohort.
Figure 2. Integrative landscape analysis of somatic…
Figure 2. Integrative landscape analysis of somatic and germline aberrations in metastatic CRPC obtained through DNA and RNA sequencing of clinically obtained biopsies
Columns represent individual patients and rows represent specific genes grouped in pathways. Mutations per Mb shown in the upper histogram while incidence of aberrations in the cohort is in the right histogram. Copy number variations (CNVs) common to mCRPC are shown in in the lower matrix with pink representing gain and light blue representing loss. Color legend of the aberrations represented including amplification, 2 copy loss, 1 copy loss, copy neutral loss of heterozygosity (LOH), splice site mutation, frameshift mutation, missense mutation, in-frame indel, and gene fusion. Cases with more aberration in a gene are represented by split colors.
Figure 3. Classes of genomic aberrations seen…
Figure 3. Classes of genomic aberrations seen in mCPRC
A, Copy number landscape of the SU2C-PCF mCRPC cohort. Individual chromosomes are represented by alternating colors and key aberrant genes are indicated. B, The gene fusion landscape of mCRPC. Pie chart of all driver fusions identified and the box plot represents specific ETS fusions. C, Mutations enriched in mCRPC relative to hormone naïve primary prostate cancer. Primary prostate cancer data derived from published studies (Barbieri et al., 2012) (TCGA, Provisional 2015). Level of CRPC enrichment represented by the×axis and MutSig CRPC significance analysis provided by the y axis. Diameters are proportional to the number of cases with the specific aberration. Genes of interest are highlighted. D, Classes of driver aberrations identified in mCRPC. E, Classes of clinically actionable mutations identified in mCRPC.
Figure 4. Aberrations in the AR pathway…
Figure 4. Aberrations in the AR pathway found in mCRPC
A, Cases with aberrations in the AR pathway. Case numbering as in Fig. 2. B, Key genes found altered in the AR pathway of mCRPC. DHT, dihydrotestosterone. C, Point mutations identified in AR. Amino acids altered are indicated. NTAD, N-terminal activation. DBD, DNA-binding. LBD, ligand binding. D, Splicing landscape of AR in mCRPC. Specific splice variants are indicated by exon boundaries and junction read level provided. SU2C, this mCRPC cohort. PRAD tumor, primary prostate cancer from the TCGA. PRAD normal, benign prostate from the TCGA. E, Homozygous deletion of ZBTB16. Copy number plots with×axis representing chromosomal location and the y axis referring to copy number level. Red outline indicates region of ZBTB16 homozygous loss.
Figure 5. Aberrations in the PI(3)K pathway…
Figure 5. Aberrations in the PI(3)K pathway found in mCRPC
A, Cases with aberrations in the PIK3 pathway. Case numbering as in Fig. 2. B, Point mutations identified in PIK3CB. Amino acids altered are indicated. Analogous, recurrent COSMIC mutations in PIK3CA are shown as expansion views. C, Outlier expression of PK3CA in CRPC case harboring the TBL1XR1-PIK3CA gene fusion. Structure of the gene fusion is inset. UTR, untranslated region. CDS, coding sequence. D. As in C, except for PIK3CB and the ACPP-PIK3CB gene fusion.
Figure 6. Aberrations in the WNT pathway…
Figure 6. Aberrations in the WNT pathway found in mCRPC
A, Cases with aberrations in the WNT pathway. Case numbering as in Fig. 2. B, Aberrations identified in APC and CTNNB1. Amino acids altered are indicated. ARM, armadillo repeat. Phos, phosphorylation domain. TAD, trans-activating domain. EB1, end binding protein-1 domain. CC, coiled coil. C, Outlier expression of RSPO2 in CRPC and the GRHL2-RSPO2 gene fusion. RNA-seq expression across our CRPC cohort. Structure of the gene fusion is inset. UTR, untranslated region. CDS, coding sequence.
Figure 7. Aberrations in the DNA repair…
Figure 7. Aberrations in the DNA repair pathway found in mCRPC
A, Cases with aberrations in the DNA repair pathway. Case numbering as in Fig. 2. B, Aberrations identified in BRCA2, ATM and BRCA1. Amino acids altered are indicated. HELC, helical domain. OB, oligonucleotide binding fold. FAT, FRAP-ATM-TRRAP domain. PIK3c, PI3 kinase domain. CC, coiled coil. BRC, Brca repeat. C, Microsatellite instability analysis of representative hypermutated CRPC cases and non-hypermutated cases.

Source: PubMed

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