Substantial interindividual and limited intraindividual genomic diversity among tumors from men with metastatic prostate cancer

Journal name:
Nature Medicine
Volume:
22,
Pages:
369–378
Year published:
DOI:
doi:10.1038/nm.4053
Received
Accepted
Published online

Abstract

Tumor heterogeneity may reduce the efficacy of molecularly guided systemic therapy for cancers that have metastasized. To determine whether the genomic alterations in a single metastasis provide a reasonable assessment of the major oncogenic drivers of other dispersed metastases in an individual, we analyzed multiple tumors from men with disseminated prostate cancer through whole-exome sequencing, array comparative genomic hybridization (CGH) and RNA transcript profiling, and we compared the genomic diversity within and between individuals. In contrast to the substantial heterogeneity between men, there was limited diversity among metastases within an individual. The number of somatic mutations, the burden of genomic copy number alterations and aberrations in known oncogenic drivers were all highly concordant, as were metrics of androgen receptor (AR) activity and cell cycle activity. AR activity was inversely associated with cell proliferation, whereas the expression of Fanconi anemia (FA)-complex genes was correlated with elevated cell cycle progression, expression of the E2F transcription factor 1 (E2F1) and loss of retinoblastoma 1 (RB1). Men with somatic aberrations in FA-complex genes or in ATM serine/threonine kinase (ATM) exhibited significantly longer treatment-response durations to carboplatin than did men without defects in genes encoding DNA-repair proteins. Collectively, these data indicate that although exceptions exist, evaluating a single metastasis provides a reasonable assessment of the major oncogenic driver alterations that are present in disseminated tumors within an individual, and thus may be useful for selecting treatments on the basis of predicted molecular vulnerabilities.

At a glance

Figures

  1. Integrated landscape of somatic aberrations and AR activity in mCRPC.
    Figure 1: Integrated landscape of somatic aberrations and AR activity in mCRPC.

    (a) Recurrent somatic molecular aberrations from an index metastasis from each of 54 men with mCRPC (columns) ascertained by transcript microarray, array CGH and WES on the same tumor. Columns represent the index tumor from each individual, and rows represent specific genes. Mutations per Mb are shown in the upper histogram, with nonsynonymous mutations in blue and synonymous mutations in green. The frequency of the aberration in the cohort is shown as a percentage (%). Copy number (CN) variations common to mCRPC are shown in the lower matrix; red represents gain, blue represents loss and purple represents no loss or gain. Cases with more than one aberration in a gene are represented by split colors. Except for arm-level CN variations (CNVs), only high-level gain and loss are shown. The 54 individuals with expression, CN and mutation data are shown. HZ, heterozygosity; nonsyn., nonsynonymous mutation. (b) AR CN quantification in the TCGA31, Taylor et al.26 and Grasso et al.19 studies of untreated primary PC and mCRPC. (c) AR activity as determined by transcript levels of 21 AR-regulated genes across CRPC tumors obtained at rapid autopsy. AR activity scores are also shown for microdissected cell populations of bladder urothelium (bladder); BP, benign prostate epithelium; CP, primary prostate cancer; G, Gleason pattern. AR somatic mutation and CN status for each tumor sample are shown in the lower matrix. (d) Consistency of the AR activity score for metastatic tumors within individuals, and diversity of the AR activity score in tumors between individuals. The y axis is the AR activity score and x axis shows individual men. Scores for individual tumors are plotted over a range of 0–100% as a box and whiskers plot, with the box showing the interquartile range (IQR) and the upper and lower whiskers extending to the values that are within 1.5 × IQR; data beyond the end of the whiskers are outliers and plotted as points. Colors are used to denote different individuals. Circles are metastatic tumors (n = 149) and triangles are primary tumors (n = 22) resected at rapid autopsy.

  2. Relationships between AR activity and the expression of AR and other nuclear hormone receptor genes.
    Figure 2: Relationships between AR activity and the expression of AR and other nuclear hormone receptor genes.

    (a) The relationship between AR transcript expression, plotted as mean centered log2 ratio, to the AR activity score for each tumor. Blue points represent adenocarcinomas, in which AR activity levels are correlated with AR level; black points are neuroendocrine tumors; red circles are tumors with high AR activity and relatively low AR expression. There was a positive overall correlation between AR transcript levels and AR activity score (Pearson's product moment correlation analysis, r = 0.74; P < 0.001). (b) Transcript levels of nuclear hormone receptors for the 15 tumors with high AR activity and low AR expression. NR3C1, nuclear receptor subfamily 3 group C member 1; PGR, progesterone receptor; ESR1, estrogen receptor 1; ESR2, estrogen receptor 2. (c) Immunohistochemical assessment of AR (also known as NR3C4), NR3C1, kallikrein-related peptidase 3 (KLK3) and chromogranin A (CHGA) proteins in mCRPC tumors from three men with different AR expression and AR activity relationships: 99-091 expresses AR and the AR-regulated protein KLK3, whereas 03-139 lacks AR expression but expresses NR3C1 and KLK3. Asterisk (*), cells with positive staining. Scale bar, 200 μm.

  3. Molecular aberrations are shared between metastases within individuals with mCRPC.
    Figure 3: Molecular aberrations are shared between metastases within individuals with mCRPC.

    (a) Gene expression pathways and putative somatic driver aberrations are consistent across metastases within an individual. Shown are selected features from five metastatic tumors from patient 99-091. Activity scores comprise transcripts of genes regulated by AR (AR activity score), genes expressed in neuroendocrine carcinoma (NE activity score). Genes shown are putative PC-driver genes. ERG transcript levels are relative to the mean-centered ratio for the cohort. NSV, number of somatic nonsynonymous (nonsyn.) nucleotide variants. Genome-wide copy number losses (blue) and gains (red) are shown for each tumor, ordered by chromosome. Approximate physical locations of the metastatic tumors are shown in orange overlaid on the skeletal bone scan (C = liver metastases; I, J, K, N = individual LN metastases). (b) Distribution of all 91 nonsynonymous point mutations and indels identified in the five tumors from patient 99-091. Individual tumors comprise rows, with columns comprising individual mutations color coded by the type of mutation or its absence (white) in each tumor. The gray scale bars indicate the frequency of a mutation in the specified gene in the TCGA (primary tumors) or the SU2C-PCF (metastatic tumors) data sets. (c) Relationships of tumors derived from a single person (red points), relative to tumors from all other individuals (blue points), based on a calculated sample similarity score that comprised single-nucleotide variants, CNAs and gene expression, using the 133 tumors with data on all three platforms. (d) Unsupervised clustering of 149 tumors by correlation of genome-wide CNVs. Tumors from the same individual are designated with the same color. Black circles denote primary tumors. (e) Heat map of the percentage of the total of 984 distinct copy number losses and gains identified in the entire cohort of tumors that differ between samples, sorted on the basis of complete linkage dendrograms. Margin line denotes tumors with very low copy number aberration burden. Tumors from the same individual are denoted by the same color, shown on the bottom and right figure margins. The diversity index is defined as the proportion of corresponding aberrations that differed between samples: limited intraindividual diversity is reflected by green areas located at the intersection of tumors from the same individual.

  4. Tumor cell cycle activity within and between individuals.
    Figure 4: Tumor cell cycle activity within and between individuals.

    (a) CCP scores are based on the expression of 31 cell cycle–associated transcripts and vary across tumors. The genes comprising the CCP score are shown with expression levels colored to reflect high (yellow) or low (blue) transcript abundance. Columns represent individual tumors, excepting bladder, benign prostate epithelium (BP), primary PC with Gleason grade 6 (CP G3) and primary PC with Gleason pattern ≥ 7 (CP G4), which are composites of 10–20 samples. The 171 CRPC tumors from 63 men with expression data are shown. (b) Correlation between CCP score and Ki67-specific immunohistochemistry (IHC) (Pearson's product moment correlation analysis, r = 0.48; P < 0.005) in 36 tumors with matching protein and RNA expression data. (c) CCP scores (y axis) for each of 171 tumors grouped by patient (x axis) are plotted as a box and whiskers, of IQR and 1.5 × IQR, respectively; data beyond the end of the whiskers are outliers and plotted as points.

  5. CCP activity and E2F1 expression are inversely associated with AR activity.
    Figure 5: CCP activity and E2F1 expression are inversely associated with AR activity.

    (a) CCP scores are inversely associated with AR activity scores, as determined by the expression levels of 21 AR-regulated genes in 171 tumors (Pearson's product moment correlation analysis, r = −0.36; P < 0.001). (b) Inverse association between CCP scores and AR activity scores was also observed in a published data set19 of 35 CRPC tumors (Pearson's product moment correlation analysis, r = −0.42; P = 0.01). (c) AR activity is inversely associated with E2F1 transcript expression in 171 tumors (Pearson's product moment correlation analysis, r = −0.43; P < 0.001). (d) AR expression level influences cellular responses to the AR ligand R1881. Left, representative western blot (n = 2) of AR and glyceraldehyde-3-phosphate dehydrogenase (GAPDH) protein levels in LNCaPWT cells and in LNCaPAR cells engineered to overexpress AR (rAR). Right, LNCaPWT and LNCaPAR cell growth measured 72 h after exposure to the indicated R1881 concentration; n = 4 in each group, box and whiskers plots showing IQR and min to max. *P < 0.0001 by two-sample t test.

  6. Expression levels of FA-complex genes are associated with CCP and E2F1 expression.
    Figure 6: Expression levels of FA-complex genes are associated with CCP and E2F1 expression.

    (a) CCP scores for each tumor are ordered from high (left) to low (right). Corresponding FA-complex genes expressed in each tumor are colored to reflect high (yellow) or low (blue) transcript abundance. Columns represent individual tumors, excepting bladder; BP, benign prostate; CP G3, primary PC with Gleason pattern 3; CP G4, primary PC with Gleason pattern 4, which are composites of 10–20 samples. The 171 CRPC tumors from 63 men with expression data are shown. (b) Higher CCP score is associated with heterozygous and homozygous RB1 inactivation by copy loss and/or mutation. *P < 0.01 by pairwise t test to wild-type (WT) group. HZ, homozygous loss; 1CL, heterozygous loss. (c) Suppression of individual FA-complex genes reduces the proliferation of multiple prostate cancer cell lines. Cell numbers were measured 5 d after introducing siRNAs that target the specified genes, relative to scrambled control siRNAs. All gene knockdowns produced a significant reduction in growth compared to scrambled control (two-sample t test; P < 0.05; error bars are mean of n = 3 biological replicates per gene and standard deviation of measurements). (d) Time course of LNCaP cell growth after the suppression of individual FA-complex genes. Growth curves measured over 3 d after introducing siRNAs targeting the specified genes. *P < 0.05 in percentage growth compared to control for each time point using two-sample t tests (error bars are mean of n = 3 biological replicates per gene and standard deviation of measurements). (e) Assessment of DNA damage in LNCaP cells by γ-H2AX assays after the knockdown of individual FA-complex genes by siRNA and exposure to 50 μM carboplatin. All FA knockdowns produced significantly greater γ-H2AX than did scrambled siRNA controls (P < 0.05 by two-sample t test), excepting SLX4 structure-specific endonuclease subunit (SLX4), NS = not significant. Plots box and whiskers plots showing median and min to max of three replicates. (f) Kaplan-Meier plot comparing the duration of carboplatin treatment for 21 men with mCRPC with or without a germline or somatic alteration in genes involved in DNA repair: BRCA2, PALB2, or ATM (P = 0.02 by log-rank test).

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Gene Expression Omnibus

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Author information

  1. These authors jointly directed this work.

    • Akash Kumar &
    • Ilsa Coleman

Affiliations

  1. Department of Genome Sciences, University of Washington, Seattle, Washington, USA.

    • Akash Kumar,
    • Jay Shendure &
    • Peter S Nelson
  2. Division of Human Biology, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA.

    • Ilsa Coleman,
    • Hamid Bolouri,
    • Thomas White,
    • Jared M Lucas,
    • Ruth F Dumpit,
    • Navonil DeSarkar,
    • Roger Coleman &
    • Peter S Nelson
  3. Department of Urology, University of Washington, Seattle, Washington, USA.

    • Colm Morrissey,
    • Xiaotun Zhang,
    • Lisha G Brown,
    • Paul H Lange,
    • Robert L Vessella &
    • Peter S Nelson
  4. Department of Pathology, University of Washington, Seattle, Washington, USA.

    • Lawrence D True,
    • Min Fang &
    • Peter S Nelson
  5. Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA.

    • Roman Gulati,
    • Ruth Etzioni &
    • Peter S Nelson
  6. Department of Medicine, University of Washington, Seattle, Washington, USA.

    • Bruce Montgomery,
    • Celestia Higano,
    • Evan Y Yu &
    • Peter S Nelson
  7. Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, New York, USA.

    • Nikolaus Schultz
  8. Division of Clinical Research, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA.

    • Min Fang &
    • Peter S Nelson

Contributions

A.K., T.W. and I.C. coordinated overall sequencing and bioinformatics analysis. I.C. and N.S. coordinated data deposition, assembly, figures and tables. R.G., R.E., I.C. and H.B. performed statistical analyses. A.K., I.C., R.C., R.F.D., T.W., N.D. and J.S. performed sequencing and analyses. L.D.T., M.F. and X.Z. coordinated central pathology review, FISH and immunohistochemistry studies. J.M.L. conducted gene-manipulation studies and growth assays. R.L.V., L.G.B. and C.M. coordinated clinical enrollment and tissue procurement. P.H.L., C.H., E.Y.Y., P.S.N. and B.M. enrolled patients and provided clinical insights. P.S.N., I.C., J.S. and A.K. wrote the manuscript, which all authors reviewed.

Competing financial interests

The authors declare no competing financial interests.

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Supplementary information

PDF files

  1. Supplementary Text and Figures (4,501 KB)

    Supplementary Figures 1–6

Excel files

  1. Supplementary Table 1 (12,747 KB)

    CRPC Patient Clinical Data

  2. Supplementary Table 2 (26,780 KB)

    Patients, Tumor Sites, and Molecular Profiling Assays

  3. Supplementary Table 3 (10,383 KB)

    TMPRSS2-ERG Fusion by CGH or FISH

  4. Supplementary Table 4 (2,787 KB)

    MAF of mutations determined by WES

  5. Supplementary Table 5 (8,467 KB)

    Target sequences for siRNAs

  6. Supplementary Table 6 (8,939 KB)

    Primer sequences for QRT-PCR

Additional data