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The Diverse Genomic Landscape of Clinically Low-risk Prostate Cancer.

ABSTRACT: BACKGROUND:Among men with clinically low-risk prostate cancer, we have previously documented heterogeneity in terms of clinical characteristics and genomic risk scores. OBJECTIVE:To further study the underlying tumor biology of this patient population, by interrogating broader patterns of gene expression among men with clinically low-risk tumors. DESIGN, SETTING, AND PARTICIPANTS:Prostate biopsies from 427 patients considered potentially suitable for active surveillance underwent central pathology review and genome-wide expression profiling. These cases were compared with 1290 higher-risk biopsy cases with diverse clinical features from a prospective genomic registry. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS:Average genomic risk (AGR) was determined from 18 published prognostic signatures, and MSigDB hallmark gene sets were analyzed using bootstrapped clustering methods. These sets were examined in relation to clinical variables and pathological and biochemical outcomes using multivariable regression analysis. RESULTS AND LIMITATIONS:A total of 408 (96%) biopsies passed RNA quality control. Based on AGR quartiles defined by the high-risk multicenter cases, the University of California, San Francisco (UCSF) low-risk patients were distributed across the quartiles as 219 (54%), 107 (26%), 61 (15%), and 21 (5%). Unsupervised clustering analysis of the hallmark gene set scores revealed three clusters, which were enriched for the previously described PAM50 luminal A, luminal B, and basal subtypes. AGR, but not the clusters, was associated with both pathological (odds ratio 1.34, 95% confidence interval [CI] 1.14-1.58) and biochemical outcomes (hazard ratio 1.53, 95% CI 1.19-1.93). These results may underestimate within-prostate genomic heterogeneity. CONCLUSIONS:Prostate cancers that are homogeneously low risk by traditional characteristics demonstrate substantial diversity at the level of genomic expression. Molecular substratification of low-risk prostate cancer will yield a better understanding of its divergent biology and, in the future may help personalize treatment recommendations. PATIENT SUMMARY:We studied the genomic characteristics of tumors from men diagnosed with low-risk prostate cancer. We found three main subtypes of prostate cancer with divergent tumor biology, similar to what has previously been found in women with breast cancer. In addition, we found that genomic risk scores were associated with worse pathology findings and prostate-specific antigen recurrence after surgery. These results suggest even greater genomic diversity among low-risk patients than has previously been documented with more limited signatures.

SUBMITTER: Cooperberg MR

PROVIDER: S-EPMC6586429 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature

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The Diverse Genomic Landscape of Clinically Low-risk Prostate Cancer.

Cooperberg Matthew R MR Erho Nicholas N Chan June M JM Feng Felix Y FY Fishbane Nick N Zhao Shuang G SG Simko Jeffry P JP Cowan Janet E JE Lehrer Jonathan J Alshalalfa Mohammed M Kolisnik Tyler T Chelliserry Jijumon J Margrave Jennifer J Aranes Maria M Plessis Marguerite du MD Buerki Christine C Tenggara Imelda I Davicioni Elai E Carroll Peter R PR

European urology 20180528 4

<h4>Background</h4>Among men with clinically low-risk prostate cancer, we have previously documented heterogeneity in terms of clinical characteristics and genomic risk scores.<h4>Objective</h4>To further study the underlying tumor biology of this patient population, by interrogating broader patterns of gene expression among men with clinically low-risk tumors.<h4>Design, setting, and participants</h4>Prostate biopsies from 427 patients considered potentially suitable for active surveillance und ...[more]

PMID: 29853306

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Project description:To prospectively evaluate diagnostic performance of T2-weighted magnetic resonance (MR) imaging and MR spectroscopic imaging in detecting lesions stratified by pathologic volume and Gleason score in men with clinically determined low-risk prostate cancer.The institutional review board approved this prospective, HIPAA-compliant study. Written informed consent was obtained from 183 men with clinically low-risk prostate cancer (cT1-cT2a, Gleason score≤6 at biopsy, prostate-specific antigen [PSA] level<10 ng/mL [10 μg/L]) undergoing MR imaging before prostatectomy. By using a scale of 1-5 (score 1, definitely no tumor; score 5, definitely tumor), two radiologists independently scored likelihood of tumor per sextant on T2-weighted images. Two spectroscopists jointly recorded locations of lesions with metabolic features consistent with tumor on MR spectroscopic images. Whole-mount step-section histopathologic analysis constituted the reference standard. Diagnostic performance at sextant level (T2-weighted imaging) and detection sensitivities (T2-weighted imaging and MR spectroscopic imaging) for lesions of 0.5 cm3 or larger were calculated.For T2-weighted imaging, areas under the receiver operating characteristic curves for sextant-level detection were 0.77 (reader 1) and 0.82 (reader 2). For lesions of ≥0.5 cm3 and, 1<cm3, sensitivities were significantly lower when the lesion Gleason score was ≤6 (0.44 [reader 1] and 0.61 [reader 2]) rather than when the Gleason score was ≥7 (0.73, P=.02 [reader 1]; and 0.84, P=.05 [reader 2]). For lesions of ≥1 cm3, lesion Gleason score did not significantly affect sensitivity (0.83 [reader 1] and 1.00 [reader 2] for Gleason score≤6 vs 0.82 and 0.92 for Gleason score≥7; P≥.07). MR spectroscopic imaging sensitivity was low and was not significantly affected by pathologic lesion volume or Gleason score.In men with clinically low-risk prostate cancer, detection of lesions of <1 cm3 with T2-weighted imaging is significantly dependent on lesion Gleason score; detection of lesions of ≥1 cm3 is significantly better than detection of smaller lesions and is not affected by lesion Gleason score. The role of MR spectroscopic imaging alone in this population is limited.

Project description:Background:Intratumoural heterogeneity (ITH) is well recognised in prostate cancer (PC), but its role in high-risk disease is uncertain. A prospective, single-arm, translational study using targeted multiregion prostate biopsies was carried out to study genomic and T-cell ITH in clinically high-risk PC aiming to identify drivers and potential therapeutic strategies. Patients and methods:Forty-nine men with elevated prostate-specific antigen and multiparametric-magnetic resonance imaging detected PC underwent image-guided multiregion transperineal biopsy. Seventy-nine tumour regions from 25 patients with PC underwent sequencing, analysis of mutations, copy number and neoepitopes combined with tumour infiltrating T-cell subset quantification. Results:We demonstrated extensive somatic nucleotide variation and somatic copy number alteration heterogeneity in high-risk PC. Overall, the mutational burden was low (0.93/Megabase), but two patients had hypermutation, with loss of mismatch repair (MMR) proteins, MSH2 and MSH6. Somatic copy number alteration burden was higher in patients with metastatic hormone-naive PC (mHNPC) than in those with high-risk localised PC (hrlPC), independent of Gleason grade. Mutations were rarely ubiquitous and mutational frequencies were similar for mHNPC and hrlPC patients. Enrichment of focal 3q26.2 and 3q21.3, regions containing putative metastasis drivers, was seen in mHNPC patients. We found evidence of parallel evolution with three separate clones containing activating mutations of ?-catenin in a single patient. We demonstrated extensive intratumoural and intertumoural T-cell heterogeneity and high inflammatory infiltrate in the MMR-deficient (MMRD) patients and the patient with parallel evolution of ?-catenin. Analysis of all patients with activating Wnt/?-catenin mutations demonstrated a low CD8+/FOXP3+?ratio, a potential surrogate marker of immune evasion. Conclusions:The PROGENY (PROstate cancer GENomic heterogeneitY) study provides a diagnostic platform suitable for studying tumour ITH. Genetic aberrations in clinically high-risk PC are associated with altered patterns of immune infiltrate in tumours. Activating mutations of Wnt/?-catenin signalling pathway or MMRD could be considered as potential biomarkers for immunomodulation therapies. Clinical Trials.gov Identifier:NCT02022371.

Project description:BackgroundMajority of prostate cancer (PCa) deaths are attributed to localized high-grade aggressive tumours which progress rapidly to metastatic disease. A critical unmet need in clinical management of PCa is discovery and characterization of the molecular drivers of aggressive tumours. The development and progression of aggressive PCa involve genetic and epigenetic alterations occurring in the germline, somatic (tumour), and epigenomes. To date, interactions between genes containing germline, somatic, and epigenetic mutations in aggressive PCa have not been characterized. The objective of this investigation was to elucidate the genomic-epigenomic interaction landscape in aggressive PCa to identify potential drivers aggressive PCa and the pathways they control. We hypothesized that aggressive PCa originates from a complex interplay between genomic (both germline and somatic mutations) and epigenomic alterations. We further hypothesized that these complex arrays of interacting genomic and epigenomic factors affect gene expression, molecular networks, and signaling pathways which in turn drive aggressive PCa.MethodsWe addressed these hypotheses by performing integrative data analysis combining information on germline mutations from genome-wide association studies with somatic and epigenetic mutations from The Cancer Genome Atlas using gene expression as the intermediate phenotype.ResultsThe investigation revealed signatures of genes containing germline, somatic, and epigenetic mutations associated with aggressive PCa. Aberrant DNA methylation had effect on gene expression. In addition, the investigation revealed molecular networks and signalling pathways enriched for germline, somatic, and epigenetic mutations including the STAT3, PTEN, PCa, ATM, AR, and P53 signalling pathways implicated in aggressive PCa.ConclusionsThe study demonstrated that integrative analysis combining diverse omics data is a powerful approach for the discovery of potential clinically actionable biomarkers, therapeutic targets, and elucidation of oncogenic interactions between genomic and epigenomic alterations in aggressive PCa.

Project description:ObjectivesTo develop an automatic method for identification and segmentation of clinically significant prostate cancer in low-risk patients and to evaluate the performance in a routine clinical setting.MethodsA consecutive cohort (n = 292) from a prospective database of low-risk patients eligible for the active surveillance was selected. A 3-T multi-parametric MRI at 3 months after inclusion was performed. Histopathology from biopsies was used as reference standard. MRI positivity was defined as PI-RADS score ≥ 3, histopathology positivity was defined as ISUP grade ≥ 2. The selected cohort contained four patient groups: (1) MRI-positive targeted biopsy-positive (n = 116), (2) MRI-negative systematic biopsy-negative (n = 55), (3) MRI-positive targeted biopsy-negative (n = 113), (4) MRI-negative systematic biopsy-positive (n = 8). Group 1 was further divided into three sets and a 3D convolutional neural network was trained using different combinations of these sets. Two MRI sequences (T2w, b = 800 DWI) and the ADC map were used as separate input channels for the model. After training, the model was evaluated on the remaining group 1 patients together with the patients of groups 2 and 3 to identify and segment clinically significant prostate cancer.ResultsThe average sensitivity achieved was 82-92% at an average specificity of 43-76% with an area under the curve (AUC) of 0.65 to 0.89 for different lesion volumes ranging from > 0.03 to > 0.5 cc.ConclusionsThe proposed deep learning computer-aided method yields promising results in identification and segmentation of clinically significant prostate cancer and in confirming low-risk cancer (ISUP grade ≤ 1) in patients on active surveillance.Key points• Clinically significant prostate cancer identification and segmentation on multi-parametric MRI is feasible in low-risk patients using a deep neural network. • The deep neural network for significant prostate cancer localization performs better for lesions with larger volumes sizes (> 0.5 cc) as compared to small lesions (> 0.03 cc). • For the evaluation of automatic prostate cancer segmentation methods in the active surveillance cohort, the large discordance group (MRI positive, targeted biopsy negative) should be included.

Project description:BackgroundThe consequences of low prostate-specific antigen (PSA) in high-grade (Gleason 8-10) prostate cancer are unknown.ObjectiveTo evaluate the clinical implications and genomic features of low-PSA, high-grade disease.Design, setting, and participantsThis was a retrospective study of clinical data for 494 793 patients from the National Cancer Data Base and 136 113 patients from the Surveillance, Epidemiology, and End Results program with cT1-4N0M0 prostate cancer (median follow-up 48.9 and 25.0 mo, respectively), and genomic data for 4960 patients from the Decipher Genomic Resource Information Database. Data were collected for 2004-2017.Outcome measurements and statistical analysisMultivariable Fine-Gray and Cox regressions were used to analyze prostate cancer-specific mortality (PCSM) and all-cause mortality, respectively.Results and limitationsFor Gleason 8-10 disease, using PSA 4.1-10.0ng/ml (n=38 719) as referent, the distribution of PCSM by PSA was U-shaped, with an adjusted hazard ratio (AHR) of 2.70 for PSA ≤2.5ng/ml (n=3862, p<0.001) versus 1.97, 1.36, and 2.56 for PSA of 2.6-4.0 (n=4199), 10.1-20.0 (n=17 372), and >20.0ng/ml (n=16 114), respectively. By contrast, the distribution of PCSM by PSA was linear for Gleason ≤7 (using PSA 4.1-10.0ng/ml as the referent, n=359 898), with an AHR of 0.41 (p=0.13) for PSA ≤2.5ng/ml (n=37 812) versus 1.38, 2.28, and 4.61 for PSA of 2.6-4.0 (n=54 152), 10.1-20.0 (n=63 319), and >20.0ng/ml (n=35 459), respectively (pinteraction<0.001). Gleason 8-10, PSA ≤2.5ng/ml disease had a significantly higher PCSM than standard high-risk/very high-risk disease with PSA >2.5ng/ml (AHR 2.15, p=0.002; 47-mo PCSM 14% vs 4.9%). Among Gleason 8-10 patients treated with radiotherapy, androgen deprivation therapy was associated with a survival benefit for PSA >2.5ng/ml (AHR 0.87; p<0.001) but not ≤2.5ng/ml (AHR 1.36; p=0.084; pinteraction=0.021). For Gleason 8-10 tumors, PSA ≤2.5ng/ml was associated with higher expression of neuroendocrine/small-cell markers compared to >2.5ng/ml (p=0.046), with no such relationship for Gleason ≤7 disease.ConclusionsLow-PSA, high-grade prostate cancer has very high risk for PCSM, potentially responds poorly to androgen deprivation therapy, and is associated with neuroendocrine genomic features.Patient summaryIn this study, we found that low-prostate-specific antigen, high-grade prostate cancer has a very high risk for prostate cancer death, may not respond well to androgen deprivation therapy, and is associated with neuroendocrine genomic features. These findings suggest that current nomograms and treatment paradigms may need modification.

Dataset Information

The Diverse Genomic Landscape of Clinically Low-risk Prostate Cancer.

Publications

The Diverse Genomic Landscape of Clinically Low-risk Prostate Cancer.

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