Characterising the contribution of rare protein-coding germline variants to prostate cancer risk and severity in 37,184 cases.

The etiology of prostate cancer, the second most common cancer in men globally, has a strong heritable component. While rare coding germline variants in several genes have been identified as risk factors from candidate gene and linkage studies, the exome-wide spectrum of causal rare variants remains to be fully explored. To more comprehensively address their contribution, we analysed data from 37,184 prostate cancer cases and 331,329 male controls from five cohorts with germline exome/genome sequencing and one cohort with imputed array data from a population enriched in low-frequency deleterious variants. Our gene-level collapsing analysis revealed that rare damaging variants in SAMHD1 as well as genes in the DNA damage response pathway (BRCA2, ATM and CHEK2) are associated with the risk of overall prostate cancer. We also found that rare damaging variants in AOX1 and BRCA2 were associated with increased severity of prostate cancer in a case-only analysis of aggressive versus non-aggressive prostate cancer. At the single-variant level, we found rare non-synonymous variants in three genes (HOXB13, CHEK2, BIK) significantly associated with increased risk of overall prostate cancer and in four genes (ANO7, SPDL1, AR, TERT) with decreased risk. Altogether, this study provides deeper insights into the genetic architecture and biological basis of prostate cancer risk and severity.

Phase Ib Trial of the Combination of Imatinib and Binimetinib in Patients with Advanced Gastrointestinal Stromal Tumors.

PURPOSE: This phase Ib trial was designed to evaluate the safety and early efficacy signal of the combination of imatinib and binimetinib in patients with imatinib-resistant advanced gastrointestinal stromal tumors (GISTs). PATIENTS AND METHODS: This trial used a standard 3 + 3 design to determine the recommended phase II dose (RP2D). Additional patients were enrolled on an expansion cohort at the RP2D enriching for succinate dehydrogenase (SDH)-deficient GISTs to explore potential efficacy. RESULTS: The trial enrolled nine patients in the dose-escalation cohort and 14 in the dose-expansion cohort including six with SDH-deficient GISTs. Imatinib 400 mg daily with binimetinib 45 mg twice daily was established as the RP2D. Dose-limiting toxicity (DLT) was asymptomatic grade 4 creatinine phosphokinase (CPK) elevation. The most common non-DLT grade 3/4 toxicity was asymptomatic CPK elevation (69.6%). Other common ≥grade 2 toxicities included peripheral edema (17.4%), acneiform rash (21.7%), anemia (30.4%), hypophosphatemia (39.1%), and aspartate aminotransferase (AST) increase (17.4%). Two serious adverse events occurred (grade 2 dropped head syndrome and grade 3 central retinal vein occlusion). No unexpected toxicities were observed. Limited clinical activity was observed in KIT-mutant GIST. For SDH-deficient GISTs, one of five had confirmed RECIST1.1 partial response (PR). The median progression-free survival (mPFS) in patients with SDH-deficient GIST was 45.1 months [95% confidence interval (CI), 15.8-not estimable (NE)]; the median overall survival (mOS) was not reached (95% CI, 31.6 months-NE). One patient with a refractory metastatic SDH-deficient GIST had an exceptional pathologic response and durable clinical benefit. CONCLUSIONS: The combination of imatinib and binimetinib is safe with manageable toxicity and has encouraging activity in SDH-deficient but not imatinib-refractory KIT/PDGFRA-mutant GISTs. The observed clinical benefits provide a motivation for a larger trial of the combination strategy in SDH-deficient GISTs.

Author Correction: Genetic alterations in the 3q26.31-32 locus confer an aggressive prostate cancer phenotype.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Genetic alterations in the 3q26.31-32 locus confer an aggressive prostate cancer phenotype.

Large-scale genetic aberrations that underpin prostate cancer development and progression, such as copy-number alterations (CNAs), have been described but the consequences of specific changes in many identified loci is limited. Germline SNPs in the 3q26.31 locus are associated with aggressive prostate cancer, and is the location of NAALADL2, a gene overexpressed in aggressive disease. The closest gene to NAALADL2 is TBL1XR1, which is implicated in tumour development and progression. Using publicly-available cancer genomic data we report that NAALADL2 and TBL1XR1 gains/amplifications are more prevalent in aggressive sub-types of prostate cancer when compared to primary cohorts. In primary disease, gains/amplifications occurred in 15.99% (95% CI: 13.02-18.95) and 14.96% (95% CI: 12.08-17.84%) for NAALADL2 and TBL1XR1 respectively, increasing in frequency in higher Gleason grade and stage tumours. Gains/amplifications result in transcriptional changes and the development of a pro-proliferative and aggressive phenotype. These results support a pivotal role for copy-number gains in this genetic region.

Development of Genome-Derived Tumor Type Prediction to Inform Clinical Cancer Care.

IMPORTANCE: Diagnosing the site of origin for cancer is a pillar of disease classification that has directed clinical care for more than a century. Even in an era of precision oncologic practice, in which treatment is increasingly informed by the presence or absence of mutant genes responsible for cancer growth and progression, tumor origin remains a critical factor in tumor biologic characteristics and therapeutic sensitivity. OBJECTIVE: To evaluate whether data derived from routine clinical DNA sequencing of tumors could complement conventional approaches to enable improved diagnostic accuracy. DESIGN, SETTING, AND PARTICIPANTS: A machine learning approach was developed to predict tumor type from targeted panel DNA sequence data obtained at the point of care, incorporating both discrete molecular alterations and inferred features such as mutational signatures. This algorithm was trained on 7791 tumors representing 22 cancer types selected from a prospectively sequenced cohort of patients with advanced cancer. RESULTS: The correct tumor type was predicted for 5748 of the 7791 patients (73.8%) in the training set as well as 8623 of 11 644 patients (74.1%) in an independent cohort. Predictions were assigned probabilities that reflected empirical accuracy, with 3388 cases (43.5%) representing high-confidence predictions (>95% probability). Informative molecular features and feature categories varied widely by tumor type. Genomic analysis of plasma cell-free DNA yielded accurate predictions in 45 of 60 cases (75.0%), suggesting that this approach may be applied in diverse clinical settings including as an adjunct to cancer screening. Likely tissues of origin were predicted from targeted tumor sequencing in 95 of 141 patients (67.4%) with cancers of unknown primary site. Applying this method prospectively to patients under active care enabled genome-directed reassessment of diagnosis in 2 patients initially presumed to have metastatic breast cancer, leading to the selection of more appropriate treatments, which elicited clinical responses. CONCLUSIONS AND RELEVANCE: These results suggest that the application of artificial intelligence to predict tissue of origin in oncologic practice can act as a useful complement to conventional histologic review to provide integrated pathologic diagnoses, often with important therapeutic implications.

Genomic and Transcriptomic Characterization of Papillary Microcarcinomas With Lateral Neck Lymph Node Metastases.

CONTEXT: Most papillary microcarcinomas (PMCs) are indolent and subclinical. However, as many as 10% can present with clinically significant nodal metastases. OBJECTIVE AND DESIGN: Characterization of the genomic and transcriptomic landscape of PMCs presenting with or without clinically important lymph node metastases. SUBJECTS AND SAMPLES: Formalin-fixed paraffin-embedded PMC samples from 40 patients with lateral neck nodal metastases (pN1b) and 71 patients with PMC with documented absence of nodal disease (pN0). OUTCOME MEASURES: To interrogate DNA alterations in 410 genes commonly mutated in cancer and test for differential gene expression using a custom NanoString panel of 248 genes selected primarily based on their association with tumor size and nodal disease in the papillary thyroid cancer TCGA project. RESULTS: The genomic landscapes of PMC with or without pN1b were similar. Mutations in TERT promoter (3%) and TP53 (1%) were exclusive to N1b cases. Transcriptomic analysis revealed differential expression of 43 genes in PMCs with pN1b compared with pN0. A random forest machine learning-based molecular classifier developed to predict regional lymph node metastasis demonstrated a negative predictive value of 0.98 and a positive predictive value of 0.72 at a prevalence of 10% pN1b disease. CONCLUSIONS: The genomic landscape of tumors with pN1b and pN0 disease was similar, whereas 43 genes selected primarily by mining the TCGA RNAseq data were differentially expressed. This bioinformatics-driven approach to the development of a custom transcriptomic assay provides a basis for a molecular classifier for pN1b risk stratification in PMC.

Sequencing of prostate cancers identifies new cancer genes, routes of progression and drug targets.

Prostate cancer represents a substantial clinical challenge because it is difficult to predict outcome and advanced disease is often fatal. We sequenced the whole genomes of 112 primary and metastatic prostate cancer samples. From joint analysis of these cancers with those from previous studies (930 cancers in total), we found evidence for 22 previously unidentified putative driver genes harboring coding mutations, as well as evidence for NEAT1 and FOXA1 acting as drivers through noncoding mutations. Through the temporal dissection of aberrations, we identified driver mutations specifically associated with steps in the progression of prostate cancer, establishing, for example, loss of CHD1 and BRCA2 as early events in cancer development of ETS fusion-negative cancers. Computational chemogenomic (canSAR) analysis of prostate cancer mutations identified 11 targets of approved drugs, 7 targets of investigational drugs, and 62 targets of compounds that may be active and should be considered candidates for future clinical trials.

Appraising the relevance of DNA copy number loss and gain in prostate cancer using whole genome DNA sequence data.

A variety of models have been proposed to explain regions of recurrent somatic copy number alteration (SCNA) in human cancer. Our study employs Whole Genome DNA Sequence (WGS) data from tumor samples (n = 103) to comprehensively assess the role of the Knudson two hit genetic model in SCNA generation in prostate cancer. 64 recurrent regions of loss and gain were detected, of which 28 were novel, including regions of loss with more than 15% frequency at Chr4p15.2-p15.1 (15.53%), Chr6q27 (16.50%) and Chr18q12.3 (17.48%). Comprehensive mutation screens of genes, lincRNA encoding sequences, control regions and conserved domains within SCNAs demonstrated that a two-hit genetic model was supported in only a minor proportion of recurrent SCNA losses examined (15/40). We found that recurrent breakpoints and regions of inversion often occur within Knudson model SCNAs, leading to the identification of ZNF292 as a target gene for the deletion at 6q14.3-q15 and NKX3.1 as a two-hit target at 8p21.3-p21.2. The importance of alterations of lincRNA sequences was illustrated by the identification of a novel mutational hotspot at the KCCAT42, FENDRR, CAT1886 and STCAT2 loci at the 16q23.1-q24.3 loss. Our data confirm that the burden of SCNAs is predictive of biochemical recurrence, define nine individual regions that are associated with relapse, and highlight the possible importance of ion channel and G-protein coupled-receptor (GPCR) pathways in cancer development. We concluded that a two-hit genetic model accounts for about one third of SCNA indicating that mechanisms, such haploinsufficiency and epigenetic inactivation, account for the remaining SCNA losses.

Mutational landscape of metastatic cancer revealed from prospective clinical sequencing of 10,000 patients.

Tumor molecular profiling is a fundamental component of precision oncology, enabling the identification of genomic alterations in genes and pathways that can be targeted therapeutically. The existence of recurrent targetable alterations across distinct histologically defined tumor types, coupled with an expanding portfolio of molecularly targeted therapies, demands flexible and comprehensive approaches to profile clinically relevant genes across the full spectrum of cancers. We established a large-scale, prospective clinical sequencing initiative using a comprehensive assay, MSK-IMPACT, through which we have compiled tumor and matched normal sequence data from a unique cohort of more than 10,000 patients with advanced cancer and available pathological and clinical annotations. Using these data, we identified clinically relevant somatic mutations, novel noncoding alterations, and mutational signatures that were shared by common and rare tumor types. Patients were enrolled on genomically matched clinical trials at a rate of 11%. To enable discovery of novel biomarkers and deeper investigation into rare alterations and tumor types, all results are publicly accessible.

KRAS and Combined KRAS/TP53 Mutations in Locally Advanced Rectal Cancer are Independently Associated with Decreased Response to Neoadjuvant Therapy.

BACKGROUND: The response of rectal cancers to neoadjuvant chemoradiation (CRT) is variable, but tools to predict response remain lacking. We evaluated whether KRAS and TP53 mutations are associated with pathologic complete response (pCR) and lymph node metastasis after adjusting for neoadjuvant regimen. METHODS: Retrospective analysis of 229 pretreatment biopsies from patients with stage II/III rectal cancer was performed. All patients received CRT. Patients received 0-8 cycles of FOLFOX either before or after CRT, but prior to surgical excision. A subset was analyzed to assess concordance between mutation calls by Sanger Sequencing and a next-generation assay. RESULTS: A total of 96 tumors (42 %) had KRAS mutation, 150 had TP53 mutation (66 %), and 59 (26 %) had both. Following neoadjuvant therapy, 59 patients (26 %) achieved pCR. Of 133 KRAS wild-type tumors, 45 (34 %) had pCR, compared with 14 of 96 (15 %) KRAS mutant tumors (p = .001). KRAS mutation remained independently associated with a lower pCR rate on multivariable analysis after adjusting for clinical stage, CRT-to-surgery interval and cycles of FOLFOX (OR 0.34; 95 % CI 0.17-0.66, p < .01). Of 29 patients with KRAS G12V or G13D, only 2 (7 %) achieved pCR. Tumors with both KRAS and TP53 mutation were associated with lymph node metastasis. The concordance between platforms was high for KRAS (40 of 43, 93 %). CONCLUSIONS: KRAS mutation is independently associated with a lower pCR rate in locally advanced rectal cancer after adjusting for variations in neoadjuvant regimen. Genomic data can potentially be used to select patients for "watch and wait" strategies.

Analysis of the genetic phylogeny of multifocal prostate cancer identifies multiple independent clonal expansions in neoplastic and morphologically normal prostate tissue.

Genome-wide DNA sequencing was used to decrypt the phylogeny of multiple samples from distinct areas of cancer and morphologically normal tissue taken from the prostates of three men. Mutations were present at high levels in morphologically normal tissue distant from the cancer, reflecting clonal expansions, and the underlying mutational processes at work in morphologically normal tissue were also at work in cancer. Our observations demonstrate the existence of ongoing abnormal mutational processes, consistent with field effects, underlying carcinogenesis. This mechanism gives rise to extensive branching evolution and cancer clone mixing, as exemplified by the coexistence of multiple cancer lineages harboring distinct ERG fusions within a single cancer nodule. Subsets of mutations were shared either by morphologically normal and malignant tissues or between different ERG lineages, indicating earlier or separate clonal cell expansions. Our observations inform on the origin of multifocal disease and have implications for prostate cancer therapy in individual cases.