Whole genome and transcriptome integrated analyses guide clinical care of pediatric poor prognosis cancers.

The role for routine whole genome and transcriptome analysis (WGTA) for poor prognosis pediatric cancers remains undetermined. Here, we characterize somatic mutations, structural rearrangements, copy number variants, gene expression, immuno-profiles and germline cancer predisposition variants in children and adolescents with relapsed, refractory or poor prognosis malignancies who underwent somatic WGTA and matched germline sequencing. Seventy-nine participants with a median age at enrollment of 8.8 y (range 6 months to 21.2 y) are included. Germline pathogenic/likely pathogenic variants are identified in 12% of participants, of which 60% were not known prior. Therapeutically actionable variants are identified by targeted gene report and whole genome in 32% and 62% of participants, respectively, and increase to 96% after integrating transcriptome analyses. Thirty-two molecularly informed therapies are pursued in 28 participants with 54% achieving a clinical benefit rate; objective response or stable disease ≥6 months. Integrated WGTA identifies therapeutically actionable variants in almost all tumors and are directly translatable to clinical care of children with poor prognosis cancers.

Base excision repair deficiency signatures implicate germline and somatic MUTYH aberrations in pancreatic ductal adenocarcinoma and breast cancer oncogenesis.

We report a case of early-onset pancreatic ductal adenocarcinoma in a patient harboring biallelic MUTYH germline mutations, whose tumor featured somatic mutational signatures consistent with defective MUTYH-mediated base excision repair and the associated driver KRAS transversion mutation p.Gly12Cys. Analysis of an additional 730 advanced cancer cases (N = 731) was undertaken to determine whether the mutational signatures were also present in tumors from germline MUTYH heterozygote carriers or if instead the signatures were only seen in those with biallelic loss of function. We identified two patients with breast cancer each carrying a pathogenic germline MUTYH variant with a somatic MUTYH copy loss leading to the germline variant being homozygous in the tumor and demonstrating the same somatic signatures. Our results suggest that monoallelic inactivation of MUTYH is not sufficient for C:G>A:T transversion signatures previously linked to MUTYH deficiency to arise (N = 9), but that biallelic complete loss of MUTYH function can cause such signatures to arise even in tumors not classically seen in MUTYH-associated polyposis (N = 3). Although defective MUTYH is not the only determinant of these signatures, MUTYH germline variants may be present in a subset of patients with tumors demonstrating elevated somatic signatures possibly suggestive of MUTYH deficiency (e.g., COSMIC Signature 18, SigProfiler SBS18/SBS36, SignatureAnalyzer SBS18/SBS36).

Genomic Classifier for Guiding Treatment of Intermediate-Risk Prostate Cancers to Dose-Escalated Image Guided Radiation Therapy Without Hormone Therapy.

PURPOSE: The National Comprehensive Cancer Network (NCCN) has recently endorsed the stratification of intermediate-risk prostate cancer (IR-PCa) into favorable and unfavorable subgroups and recommend the addition of androgen deprivation therapy (ADT) to radiation therapy (RT) for unfavorable IR-PCa. Recently, more accurate prognostication was demonstrated by integrating a 22-feature genomic classifier (GC) to the NCCN stratification system. Here, we test the utility of the GC to better identify patients with IR-PCa who are sufficiently treated by RT alone. METHODS AND MATERIALS: We identified a novel cohort comprising 121 patients with IR-PCa treated with dose-escalated image guided RT (78 Gy in 39 fractions) without ADT. GC scores were derived from tumors sampled in diagnostic biopsies. Multivariable analyses, including both NCCN subclassification and GC scores, were performed for biochemical failure (prostate-specific antigen nadir + 2 ng/mL) and metastasis occurrence. RESULTS: By NCCN subclassification, 33 (27.3%) and 87 (71.9%) of men were classified as having favorable and unfavorable IR-PCa, respectively (1 case unclassifiable). GC scores were high in 3 favorable IR-PCa and low in 60 unfavorable IR-PCa. Higher GC scores, but not NCCN risk subgroups, were associated with biochemical relapse (hazard ratio, 1.36; 95% confidence interval [CI], 1.09-1.71] per 10% increase; P = .007) and metastasis (hazard ratio, 2.05; 95% CI, 1.24-4.24; P = .004). GC predicted biochemical failure at 5 years (area under the curve, 0.78; 95% CI, 0.59-0.91), and the combinatorial NCCN + GC model significantly outperformed the NCCN alone model for predicting early-onset metastasis (area under the curve for 5-year metastasis of 0.89 vs 0.86 [GC alone] vs 0.54 [NCCN alone]). CONCLUSIONS: We demonstrated the accuracy of the GC for predicting disease recurrence in IR-PCa treated with dose-escalated image guided RT alone. Our findings highlight the need to evaluate this GC in a prospective clinical trial investigating the role of ADT-RT in clinicogenomic-defined IR-PCa subgroups.

Homologous Recombination Deficiency and Platinum-Based Therapy Outcomes in Advanced Breast Cancer.

Purpose: Recent studies have identified mutation signatures of homologous recombination deficiency (HRD) in over 20% of breast cancers, as well as pancreatic, ovarian, and gastric cancers. There is an urgent need to understand the clinical implications of HRD signatures. Whereas BRCA1/2 mutations confer sensitivity to platinum-based chemotherapies, it is not yet clear whether mutation signatures can independently predict platinum response.Experimental Design: In this observational study, we sequenced tumor whole genomes (100× depth) and matched normals (60×) of 93 advanced-stage breast cancers (33 platinum-treated). We computed a published metric called HRDetect, independently trained to predict BRCA1/2 status, and assessed its capacity to predict outcomes on platinum-based chemotherapies. Clinical endpoints were overall survival (OS), total duration on platinum-based therapy (TDT), and radiographic evidence of clinical improvement (CI).Results: HRDetect predicted BRCA1/2 status with an area under the curve (AUC) of 0.94 and optimal threshold of 0.7. Elevated HRDetect was also significantly associated with CI on platinum-based therapy (AUC = 0.89; P = 0.006) with the same optimal threshold, even after adjusting for BRCA1/2 mutation status and treatment timing. HRDetect scores over 0.7 were associated with a 3-month extended median TDT (P = 0.0003) and 1.3-year extended median OS (P = 0.04).Conclusions: Our findings not only independently validate HRDetect, but also provide the first evidence of its association with platinum response in advanced breast cancer. We demonstrate that HRD mutation signatures may offer clinically relevant information independently of BRCA1/2 mutation status and hope this work will guide the development of clinical trials. Clin Cancer Res; 23(24); 7521-30. ©2017 AACR.

Genomic profiling of pelvic genital type leiomyosarcoma in a woman with a germline CHEK2:c.1100delC mutation and a concomitant diagnosis of metastatic invasive ductal breast carcinoma.

We describe a woman with the known pathogenic germline variant CHEK2:c.1100delC and synchronous diagnoses of both pelvic genital type leiomyosarcoma (LMS) and metastatic invasive ductal breast carcinoma. CHEK2 (checkpoint kinase 2) is a tumor-suppressor gene encoding a serine/threonine-protein kinase (CHEK2) involved in double-strand DNA break repair and cell cycle arrest. The CHEK2:c.1100delC variant is a moderate penetrance allele resulting in an approximately twofold increase in breast cancer risk. Whole-genome and whole-transcriptome sequencing were performed on the leiomyosarcoma and matched blood-derived DNA. Despite the presence of several genomic hits within the double-strand DNA damage pathway (CHEK2 germline variant and multiple RAD51B somatic structural variants), tumor profiling did not show an obvious DNA repair deficiency signature. However, even though the LMS displayed clear malignant features, its genomic profiling revealed several characteristics classically associated with leiomyomas including a translocation, t(12;14), with one breakpoint disrupting RAD51B and the other breakpoint upstream of HMGA2 with very high expression of HMGA2 and PLAG1 This is the first report of LMS genomic profiling in a patient with the germline CHEK2:c.1100delC variant and an additional diagnosis of metastatic invasive ductal breast carcinoma. We also describe a possible mechanistic relationship between leiomyoma and LMS based on genomic and transcriptome data. Our findings suggest that RAD51B translocation and HMGA2 overexpression may play an important role in LMS oncogenesis.

Personalized oncogenomics: clinical experience with malignant peritoneal mesothelioma using whole genome sequencing.

Peritoneal mesothelioma is a rare and sometimes lethal malignancy that presents a clinical challenge for both diagnosis and management. Recent studies have led to a better understanding of the molecular biology of peritoneal mesothelioma. Translation of the emerging data into better treatments and outcome is needed. From two patients with peritoneal mesothelioma, we derived whole genome sequences, RNA expression profiles, and targeted deep sequencing data. Molecular data were made available for translation into a clinical treatment plan. Treatment responses and outcomes were later examined in the context of molecular findings. Molecular studies presented here provide the first reported whole genome sequences of peritoneal mesothelioma. Mutations in known mesothelioma-related genes NF2, CDKN2A, LATS2, amongst others, were identified. Activation of MET-related signaling pathways was demonstrated in both cases. A hypermutated phenotype was observed in one case (434 vs. 18 single nucleotide variants) and was associated with a favourable outcome despite sarcomatoid histology and multifocal disease. This study represents the first report of whole genome analyses of peritoneal mesothelioma, a key step in the understanding and treatment of this disease.

Meta-Analysis of Gene Expression in Autism Spectrum Disorder.

Autism spectrum disorders (ASD) are clinically heterogeneous and biologically complex. In general it remains unclear, what biological factors lead to changes in the brains of autistic individuals. A considerable number of transcriptome analyses have been performed in attempts to address this question, but their findings lack a clear consensus. As a result, each of these individual studies has not led to any significant advance in understanding the autistic phenotype as a whole. Here, we report a meta-analysis of more than 1000 microarrays across twelve independent studies on expression changes in ASD compared to unaffected individuals, in both blood and brain tissues. We identified a number of known and novel genes that are consistently differentially expressed across three studies of the brain (71 samples in total). A subset of the highly ranked genes is suggestive of effects on mitochondrial function. In blood, consistent changes were more difficult to identify, despite individual studies tending to exhibit larger effects than the brain studies. Our results are the strongest evidence to date of a common transcriptome signature in the brains of individuals with ASD.

Lessons learned from the application of whole-genome analysis to the treatment of patients with advanced cancers.

Given the success of targeted agents in specific populations it is expected that some degree of molecular biomarker testing will become standard of care for many, if not all, cancers. To facilitate this, cancer centers worldwide are experimenting with targeted "panel" sequencing of selected mutations. Recent advances in genomic technology enable the generation of genome-scale data sets for individual patients. Recognizing the risk, inherent in panel sequencing, of failing to detect meaningful somatic alterations, we sought to establish processes to integrate data from whole-genome analysis (WGA) into routine cancer care. Between June 2012 and August 2014, 100 adult patients with incurable cancers consented to participate in the Personalized OncoGenomics (POG) study. Fresh tumor and blood samples were obtained and used for whole-genome and RNA sequencing. Computational approaches were used to identify candidate driver mutations, genes, and pathways. Diagnostic and drug information were then sought based on these candidate "drivers." Reports were generated and discussed weekly in a multidisciplinary team setting. Other multidisciplinary working groups were assembled to establish guidelines on the interpretation, communication, and integration of individual genomic findings into patient care. Of 78 patients for whom WGA was possible, results were considered actionable in 55 cases. In 23 of these 55 cases, the patients received treatments motivated by WGA. Our experience indicates that a multidisciplinary team of clinicians and scientists can implement a paradigm in which WGA is integrated into the care of late stage cancer patients to inform systemic therapy decisions.

Neurocarta: aggregating and sharing disease-gene relations for the neurosciences.

BACKGROUND: Understanding the genetic basis of diseases is key to the development of better diagnoses and treatments. Unfortunately, only a small fraction of the existing data linking genes to phenotypes is available through online public resources and, when available, it is scattered across multiple access tools. DESCRIPTION: Neurocarta is a knowledgebase that consolidates information on genes and phenotypes across multiple resources and allows tracking and exploring of the associations. The system enables automatic and manual curation of evidence supporting each association, as well as user-enabled entry of their own annotations. Phenotypes are recorded using controlled vocabularies such as the Disease Ontology to facilitate computational inference and linking to external data sources. The gene-to-phenotype associations are filtered by stringent criteria to focus on the annotations most likely to be relevant. Neurocarta is constantly growing and currently holds more than 30,000 lines of evidence linking over 7,000 genes to 2,000 different phenotypes. CONCLUSIONS: Neurocarta is a one-stop shop for researchers looking for candidate genes for any disorder of interest. In Neurocarta, they can review the evidence linking genes to phenotypes and filter out the evidence they're not interested in. In addition, researchers can enter their own annotations from their experiments and analyze them in the context of existing public annotations. Neurocarta's in-depth annotation of neurodevelopmental disorders makes it a unique resource for neuroscientists working on brain development.