Ultra-Deep Sequencing Reveals the Mutational Landscape of Classical Hodgkin Lymphoma.

The malignant Hodgkin and Reed Sternberg (HRS) cells of classical Hodgkin lymphoma (cHL) are scarce in affected lymph nodes, creating a challenge to detect driver somatic mutations. As an alternative to cell purification techniques, we hypothesized that ultra-deep exome sequencing would allow genomic study of HRS cells, thereby streamlining analysis and avoiding technical pitfalls. To test this, 31 cHL tumor/normal pairs were exome sequenced to approximately 1,000× median depth of coverage. An orthogonal error-corrected sequencing approach verified >95% of the discovered mutations. We identified mutations in genes novel to cHL including: CDH5 and PCDH7, novel stop gain mutations in IL4R, and a novel pattern of recurrent mutations in pathways regulating Hippo signaling. As a further application of our exome sequencing, we attempted to identify expressed somatic single-nucleotide variants (SNV) in single-nuclei RNA sequencing (snRNA-seq) data generated from a patient in our cohort. Our snRNA analysis identified a clear cluster of cells containing a somatic SNV identified in our deep exome data. This cluster has differentially expressed genes that are consistent with genes known to be dysregulated in HRS cells (e.g., PIM1 and PIM3). The cluster also contains cells with an expanded B-cell clonotype further supporting a malignant phenotype. This study provides proof-of-principle that ultra-deep exome sequencing can be utilized to identify recurrent mutations in HRS cells and demonstrates the feasibility of snRNA-seq in the context of cHL. These studies provide the foundation for the further analysis of genomic variants in large cohorts of patients with cHL. SIGNIFICANCE: Our data demonstrate the utility of ultra-deep exome sequencing in uncovering somatic variants in Hodgkin lymphoma, creating new opportunities to define the genes that are recurrently mutated in this disease. We also show for the first time the successful application of snRNA-seq in Hodgkin lymphoma and describe the expression profile of a putative cluster of HRS cells in a single patient.

Proteogenomic data and resources for pan-cancer analysis.

The National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium (CPTAC) investigates tumors from a proteogenomic perspective, creating rich multi-omics datasets connecting genomic aberrations to cancer phenotypes. To facilitate pan-cancer investigations, we have generated harmonized genomic, transcriptomic, proteomic, and clinical data for >1000 tumors in 10 cohorts to create a cohesive and powerful dataset for scientific discovery. We outline efforts by the CPTAC pan-cancer working group in data harmonization, data dissemination, and computational resources for aiding biological discoveries. We also discuss challenges for multi-omics data integration and analysis, specifically the unique challenges of working with both nucleotide sequencing and mass spectrometry proteomics data.

Genetic characterization of primary and metastatic high-grade serous ovarian cancer tumors reveals distinct features associated with survival.

High-grade serous ovarian cancer (HGSC) is the most lethal histotype of ovarian cancer and the majority of cases present with metastasis and late-stage disease. Over the last few decades, the overall survival for patients has not significantly improved, and there are limited targeted treatment options. We aimed to better characterize the distinctions between primary and metastatic tumors based on short- or long-term survival. We characterized 39 matched primary and metastatic tumors by whole exome and RNA sequencing. Of these, 23 were short-term (ST) survivors (overall survival (OS) < 3.5 years) and 16 were long-term (LT) survivors (OS > 5 years). We compared somatic mutations, copy number alterations, mutational burden, differential gene expression, immune cell infiltration, and gene fusion predictions between the primary and metastatic tumors and between ST and LT survivor cohorts. There were few differences in RNA expression between paired primary and metastatic tumors, but significant differences between the transcriptomes of LT and ST survivors in both their primary and metastatic tumors. These findings will improve the understanding of the genetic variation in HGSC that exist between patients with different prognoses and better inform treatments by identifying new targets for drug development.

Loss of KMT2C reprograms the epigenomic landscape in hPSCs resulting in NODAL overexpression and a failure of hemogenic endothelium specification.

Germline or somatic variation in the family of KMT2 lysine methyltransferases have been associated with a variety of congenital disorders and cancers. Notably, KMT2A-fusions are prevalent in 70% of infant leukaemias but fail to phenocopy short latency leukaemogenesis in mammalian models, suggesting additional factors are necessary for transformation. Given the lack of additional somatic mutation, the role of epigenetic regulation in cell specification, and our prior results of germline KMT2C variation in infant leukaemia patients, we hypothesized that germline dysfunction of KMT2C altered haematopoietic specification. In isogenic KMT2C KO hPSCs, we found genome-wide differences in histone modifications at active and poised enhancers, leading to gene expression profiles akin to mesendoderm rather than mesoderm highlighted by a significant increase in NODAL expression and WNT inhibition, ultimately resulting in a lack of in vitro hemogenic endothelium specification. These unbiased multi-omic results provide new evidence for germline mechanisms increasing risk of early leukaemogenesis.

Genomic Profiling of Lung Adenocarcinoma in Never-Smokers.

PURPOSE: Approximately 10%-40% of patients with lung cancer report no history of tobacco smoking (never-smokers). We analyzed whole-exome and RNA-sequencing data of 160 tumor and normal lung adenocarcinoma (LUAD) samples from never-smokers to identify clinically actionable alterations and gain insight into the environmental and hereditary risk factors for LUAD among never-smokers. METHODS: We performed whole-exome and RNA-sequencing of 88 and 69 never-smoker LUADs. We analyzed these data in conjunction with data from 76 never-smoker and 299 smoker LUAD samples sequenced by The Cancer Genome Atlas and Clinical Proteomic Tumor Analysis Consortium. RESULTS: We observed a high prevalence of clinically actionable driver alterations in never-smoker LUADs compared with smoker LUADs (78%-92% v 49.5%; P < .0001). Although a subset of never-smoker samples demonstrated germline alterations in DNA repair genes, the frequency of samples showing germline variants in cancer predisposing genes was comparable between smokers and never-smokers (6.4% v 6.9%; P = .82). A subset of never-smoker samples (5.9%) showed mutation signatures that were suggestive of passive exposure to cigarette smoke. Finally, analysis of RNA-sequencing data showed distinct immune transcriptional subtypes of never-smoker LUADs that varied in their expression of clinically relevant immune checkpoint molecules and immune cell composition. CONCLUSION: In this comprehensive genomic and transcriptome analysis of never-smoker LUADs, we observed a potential role for germline variants in DNA repair genes and passive exposure to cigarette smoke in the pathogenesis of a subset of never-smoker LUADs. Our findings also show that clinically actionable driver alterations are highly prevalent in never-smoker LUADs, highlighting the need for obtaining biopsies with adequate cellularity for clinical genomic testing in these patients.

Functional analysis of BARD1 missense variants in homology-directed repair and damage sensitivity.

The BARD1 protein, which heterodimerizes with BRCA1, is encoded by a known breast cancer susceptibility gene. While several BARD1 variants have been identified as pathogenic, many more missense variants exist that do not occur frequently enough to assign a clinical risk. In this paper, whole exome sequencing of over 10,000 cancer samples from 33 cancer types identified from somatic mutations and loss of heterozygosity in tumors 76 potentially cancer-associated BARD1 missense and truncation variants. These variants were tested in a functional assay for homology-directed repair (HDR), as HDR deficiencies have been shown to correlate with clinical pathogenicity for BRCA1 variants. From these 76 variants, 4 in the ankyrin repeat domain and 5 in the BRCT domain were found to be non-functional in HDR. Two known benign variants were found to be functional in HDR, and three known pathogenic variants were non-functional, supporting the notion that the HDR assay can be used to predict the clinical risk of BARD1 variants. The identification of HDR-deficient variants in the ankyrin repeat domain indicates there are DNA repair functions associated with this domain that have not been closely examined. In order to examine whether BARD1-associated loss of HDR function results in DNA damage sensitivity, cells expressing non-functional BARD1 variants were treated with ionizing radiation or cisplatin. These cells were found to be more sensitive to DNA damage, and variations in the residual HDR function of non-functional variants did not correlate with variations in sensitivity. These findings improve the understanding of BARD1 functional domains in DNA repair and support that this functional assay is useful for predicting the cancer association of BARD1 variants.

CharGer: clinical Characterization of Germline variants.

SUMMARY: CharGer (Characterization of Germline variants) is a software tool for interpreting and predicting clinical pathogenicity of germline variants. CharGer gathers evidence from databases and annotations, provided by local tools and files or via ReST APIs, and classifies variants according to ACMG guidelines for assessing variant pathogenicity. User-designed pathogenicity criteria can be incorporated into CharGer's flexible framework, thereby allowing users to create a customized classification protocol. AVAILABILITY AND IMPLEMENTATION: Source code is freely available at https://github.com/ding-lab/CharGer and is distributed under the GNU GPL-v3.0 license. Software is also distributed through the Python Package Index (PyPI) repository. CharGer is implemented in Python 2.7 and is supported on Unix-based operating systems. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Brazilian red propolis induces apoptosis-like cell death and decreases migration potential in bladder cancer cells.

Natural products continue to be an invaluable resource of anticancer drug discovery in recent years. Propolis is known for its biological activities such as antimicrobial and antitumor effects. This study assessed the effects of Brazilian red propolis (BRP) on apoptosis and migration potential in human bladder cancer cells. The effect of BRP ethanolic extract (25, 50, and 100 µg/mL) on 5637 cells was determined by MTT, LIVE/DEAD, and migration (scratch assay) assays. Apoptosis induction was investigated through flow cytometry and gene expression profile was investigated by qRT-PCR. Results showed cytotoxicity on MTT and LIVE/DEAD assays, with IC50 values of 95 µg/mL in 24 h of treatment. Cellular migration of 5637 cells was significantly inhibited through lower doses of BRP ethanolic extract (25 and 50 µg/mL). Flow cytometry analyses showed that BRP induced cytotoxicity through apoptosis-like mechanisms in 5637 cells and qRT-PCR revealed increased levels of Bax/Bcl-2 ratio, p53, AIF, and antioxidant enzymes genes. Data suggest that BRP may be a potential source of drugs to bladder cancer treatment.