Chromothripsis and human disease: piecing together the shattering process.

The unprecedented resolution of high-throughput genomics has enabled the recent discovery of a phenomenon by which specific regions of the genome are shattered and then stitched together via a single devastating event, referred to as chromothripsis. Potential mechanisms governing this process are now emerging, with implications for our understanding of the role of genomic rearrangements in development and disease.

Genomic landscape of non-small cell lung cancer in smokers and never-smokers.

We report the results of whole-genome and transcriptome sequencing of tumor and adjacent normal tissue samples from 17 patients with non-small cell lung carcinoma (NSCLC). We identified 3,726 point mutations and more than 90 indels in the coding sequence, with an average mutation frequency more than 10-fold higher in smokers than in never-smokers. Novel alterations in genes involved in chromatin modification and DNA repair pathways were identified, along with DACH1, CFTR, RELN, ABCB5, and HGF. Deep digital sequencing revealed diverse clonality patterns in both never-smokers and smokers. All validated EFGR and KRAS mutations were present in the founder clones, suggesting possible roles in cancer initiation. Analysis revealed 14 fusions, including ROS1 and ALK, as well as novel metabolic enzymes. Cell-cycle and JAK-STAT pathways are significantly altered in lung cancer, along with perturbations in 54 genes that are potentially targetable with currently available drugs.

PACT: a pipeline for analysis of circulating tumor DNA.

MOTIVATION: Detection of genomic alterations in circulating tumor DNA (ctDNA) is currently used for active clinical monitoring of cancer progression and treatment response. While methods for analysis of small mutations are more developed, strategies for detecting structural variants (SVs) in ctDNA are limited. Additionally, reproducibly calling small-scale mutations, copy number alterations, and SVs in ctDNA is challenging due to the lack to unified tools for these different classes of variants. RESULTS: We developed a unified pipeline for the analysis of ctDNA [Pipeline for the Analysis of ctDNA (PACT)] that accurately detects SVs and consistently outperformed similar tools when applied to simulated, cell line, and clinical data. We provide PACT in the form of a Common Workflow Language pipeline which can be run by popular workflow management systems in high-performance computing environments. AVAILABILITY AND IMPLEMENTATION: PACT is freely available at https://github.com/ChrisMaherLab/PACT.

Characterization of the EZH2-MMSET histone methyltransferase regulatory axis in cancer.

Histone methyltransferases (HMTases), as chromatin modifiers, regulate the transcriptomic landscape in normal development as well in diseases such as cancer. Here, we molecularly order two HMTases, EZH2 and MMSET, that have established genetic links to oncogenesis. EZH2, which mediates histone H3K27 trimethylation and is associated with gene silencing, was shown to be coordinately expressed and function upstream of MMSET, which mediates H3K36 dimethylation and is associated with active transcription. We found that the EZH2-MMSET HMTase axis is coordinated by a microRNA network and that the oncogenic functions of EZH2 require MMSET activity. Together, these results suggest that the EZH2-MMSET HMTase axis coordinately functions as a master regulator of transcriptional repression, activation, and oncogenesis and may represent an attractive therapeutic target in cancer.

Sclerosing epithelioid mesenchymal neoplasm of the pancreas - a proposed new entity.

We have encountered pancreatic tumors with unique histologic features, which do not conform to any of the known tumors of the pancreas or other anatomical sites. We aimed to define their clinicopathologic features and whether they are characterized by recurrent molecular signatures. Eight cases were identified; studied histologically and by immunohistochemistry. Selected cases were also subjected to whole-exome sequencing (WES; n = 4), RNA-sequencing (n = 6), Archer FusionPlex assay (n = 5), methylation profiling using the Illumina MethylationEPIC (850k) array platform (n = 6), and TERT promoter sequencing (n = 5). Six neoplasms occurred in females. The mean age was 43 years (range: 26-75). Five occurred in the head/neck of the pancreas. All patients were treated surgically; none received neoadjuvant/adjuvant therapy. All patients are free of disease after 53 months of median follow-up (range: 8-94). The tumors were well-circumscribed, and the median size was 1.8 cm (range: 1.3-5.8). Microscopically, the unencapsulated tumors had a geographic pattern of epithelioid cell nests alternating with spindle cell fascicles. Some areas showed dense fibrosis, in which enmeshed tumor cells imparted a slit-like pattern. The predominant epithelioid cells had scant cytoplasm and round-oval nuclei with open chromatin. The spindle cells displayed irregular, hyperchromatic nuclei. Mitoses were rare. No lymph node metastases were identified. All tumors were positive for vimentin, CD99 and cytokeratin (patchy), while negative for markers of solid pseudopapillary neoplasm, neuroendocrine, acinar, myogenic/rhabdoid, vascular, melanocytic, or lymphoid differentiation, gastrointestinal stromal tumor as well as MUC4. Whole-exome sequencing revealed no recurrent somatic mutations or amplifications/homozygous deletions in any known oncogenes or tumor suppressor genes. RNA-sequencing and the Archer FusionPlex assay did not detect any recurrent likely pathogenic gene fusions. Single sample gene set enrichment analysis revealed that these tumors display a likely mesenchymal transcriptomic program. Unsupervised analysis (t-SNE) of their methylation profiles against a set of different mesenchymal neoplasms demonstrated a distinct methylation pattern. Here, we describe pancreatic neoplasms with unique morphologic/immunophenotypic features and a distinct methylation pattern, along with a lack of abnormalities in any of key genetic drivers, supporting that these neoplasms represent a novel entity with an indolent clinical course. Given their mesenchymal transcriptomic features, we propose the designation of "sclerosing epithelioid mesenchymal neoplasm" of the pancreas.

INTEGRATE: gene fusion discovery using whole genome and transcriptome data.

While next-generation sequencing (NGS) has become the primary technology for discovering gene fusions, we are still faced with the challenge of ensuring that causative mutations are not missed while minimizing false positives. Currently, there are many computational tools that predict structural variations (SV) and gene fusions using whole genome (WGS) and transcriptome sequencing (RNA-seq) data separately. However, as both WGS and RNA-seq have their limitations when used independently, we hypothesize that the orthogonal validation from integrating both data could generate a sensitive and specific approach for detecting high-confidence gene fusion predictions. Fortunately, decreasing NGS costs have resulted in a growing quantity of patients with both data available. Therefore, we developed a gene fusion discovery tool, INTEGRATE, that leverages both RNA-seq and WGS data to reconstruct gene fusion junctions and genomic breakpoints by split-read mapping. To evaluate INTEGRATE, we compared it with eight additional gene fusion discovery tools using the well-characterized breast cell line HCC1395 and peripheral blood lymphocytes derived from the same patient (HCC1395BL). The predictions subsequently underwent a targeted validation leading to the discovery of 131 novel fusions in addition to the seven previously reported fusions. Overall, INTEGRATE only missed six out of the 138 validated fusions and had the highest accuracy of the nine tools evaluated. Additionally, we applied INTEGRATE to 62 breast cancer patients from The Cancer Genome Atlas (TCGA) and found multiple recurrent gene fusions including a subset involving estrogen receptor. Taken together, INTEGRATE is a highly sensitive and accurate tool that is freely available for academic use.

INTEGRATE-neo: a pipeline for personalized gene fusion neoantigen discovery.

Motivation: While high-throughput sequencing (HTS) has been used successfully to discover tumor-specific mutant peptides (neoantigens) from somatic missense mutations, the field currently lacks a method for identifying which gene fusions may generate neoantigens. Results: We demonstrate the application of our gene fusion neoantigen discovery pipeline, called INTEGRATE-Neo, by identifying gene fusions in prostate cancers that may produce neoantigens. Availability and Implementation: INTEGRATE-Neo is implemented in C ++ and Python. Full source code and installation instructions are freely available from https://github.com/ChrisMaherLab/INTEGRATE-Neo . Contact: christophermaher@wustl.edu. Supplementary information: Supplementary data are available at Bioinformatics online.

Whole-genome analysis informs breast cancer response to aromatase inhibition.

To correlate the variable clinical features of oestrogen-receptor-positive breast cancer with somatic alterations, we studied pretreatment tumour biopsies accrued from patients in two studies of neoadjuvant aromatase inhibitor therapy by massively parallel sequencing and analysis. Eighteen significantly mutated genes were identified, including five genes (RUNX1, CBFB, MYH9, MLL3 and SF3B1) previously linked to haematopoietic disorders. Mutant MAP3K1 was associated with luminal A status, low-grade histology and low proliferation rates, whereas mutant TP53 was associated with the opposite pattern. Moreover, mutant GATA3 correlated with suppression of proliferation upon aromatase inhibitor treatment. Pathway analysis demonstrated that mutations in MAP2K4, a MAP3K1 substrate, produced similar perturbations as MAP3K1 loss. Distinct phenotypes in oestrogen-receptor-positive breast cancer are associated with specific patterns of somatic mutations that map into cellular pathways linked to tumour biology, but most recurrent mutations are relatively infrequent. Prospective clinical trials based on these findings will require comprehensive genome sequencing.

An Analysis of the Sensitivity of Proteogenomic Mapping of Somatic Mutations and Novel Splicing Events in Cancer.

Improvements in mass spectrometry (MS)-based peptide sequencing provide a new opportunity to determine whether polymorphisms, mutations, and splice variants identified in cancer cells are translated. Herein, we apply a proteogenomic data integration tool (QUILTS) to illustrate protein variant discovery using whole genome, whole transcriptome, and global proteome datasets generated from a pair of luminal and basal-like breast-cancer-patient-derived xenografts (PDX). The sensitivity of proteogenomic analysis for singe nucleotide variant (SNV) expression and novel splice junction (NSJ) detection was probed using multiple MS/MS sample process replicates defined here as an independent tandem MS experiment using identical sample material. Despite analysis of over 30 sample process replicates, only about 10% of SNVs (somatic and germline) detected by both DNA and RNA sequencing were observed as peptides. An even smaller proportion of peptides corresponding to NSJ observed by RNA sequencing were detected (<0.1%). Peptides mapping to DNA-detected SNVs without a detectable mRNA transcript were also observed, suggesting that transcriptome coverage was incomplete (∼80%). In contrast to germline variants, somatic variants were less likely to be detected at the peptide level in the basal-like tumor than in the luminal tumor, raising the possibility of differential translation or protein degradation effects. In conclusion, this large-scale proteogenomic integration allowed us to determine the degree to which mutations are translated and identify gaps in sequence coverage, thereby benchmarking current technology and progress toward whole cancer proteome and transcriptome analysis.

miR-24 Inhibits cell proliferation by targeting E2F2, MYC, and other cell-cycle genes via binding to "seedless" 3'UTR microRNA recognition elements.

miR-24, upregulated during terminal differentiation of multiple lineages, inhibits cell-cycle progression. Antagonizing miR-24 restores postmitotic cell proliferation and enhances fibroblast proliferation, whereas overexpressing miR-24 increases the G1 compartment. The 248 mRNAs downregulated upon miR-24 overexpression are highly enriched for DNA repair and cell-cycle regulatory genes that form a direct interaction network with prominent nodes at genes that enhance (MYC, E2F2, CCNB1, and CDC2) or inhibit (p27Kip1 and VHL) cell-cycle progression. miR-24 directly regulates MYC and E2F2 and some genes that they transactivate. Enhanced proliferation from antagonizing miR-24 is abrogated by knocking down E2F2, but not MYC, and cell proliferation, inhibited by miR-24 overexpression, is rescued by miR-24-insensitive E2F2. Therefore, E2F2 is a critical miR-24 target. The E2F2 3'UTR lacks a predicted miR-24 recognition element. In fact, miR-24 regulates expression of E2F2, MYC, AURKB, CCNA2, CDC2, CDK4, and FEN1 by recognizing seedless but highly complementary sequences.

Visualizing tumor evolution with the fishplot package for R.

BACKGROUND: Massively-parallel sequencing at depth is now enabling tumor heterogeneity and evolution to be characterized in unprecedented detail. Tracking these changes in clonal architecture often provides insight into therapeutic response and resistance. In complex cases involving multiple timepoints, standard visualizations, such as scatterplots, can be difficult to interpret. Current data visualization methods are also typically manual and laborious, and often only approximate subclonal fractions. RESULTS: We have developed an R package that accurately and intuitively displays changes in clonal structure over time. It requires simple input data and produces illustrative and easy-to-interpret graphs suitable for diagnosis, presentation, and publication. CONCLUSIONS: The simplicity, power, and flexibility of this tool make it valuable for visualizing tumor evolution, and it has potential utility in both research and clinical settings. The fishplot package is available at https://github.com/chrisamiller/fishplot .

Genome Modeling System: A Knowledge Management Platform for Genomics.

In this work, we present the Genome Modeling System (GMS), an analysis information management system capable of executing automated genome analysis pipelines at a massive scale. The GMS framework provides detailed tracking of samples and data coupled with reliable and repeatable analysis pipelines. The GMS also serves as a platform for bioinformatics development, allowing a large team to collaborate on data analysis, or an individual researcher to leverage the work of others effectively within its data management system. Rather than separating ad-hoc analysis from rigorous, reproducible pipelines, the GMS promotes systematic integration between the two. As a demonstration of the GMS, we performed an integrated analysis of whole genome, exome and transcriptome sequencing data from a breast cancer cell line (HCC1395) and matched lymphoblastoid line (HCC1395BL). These data are available for users to test the software, complete tutorials and develop novel GMS pipeline configurations. The GMS is available at https://github.com/genome/gms.

SigFuge: single gene clustering of RNA-seq reveals differential isoform usage among cancer samples.

High-throughput sequencing technologies, including RNA-seq, have made it possible to move beyond gene expression analysis to study transcriptional events including alternative splicing and gene fusions. Furthermore, recent studies in cancer have suggested the importance of identifying transcriptionally altered loci as biomarkers for improved prognosis and therapy. While many statistical methods have been proposed for identifying novel transcriptional events with RNA-seq, nearly all rely on contrasting known classes of samples, such as tumor and normal. Few tools exist for the unsupervised discovery of such events without class labels. In this paper, we present SigFuge for identifying genomic loci exhibiting differential transcription patterns across many RNA-seq samples. SigFuge combines clustering with hypothesis testing to identify genes exhibiting alternative splicing, or differences in isoform expression. We apply SigFuge to RNA-seq cohorts of 177 lung and 279 head and neck squamous cell carcinoma samples from the Cancer Genome Atlas, and identify several cases of differential isoform usage including CDKN2A, a tumor suppressor gene known to be inactivated in a majority of lung squamous cell tumors. By not restricting attention to known sample stratifications, SigFuge offers a novel approach to unsupervised screening of genetic loci across RNA-seq cohorts. SigFuge is available as an R package through Bioconductor.

Recurrent reciprocal RNA chimera involving YPEL5 and PPP1CB in chronic lymphocytic leukemia.

Chronic lymphocytic leukemia (CLL) is the most common form of leukemia in adults in the Western hemisphere. Tumor-specific chromosomal translocations, characteristic findings in several human malignancies that directly lead to malignant transformation, have not been identified in CLL. Using paired-end transcriptome sequencing, we identified recurrent and reciprocal RNA chimeras involving yippee like 5 (YPEL5) and serine/threonine-protein phosphatase PP1-beta-catalytic subunit (PPP1CB) in CLL. Two of seven index cases (28%) harbored the reciprocal RNA chimeras in our initial screening. Using quantitative real-time PCR (q real-time PCR), YPEL5/PPP1CB and PPP1CB/YPEL5 fusion transcripts were detected in 97 of 103 CLL samples (95%) but not in paired normal samples, benign lymphocytes, or various unrelated cancers. Whole-genome sequencing and Southern blotting demonstrated no evidence for a genomic fusion between YPEL5 and PPP1CB. YPEL5/PPP1CB chimera, when introduced into mammalian cells, expressed a truncated PPP1CB protein that demonstrated diminished phosphatase activity. PPP1CB silencing resulted in enhanced proliferation and colony formation of MEC1 and JVM3 cells, implying a role in the pathogenesis of mature B-cell leukemia. These studies uncover a potential role for recurrent RNA chimeras involving phosphatases in the pathogenesis of a common form of leukemia.

Pan-cancer transcriptome analysis reveals long noncoding RNAs with conserved function.

A growing number of gene-centric studies have highlighted the emerging significance of lncRNAs in cancer. However, these studies primarily focus on a single cancer type. Therefore, we conducted a pan-cancer analysis of lncRNAs comparing tumor and matched normal expression levels using RNA-Seq data from ∼ 3,000 patients in 8 solid tumor types. While the majority of differentially expressed lncRNAs display tissue-specific expression we discovered 229 lncRNAs with outlier or differential expression across multiple cancers, which we refer to as 'onco-lncRNAs'. Due to their consistent altered expression, we hypothesize that these onco-lncRNAs may have conserved oncogenic and tumor suppressive functions across cancers. To address this, we associated the onco-lncRNAs in biological processes based on their co-expressed protein coding genes. To validate our predictions, we experimentally confirmed cell growth dependence of 2 novel oncogenic lncRNAs, onco-lncRNA-3 and onco-lncRNA-12, and a previously identified lncRNA CCAT1. Overall, we discovered lncRNAs that may have broad oncogenic and tumor suppressor roles that could significantly advance our understanding of cancer lncRNA biology.

Characterization of the genomic features and expressed fusion genes in micropapillary carcinomas of the breast.

Micropapillary carcinoma (MPC) is a rare histological special type of breast cancer, characterized by an aggressive clinical behaviour and a pattern of copy number aberrations (CNAs) distinct from that of grade- and oestrogen receptor (ER)-matched invasive carcinomas of no special type (IC-NSTs). The aims of this study were to determine whether MPCs are underpinned by a recurrent fusion gene(s) or mutations in 273 genes recurrently mutated in breast cancer. Sixteen MPCs were subjected to microarray-based comparative genomic hybridization (aCGH) analysis and Sequenom OncoCarta mutation analysis. Eight and five MPCs were subjected to targeted capture and RNA sequencing, respectively. aCGH analysis confirmed our previous observations about the repertoire of CNAs of MPCs. Sequencing analysis revealed a spectrum of mutations similar to those of luminal B IC-NSTs, and recurrent mutations affecting mitogen-activated protein kinase family genes and NBPF10. RNA-sequencing analysis identified 17 high-confidence fusion genes, eight of which were validated and two of which were in-frame. No recurrent fusions were identified in an independent series of MPCs and IC-NSTs. Forced expression of in-frame fusion genes (SLC2A1-FAF1 and BCAS4-AURKA) resulted in increased viability of breast cancer cells. In addition, genomic disruption of CDK12 caused by out-of-frame rearrangements was found in one MPC and in 13% of HER2-positive breast cancers, identified through a re-analysis of publicly available massively parallel sequencing data. In vitro analyses revealed that CDK12 gene disruption results in sensitivity to PARP inhibition, and forced expression of wild-type CDK12 in a CDK12-null cell line model resulted in relative resistance to PARP inhibition. Our findings demonstrate that MPCs are neither defined by highly recurrent mutations in the 273 genes tested, nor underpinned by a recurrent fusion gene. Although seemingly private genetic events, some of the fusion transcripts found in MPCs may play a role in maintenance of a malignant phenotype and potentially offer therapeutic opportunities.

Transcriptome sequencing to detect gene fusions in cancer.

Recurrent gene fusions, typically associated with haematological malignancies and rare bone and soft-tissue tumours, have recently been described in common solid tumours. Here we use an integrative analysis of high-throughput long- and short-read transcriptome sequencing of cancer cells to discover novel gene fusions. As a proof of concept, we successfully used integrative transcriptome sequencing to 're-discover' the BCR-ABL1 (ref. 10) gene fusion in a chronic myelogenous leukaemia cell line and the TMPRSS2-ERG gene fusion in a prostate cancer cell line and tissues. Additionally, we nominated, and experimentally validated, novel gene fusions resulting in chimaeric transcripts in cancer cell lines and tumours. Taken together, this study establishes a robust pipeline for the discovery of novel gene chimaeras using high-throughput sequencing, opening up an important class of cancer-related mutations for comprehensive characterization.

The Sorghum bicolor genome and the diversification of grasses.

Sorghum, an African grass related to sugar cane and maize, is grown for food, feed, fibre and fuel. We present an initial analysis of the approximately 730-megabase Sorghum bicolor (L.) Moench genome, placing approximately 98% of genes in their chromosomal context using whole-genome shotgun sequence validated by genetic, physical and syntenic information. Genetic recombination is largely confined to about one-third of the sorghum genome with gene order and density similar to those of rice. Retrotransposon accumulation in recombinationally recalcitrant heterochromatin explains the approximately 75% larger genome size of sorghum compared with rice. Although gene and repetitive DNA distributions have been preserved since palaeopolyploidization approximately 70 million years ago, most duplicated gene sets lost one member before the sorghum-rice divergence. Concerted evolution makes one duplicated chromosomal segment appear to be only a few million years old. About 24% of genes are grass-specific and 7% are sorghum-specific. Recent gene and microRNA duplications may contribute to sorghum's drought tolerance.

Deep sequencing reveals distinct patterns of DNA methylation in prostate cancer.

Beginning with precursor lesions, aberrant DNA methylation marks the entire spectrum of prostate cancer progression. We mapped the global DNA methylation patterns in select prostate tissues and cell lines using MethylPlex-next-generation sequencing (M-NGS). Hidden Markov model-based next-generation sequence analysis identified ∼68,000 methylated regions per sample. While global CpG island (CGI) methylation was not differential between benign adjacent and cancer samples, overall promoter CGI methylation significantly increased from ~12.6% in benign samples to 19.3% and 21.8% in localized and metastatic cancer tissues, respectively (P-value < 2 × 10(-16)). We found distinct patterns of promoter methylation around transcription start sites, where methylation occurred not only on the CGIs, but also on flanking regions and CGI sparse promoters. Among the 6691 methylated promoters in prostate tissues, 2481 differentially methylated regions (DMRs) are cancer-specific, including numerous novel DMRs. A novel cancer-specific DMR in the WFDC2 promoter showed frequent methylation in cancer (17/22 tissues, 6/6 cell lines), but not in the benign tissues (0/10) and normal PrEC cells. Integration of LNCaP DNA methylation and H3K4me3 data suggested an epigenetic mechanism for alternate transcription start site utilization, and these modifications segregated into distinct regions when present on the same promoter. Finally, we observed differences in repeat element methylation, particularly LINE-1, between ERG gene fusion-positive and -negative cancers, and we confirmed this observation using pyrosequencing on a tissue panel. This comprehensive methylome map will further our understanding of epigenetic regulation in prostate cancer progression.

BCAR4 Expression as a Predictive Biomarker for Endocrine Therapy Resistance in Breast Cancer.

BACKGROUND: Breast cancer, particularly the estrogen receptor positive (ER+) subtype, remains a leading cause of cancer-related death among women. Endocrine therapy is the most effective treatment for ER+ breast cancer; however, the development of resistance presents a significant challenge. This study explored the role of the breast cancer antiestrogen resistance 4 (BCAR4) gene as a potential driver of resistance and a pivotal biomarker in breast cancer. PATIENTS AND METHODS: The researchers undertook a comprehensive analysis of 1743 patients spanning 6 independent cohorts. They examined the association of BCAR4 expression with patient outcomes across all breast cancer types and the PAM50 molecular subtypes. The relationship between elevated BCAR4 expression and resistance to endocrine therapy including AIs, the prevailing standard-of-care for endocrine therapy, was also investigated. RESULTS: This meta-analysis corroborated the link between BCAR4 expression and adverse outcomes as well as resistance to endocrine therapy in breast cancer. Notably, BCAR4 expression is clinically significant in luminal A and B subtypes. Additionally, an association between BCAR4 expression and resistance to AI treatment was discerned. CONCLUSION: This study expands on previous findings by demonstrating that BCAR4 expression is associated with resistance to newer therapies. The identification of patients with intrinsic resistance to hormone therapy is crucial to avoid ineffective treatment strategies. These findings contribute to our understanding of endocrine therapy resistance in breast cancer and could potentially guide the development of more effective treatment strategies.