Somatic rearrangements across cancer reveal classes of samples with distinct patterns of DNA breakage and rearrangement-induced hypermutability

Whole-genome sequencing using massively parallel sequencing technologies enables accurate detection of somatic rearrangements in cancer. Pinpointing large numbers of rearrangement breakpoints to base-pair resolution allows analysis of rearrangement microhomology and genomic location for every sample. Here we analyze 95 tumor genome sequences from breast, head and neck, colorectal, and prostate carcinomas, and from melanoma, multiple myeloma, and chronic lymphocytic leukemia. We discover three genomic factors that are significantly correlated with the distribution of rearrangements: replication time, transcription rate, and GC content. The correlation is complex, and different patterns are observed between tumor types, within tumor types, and even between different types of rearrangements. Mutations in the APC gene correlate with and, hence, potentially contribute to DNA breakage in late-replicating, low %GC, untranscribed regions of the genome. We show that somatic rearrangements display less microhomology than germline rearrangements, and that breakpoint loci are correlated with local hypermutability with a particular enrichment for C ↔ G transversions

Single-cell RNA sequencing identifies a paracrine interaction that may drive oncogenic notch signaling in human adenoid cystic carcinoma

Salivary adenoid cystic carcinoma (ACC) is a rare, biologically unique biphasic tumor that consists of malignant myoepithelial and luminal cells. MYB and Notch signaling have been implicated in ACC pathophysiology, but in vivo descriptions of these two programs in human tumors and investigation into their active coordination remain incomplete. We utilize single-cell RNA sequencing to profile human head and neck ACC, including a comparison of primary ACC with a matched local recurrence. We define expression heterogeneity in these rare tumors, uncovering diversity in myoepithelial and luminal cell expression. We find differential expression of Notch ligands DLL1, JAG1, and JAG2 in myoepithelial cells, suggesting a paracrine interaction that may support oncogenic Notch signaling. We validate this selective expression in three published cohorts of patients with ACC. Our data provide a potential explanation for the biphasic nature of low- and intermediate-grade ACC and may help direct new therapeutic strategies against these tumors

Do Two Machine-Learning Based Prognostic Signatures for Breast Cancer Capture the Same Biological Processes?

The fact that there is very little if any overlap between the genes of different prognostic signatures for early-discovery breast cancer is well documented. The reasons for this apparent discrepancy have been explained by the limits of simple machine-learning identification and ranking techniques, and the biological relevance and meaning of the prognostic gene lists was questioned. Subsequently, proponents of the prognostic gene lists claimed that different lists do capture similar underlying biological processes and pathways. The present study places under scrutiny the validity of this claim, for two important gene lists that are at the focus of current large-scale validation efforts. We performed careful enrichment analysis, controlling the effects of multiple testing in a manner which takes into account the nested dependent structure of gene ontologies. In contradiction to several previous publications, we find that the only biological process or pathway for which statistically significant concordance can be claimed is cell proliferation, a process whose relevance and prognostic value was well known long before gene expression profiling. We found that the claims reported by others, of wider concordance between the biological processes captured by the two prognostic signatures studied, were found either to be lacking statistical rigor or were in fact based on addressing some other question

Mutational heterogeneity in cancer and the search for new cancer genes

Major international projects are now underway aimed at creating a comprehensive catalog of all genes responsible for the initiation and progression of cancer. These studies involve sequencing of matched tumor–normal samples followed by mathematical analysis to identify those genes in which mutations occur more frequently than expected by random chance. Here, we describe a fundamental problem with cancer genome studies: as the sample size increases, the list of putatively significant genes produced by current analytical methods burgeons into the hundreds. The list includes many implausible genes (such as those encoding olfactory receptors and the muscle protein titin), suggesting extensive false positive findings that overshadow true driver events. Here, we show that this problem stems largely from mutational heterogeneity and provide a novel analytical methodology, MutSigCV, for resolving the problem. We apply MutSigCV to exome sequences from 3,083 tumor-normal pairs and discover extraordinary variation in (i) mutation frequency and spectrum within cancer types, which shed light on mutational processes and disease etiology, and (ii) mutation frequency across the genome, which is strongly correlated with DNA replication timing and also with transcriptional activity. By incorporating mutational heterogeneity into the analyses, MutSigCV is able to eliminate most of the apparent artefactual findings and allow true cancer genes to rise to attention

Genomic sequencing of colorectal adenocarcinomas identifies a recurrent VTI1A-TCF7L2 fusion

Prior studies have identified recurrent oncogenic mutations in colorectal adenocarcinoma1 and have surveyed exons of protein-coding genes for mutations in 11 affected individuals2,3. Here we report whole-genome sequencing from nine individuals with colorectal cancer, including primary colorectal tumors and matched adjacent non-tumor tissues, at an average of 30.7× and 31.9× coverage, respectively. We identify an average of 75 somatic rearrangements per tumor, including complex networks of translocations between pairs of chromosomes. Eleven rearrangements encode predicted in-frame fusion proteins, including a fusion of VTI1A and TCF7L2 found in 3 out of 97 colorectal cancers. Although TCF7L2 encodes TCF4, which cooperates with β-catenin4 in colorectal carcinogenesis5,6, the fusion lacks the TCF4 β-catenin–binding domain. We found a colorectal carcinoma cell line harboring the fusion gene to be dependent on VTI1A-TCF7L2 for anchorage-independent growth using RNA interference-mediated knockdown. This study shows previously unidentified levels of genomic rearrangements in colorectal carcinoma that can lead to essential gene fusions and other oncogenic events

SARS-CoV-2 infection perturbs enhancer mediated transcriptional regulation of key pathways.

Despite extensive studies on the effects of SARS-CoV-2 infection, there is still a lack of understanding of the downstream epigenetic and regulatory alterations in infected cells. In this study, we investigated changes in enhancer acetylation in epithelial lung cells infected with SARS-CoV-2 and their influence on transcriptional regulation and pathway activity. To achieve this, we integrated and reanalyzed data of enhancer acetylation, ex-vivo infection and single cell RNA-seq data from human patients. Our findings revealed coordinated changes in enhancers and transcriptional networks. We found that infected cells lose the WT1 transcription factor and demonstrate disruption of WT1-bound enhancers and of their associated target genes. Downstream targets of WT1 are involved in the regulation of the Wnt signaling and the mitogen-activated protein kinase cascade, which indeed exhibit increased activation levels. These findings may provide a potential explanation for the development of pulmonary fibrosis, a lethal complication of COVID-19. Moreover, we revealed over-acetylated enhancers associated with upregulated genes involved in cell adhesion, which could contribute to cell-cell infection of SARS-CoV-2. Furthermore, we demonstrated that enhancers may play a role in the activation of pro-inflammatory cytokines and contribute to excessive inflammation in the lungs, a typical complication of COVID-19. Overall, our analysis provided novel insights into the cell-autonomous dysregulation of enhancer regulation caused by SARS-CoV-2 infection, a step on the path to a deeper molecular understanding of the disease