A somatic-mutational process recurrently duplicates germline susceptibility loci and tissue-specific super-enhancers in breast cancers

Whole genome sequencing refines stratification and therapy of patients with clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is the most common form of kidney cancer, but a comprehensive description of its genomic landscape is lacking. We report the whole genome sequencing of 778 ccRCC patients enrolled in the 100,000 Genomes Project, providing for a detailed description of the somatic mutational landscape of ccRCC. We identify candidate driver genes, which as well as emphasising the major role of epigenetic regulation in ccRCC highlight additional biological pathways extending opportunities for therapeutic interventions. Genomic characterisation identified patients with divergent clinical outcome; higher number of structural copy number alterations associated with poorer prognosis, whereas VHL mutations were independently associated with a better prognosis. The observations that higher T-cell infiltration is associated with better overall survival and that genetically predicted immune evasion is not common supports the rationale for immunotherapy. These findings should inform personalised surveillance and treatment strategies for ccRCC patients.

Accurate identification of structural variations from cancer samples

Structural variations (SVs) are commonly found in cancer genomes. They can cause gene amplification, deletion and fusion, among other functional consequences. With an average read length of hundreds of kilobases, nano-channel-based optical DNA mapping is powerful in detecting large SVs. However, existing SV calling methods are not tailored for cancer samples, which have special properties such as mixed cell types and sub-clones. Here we propose the Cancer Optical Mapping for detecting Structural Variations (COMSV) method that is specifically designed for cancer samples. It shows high sensitivity and specificity in benchmark comparisons. Applying to cancer cell lines and patient samples, COMSV identifies hundreds of novel SVs per sample.

Genome-guided discovery of cancer therapeutic targets

The success of precision oncology-which aims to match the right therapies to the right patients based on molecular status-is predicated on a robust pipeline of molecular targets against which therapies can be developed. Recent advances in genomics and functional genetics have enabled the unbiased discovery of novel molecular targets at scale. We summarize the promise and challenges in integrating genomic and functional genetic landscapes of cancer to establish the next generation of cancer targets.

Visualizing and exploring patterns of large mutational events with SigProfilerMatrixGenerator

BACKGROUND

All cancers harbor somatic mutations in their genomes. In principle, mutations affecting between one and fifty base pairs are generally classified as small mutational events. Conversely, large mutational events affect more than fifty base pairs, and, in most cases, they encompass copy-number and structural variants affecting many thousands of base pairs. Prior studies have demonstrated that examining patterns of somatic mutations can be leveraged to provide both biological and clinical insights, thus, resulting in an extensive repertoire of tools for evaluating small mutational events. Recently, classification schemas for examining large-scale mutational events have emerged and shown their utility across the spectrum of human cancers. However, there has been no computationally efficient bioinformatics tool that allows visualizing and exploring these large-scale mutational events.

RESULTS

Here, we present a new version of SigProfilerMatrixGenerator that now delivers integrated capabilities for examining large mutational events. The tool provides support for examining copy-number variants and structural variants under two previously developed classification schemas and it supports data from numerous algorithms and data modalities. SigProfilerMatrixGenerator is written in Python with an R wrapper package provided for users that prefer working in an R environment.

CONCLUSIONS

The new version of SigProfilerMatrixGenerator provides the first standardized bioinformatics tool for optimized exploration and visualization of two previously developed classification schemas for copy number and structural variants. The tool is freely available at https://github.com/AlexandrovLab/SigProfilerMatrixGenerator with an extensive documentation at https://osf.io/s93d5/wiki/home/ .

Etiology of super-enhancer reprogramming and activation in cancer

Super-enhancers are large, densely concentrated swaths of enhancers that regulate genes critical for cell identity. Tumorigenesis is accompanied by changes in the super-enhancer landscape. These aberrant super-enhancers commonly form to activate proto-oncogenes, or other genes upon which cancer cells depend, that initiate tumorigenesis, promote tumor proliferation, and increase the fitness of cancer cells to survive in the tumor microenvironment. These include well-recognized master regulators of proliferation in the setting of cancer, such as the transcription factor MYC which is under the control of numerous super-enhancers gained in cancer compared to normal tissues. This Review will cover the expanding cell-intrinsic and cell-extrinsic etiology of these super-enhancer changes in cancer, including somatic mutations, copy number variation, fusion events, extrachromosomal DNA, and 3D chromatin architecture, as well as those activated by inflammation, extra-cellular signaling, and the tumor microenvironment.

Super-enhancer landscape rewiring in cancer: The epigenetic control at distal sites

Super-enhancers evolve as elements at the top of the hierarchical control of gene expression. They are important end-gatherers of signaling pathways that control stemness, differentiation or adaptive responses. Many epigenetic regulations focus on these regions, and not surprisingly, during the process of tumorigenesis, various alterations can account for their dysfunction. Super-enhancers are emerging as key drivers of the aberrant gene expression landscape that sustain the aggressiveness of cancer cells. In this review, we will describe and discuss about the structure of super-enhancers, their epigenetic regulation, and the major changes affecting their functionality in cancer.

Visualizing and exploring patterns of large mutational events with SigProfilerMatrixGenerator

Background

All cancers harbor somatic mutations in their genomes. In principle, mutations affecting between one and fifty base pairs are generally classified as small mutational events. Conversely, large mutational events affect more than fifty base pairs, and, in most cases, they encompass copy-number and structural variants affecting many thousands of base pairs. Prior studies have demonstrated that examining patterns of somatic mutations can be leveraged to provide both biological and clinical insights, thus, resulting in an extensive repertoire of tools for evaluating small mutational events. Recently, classification schemas for examining large-scale mutational events have emerged and shown their utility across the spectrum of human cancers. However, there has been no standard bioinformatics tool that allows visualizing and exploring these large-scale mutational events.

Results

Here, we present a new version of SigProfilerMatrixGenerator that now delivers integrated capabilities for examining large mutational events. The tool provides support for examining copy-number variants and structural variants under two previously developed classification schemas and it supports data from numerous algorithms and data modalities. SigProfilerMatrixGenerator is written in Python with an R wrapper package provided for users that prefer working in an R environment.

Conclusions

The new version of SigProfilerMatrixGenerator provides the first standardized bioinformatics tool for optimized exploration and visualization of two previously developed classification schemas for copy number and structural variants. The tool is freely available at https://github.com/AlexandrovLab/SigProfilerMatrixGenerator with an extensive documentation at https://osf.io/s93d5/wiki/home/ .

Genetic determinants and absence of breast cancer in Xavante Indians in Sangradouro Reserve, Brazil

Genetic compositions of distinct human populations are different. How genomic variants influence many common and rare genetic diseases is always of great medical and anthropological interest, and understanding of genetic architectures of population groups in relation to diseases can advance our knowledge of medicine. Here, we have studied the genomic architecture of a group of Xavante Indians, an indigenous population in Brazil, and compared them with normal populations from the 1000 Genomes Projects. Principal component analysis (PCA) indicates that the Xavante Indians are genetically distinctive when compared to other ethnic groups. No incidence of breast cancer cases has ever been reported in the population, and polygenic risk analysis indicates extremely low breast cancer risk in this population when compared with germline TCGA (The Cancer Genome Atlas) breast cancer normal control samples. Low germinal mutation burden among this population is also observed. Our findings will help to deepen the understanding of breast cancer and might also provide new approaches to study the disease.

Characterization of somatic structural variations in 528 Chinese individuals with Esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC) demonstrates high genome instability. Here, we analyze 528 whole genomes to investigate structural variations' mechanisms and biological functions. SVs show multi-mode distributions in size, indicating distinct mutational processes. We develop a tool and define five types of complex rearrangements with templated insertions. We highlight a type of fold-back inversion, which is associated with poor outcomes. Distinct rearrangement signatures demonstrate variable genomic metrics such as replicating time, spatial proximity, and chromatin accessibility. Specifically, fold-back inversion tends to occur near the centrosome; TD-c2 (Tandem duplication-cluster2) is significantly enriched in chromatin-accessibility and early-replication region compared to other signatures. Analyses of TD-c2 signature reveal 9 TD hotspots, of which we identify a hotspot consisting of a super-enhancer of PTHLH. We confirm the oncogenic effect of the PTHLH gene and its interaction with enhancers through functional experiments. Finally, extrachromosomal circular DNAs (ecDNAs) are present in 14% of ESCCs and have strong selective advantages to driver genes.

Patterns of structural variation define prostate cancer across disease states

The complex genomic landscape of prostate cancer evolves across disease states under therapeutic pressure directed toward inhibiting androgen receptor (AR) signaling. While significantly altered genes in prostate cancer have been extensively defined, there have been fewer systematic analyses of how structural variation shapes the genomic landscape of this disease across disease states. We uniformly characterized structural alterations across 531 localized and 143 metastatic prostate cancers profiled by whole genome sequencing, 125 metastatic samples of which were also profiled via whole transcriptome sequencing. We observed distinct significantly recurrent breakpoints in localized and metastatic castration-resistant prostate cancers (mCRPC), with pervasive alterations in noncoding regions flanking the AR, MYC, FOXA1, and LSAMP genes enriched in mCRPC and TMPRSS2-ERG rearrangements enriched in localized prostate cancer. We defined 9 subclasses of mCRPC based on signatures of structural variation, each associated with distinct genetic features and clinical outcomes. Our results comprehensively define patterns of structural variation in prostate cancer and identify clinically actionable subgroups based on whole genome profiling.

Genomic and epigenomic BRCA alterations predict adaptive resistance and response to platinum-based therapy in patients with triple-negative breast and ovarian carcinomas

Triple-negative breast cancer (TNBC) and ovarian carcinomas (OvCas) with BRCA1 promoter methylation ( BRCA1 meth) respond more poorly to alkylating agents compared to those bearing mutations in BRCA1 and BRCA2 ( BRCA mut). This is a conundrum given the biologically equivalent homologous recombination deficiency (HRD) induced by these genetic and epigenetic BRCA perturbations. We dissected this problem through detailed genomic analyses of TNBC and OvCa cohorts and experimentation with patient-derived xenografts and genetically engineered cell lines. We found that despite identical downstream genomic mutational signatures associated with BRCA1 meth and BRCA mut states, BRCA1 meth uniformly associates with poor outcomes. Exposure of BRCA1 meth TNBCs to platinum chemotherapy, either as clinical treatment of a patient or as experimental in vivo exposure of preclinical patient derived xenografts, resulted in allelic loss of BRCA1 methylation and increased BRCA1 expression and platinum resistance. These data suggest that, unlike BRCA mut cancers, where BRCA loss is a genetically “fixed” deficiency state, BRCA1 meth cancers are highly adaptive to genotoxin exposure and, through reversal of promoter methylation, recover BRCA1 expression and become resistant to therapy. We further found a specific augmented immune transcriptional signal associated with enhanced response to platinum chemotherapy but only in patients with BRCA-proficient cancers. We showed how integrating both this cancer immune signature and the presence of BRCA mutations results in more accurate predictions of patient response when compared to either HRD status or BRCA status alone. This underscores the importance of defining BRCA heterogeneity in optimizing the predictive precision of assigning response probabilities in TNBC and OvCa.

Computational analysis of cancer genome sequencing data

Distilling biologically meaningful information from cancer genome sequencing data requires comprehensive identification of somatic alterations using rigorous computational methods. As the amount and complexity of sequencing data have increased, so has the number of tools for analysing them. Here, we describe the main steps involved in the bioinformatic analysis of cancer genomes, review key algorithmic developments and highlight popular tools and emerging technologies. These tools include those that identify point mutations, copy number alterations, structural variations and mutational signatures in cancer genomes. We also discuss issues in experimental design, the strengths and limitations of sequencing modalities and methodological challenges for the future.

Rearrangement processes and structural variations show evidence of selection in oesophageal adenocarcinomas

Oesophageal adenocarcinoma (OAC) provides an ideal case study to characterize large-scale rearrangements. Using whole genome short-read sequencing of 383 cases, for which 214 had matched whole transcriptomes, we observed structural variations (SV) with a predominance of deletions, tandem duplications and inter-chromosome junctions that could be identified as LINE-1 mobile element (ME) insertions. Complex clusters of rearrangements resembling breakage-fusion-bridge cycles or extrachromosomal circular DNA accounted for 22% of complex SVs affecting known oncogenes. Counting SV events affecting known driver genes substantially increased the recurrence rates of these drivers. After excluding fragile sites, we identified 51 candidate new drivers in genomic regions disrupted by SVs, including ETV5, KAT6B and CLTC. RUNX1 was the most recurrently altered gene (24%), with many deletions inactivating the RUNT domain but preserved the reading frame, suggesting an altered protein product. These findings underscore the importance of identification of SV events in OAC with implications for targeted therapies.

Spectrum of DNA mismatch repair failures viewed through the lens of cancer genomics and implications for therapy

Genome sequencing can be used to detect DNA repair failures in tumors and learn about underlying mechanisms. Here, we synthesize findings from genomic studies that examined deficiencies of the DNA mismatch repair (MMR) pathway. The impairment of MMR results in genome-wide hypermutation and in the ‘microsatellite instability’ (MSI) phenotype—occurrence of indel mutations at short tandem repeat (microsatellite) loci. The MSI status of tumors was traditionally assessed by molecular testing of a selected set of MS loci or by measuring MMR protein expression levels. Today, genomic data can provide a more complete picture of the consequences on genomic instability. Multiple computational studies examined somatic mutation distributions that result from failed DNA repair pathways in tumors. These include analyzing the commonly studied trinucleotide mutational spectra of single-nucleotide variants (SNVs), as well as of other features such as indels, structural variants, mutation clusters and regional mutation rate redistribution. The identified mutation patterns can be used to rigorously measure prevalence of MMR failures across cancer types, and potentially to subcategorize the MMR deficiencies. Diverse data sources, genomic and pre-genomic, from human and from experimental models, suggest there are different ways in which MMR can fail, and/or that the cell-type or genetic background may result in different types of MMR mutational patterns. The spectrum of MMR failures may direct cancer evolution, generating particular sets of driver mutations. Moreover, MMR affects outcomes of therapy by DNA damaging drugs, antimetabolites, nonsense-mediated mRNA decay (NMD) inhibitors, and immunotherapy by promoting either resistance or sensitivity, depending on the type of therapy.

Defining genomic events involved in the evolutionary trajectories of myeloma and its precursor conditions

All patients with a diagnosis of multiple myeloma (MM) have a preceding, asymptomatic expansion of clonal plasma cells, clinically recognized as monoclonal gammopathy of undetermined significance or smoldering multiple myeloma (SMM). While most patients with monoclonal gammopathy of undetermined significance have a very small rate of progression, SMM is a widely heterogeneous condition where a fraction of patients will progress to symptomatic MM rather quickly, while others will experience an indolent clinical course. The differentiation between progressive and stable precursor condition thus represents one of the most important unmet clinical needs in the MM community. The ability to identify patients at high-risk of progression before major clonal expansion and onset of end-organ damage would enable strategies for early prevention and perhaps more effective intervention. All proposed criteria to predict the progression of myeloma precursor conditions are built around indirect markers of disease burden and, therefore, are generally able to accurately identify only a small fraction of patients in whom progression to MM is already occurring. Leveraging whole genome and exome sequencing, it has been shown that patients with stable myeloma precursor conditions are characterized by either absence or lower prevalence of distinct genomic events that are detectable in progressive precursor condition years before the progression. In this review, we discuss evolving genomic concepts and tools; and their ability to differentiate myeloma precursor conditions into two distinct entities: one benign (monoclonal gammopathy of benign significance) and another malignant (asymptomatic multiple myeloma).

Mutational signatures: emerging concepts, caveats and clinical applications

Whole-genome sequencing has brought the cancer genomics community into new territory. Thanks to the sheer power provided by the thousands of mutations present in each patient's cancer, we have been able to discern generic patterns of mutations, termed 'mutational signatures', that arise during tumorigenesis. These mutational signatures provide new insights into the causes of individual cancers, revealing both endogenous and exogenous factors that have influenced cancer development. This Review brings readers up to date in a field that is expanding in computational, experimental and clinical directions. We focus on recent conceptual advances, underscoring some of the caveats associated with using the mutational signature frameworks and highlighting the latest experimental insights. We conclude by bringing attention to areas that are likely to see advancements in clinical applications.

Gene Duplication and Gene Fusion Are Important Drivers of Tumourigenesis during Cancer Evolution

Chromosomal rearrangement and genome instability are common features of cancer cells in human. Consequently, gene duplication and gene fusion events are frequently observed in human malignancies and many of the products of these events are pathogenic, representing significant drivers of tumourigenesis and cancer evolution. In certain subsets of cancers duplicated and fused genes appear to be essential for initiation of tumour formation, and some even have the capability of transforming normal cells, highlighting the importance of understanding the events that result in their formation. The mechanisms that drive gene duplication and fusion are unregulated in cancer and they facilitate rapid evolution by selective forces akin to Darwinian survival of the fittest on a cellular level. In this review, we examine current knowledge of the landscape and prevalence of gene duplication and gene fusion in human cancers.

Evolution and genomic signatures of spontaneous somatic mutation in Drosophila intestinal stem cells

Spontaneous mutations can alter tissue dynamics and lead to cancer initiation. Although large-scale sequencing projects have illuminated processes that influence somatic mutation and subsequent tumor evolution, the mutational dynamics operating in the very early stages of cancer development are currently not well understood. To explore mutational processes in the early stages of cancer evolution, we exploited neoplasia arising spontaneously in the Drosophila intestine. Analysing whole-genome sequencing data with a dedicated bioinformatic pipeline, we found neoplasia formation to be driven largely through the inactivation of Notch by structural variants, many of which involve highly complex genomic rearrangements. The genome-wide mutational burden in neoplasia was found to be similar to that of several human cancers. Finally, we identified genomic features associated with spontaneous mutation, and defined the evolutionary dynamics and mutational landscape operating within intestinal neoplasia over the short lifespan of the adult fly. Our findings provide unique insight into mutational dynamics operating over a short timescale in the genetic model system, Drosophila melanogaster.

Chromothripsis drives the evolution of gene amplification in cancer

Focal chromosomal amplification is an important route to generating cancer through mediating over-expression of oncogenes^1–3 or to developing cancer therapy resistance by increasing expression of a gene whose action diminishes efficacy of an anti-cancer drug. Here we used whole-genome sequencing of clonal isolates developing chemotherapeutic resistance to identify chromothripsis as a major driver of extrachromosomal DNA (ecDNA) amplification into circular double minutes (DMs) through PARP- and DNA-PKcs-dependent mechanisms. Longitudinal analyses revealed that DMs undergo continuing structural evolution to promote increased drug tolerance through additional chromothriptic events. In-situ Hi-C sequencing is used to demonstrate that DMs preferentially tether near chromosome ends where they re-integrate when DNA damage is present. Intrachromosomal amplifications formed initially under low-level drug selection undergo continuing breakage-fusion-bridge cycles, generating >100 megabase-long amplicons that we show become trapped within interphase bridges and then shattered, producing micronuclei that mediate DM formation. Similar genome rearrangement profiles linked to localized gene amplification are identified in human cancers with acquired drug resistance or with oncogene amplifications. We propose that chromothripsis is a primary mechanism accelerating genomic DNA amplification and which enables rapid acquisition of tolerance to altered growth conditions.

Targeting DNA Damage Response in Prostate and Breast Cancer

Steroid hormone signaling induces vast gene expression programs which necessitate the local formation of transcription factories at regulatory regions and large-scale alterations of the genome architecture to allow communication among distantly related cis-acting regions. This involves major stress at the genomic DNA level. Transcriptionally active regions are generally instable and prone to breakage due to the torsional stress and local depletion of nucleosomes that make DNA more accessible to damaging agents. A dedicated DNA damage response (DDR) is therefore essential to maintain genome integrity at these exposed regions. The DDR is a complex network involving DNA damage sensor proteins, such as the poly(ADP-ribose) polymerase 1 (PARP-1), the DNA-dependent protein kinase catalytic subunit (DNA-PKcs), the ataxia-telangiectasia-mutated (ATM) kinase and the ATM and Rad3-related (ATR) kinase, as central regulators. The tight interplay between the DDR and steroid hormone receptors has been unraveled recently. Several DNA repair factors interact with the androgen and estrogen receptors and support their transcriptional functions. Conversely, both receptors directly control the expression of agents involved in the DDR. Impaired DDR is also exploited by tumors to acquire advantageous mutations. Cancer cells often harbor germline or somatic alterations in DDR genes, and their association with disease outcome and treatment response led to intensive efforts towards identifying selective inhibitors targeting the major players in this process. The PARP-1 inhibitors are now approved for ovarian, breast, and prostate cancer with specific genomic alterations. Additional DDR-targeting agents are being evaluated in clinical studies either as single agents or in combination with treatments eliciting DNA damage (e.g., radiation therapy, including targeted radiotherapy, and chemotherapy) or addressing targets involved in maintenance of genome integrity. Recent preclinical and clinical findings made in addressing DNA repair dysfunction in hormone-dependent and -independent prostate and breast tumors are presented. Importantly, the combination of anti-hormonal therapy with DDR inhibition or with radiation has the potential to enhance efficacy but still needs further investigation.

Revealing the impact of structural variants in multiple myeloma

The landscape of structural variants (SVs) in multiple myeloma remains poorly understood. Here, we performed comprehensive analysis of SVs in a large cohort of 752 multiple myeloma patients by low coverage long-insert whole genome sequencing. We identified 68 SV hotspots involving 17 new candidate driver genes, including the therapeutic targets BCMA (TNFRSF17), SLAMF and MCL1. Catastrophic complex rearrangements termed chromothripsis were present in 24% of patients and independently associated with poor clinical outcomes. Templated insertions were the second most frequent complex event (19%), mostly involved in super-enhancer hijacking and activation of oncogenes such as CCND1 and MYC. Importantly, in 31% of patients two or more seemingly independent putative driver events were caused by a single structural event, demonstrating that the complex genomic landscape of multiple myeloma can be acquired through few key events during tumor evolutionary history. Overall, this study reveals the critical role of SVs in multiple myeloma pathogenesis.

Aberrant super-enhancer landscape reveals core transcriptional regulatory circuitry in lung adenocarcinoma

Lung adenocarcinoma (LUAD) relies on dysregulated gene expression to sustain its infinite growth and progression. Emerging evidence indicates that aberrant transcriptional program results from core transcriptional regulatory circuitry (CRC) which is driven by super-enhancers (SEs). In this study, by integrating profiles of H3K27Ac chromatin immunoprecipitation sequencing (ChIP-seq) from normal adult lung and LUAD cell lines, we revealed that widespread alterations of the super-enhancer were presence during lung carcinogenesis. With SE-based modeling of regulatory circuits and assessments of transcription factor (TF) dependencies, we reconstructed an interconnected transcriptional regulation network formed by three master TFs, including ELF3, EHF, and TGIF1, all of which promoted each other’s expression that confirmed by ChIP-qPCR and western blot. Loss-of function assay revealed that each of them is essential for LUAD cells survival, invasion and metastasis. Meanwhile, the rescue assay also illustrated the transacting transcriptional regulatory circuitry. In addition, the mRNA levels of ELF3, EHF, and TGIF1 were differentially expressed in LUAD tumors and peritumoral tissue. IHC of serial sections revealed that high expressions of CRC (ELF3/EHF/TGIF1-High) were closely associated with high proliferative activity in tumor tissue and poor prognosis on patients with LUAD. Finally, we used small molecular inhibitors to perturb the transcriptional circuitry, also exhibited a prominent anti-cancer effect in vitro. Our findings reveal the mechanism of the transcriptional dysregulation and addiction of LUAD.

Disruption of super-enhancer-driven tumor suppressor gene RCAN1.4 expression promotes the malignancy of breast carcinoma

Background

Super-enhancers (SEs) play a crucial role in cancer, which is often associate with activated oncogenes. However, little is known about how SEs facilitate tumour suppression. Individuals with Down syndrome exhibit a remarkably reduced incidence of breast cancer (BC), moving the search for tumor suppressor genes on human chromosome 21 (HSA21). In this study, we aim to identify and explore potential mechanisms by which SEs are established for tumor suppressor RCAN1.4 on HSA21 in BC.

Methods

In silico analysis and immunohistochemical staining were used to assess the expression and clinical relevance of RCAN1.4 and RUNX3 in BC. Function experiments were performed to evaluate the effects of RCAN1.4 on the malignancy of breast carcinoma in vitro and in vivo. ChIP-seq data analysis, ChIP-qPCR, double-CRISPR genome editing, and luciferase reporter assay were utilized to confirm RUNX3 was involved in regulating RCAN1.4-associated SE in BC. The clinical value of co-expression of RCAN1.4 and RUNX3 was evaluated in BC patients.

Results

Here, we characterized RCAN1.4 as a potential tumour suppressor in BC. RCAN1.4 loss promoted tumour metastasis to bone and brain, and its overexpression inhibited tumour growth by blocking the calcineurin-NFATc1 pathway. Unexpectedly, we found RCAN1.4 expression was driven by a ~ 23 kb-long SE. RCAN1.4-SE^distal was sensitive to BRD4 inhibition, and its deletion decreased RCAN1.4 expression by over 90% and induced the malignant phenotype of BC cells. We also discovered that the binding sites in the SE region of RCAN1.4 were enriched for consensus sequences of transcription factor RUNX3. Knockdown of RUNX3 repressed the luciferase activity and also decreased H3K27ac enrichment binding at the SE region of RCAN1.4. Furthermore, abnormal SE-driven RCAN1.4 expression mediated by RUNX3 loss could be physiologically significant and clinically relevant in BC patients. Notably, we established a prognostic model based on RCAN1.4 and RUNX3 co-expression that effectively predicted the overall survival in BC patients.

Conclusions

These findings reveal an important role of SEs in facilitating tumour suppression in BC. Considering that the combination of low RCAN1.4 and low RUNX3 expression has worse prognosis, RUNX3-RCAN1.4 axis maybe a novel prognostic biomarker and therapeutic target for BC patients.

A practical framework and online tool for mutational signature analyses show inter-tissue variation and driver dependencies

Mutational signatures are patterns of mutations that arise during tumorigenesis. We present an enhanced, practical framework for mutational signature analyses. Applying these methods on 3,107 whole genome sequenced (WGS) primary cancers of 21 organs reveals known signatures and nine previously undescribed rearrangement signatures. We highlight inter-organ variability of signatures and present a way of visualizing that diversity, reinforcing our findings in an independent analysis of 3,096 WGS metastatic cancers. Signatures with a high level of genomic instability are dependent on TP53 dysregulation. We illustrate how uncertainty in mutational signature identification and assignment to samples affects tumor classification, reinforcing that using multiple orthogonal mutational signature data is not only beneficial, it is essential for accurate tumor stratification. Finally, we present a reference web-based tool for cancer and experimentally-generated mutational signatures, called Signal (https://signal.mutationalsignatures.com), that also supports performing mutational signature analyses.

Mutational signatures in tumours induced by high and low energy radiation in Trp53 deficient mice

Ionising radiation (IR) is a recognised carcinogen responsible for cancer development in patients previously treated using radiotherapy, and in individuals exposed as a result of accidents at nuclear energy plants. However, the mutational signatures induced by distinct types and doses of radiation are unknown. Here, we analyse the genetic architecture of mammary tumours, lymphomas and sarcomas induced by high (56Fe-ions) or low (gamma) energy radiation in mice carrying Trp53 loss of function alleles. In mammary tumours, high-energy radiation is associated with induction of focal structural variants, leading to genomic instability and Met amplification. Gamma-radiation is linked to large-scale structural variants and a point mutation signature associated with oxidative stress. The genomic architecture of carcinomas, sarcomas and lymphomas arising in the same animals are significantly different. Our study illustrates the complex interactions between radiation quality, germline Trp53 deficiency and tissue/cell of origin in shaping the genomic landscape of IR-induced tumours.

Targeting Super-Enhancer-Associated Oncogenes in Osteosarcoma with THZ2, a Covalent CDK7 Inhibitor

PURPOSE

Malignancy of cancer cells depends on the active transcription of tumor-associated genes. Recently, unique clusters of transcriptional enhancers, termed super-enhancers, have been reported to drive the expression of genes that define cell identity. In this study, we characterized specific super-enhancer-associated genes of osteosarcoma, and explored their potential therapeutic value.

EXPERIMENTAL DESIGN

Super-enhancer regions were characterized through chromatin immunoprecipitation sequencing (ChIP-seq). RT-qPCR was used to detect the mRNA level of CDK7 in patient specimens and confirm the regulation of sensitive oncogenes by THZ2. The phosphorylation of the initiation-associated sites of RNA polymerase II (RNAPII) C-terminal repeat domain (CTD) was measured using Western blotting. Microarray expression analysis was conducted to explore transcriptional changes after THZ2 treatment. A variety of in vitro and in vivo assays were performed to assess the effects of CDK7 knockdown and THZ2 treatment in osteosarcoma.

RESULTS

Super-enhancers were associated with oncogenic transcripts and key genes encoding cell-type-specific transcription factors in osteosarcoma. Knockdown of transcription factor CDK7 reduced phosphorylation of the RNAPII CTD, and suppressed the growth and metastasis of osteosarcoma. A new specific CDK7 inhibitor, THZ2, suppressed cancer biology by inhibition of transcriptional activity. Compared with typical enhancers, osteosarcoma super-enhancer-associated oncogenes were particular vulnerable to this transcriptional disruption. THZ2 exhibited a powerful anti-osteosarcoma effect in vitro and in vivo.

CONCLUSIONS

Super-enhancer-associated genes contribute to the malignant potential of osteosarcoma, and selectively targeting super-enhancer-associated oncogenes with the specific CDK7 inhibitor THZ2 might be a promising therapeutic strategy for patients with osteosarcoma.

Holistic cancer genome profiling for every patient

Technological advances in the ability to read the human genome have accelerated the speed of sequencing, such that today we can perform whole genome sequencing (WGS) in one day. Until recently, genomic studies have largely been limited to seeking novel scientific discoveries. The application of new insights gained through cancer WGS into the clinical domain, have been relatively limited. Looking ahead, a vast amount of data can be generated by genomic studies. Of note, excellent organisation of genomic and clinical data permits the application of machine-learning methods which can lead to the development of clinical algorithms that could assist future clinicians and genomicists in the analysis and interpretation of individual cancer genomes. Here, we describe what can be gleaned from holistic whole cancer genome profiling and argue that we must build the infrastructure and educational frameworks to support the modern clinical genomicist to prepare for a future where WGS will be the norm.

Whole-genome sequencing of prostate cancer reveals novel mutation-driven processes and molecular subgroups

Prostate cancer (PCa) is the second most frequently diagnosed cancer in men. However, its genetic characteristics in the Chinese population have not been extensively profiled. Here we screened 27 Chinese patients and preformed whole-genome sequencing to dissect their genomic patterns. We found that 18.5% (5/27) tumors harbored non-protein coding mutations on FOXA1. Besides, novel focal amplifications/deletions involving ZBTB7B, SLC4A4, TBX18, CYSLTR2 and EFNA5 were frequently present in tumors. Notably, group specificity of base substitution signature B displayed a strong link to hotspot mutations on SPOP gene. Furthermore, based on six rearrangement signatures, tumors were assigned to five subgroups that revealed different biological mechanisms. Of which, tandem duplicator subgroup harbored all CDK12 mutations, small deletor subgroup owned 75% TP53 changes, and large deletor subgroup had 66.7% SPOP mutations. Taken together, we provide a comprehensive view of genomic patterns which affect the critical cell regulators of PCa in the Chinese population. Our findings may provide valuable insights for designing specific treatments for Chinese patients with PCa.

Whole-genome sequencing of triple-negative breast cancers in a population-based clinical study

Whole-genome sequencing (WGS) brings comprehensive insights to cancer genome interpretation. To explore the clinical value of WGS, we sequenced 254 triple-negative breast cancers (TNBCs) for which associated treatment and outcome data were collected between 2010 and 2015 via the population-based Sweden Cancerome Analysis Network-Breast (SCAN-B) project (ClinicalTrials.gov ID:NCT02306096). Applying the HRDetect mutational-signature-based algorithm to classify tumors, 59% were predicted to have homologous-recombination-repair deficiency (HRDetect-high): 67% explained by germline/somatic mutations of BRCA1/BRCA2, BRCA1 promoter hypermethylation, RAD51C hypermethylation or biallelic loss of PALB2. A novel mechanism of BRCA1 abrogation was discovered via germline SINE-VNTR-Alu retrotransposition. HRDetect provided independent prognostic information, with HRDetect-high patients having better outcome on adjuvant chemotherapy for invasive disease-free survival (hazard ratio (HR) = 0.42; 95% confidence interval (CI) = 0.2-0.87) and distant relapse-free interval (HR = 0.31, CI = 0.13-0.76) compared to HRDetect-low, regardless of whether a genetic/epigenetic cause was identified. HRDetect-intermediate, some possessing potentially targetable biological abnormalities, had the poorest outcomes. HRDetect-low cancers also had inadequate outcomes: ~4.7% were mismatch-repair-deficient (another targetable defect, not typically sought) and they were enriched for (but not restricted to) PIK3CA/AKT1 pathway abnormalities. New treatment options need to be considered for now-discernible HRDetect-intermediate and HRDetect-low categories. This population-based study advocates for WGS of TNBC to better inform trial stratification and improve clinical decision-making.

Dysregulated Transcriptional Control in Prostate Cancer

Recent advances in whole-genome and transcriptome sequencing of prostate cancer at different stages indicate that a large number of mutations found in tumors are present in non-protein coding regions of the genome and lead to dysregulated gene expression. Single nucleotide variations and small mutations affecting the recruitment of transcription factor complexes to DNA regulatory elements are observed in an increasing number of cases. Genomic rearrangements may position coding regions under the novel control of regulatory elements, as exemplified by the TMPRSS2-ERG fusion and the amplified enhancer identified upstream of the androgen receptor (AR) gene. Super-enhancers are increasingly found to play important roles in aberrant oncogenic transcription. Several players involved in these processes are currently being evaluated as drug targets and may represent new vulnerabilities that can be exploited for prostate cancer treatment. They include factors involved in enhancer and super-enhancer function such as bromodomain proteins and cyclin-dependent kinases. In addition, non-coding RNAs with an important gene regulatory role are being explored. The rapid progress made in understanding the influence of the non-coding part of the genome and of transcription dysregulation in prostate cancer could pave the way for the identification of novel treatment paradigms for the benefit of patients.

Whole-genome sequencing reveals novel tandem-duplication hotspots and a prognostic mutational signature in gastric cancer

Genome-wide analysis of genomic signatures might reveal novel mechanisms for gastric cancer (GC) tumorigenesis. Here, we analysis structural variations (SVs) and mutational signatures via whole-genome sequencing of 168 GCs. Our data demonstrates diverse models of complex SVs operative in GC, which lead to high-level amplification of oncogenes. We find varying proportion of tandem-duplications (TDs) among individuals and identify 24 TD hotspots involving well-established cancer genes such as CCND1, ERBB2 and MYC. Specifically, we nominate a novel hotspot involving the super-enhancer of ZFP36L2 presents in approximately 10% GCs from different cohorts, the oncogenic role of which is further confirmed by experimental data. In addition, our data reveal a mutational signature, specifically occurring in noncoding region, significantly enriched in tumors with cadherin 1 mutations, and associated with poor prognoses. Collectively, our data suggest that TDs might serve as an important mechanism for cancer gene activation and provide a novel signature for stratification.

Structural variations in gastric cancer impact progression. Here, the authors perform whole-genome sequencing on 168 gastric cancer patients and identified tandem-duplications of super-enhancer ZFP36L2 in 10% of gastric cancer, and mutational signatures in tumors with cadherin 1 mutations that associated with poor prognoses.

Targeting Super-Enhancers as a Therapeutic Strategy for Cancer Treatment

Super-enhancers (SEs) refer to large clusters of enhancers that drive gene expressions. Recent data has provided novel insights in elucidating the roles of SEs in many diseases, including cancer. Many mechanisms involved in tumorigenesis and progression, ranging from internal gene mutation and rearrangement to external damage and inducement, have been demonstrated to be highly associated with SEs. Moreover, translocation, formation, deletion, or duplication of SEs themselves could lead to tumor development. It has been reported that various oncogenic molecules and pathways are tightly regulated by SEs. Moreover, several clinical trials on novel SEs blockers, such as BET inhibitor and CDK7i, have indicated the potential roles of SEs in cancer therapy. In this review, we highlighted the underlying mechanism of action of SEs in cancer development and the corresponding novel potential therapeutic strategies. It is speculated that targeting SEs could complement the traditional approaches and lead to more effective treatment for cancer patients.

Undifferentiated Sarcomas Develop through Distinct Evolutionary Pathways

Undifferentiated sarcomas (USARCs) of adults are diverse, rare, and aggressive soft tissue cancers. Recent sequencing efforts have confirmed that USARCs exhibit one of the highest burdens of structural aberrations across human cancer. Here, we sought to unravel the molecular basis of the structural complexity in USARCs by integrating DNA sequencing, ploidy analysis, gene expression, and methylation profiling. We identified whole genome duplication as a prevalent and pernicious force in USARC tumorigenesis. Using mathematical deconvolution strategies to unravel the complex copy-number profiles and mutational timing models we infer distinct evolutionary pathways of these rare cancers. In addition, 15% of tumors exhibited raised mutational burdens that correlated with gene expression signatures of immune infiltration, and good prognosis.

Super-enhancers in cancer

Cancer is fueled by the aberrant activity of oncogenic and tumor suppressive pathways. Transcriptional dysregulation of these pathways play a major role both in the genesis and development of cancer. Dysregulation of transcriptional programs can be mediated by genetic and epigenetic alterations targeting both protein coding genes and non-coding regulatory elements like enhancers and super-enhancers. Super-enhancers, characterized as large clusters of enhancers in close proximity, have been identified as essential oncogenic drivers required for the maintenance of cancer cell identity. As a result, cancer cells are often addicted to the super-enhancer driven transcriptional programs. Furthermore, pharmacological inhibitors targeting key components of super-enhancer assembly and activation have shown great promise in reducing tumor growth and proliferation in several pre-clinical tumor models. This article reviews the current understanding of super-enhancer assembly and activation, the different mechanisms by which cancer cells acquire oncogenic super-enhancers and, finally, the potential of targeting super-enhancers as future therapeutics.

Dissecting Tissue-Specific Super-Enhancers by Integrating Genome-Wide Analyses and CRISPR/Cas9 Genome Editing

Recent advances in genome-wide sequencing technologies have provided researchers with unprecedented opportunities to discover the genomic structures of gene regulatory units in living organisms. In particular, the integration of ChIP-seq, RNA-seq, and DNase-seq techniques has facilitated the mapping of a new class of regulatory elements. These elements, called super-enhancers, can regulate cell-type-specific gene sets and even fine-tune gene expression regulation in response to external stimuli, and have become a hot topic in genome biology. However, there is scant genetic evidence demonstrating their unique biological relevance and the mechanisms underlying these biological functions. In this review, we describe a robust genome-wide strategy for mapping cell-type-specific enhancers or super-enhancers in the mammary genome. In this strategy, genome-wide screening of active enhancer clusters that are co-occupied by mammary-enriched transcription factors, co-factors, and active enhancer marks is used to identify bona fide mammary tissue-specific super-enhancers. The in vivo function of these super-enhancers and their associated regulatory elements may then be investigated in various ways using the advanced CRISPR/Cas9 genome-editing technology. Based on our experience targeting various mammary genomic sites using CRISPR/Cas9 in mice, we comprehensively discuss the molecular consequences of the different targeting methods, such as the number of gRNAs and the dependence on their simultaneous or sequential injections. We also mention the considerations that are essential for obtaining accurate results and shed light on recent progress that has been made in developing modified CRISPR/Cas9 genome-editing techniques. In the future, the coupling of advanced genome-wide sequencing and genome-editing technologies could provide new insights into the complex genetic regulatory networks involved in mammary-gland development.

Modeling double strand break susceptibility to interrogate structural variation in cancer

BACKGROUND

Structural variants (SVs) are known to play important roles in a variety of cancers, but their origins and functional consequences are still poorly understood. Many SVs are thought to emerge from errors in the repair processes following DNA double strand breaks (DSBs).

RESULTS

We used experimentally quantified DSB frequencies in cell lines with matched chromatin and sequence features to derive the first quantitative genome-wide models of DSB susceptibility. These models are accurate and provide novel insights into the mutational mechanisms generating DSBs. Models trained in one cell type can be successfully applied to others, but a substantial proportion of DSBs appear to reflect cell type-specific processes. Using model predictions as a proxy for susceptibility to DSBs in tumors, many SV-enriched regions appear to be poorly explained by selectively neutral mutational bias alone. A substantial number of these regions show unexpectedly high SV breakpoint frequencies given their predicted susceptibility to mutation and are therefore credible targets of positive selection in tumors. These putatively positively selected SV hotspots are enriched for genes previously shown to be oncogenic. In contrast, several hundred regions across the genome show unexpectedly low levels of SVs, given their relatively high susceptibility to mutation. These novel coldspot regions appear to be subject to purifying selection in tumors and are enriched for active promoters and enhancers.

CONCLUSIONS

We conclude that models of DSB susceptibility offer a rigorous approach to the inference of SVs putatively subject to selection in tumors.

Structural rearrangements generate cell-specific, gene-independent CRISPR-Cas9 loss of fitness effects

BACKGROUND

CRISPR-Cas9 genome editing is widely used to study gene function, from basic biology to biomedical research. Structural rearrangements are a ubiquitous feature of cancer cells and their impact on the functional consequences of CRISPR-Cas9 gene-editing has not yet been assessed.

RESULTS

Utilizing CRISPR-Cas9 knockout screens for 250 cancer cell lines, we demonstrate that targeting structurally rearranged regions, in particular tandem or interspersed amplifications, is highly detrimental to cellular fitness in a gene-independent manner. In contrast, amplifications caused by whole chromosomal duplication have little to no impact on fitness. This effect is cell line specific and dependent on the ploidy status. We devise a copy-number ratio metric that substantially improves the detection of gene-independent cell fitness effects in CRISPR-Cas9 screens. Furthermore, we develop a computational tool, called Crispy, to account for these effects on a single sample basis and provide corrected gene fitness effects.

CONCLUSION

Our analysis demonstrates the importance of structural rearrangements in mediating the effect of CRISPR-Cas9-induced DNA damage, with implications for the use of CRISPR-Cas9 gene-editing in cancer cells.

Cyclin A2/E1 activation defines a hepatocellular carcinoma subclass with a rearrangement signature of replication stress

Cyclins A2 and E1 regulate the cell cycle by promoting S phase entry and progression. Here, we identify a hepatocellular carcinoma (HCC) subgroup exhibiting cyclin activation through various mechanisms including hepatitis B virus (HBV) and adeno-associated virus type 2 (AAV2) insertions, enhancer hijacking and recurrent CCNA2 fusions. Cyclin A2 or E1 alterations define a homogenous entity of aggressive HCC, mostly developed in non-cirrhotic patients, characterized by a transcriptional activation of E2F and ATR pathways and a high frequency of RB1 and PTEN inactivation. Cyclin-driven HCC display a unique signature of structural rearrangements with hundreds of tandem duplications and templated insertions frequently activating TERT promoter. These rearrangements, strongly enriched in early-replicated active chromatin regions, are consistent with a break-induced replication mechanism. Pan-cancer analysis reveals a similar signature in BRCA1-mutated breast and ovarian cancers. Together, this analysis reveals a new poor prognosis HCC entity and a rearrangement signature related to replication stress.

Cyclins A2 and E1 are known to regulate the cell cycle by promoting S phase entry and progression. Here, they identify an aggressive hepatocellular carcinoma subgroup exhibiting cyclin activation through various mechanisms and find this subgroup to display replication stress-induced structural rearrangements frequently activating TERT promoter.

Breaking point: the genesis and impact of structural variation in tumours

Somatic structural variants undoubtedly play important roles in driving tumourigenesis. This is evident despite the substantial technical challenges that remain in accurately detecting structural variants and their breakpoints in tumours and in spite of our incomplete understanding of the impact of structural variants on cellular function. Developments in these areas of research contribute to the ongoing discovery of structural variation with a clear impact on the evolution of the tumour and on the clinical importance to the patient. Recent large whole genome sequencing studies have reinforced our impression of each tumour as a unique combination of mutations but paradoxically have also discovered similar genome-wide patterns of single-nucleotide and structural variation between tumours. Statistical methods have been developed to deconvolute mutation patterns, or signatures, that recur across samples, providing information about the mutagens and repair processes that may be active in a given tumour. These signatures can guide treatment by, for example, highlighting vulnerabilities in a particular tumour to a particular chemotherapy. Thus, although the complete reconstruction of the full evolutionary trajectory of a tumour genome remains currently out of reach, valuable data are already emerging to improve the treatment of cancer.

Aberrant PRDM9 expression impacts the pan-cancer genomic landscape

The binding of PRDM9 to chromatin is a key step in the induction of DNA double-strand breaks associated with meiotic recombination hotspots; it is normally expressed solely in germ cells. We interrogated 1879 cancer samples in 39 different cancer types and found that PRDM9 is unexpectedly expressed in 20% of these tumors even after stringent gene homology correction. The expression levels of PRDM9 in tumors are significantly higher than those found in healthy neighboring tissues and in healthy nongerm tissue databases. Recurrently mutated regions located within 5 Mb of the PRDM9 loci, as well as differentially expressed genes in meiotic pathways, correlate with PRDM9 expression. In samples with aberrant PRDM9 expression, structural variant breakpoints frequently neighbor the DNA motif recognized by PRDM9, and there is an enrichment of structural variants at sites of known meiotic PRDM9 activity. This study is the first to provide evidence of an association between aberrant expression of the meiosis-specific gene PRDM9 with genomic instability in cancer.

The Tandem Duplicator Phenotype Is a Prevalent Genome-Wide Cancer Configuration Driven by Distinct Gene Mutations

The tandem duplicator phenotype (TDP) is a genome-wide instability configuration primarily observed in breast, ovarian, and endometrial carcinomas. Here, we stratify TDP tumors by classifying their tandem duplications (TDs) into three span intervals, with modal values of 11 kb, 231 kb, and 1.7 Mb, respectively. TDPs with ∼11 kb TDs feature loss of TP53 and BRCA1. TDPs with ∼231 kb and ∼1.7 Mb TDs associate with CCNE1 pathway activation and CDK12 disruptions, respectively. We demonstrate that p53 and BRCA1 conjoint abrogation drives TDP induction by generating short-span TDP mammary tumors in genetically modified mice lacking them. Lastly, we show how TDs in TDP tumors disrupt heterogeneous combinations of tumor suppressors and chromatin topologically associating domains while duplicating oncogenes and super-enhancers.

Patterns and mechanisms of structural variations in human cancer

Next-generation sequencing technology has enabled the comprehensive detection of genomic alterations in human somatic cells, including point mutations, chromosomal rearrangements, and structural variations (SVs). Using sophisticated bioinformatics algorithms, unbiased catalogs of SVs are emerging from thousands of human cancer genomes for the first time. Via careful examination of SV breakpoints at single-nucleotide resolution as well as local DNA copy number changes, diverse patterns of genomic rearrangements are being revealed. These "SV signatures" provide deep insight into the mutational processes that have shaped genome changes in human somatic cells. This review summarizes the characteristics of recently identified complex SVs, including chromothripsis, chromoplexy, microhomology-mediated breakage-induced replication (MMBIR), and others, to provide a holistic snapshot of the current knowledge on genomic rearrangements in somatic cells.

Structural Alterations Driving Castration-Resistant Prostate Cancer Revealed by Linked-Read Genome Sequencing

Nearly all prostate cancer deaths are from metastatic castration-resistant prostate cancer (mCRPC), but there have been few whole-genome sequencing (WGS) studies of this disease state. We performed linked-read WGS on 23 mCRPC biopsy specimens and analyzed cell-free DNA sequencing data from 86 patients with mCRPC. In addition to frequent rearrangements affecting known prostate cancer genes, we observed complex rearrangements of the AR locus in most cases. Unexpectedly, these rearrangements include highly recurrent tandem duplications involving an upstream enhancer of AR in 70%-87% of cases compared with <2% of primary prostate cancers. A subset of cases displayed AR or MYC enhancer duplication in the context of a genome-wide tandem duplicator phenotype associated with CDK12 inactivation. Our findings highlight the complex genomic structure of mCRPC, nominate alterations that may inform prostate cancer treatment, and suggest that additional recurrent events in the non-coding mCRPC genome remain to be discovered.

Integration of Enhancer-Promoter Interactions with GWAS Summary Results Identifies Novel Schizophrenia-Associated Genes and Pathways

It remains challenging to boost statistical power of genome-wide association studies (GWASs) to identify more risk variants or loci that can account for "missing heritability." Furthermore, since most identified variants are not in gene-coding regions, a biological interpretation of their function is largely lacking. On the other hand, recent biotechnological advances have made it feasible to experimentally measure the three-dimensional organization of the genome, including enhancer-promoter interactions in high resolutions. Due to the well-known critical roles of enhancer-promoter interactions in regulating gene expression programs, such data have been applied to link GWAS risk variants to their putative target genes, gaining insights into underlying biological mechanisms. However, their direct use in GWAS association testing is yet to be exploited. Here we propose integrating enhancer-promoter interactions into GWAS association analysis to both boost statistical power and enhance interpretability. We demonstrate that through an application to two large-scale schizophrenia (SCZ) GWAS summary data sets, the proposed method could identify some novel SCZ-associated genes and pathways (containing no significant SNPs). For example, after the Bonferroni correction, for the larger SCZ data set with 36,989 cases and 113,075 controls, our method applied to the gene body and enhancer regions identified 27 novel genes and 11 novel KEGG pathways to be significant, all missed by the transcriptome-wide association study (TWAS) approach. We conclude that our proposed method is potentially useful and is complementary to TWAS and other standard gene- and pathway-based methods.

Enhancer reprogramming in tumor progression: a new route towards cancer cell plasticity

Cancer heterogeneity arises during tumor progression as a consequence of genetic insults, environmental cues, and reversible changes in the epigenetic state, favoring tumor cell plasticity. The role of enhancer reprogramming is emerging as a relevant field in cancer biology as it supports adaptation of cancer cells to those environmental changes encountered during tumor progression and metastasis seeding. In this review, we describe the cancer-related alterations that drive oncogenic enhancer activity, leading to dysregulated transcriptional programs. We discuss the molecular mechanisms of both cis- and trans-factors in overriding the regulatory circuits that maintain cell-type specificity and imposing an alternative, de-regulated enhancer activity in cancer cells. We further comment on the increasing evidence which implicates stress response and aging-signaling pathways in the enhancer landscape reprogramming during tumorigenesis. Finally, we focus on the potential therapeutic implications of these enhancer-mediated subverted transcriptional programs, putting particular emphasis on the lack of information regarding tumor progression and the metastatic outgrowth, which still remain the major cause of mortality related to cancer.

Promoter of lncRNA Gene PVT1 Is a Tumor-Suppressor DNA Boundary Element

Noncoding mutations in cancer genomes are frequent but challenging to interpret. PVT1 encodes an oncogenic lncRNA, but recurrent translocations and deletions in human cancers suggest alternative mechanisms. Here, we show that the PVT1 promoter has a tumor-suppressor function that is independent of PVT1 lncRNA. CRISPR interference of PVT1 promoter enhances breast cancer cell competition and growth in vivo. The promoters of the PVT1 and the MYC oncogenes, located 55 kb apart on chromosome 8q24, compete for engagement with four intragenic enhancers in the PVT1 locus, thereby allowing the PVT1 promoter to regulate pause release of MYC transcription. PVT1 undergoes developmentally regulated monoallelic expression, and the PVT1 promoter inhibits MYC expression only from the same chromosome via promoter competition. Cancer genome sequencing identifies recurrent mutations encompassing the human PVT1 promoter, and genome editing verified that PVT1 promoter mutation promotes cancer cell growth. These results highlight regulatory sequences of lncRNA genes as potential disease-associated DNA elements.

Whole-genome sequencing reveals genomic signatures associated with the inflammatory microenvironments in Chinese NSCLC patients

Chinese lung cancer patients have distinct epidemiologic and genomic features, highlighting the presence of specific etiologic mechanisms other than smoking. Here, we present a comprehensive genomic landscape of 149 non-small cell lung cancer (NSCLC) cases and identify 15 potential driver genes. We reveal that Chinese patients are specially characterized by not only highly clustered EGFR mutations but a mutational signature (MS3, 33.7%), that is associated with inflammatory tumor-infiltrating B lymphocytes (P = 0.001). The EGFR mutation rate is significantly increased with the proportion of the MS3 signature (P = 9.37 × 10⁻⁵). TCGA data confirm that the infiltrating B lymphocyte abundance is significantly higher in the EGFR-mutated patients (P = 0.007). Additionally, MS3-high patients carry a higher contribution of distant chromosomal rearrangements >1 Mb (P = 1.35 × 10⁻⁷), some of which result in fusions involving genes with important functions (i.e., ALK and RET). Thus, inflammatory infiltration may contribute to the accumulation of EGFR mutations, especially in never-smokers.

The distinct genomic and epidemiological features of Chinese lung cancer patients suggest the presence of alternative causal mechanisms. Here, the authors present the genomic landscape of 149 Chinese NSCLC patients and reveal distinct mutational signatures associated with inflammatory microenvironments.

Validating the concept of mutational signatures with isogenic cell models

The diversity of somatic mutations in human cancers can be decomposed into individual mutational signatures, patterns of mutagenesis that arise because of DNA damage and DNA repair processes that have occurred in cells as they evolved towards malignancy. Correlations between mutational signatures and environmental exposures, enzymatic activities and genetic defects have been described, but human cancers are not ideal experimental systems-the exposures to different mutational processes in a patient's lifetime are uncontrolled and any relationships observed can only be described as an association. Here, we demonstrate the proof-of-principle that it is possible to recreate cancer mutational signatures in vitro using CRISPR-Cas9-based gene-editing experiments in an isogenic human-cell system. We provide experimental and algorithmic methods to discover mutational signatures generated under highly experimentally-controlled conditions. Our in vitro findings strikingly recapitulate in vivo observations of cancer data, fundamentally validating the concept of (particularly) endogenously-arising mutational signatures.

Mutation hotspots at CTCF binding sites coupled to chromosomal instability in gastrointestinal cancers

Tissue-specific driver mutations in non-coding genomic regions remain undefined for most cancer types. Here, we unbiasedly analyze 212 gastric cancer (GC) whole genomes to identify recurrently mutated non-coding regions in GC. Applying comprehensive statistical approaches to accurately model background mutational processes, we observe significant enrichment of non-coding indels (insertions/deletions) in three gastric lineage-specific genes. We further identify 34 mutation hotspots, of which 11 overlap CTCF binding sites (CBSs). These CBS hotspots remain significant even after controlling for a genome-wide elevated mutation rate at CBSs. In 3 out of 4 tested CBS hotspots, mutations are nominally associated with expression change of neighboring genes. CBS hotspot mutations are enriched in tumors showing chromosomal instability, co-occur with neighboring chromosomal aberrations, and are common in gastric (25%) and colorectal (19%) tumors but rare in other cancer types. Mutational disruption of specific CBSs may thus represent a tissue-specific mechanism of tumorigenesis conserved across gastrointestinal cancers.

The impact of non-coding somatic mutations in gastric cancer is unknown. Here, using whole genome sequencing data from 212 gastric tumors, the authors identify recurring mutations at specific CTCF binding sites that are common across gastrointestinal cancers and associated with chromosomal instability.