A Pan-Cancer Compendium of Genes Deregulated by Somatic Genomic Rearrangement across More Than 1,400 Cases

Germline structural variation globally impacts the cancer transcriptome including disease-relevant genes

Germline variation and somatic alterations contribute to the molecular profile of cancers. We combine RNA with whole genome sequencing across 1,218 cancer patients to determine the extent germline structural variants (SVs) impact expression of nearby genes. For hundreds of genes, recurrent and common germline SV breakpoints within 100 kb associate with increased or decreased expression in tumors spanning various tissues of origin. A significant fraction of germline SV expression associations involves duplication of intergenic enhancers or 3' UTR disruption. Genes altered by both somatic and germline SVs include ATRX and CEBPA. Genes essential in cancer cell lines include BARD1 and IRS2. Genes with both expression and germline SV breakpoint patterns associated with patient survival include GCLM. Our results capture a class of phenotypic variation at work in the disease setting, including genes with cancer roles. Specific germline SVs represent potential cancer risk variants for genetic testing, including those involving genes with targeting implications.

Spatial promoter-enhancer hubs in cancer: organization, regulation, and function

Transcriptional dysregulation is a hallmark of cancer and can be driven by altered enhancer landscapes. Recent studies in genome organization have revealed that multiple enhancers and promoters can spatially coalesce to form dynamic topological assemblies, known as promoter-enhancer hubs, which strongly correlate with elevated gene expression. In this review, we discuss the structure and complexity of promoter-enhancer hubs recently identified in multiple cancer types. We further discuss underlying mechanisms driving dysregulation of promoter-enhancer hubs and speculate on their functional role in pathogenesis. Understanding the role of promoter-enhancer hubs in transcriptional dysregulation can provide insight into new therapeutic approaches to target these complex features of genome organization.

Multi-Omics Mining of lncRNAs with Biological and Clinical Relevance in Cancer

In this review, we provide a general overview of the current panorama of mining strategies for multi-omics data to investigate lncRNAs with an actual or potential role as biological markers in cancer. Several multi-omics studies focusing on lncRNAs have been performed in the past with varying scopes. Nevertheless, many questions remain regarding the pragmatic application of different molecular technologies and bioinformatics algorithms for mining multi-omics data. Here, we attempt to address some of the less discussed aspects of the practical applications using different study designs for incorporating bioinformatics and statistical analyses of multi-omics data. Finally, we discuss the potential improvements and new paradigms aimed at unraveling the role and utility of lncRNAs in cancer and their potential use as molecular markers for cancer diagnosis and outcome prediction.

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.

Chromatin compartmentalization regulates the response to DNA damage

The DNA damage response is essential to safeguard genome integrity. Although the contribution of chromatin in DNA repair has been investigated1,2, the contribution of chromosome folding to these processes remains unclear3. Here we report that, after the production of double-stranded breaks (DSBs) in mammalian cells, ATM drives the formation of a new chromatin compartment (D compartment) through the clustering of damaged topologically associating domains, decorated with γH2AX and 53BP1. This compartment forms by a mechanism that is consistent with polymer-polymer phase separation rather than liquid-liquid phase separation. The D compartment arises mostly in G1 phase, is independent of cohesin and is enhanced after pharmacological inhibition of DNA-dependent protein kinase (DNA-PK) or R-loop accumulation. Importantly, R-loop-enriched DNA-damage-responsive genes physically localize to the D compartment, and this contributes to their optimal activation, providing a function for DSB clustering in the DNA damage response. However, DSB-induced chromosome reorganization comes at the expense of an increased rate of translocations, also observed in cancer genomes. Overall, we characterize how DSB-induced compartmentalization orchestrates the DNA damage response and highlight the critical impact of chromosome architecture in genomic instability.

Global impact of somatic structural variation on the cancer proteome

Both proteome and transcriptome data can help assess the relevance of non-coding somatic mutations in cancer. Here, we combine mass spectrometry-based proteomics data with whole genome sequencing data across 1307 human tumors spanning various tissues to determine the extent somatic structural variant (SV) breakpoint patterns impact protein expression of nearby genes. We find that about 25% of the hundreds of genes with SV-associated cis-regulatory alterations at the mRNA level are similarly associated at the protein level. SVs associated with enhancer hijacking, retrotransposon translocation, altered DNA methylation, or fusion transcripts are implicated in protein over-expression. SVs combined with altered protein levels considerably extend the numbers of patients with tumors somatically altered for critical pathways. We catalog both SV breakpoint patterns involving patient survival and genes with nearby SV breakpoints associated with increased cell dependency in cancer cell lines. Pan-cancer proteogenomics identifies targetable non-coding alterations, by virtue of the associated deregulated genes.

Function and Evolution of the Loop Extrusion Machinery in Animals

Structural maintenance of chromosomes (SMC) complexes are essential proteins found in genomes of all cellular organisms. Essential functions of these proteins, such as mitotic chromosome formation and sister chromatid cohesion, were discovered a long time ago. Recent advances in chromatin biology showed that SMC proteins are involved in many other genomic processes, acting as active motors extruding DNA, which leads to the formation of chromatin loops. Some loops formed by SMC proteins are highly cell type and developmental stage specific, such as SMC-mediated DNA loops required for VDJ recombination in B-cell progenitors, or dosage compensation in Caenorhabditis elegans and X-chromosome inactivation in mice. In this review, we focus on the extrusion-based mechanisms that are common for multiple cell types and species. We will first describe an anatomy of SMC complexes and their accessory proteins. Next, we provide biochemical details of the extrusion process. We follow this by the sections describing the role of SMC complexes in gene regulation, DNA repair, and chromatin topology.

A nine-month-old boy with regression of milestones and severe constipation: an unusual case of a large spinal NTRK1 fusion pilocytic astrocytoma

INTRODUCTION

Pilocytic astrocytoma, a World Health Organization grade 1 tumor, is the most common brain tumor in children between 5 and 14 years of age and the second most common in children younger than 5 and older than 14. Although classical to the cerebellum and hypothalamic regions, it can also arise in the spinal cord. Larotrectinib, a selective inhibitor of tropomyosin receptor kinase, has been effective in pediatric tumors with NTRK fusion mutations in children as young as 1-month-old.

CASE

We share the case of a 9-month-old boy who presented with a 4-month history of regression of his milestones and severe constipation who was found to have a large spinal pilocytic astrocytoma with multiple intracranial periventricular lesions.

Long-read sequencing identifies novel structural variations in colorectal cancer

Structural variations (SVs) are a key type of cancer genomic alterations, contributing to oncogenesis and progression of many cancers, including colorectal cancer (CRC). However, SVs in CRC remain difficult to be reliably detected due to limited SV-detection capacity of the commonly used short-read sequencing. This study investigated the somatic SVs in 21 pairs of CRC samples by Nanopore whole-genome long-read sequencing. 5200 novel somatic SVs from 21 CRC patients (494 SVs / patient) were identified. A 4.9-Mbp long inversion that silences APC expression (confirmed by RNA-seq) and an 11.2-kbp inversion that structurally alters CFTR were identified. Two novel gene fusions that might functionally impact the oncogene RNF38 and the tumor-suppressor SMAD3 were detected. RNF38 fusion possesses metastasis-promoting ability confirmed by in vitro migration and invasion assay, and in vivo metastasis experiments. This work highlighted the various applications of long-read sequencing in cancer genome analysis, and shed new light on how somatic SVs structurally alter critical genes in CRC. The investigation on somatic SVs via nanopore sequencing revealed the potential of this genomic approach in facilitating precise diagnosis and personalized treatment of CRC.

Survival Outcomes of Patients With Tropomyosin Receptor Kinase Fusion-Positive Cancer Receiving Larotrectinib Versus Standard of Care: A Matching-Adjusted Indirect Comparison Using Real-World Data

PURPOSE

Larotrectinib, a highly specific tropomyosin receptor kinase (TRK) inhibitor, previously demonstrated high response rates in single-arm trials of patients with TRK fusion-positive cancer, but there are limited data on comparative effectiveness against standard-of-care (SoC) regimens used in routine health care practice, before widespread adoption of TRK inhibitors as SoC for TRK fusion-positive cancers. Matching-adjusted indirect comparison, a validated methodology that balances population characteristics to facilitate cross-trial comparisons, was used to compare the overall survival (OS) of larotrectinib versus non-TRK-inhibitor SoC.

MATERIALS AND METHODS

Individual patient data from three larotrectinib trials (ClinicalTrials.gov identifiers: NCT02122913, NCT02637687, and NCT02576431) were compared with published aggregate real-world data from patients with locally advanced/metastatic TRK fusion-positive cancer identified in the Flatiron Health/Foundation Medicine database. OS was defined as the time from advanced/metastatic disease diagnosis to death. After matching population characteristics, the analyses included (1) a log-rank test of equality to test whether the two groups were similar before larotrectinib initiation; and (2) estimation of treatment effect of larotrectinib versus non-TRK-inhibitor SoC. These analyses are limited to prognostic variables available in real-world data.

RESULTS

Eighty-five larotrectinib patients and 28 non-TRK-inhibitor SoC patients were included in the analyses. After matching, log-rank testing showed no difference in baseline characteristics between the two groups (P = .31). After matching, larotrectinib was associated with a 78% lower risk of death, compared with non-TRK-inhibitor SoC (adjusted hazard ratio, 0.22 [95% CI, 0.09 to 0.52]; P = .001); median OS was 39.7 months (95% CI: 16.4, NE [not estimable]) for larotrectinib and 10.2 months (95% CI: 7.2, 14.1) for SoC.

CONCLUSION

Matching-adjusted indirect comparison analyses suggest longer OS with larotrectinib, compared with non-TRK-inhibitor SoC, in adult patients with TRK fusion-positive cancer.

Clinical proteomics towards multiomics in cancer

Recent technological advancements in mass spectrometry (MS)-based proteomics technologies have accelerated its application to study greater and greater numbers of human tumor specimens. Over the last several years, the Clinical Proteomic Tumor Analysis Consortium, the International Cancer Proteogenome Consortium, and others have generated MS-based proteomic profiling data combined with corresponding multiomics data on thousands of human tumors to date. Proteomic data sets in the public domain can be re-examined by other researchers with different questions in mind from what the original studies explored. In this review, we examine the increasing role of proteomics in studying cancer, along with the potential for previous studies and their associated data sets to contribute to improving the diagnosis and treatment of cancer in the clinical setting. We also explore publicly available proteomics and multi-omics data from cancer cell line models to show how such data may aid in identifying therapeutic strategies for cancer subsets.

Modeling tissue-specific breakpoint proximity of structural variations from whole-genomes to identify cancer drivers

Structural variations (SVs) in cancer cells often impact large genomic regions with functional consequences. However, identification of SVs under positive selection is a challenging task because little is known about the genomic features related to the background breakpoint distribution in different cancers. We report a method that uses a generalized additive model to investigate the breakpoint proximity curves from 2,382 whole-genomes of 32 cancer types. We find that a multivariate model, which includes linear and nonlinear partial contributions of various tissue-specific features and their interaction terms, can explain up to 57% of the observed deviance of breakpoint proximity. In particular, three-dimensional genomic features such as topologically associating domains (TADs), TAD-boundaries and their interaction with other features show significant contributions. The model is validated by identification of known cancer genes and revealed putative drivers in cancers different than those with previous evidence of positive selection.

Identifying structural variants (SVs) under positive selection in cancer is challenging. Here, the authors develop CSVDriver, a method that computes SV breakpoint proximity and the contribution of elements such as topologically associating domains, and identifies loci that show signs of positive selection and contain known and putative drivers.

Towards accurate and reliable resolution of structural variants for clinical diagnosis

Structural variants (SVs) are a major source of human genetic diversity and have been associated with different diseases and phenotypes. The detection of SVs is difficult, and a diverse range of detection methods and data analysis protocols has been developed. This difficulty and diversity make the detection of SVs for clinical applications challenging and requires a framework to ensure accuracy and reproducibility. Here, we discuss current developments in the diagnosis of SVs and propose a roadmap for the accurate and reproducible detection of SVs that includes case studies provided from the FDA-led SEquencing Quality Control Phase II (SEQC-II) and other consortium efforts.

Pan-Cancer DNA Methylation Analysis and Tumor Origin Identification of Carcinoma of Unknown Primary Site Based on Multi-Omics

The metastatic cancer of unknown primary (CUP) sites remains a leading cause of cancer death with few therapeutic options. The aberrant DNA methylation (DNAm) is the most important risk factor for cancer, which has certain tissue specificity. However, how DNAm alterations in tumors differ among the regulatory network of multi-omics remains largely unexplored. Therefore, there is room for improvement in our accuracy in the prediction of tumor origin sites and a need for better understanding of the underlying mechanisms. In our study, an integrative analysis based on multi-omics data and molecular regulatory network uncovered genome-wide methylation mechanism and identified 23 epi-driver genes. Apart from the promoter region, we also found that the aberrant methylation within the gene body or intergenic region was significantly associated with gene expression. Significant enrichment analysis of the epi-driver genes indicated that these genes were highly related to cellular mechanisms of tumorigenesis, including T-cell differentiation, cell proliferation, and signal transduction. Based on the ensemble algorithm, six CpG sites located in five epi-driver genes were selected to construct a tissue-specific classifier with a better accuracy (>95%) using TCGA datasets. In the independent datasets and the metastatic cancer datasets from GEO, the accuracy of distinguishing tumor subtypes or original sites was more than 90%, showing better robustness and stability. In summary, the integration analysis of large-scale omics data revealed complex regulation of DNAm across various cancer types and identified the epi-driver genes participating in tumorigenesis. Based on the aberrant methylation status located in epi-driver genes, a classifier that provided the highest accuracy in tracing back to the primary sites of metastatic cancer was established. Our study provides a comprehensive and multi-omics view of DNAm-associated changes across cancer types and has potential for clinical application.

Rearrangement-mediated cis-regulatory alterations in advanced patient tumors reveal interactions with therapy

The global impact of somatic structural variants (SVs) on gene regulation in advanced tumors with complex treatment histories has been mostly uncharacterized. Here, using whole-genome and RNA sequencing from 570 recurrent or metastatic tumors, we report the altered expression of hundreds of genes in association with nearby SV breakpoints, including oncogenes and G-protein-coupled receptor-related genes such as PLEKHG2. A significant fraction of genes with SV-expression associations correlate with worse patient survival in primary and advanced cancers, including SRD5A1. In many instances, SV-expression associations involve retrotransposons being translocated near genes. High overall SV burden is associated with treatment with DNA alkylating agents or taxanes and altered expression of metabolism-associated genes. SV-expression associations within tumors from topoisomerase I inhibitor-treated patients include chromatin-related genes. Within anthracycline-treated tumors, SV breakpoints near chromosome 1p genes include PDE4B. Patient treatment and history can help understand the widespread SV-mediated cis-regulatory alterations found in cancer.

QNBC Is Associated with High Genomic Instability Characterized by Copy Number Alterations and miRNA Deregulation

Triple-negative breast cancer (TNBC) can be further classified into androgen receptor (AR)-positive TNBC and AR-negative TNBC or quadruple-negative breast cancer (QNBC). Here, we investigated genomic instability in 53 clinical cases by array-CGH and miRNA expression profiling. Immunohistochemical analysis revealed that 64% of TNBC samples lacked AR expression. This group of tumors exhibited a higher level of copy number alterations (CNAs) and a higher frequency of cases affected by CNAs than TNBCs. CNAs in genes of the chromosome instability 25 (CIN25) and centrosome amplification (CA) signatures were more frequent in the QNBCs and were similar between the groups, respectively. However, expression levels of CIN25 and CA20 genes were higher in QNBCs. miRNA profiling revealed 184 differentially expressed miRNAs between the groups. Fifteen of these miRNAs were mapped at cytobands with CNAs, of which eight (miR-1204, miR-1265, miR-1267, miR-23c, miR-548ai, miR-567, miR-613, and miR-943), and presented concordance of expression and copy number levels. Pathway enrichment analysis of these miRNAs/mRNAs pairings showed association with genomic instability, cell cycle, and DNA damage response. Furthermore, the combined expression of these eight miRNAs robustly discriminated TNBCs from QNBCs (AUC = 0.946). Altogether, our results suggest a significant loss of AR in TNBC and a profound impact in genomic instability characterized by CNAs and deregulation of miRNA expression.

Impact of Disease Evolution on Efficacy Outcomes From Larotrectinib in Patients With Locally Advanced or Metastatic Tropomyosin Receptor Kinase Fusion-Positive Solid Tumors

Neurotrophic tyrosine receptor kinase (NTRK) gene fusions encode oncogenic, chimeric tropomyosin receptor kinase (TRK) proteins. Larotrectinib, an approved TRK inhibitor, is efficacious in locally advanced or metastatic (adv/met) TRK fusion cancer. We evaluated the time from initial diagnosis to locally advanced or metastatic disease and to initiation of larotrectinib treatment as well as larotrectinib impact on disease course.

Patients with NTRK gene fusion do not seem to carry a more favorable prognosis and they benefit durably from Larotrectinib

Pan-cancer analysis of pathway-based gene expression pattern at the individual level reveals biomarkers of clinical prognosis

Identifying biomarkers to predict the clinical outcomes of individual patients is a fundamental problem in clinical oncology. Multiple single-gene biomarkers have already been identified and used in clinics. However, multiple oncogenes or tumor-suppressor genes are involved during the process of tumorigenesis. Additionally, the efficacy of single-gene biomarkers is limited by the extensively variable expression levels measured by high-throughput assays. In this study, we hypothesize that in individual tumor samples, the disruption of transcription homeostasis in key pathways or gene sets plays an important role in tumorigenesis and has profound implications for the patient's clinical outcome. We devised a computational method named iPath to identify, at the individual-sample level, which pathways or gene sets significantly deviate from their norms. We conducted a pan-cancer analysis and demonstrated that iPath is capable of identifying highly predictive biomarkers for clinical outcomes, including overall survival, tumor subtypes, and tumor-stage classifications.

Gene Fusions Create Partner and Collateral Dependencies Essential to Cancer Cell Survival

Gene fusions frequently result from rearrangements in cancer genomes. In many instances, gene fusions play an important role in oncogenesis; in other instances, they are thought to be passenger events. Although regulatory element rearrangements and copy number alterations resulting from these structural variants are known to lead to transcriptional dysregulation across cancers, the extent to which these events result in functional dependencies with an impact on cancer cell survival is variable. Here we used CRISPR-Cas9 dependency screens to evaluate the fitness impact of 3,277 fusions across 645 cell lines from the Cancer Dependency Map. We found that 35% of cell lines harbored either a fusion partner dependency or a collateral dependency on a gene within the same topologically associating domain as a fusion partner. Fusion-associated dependencies revealed numerous novel oncogenic drivers and clinically translatable alterations. Broadly, fusions can result in partner and collateral dependencies that have biological and clinical relevance across cancer types. SIGNIFICANCE: This study provides insights into how fusions contribute to fitness in different cancer contexts beyond partner-gene activation events, identifying partner and collateral dependencies that may have direct implications for clinical care.

Breast Cancer and Anaesthesia: Genetic Influence

Breast cancer is the leading cause of mortality in women. It is a heterogeneous disease with a high degree of inter-subject variability even in patients with the same type of tumor, with individualized medicine having acquired significant relevance in this field. The clinical and morphological heterogeneity of the different types of breast tumors has led to a diversity of staging and classification systems. Thus, these tumors show wide variability in genetic expression and prognostic biomarkers. Surgical treatment is essential in the management of these patients. However, the perioperative period has been found to significantly influence survival and cancer recurrence. There is growing interest in the pro-tumoral effect of different anaesthetic and analgesic agents used intraoperatively and their relationship with metastatic progression. There is cumulative evidence of the influence of anaesthetic techniques on the physiopathological mechanisms of survival and growth of the residual neoplastic cells released during surgery. Prospective randomized clinical trials are needed to obtain quality evidence on the relationship between cancer and anaesthesia. This document summarizes the evidence currently available about the effects of the anaesthetic agents and techniques used in primary cancer surgery and long-term oncologic outcomes, and the biomolecular mechanisms involved in their interaction.

SVExpress: identifying gene features altered recurrently in expression with nearby structural variant breakpoints

Background

Combined whole-genome sequencing (WGS) and RNA sequencing of cancers offer the opportunity to identify genes with altered expression due to genomic rearrangements. Somatic structural variants (SVs), as identified by WGS, can involve altered gene cis-regulation, gene fusions, copy number alterations, or gene disruption. The absence of computational tools to streamline integrative analysis steps may represent a barrier in identifying genes recurrently altered by genomic rearrangement.

Results

Here, we introduce SVExpress, a set of tools for carrying out integrative analysis of SV and gene expression data. SVExpress enables systematic cataloging of genes that consistently show increased or decreased expression in conjunction with the presence of nearby SV breakpoints. SVExpress can evaluate breakpoints in proximity to genes for potential enhancer translocation events or disruption of topologically associated domains, two mechanisms by which SVs may deregulate genes. The output from any commonly used SV calling algorithm may be easily adapted for use with SVExpress. SVExpress can readily analyze genomic datasets involving hundreds of cancer sample profiles. Here, we used SVExpress to analyze SV and expression data across 327 cancer cell lines with combined SV and expression data in the Cancer Cell Line Encyclopedia (CCLE). In the CCLE dataset, hundreds of genes showed altered gene expression in relation to nearby SV breakpoints. Altered genes involved TAD disruption, enhancer hijacking, and gene fusions. When comparing the top set of SV-altered genes from cancer cell lines with the top SV-altered genes previously reported for human tumors from The Cancer Genome Atlas and the Pan-Cancer Analysis of Whole Genomes datasets, a significant number of genes overlapped in the same direction for both cell lines and tumors, while some genes were significant for cell lines but not for human tumors and vice versa.

Conclusion

Our SVExpress tools allow computational biologists with a working knowledge of R to integrate gene expression with SV breakpoint data to identify recurrently altered genes. SVExpress is freely available for academic or commercial use at https://github.com/chadcreighton/SVExpress. SVExpress is implemented as a set of Excel macros and R code. All source code (R and Visual Basic for Applications) is available.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-021-04072-0.

A pediatric brain tumor atlas of genes deregulated by somatic genomic rearrangement

The global impact of somatic structural variants (SSVs) on gene expression in pediatric brain tumors has not been thoroughly characterised. Here, using whole-genome and RNA sequencing from 854 tumors of more than 30 different types from the Children's Brain Tumor Tissue Consortium, we report the altered expression of hundreds of genes in association with the presence of nearby SSV breakpoints. SSV-mediated expression changes involve gene fusions, altered cis-regulation, or gene disruption. SSVs considerably extend the numbers of patients with tumors somatically altered for critical pathways, including receptor tyrosine kinases (KRAS, MET, EGFR, NF1), Rb pathway (CDK4), TERT, MYC family (MYC, MYCN, MYB), and HIPPO (NF2). Compared to initial tumors, progressive or recurrent tumors involve a distinct set of SSV-gene associations. High overall SSV burden associates with TP53 mutations, histone H3.3 gene H3F3C mutations, and the transcription of DNA damage response genes. Compared to adult cancers, pediatric brain tumors would involve a different set of genes with SSV-altered cis-regulation. Our comprehensive and pan-histology genomic analyses reveal SSVs to play a major role in shaping the transcriptome of pediatric brain tumors.

Loss of TGFβ signaling increases alternative end-joining DNA repair that sensitizes to genotoxic therapies across cancer types

Among the pleotropic roles of transforming growth factor-β (TGFβ) signaling in cancer, its impact on genomic stability is least understood. Inhibition of TGFβ signaling increases use of alternative end joining (alt-EJ), an error-prone DNA repair process that typically functions as a "backup" pathway if double-strand break repair by homologous recombination or nonhomologous end joining is compromised. However, the consequences of this functional relationship on therapeutic vulnerability in human cancer remain unknown. Here, we show that TGFβ broadly controls the DNA damage response and suppresses alt-EJ genes that are associated with genomic instability. Mechanistically based TGFβ and alt-EJ gene expression signatures were anticorrelated in glioblastoma, squamous cell lung cancer, and serous ovarian cancer. Consistent with error-prone repair, more of the genome was altered in tumors classified as low TGFβ and high alt-EJ, and the corresponding patients had better outcomes. Pan-cancer analysis of solid neoplasms revealed that alt-EJ genes were coordinately expressed and anticorrelated with TGFβ competency in 16 of 17 cancer types tested. Moreover, regardless of cancer type, tumors classified as low TGFβ and high alt-EJ were characterized by an insertion-deletion mutation signature containing short microhomologies and were more sensitive to genotoxic therapy. Collectively, experimental studies revealed that loss or inhibition of TGFβ signaling compromises the DNA damage response, resulting in ineffective repair by alt-EJ. Translation of this mechanistic relationship into gene expression signatures identified a robust anticorrelation that predicts response to genotoxic therapies, thereby expanding the potential therapeutic scope of TGFβ biology.

Systematic identification of non-coding somatic single nucleotide variants associated with altered transcription and DNA methylation in adult and pediatric cancers

Whole-genome sequencing combined with transcriptomics can reveal impactful non-coding single nucleotide variants (SNVs) in cancer. Here, we developed an integrative analytical approach that, as a first step, identifies genes altered in expression or DNA methylation in association with nearby somatic SNVs, in contrast to alternative approaches that first identify mutational hotspots. Using genomic datasets from the Pan-Cancer Analysis of Whole Genomes (PCAWG) consortium and the Children's Brain Tumor Tissue Consortium (CBTTC), we identified hundreds of genes and associated CpG islands for which the nearby presence of a non-coding somatic SNV recurrently associated with altered expression or DNA methylation, respectively. Genomic regions upstream or downstream of genes, gene introns and gene untranslated regions were all involved. The PCAWG adult cancer cohort yielded different significant SNV-expression associations from the CBTTC pediatric brain tumor cohort. The SNV-expression associations involved a wide range of cancer types and histologies, as well as potential gain or loss of transcription factor binding sites. Notable genes with SNV-associated increased expression include TERT, COPS3, POLE2 and HDAC2—involving multiple cancer types—MYC, BCL2, PIM1 and IGLL5—involving lymphomas—and CYHR1—involving pediatric low-grade gliomas. Non-coding somatic SNVs show a major role in shaping the cancer transcriptome, not limited to mutational hotspots.

PI4KIIIβ is a therapeutic target in chromosome 1q-amplified lung adenocarcinoma

Heightened secretion of protumorigenic effector proteins is a feature of malignant cells. Yet, the molecular underpinnings and therapeutic implications of this feature remain unclear. Here, we identify a chromosome 1q region that is frequently amplified in diverse cancer types and encodes multiple regulators of secretory vesicle biogenesis and trafficking, including the Golgi-dedicated enzyme phosphatidylinositol (PI)-4-kinase IIIβ (PI4KIIIβ). Molecular, biochemical, and cell biological studies show that PI4KIIIβ-derived PI-4-phosphate (PI4P) synthesis enhances secretion and accelerates lung adenocarcinoma progression by activating Golgi phosphoprotein 3 (GOLPH3)-dependent vesicular release from the Golgi. PI4KIIIβ-dependent secreted factors maintain 1q-amplified cancer cell survival and influence prometastatic processes in the tumor microenvironment. Disruption of this functional circuitry in 1q-amplified cancer cells with selective PI4KIIIβ antagonists induces apoptosis and suppresses tumor growth and metastasis. These results support a model in which chromosome 1q amplifications create a dependency on PI4KIIIβ-dependent secretion for cancer cell survival and tumor progression.

svMIL: predicting the pathogenic effect of TAD boundary-disrupting somatic structural variants through multiple instance learning

Motivation

Despite the fact that structural variants (SVs) play an important role in cancer, methods to predict their effect, especially for SVs in non-coding regions, are lacking, leaving them often overlooked in the clinic. Non-coding SVs may disrupt the boundaries of Topologically Associated Domains (TADs), thereby affecting interactions between genes and regulatory elements such as enhancers. However, it is not known when such alterations are pathogenic. Although machine learning techniques are a promising solution to answer this question, representing the large number of interactions that an SV can disrupt in a single feature matrix is not trivial.

Results

We introduce svMIL: a method to predict pathogenic TAD boundary-disrupting SV effects based on multiple instance learning, which circumvents the need for a traditional feature matrix by grouping SVs into bags that can contain any number of disruptions. We demonstrate that svMIL can predict SV pathogenicity, measured through same-sample gene expression aberration, for various cancer types. In addition, our approach reveals that somatic pathogenic SVs alter different regulatory interactions than somatic non-pathogenic SVs and germline SVs.

Availability and implementation

All code for svMIL is publicly available on GitHub: https://github.com/UMCUGenetics/svMIL.

Supplementary information

Supplementary data are available at Bioinformatics online.

Cancer-associated mutations in endometriosis: shedding light on the pathogenesis and pathophysiology

BACKGROUND

Endometriosis is a benign gynaecological disease. Thus, it came as a complete surprise when it was reported recently that the majority of deep endometriosis lesions harbour somatic mutations and a sizeable portion of them contain known cancer-associated mutations (CAMs). Four more studies have since been published, all demonstrating the existence of CAMs in different subtypes of endometriosis. While the field is still evolving, the confirmation of CAMs has raised many questions that were previously overlooked.

OBJECTIVE AND RATIONALE

A comprehensive overview of CAMs in endometriosis has been produced. In addition, with the recently emerged understanding of the natural history of endometriotic lesions as well as CAMs in normal and apparently healthy tissues, this review attempts to address the following questions: Why has there been such a wild discrepancy in reported mutation frequencies? Why does ectopic endometrium have a higher mutation rate than that of eutopic endometrium? Would the presence of CAMs in endometriotic lesions increase the risk of cancer to the bearers? Why do endometriotic epithelial cells have much higher mutation frequencies than their stromal counterpart? What clinical implications, if any, do the CAMs have for the bearers? Do these CAMs tell us anything about the pathogenesis and/or pathophysiology of endometriosis?

SEARCH METHODS

The PubMed database was searched, from its inception to September 2019, for all papers in English using the term 'endometriosis and CAM', 'endometriosis and cancer-driver mutation', 'somatic mutations', 'fibrosis', 'fibrosis and epigenetic', 'CAMs and tumorigenesis', 'somatic mutation and normal tissues', 'oestrogen receptor and fibrosis', 'oxidative stress and fibrosis', 'ARID1A mutation', and 'Kirsten rat sarcoma mutation and therapeutics'. All retrieved papers were read and, when relevant, incorporated into the review results.

OUTCOMES

Seven papers that identified CAMs in endometriosis using various sequencing methods were retrieved, and their results were somewhat different. Yet, it is apparent that those using microdissection techniques and more accurate sequencing methods found more CAMs, echoing recent discoveries that apparently healthy tissues also harbour CAMs as a result of the replicative aging process. Hence endometriotic lesions, irrespective of subtype, if left intact, would generate CAMs as part of replicative aging, oxidative stress and perhaps other factors yet to be identified and, in some rare cases, develop cancer. The published data still are unable to paint a clear picture on pathogenesis of endometriosis. However, since endometriotic epithelial cells have a higher turnover than their stromal counterpart due to cyclic bleeding, and since the endometriotic stromal component can be formed by refresh influx of mesenchymal cells through epithelial-mesenchymal transition, endothelial-mesenchymal transition, mesothelial-mesenchymal transition and other processes as well as recruitment of bone-marrow-derived stem cells and outflow due to smooth muscle metaplasia, endometriotic epithelial cells have much higher mutation frequencies than their stromal counterpart. The epithelial and stromal cellular components develop in a dependent and co-evolving manner. Genes involved in CAMs are likely to be active players in lesional fibrogenesis, and hyperestrogenism and oxidative stress are likely drivers of both CAMs and fibrogenesis. Finally, endometriotic lesions harbouring CAMs would conceivably be more refractory to medical treatment, due, in no small part, to their high fibrotic content and reduced vascularity and cellularity.

WIDER IMPLICATIONS

The accumulating data on CAMs in endometriosis have shed new light on the pathogenesis and pathophysiology of endometriosis. They also suggest new challenges in management. The distinct yet co-evolving developmental trajectories of endometriotic stroma and epithelium underscore the importance of the lesional microenvironment and ever-changing cellular identity. Mutational profiling of normal endometrium from women of different ages and reproductive history is needed in order to gain a deeper understanding of the pathogenesis. Moreover, one area that has conspicuously received scant attention is the epigenetic landscape of ectopic, eutopic and normal endometrium.

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.

SV-HotSpot: detection and visualization of hotspots targeted by structural variants associated with gene expression

Whole genome sequencing (WGS) has enabled the discovery of genomic structural variants (SVs), including those targeting intergenic and intronic non-coding regions that eluded previous exome focused strategies. However, the field currently lacks an automated tool that analyzes SV candidates to identify recurrent SVs and their targeted sites (hotspot regions), visualizes these genomic events within the context of various functional elements, and evaluates their potential effect on gene expression. To address this, we developed SV-HotSpot, an automated tool that integrates SV candidates, copy number alterations, gene expression, and genome annotations (e.g. gene and regulatory elements) to discover, annotate, and visualize recurrent SVs and their targeted hotspot regions that may affect gene expression. We applied SV-HotSpot to WGS and matched transcriptome data from metastatic castration resistant prostate cancer patients and rediscovered recurrent SVs targeting coding and non-coding functional elements known to promote prostate cancer progression and metastasis. SV-HotSpot provides a valuable resource to integrate SVs, gene expression, and genome annotations for discovering biologically relevant SVs altering coding and non-coding genome. SV-HotSpot is available at https://github.com/ChrisMaherLab/SV-HotSpot .

Integrating proteomics into precision oncology

DNA sequencing and RNA sequencing are increasingly applied in precision oncology, where molecular tumor boards evaluate the actionability of genetic events in individual tumors to guide targeted treatment. To work toward an additional level of patient characterization, we assessed the abundance and activity of 27 proteins in 134 patients whose tumors had previously undergone whole-exome and RNA sequencing within the Molecularly Aided Stratification for Tumor Eradication Research (MASTER) program of National Center for Tumor Diseases, Heidelberg. Proteomic and phosphoproteomic targets were selected to reflect the most relevant therapeutic baskets in MASTER. Among six different therapeutic baskets, the proteomic data supported treatment recommendations that were based on DNA and RNA analyses in 10% to 57% and frequently suggested alternative treatment options. In several cases, protein activities explained the patients' clinical course and provided potential explanations for treatment failure. Our study indicates that the integrative analysis of DNA, RNA and protein data may refine therapeutic stratification of individual patients and, thus, holds potential to increase the success rate of precision cancer therapy. Prospective validation studies are needed to advance the integration of proteomic analysis into precision oncology.

A Practical Guide for Structural Variation Detection in the Human Genome

Profiling genetic variants-including single nucleotide variants, small insertions and deletions, copy number variations, and structural variations (SVs)-from both healthy individuals and individuals with disease is a key component of genetic and biomedical research. SVs are large-scale changes in the genome and involve breakage and rejoining of DNA fragments. They may affect thousands to millions of nucleotides and can lead to loss, gain, and reshuffling of genes and regulatory elements. SVs are known to impact gene expression and potentially result in altered phenotypes and diseases. Therefore, identifying SVs from the human genomes is particularly important. In this review, I describe advantages and disadvantages of the available high-throughput assays for the discovery of SVs, which are the most challenging genetic alterations to detect. A practical guide is offered to suggest the most suitable strategies for discovering different types of SVs including common germline, rare, somatic, and complex variants. I also discuss factors to be considered, such as cost and performance, for different strategies when designing experiments. Last, I present several approaches to identify potential SV artifacts caused by samples, experimental procedures, and computational analysis. © 2020 Wiley Periodicals LLC.

DNA mismatch repair promotes APOBEC3-mediated diffuse hypermutation in human cancers

Certain mutagens, including the APOBEC3 (A3) cytosine deaminase enzymes, can create multiple genetic changes in a single event. Activity of A3s results in striking 'mutation showers' occurring near DNA breakpoints; however, less is known about the mechanisms underlying the majority of A3 mutations. We classified the diverse patterns of clustered mutagenesis in tumor genomes, which identified a new A3 pattern: nonrecurrent, diffuse hypermutation (omikli). This mechanism occurs independently of the known focal hypermutation (kataegis), and is associated with activity of the DNA mismatch-repair pathway, which can provide the single-stranded DNA substrate needed by A3, and contributes to a substantial proportion of A3 mutations genome wide. Because mismatch repair is directed towards early-replicating, gene-rich chromosomal domains, A3 mutagenesis has a high propensity to generate impactful mutations, which exceeds that of other common carcinogens such as tobacco smoke and ultraviolet exposure. Cells direct their DNA repair capacity towards more important genomic regions; thus, carcinogens that subvert DNA repair can be remarkably potent.

Anaesthesia and cancer: can anaesthetic drugs modify gene expression?

Cancer remains a primary cause of morbidity and mortality worldwide, and its incidence continues to increase. The most common cause of death in cancer patients is tumour recurrence. Surgery is the gold standard in the treatment of most tumours. However, cancer surgery can lead to the release of tumour cells into the systemic circulation. Surgical stress and several perioperative factors have been suggested to boost tumour growth, thereby increasing the risk of metastatic recurrence.

Preclinical and clinical studies suggest that anaesthetics and adjuvants administered during the perioperative period may impact cancer recurrence and survival. This document summarises the current evidence regarding the effects of anaesthetic drugs and analgesic techniques on the immune system, systemic inflammatory response and tumour cells, as well as their impact on cancer recurrence.

Epigenomic technologies for precision oncology

Epigenetic patterns in a cell control the expression of genes and consequently determine the phenotype of a cell. Cancer cells possess altered epigenomes which include aberrant patterns of DNA methylation, histone tail modifications, nucleosome positioning and of the three-dimensional chromatin organization within a nucleus. These altered epigenetic patterns are potential useful biomarkers to detect cancer cells and to classify tumor types. In addition, the cancer epigenome dictates the response of a cancer cell to therapeutic intervention and, therefore its knowledge, will allow to predict response to different therapeutic approaches. Here we review the current state-of-the-art technologies that have been developed to decipher epigenetic patterns on the genomic level and discuss how these methods are potentially useful for precision oncology.

Dysregulation of cancer genes by recurrent intergenic fusions

Background

Gene fusions have been studied extensively, as frequent drivers of tumorigenesis as well as potential therapeutic targets. In many well-known cases, breakpoints occur at two intragenic positions, leading to in-frame gene-gene fusions that generate chimeric mRNAs. However, fusions often occur with intergenic breakpoints, and the role of such fusions has not been carefully examined.

Results

We analyze whole-genome sequencing data from 268 patients to catalog gene-intergenic and intergenic-intergenic fusions and characterize their impact. First, we discover that, in contrast to the common assumption, chimeric oncogenic transcripts—such as those involving ETV4, ERG, RSPO3, and PIK3CA—can be generated by gene-intergenic fusions through splicing of the intervening region. Second, we find that over-expression of an upstream or downstream gene by a fusion-mediated repositioning of a regulatory sequence is much more common than previously suspected, with enhancers sometimes located megabases away. We detect a number of recurrent fusions, such as those involving ANO3, RGS9, FUT5, CHI3L1, OR1D4, and LIPG in breast; IGF2 in colon; ETV1 in prostate; and IGF2BP3 and SIX2 in thyroid cancers.

Conclusion

Our findings elucidate the potential oncogenic function of intergenic fusions and highlight the wide-ranging consequences of structural rearrangements in cancer genomes.

Technologies to study spatial genome organization: beyond 3C

The way that chromatin is organized in three-dimensional nuclear space is now acknowledged as a factor critical for the major cell processes, like transcription, replication and cell division. Researchers have been armed with new molecular and imaging technologies to study this structure-to-function link of genomes, spearheaded by the introduction of the 'chromosome conformation capture' technology more than a decade ago. However, this technology is not without shortcomings, and novel variants and orthogonal approaches are being developed to overcome these. As a result, the field of nuclear organization is constantly fueled by methods of increasing resolution and/or throughput that strive to eliminate systematic biases and increase precision. In this review, we attempt to highlight the most recent advances in technology that promise to provide novel insights on how chromosomes fold and function.

CDK12 and PAK2 as novel therapeutic targets for human gastric cancer

Background: Gastric cancer remains the second leading cause of cancer-related death, and the third in mortality due to lack of effective therapeutic targets for late stage cancer patients. This study aims to identify potential druggable target biomarkers as potential therapeutic options for patients with gastric cancer.

Methods: Immunohistochemistry of human gastric tumor tissues was conducted to determine the expression level of cyclin-dependent kinase 12 (CDK12). Multiple in vitro and in vivo assays such as RNAi, mass spectrometry, computer docking models, kinase assays, cell xenograft NU/NU mouse models (CDXs) and patient-derived xenograft NOD/SCID mouse models (PDXs) were conducted to study the function and molecular interaction of CDK12 with p21 activated kinase 2 (PAK2), as well as to find CDK12 inhibitors as potential treatment options for human gastric cancer.

Results: Here we identified that CDK12 is a driver gene in human gastric cancer growth. Mechanistically, CDK12 directly binds to and phosphorylates PAK2 at T134/T169 to activate MAPK signaling pathway. We further identified FDA approved clinical drug procaterol can serve as an effective CDK12 inhibitor, leading to dramatic restriction of cancer cell proliferation and tumor growth in human gastric cancer cells and PDXs.

Conclusions: Our data highlight the potential of CDK12/PAK2 as therapeutic targets for patients with gastric cancer, and we propose procaterol treatment as a novel therapeutic strategy for human gastric cancer.

Detection of somatic structural variants from short-read next-generation sequencing data

Somatic structural variants (SVs), which are variants that typically impact >50 nucleotides, play a significant role in cancer development and evolution but are notoriously more difficult to detect than small variants from short-read next-generation sequencing (NGS) data. This is due to a combination of challenges attributed to the purity of tumour samples, tumour heterogeneity, limitations of short-read information from NGS and sequence alignment ambiguities. In spite of active development of SV detection tools (callers) over the past few years, each method has inherent advantages and limitations. In this review, we highlight some of the important factors affecting somatic SV detection and compared the performance of seven commonly used SV callers. In particular, we focus on the extent of change in sensitivity and precision for detecting different SV types and size ranges from samples with differing variant allele frequencies and sequencing depths of coverage. We highlight the reasons for why some SV callers perform well in some settings but not others, allowing our evaluation findings to be extended beyond the seven SV callers examined in this paper. As the importance of large SVs become increasingly recognized in cancer genomics, this paper provides a timely review on some of the most impactful factors influencing somatic SV detection that should be considered when choosing SV callers.

The mutational landscape of normal human endometrial epithelium

All normal somatic cells are thought to acquire mutations, but understanding of the rates, patterns, causes and consequences of somatic mutations in normal cells is limited. The uterine endometrium adopts multiple physiological states over a lifetime and is lined by a gland-forming epithelium1,2. Here, using whole-genome sequencing, we show that normal human endometrial glands are clonal cell populations with total mutation burdens that increase at about 29 base substitutions per year and that are many-fold lower than those of endometrial cancers. Normal endometrial glands frequently carry 'driver' mutations in cancer genes, the burden of which increases with age and decreases with parity. Cell clones with drivers often originate during the first decades of life and subsequently progressively colonize the epithelial lining of the endometrium. Our results show that mutational landscapes differ markedly between normal tissues-perhaps shaped by differences in their structure and physiology-and indicate that the procession of neoplastic change that leads to endometrial cancer is initiated early in life.

Immuno-Oncology Biomarkers for Personalized Immunotherapy in Breast Cancer

The immune checkpoint blockade therapy has drastically advanced treatment of different types of cancer over the past few years. Female breast cancer is the second leading cause of death in the overall burden of cancers worldwide that is encouraging healthcare professionals to improve cancer care management. The checkpoint blockade therapies combined with novel agents become the recent focus of various clinical trials in breast cancer. However, identification of the patients who are responsive to these therapeutic strategies remained as a major issue for enhancing the efficacy of these treatments. This highlights the unmet need in discovery and development of novel biomarkers to add predictive values for prosperous personalized medicine. In this review we summarize the advances done in the era of biomarker studies and highlight their link in supporting breast cancer immunotherapy.

Genome rearrangements associated with aberrant telomere maintenance

There is unequivocal evidence that telomeres are crucial for cellular homeostasis and that telomere dysfunction can elicit genome instability and potentially initiate events that culminate in cancer. Mounting evidence points to telomeres having a crucial role in driving local and systemic structural rearrangements that drive cancer. These include the classical 'breakage-fusion-bridge' (BFB) cycles and more recently identified genome re-shaping events like kataegis and chromothripsis. In this brief review, we outline the established and most recent advances describing the roles that telomere dysfunction has in the origin of these catastrophic genome rearrangements. We discuss how local and systemic structural rearrangements enable telomere length maintenance, by either telomerase or the alternative lengthening of telomeres, that is essential to sustain cancer cell proliferation.

Larotrectinib in patients with TRK fusion-positive solid tumours: a pooled analysis of three phase 1/2 clinical trials

BACKGROUND

The selective TRK inhibitor larotrectinib was approved for paediatric and adult patients with advanced TRK fusion-positive solid tumours based on a primary analysis set of 55 patients. The aim of our analysis was to explore the efficacy and long-term safety of larotrectinib in a larger population of patients with TRK fusion-positive solid tumours.

METHODS

Patients were enrolled and treated in a phase 1 adult, a phase 1/2 paediatric, or a phase 2 adolescent and adult trial. Some eligibility criteria differed between these studies. For this pooled analysis, eligible patients were aged 1 month or older, with a locally advanced or metastatic non-CNS primary, TRK fusion-positive solid tumour, who had received standard therapy previously if available. This analysis set includes the 55 patients on which approval of larotrectinib was based. Larotrectinib was administered orally (capsule or liquid formulation), on a continuous 28-day schedule, to adults mostly at a dose of 100 mg twice daily, and to paediatric patients mostly at a dose of 100 mg/m² (maximum of 100 mg) twice daily. The primary endpoint was objective response as assessed by local investigators in an intention-to-treat analysis. Contributing trials are registered with ClinicalTrials.gov, NCT02122913 (active not recruiting), NCT02637687 (recruiting), and NCT02576431 (recruiting).

FINDINGS

Between May 1, 2014, and Feb 19, 2019, 159 patients with TRK fusion-positive cancer were enrolled and treated with larotrectinib. Ages ranged from less than 1 month to 84 years. The proportion of patients with an objective response according to investigator assessment was 121 (79%, 95% CI 72-85) of 153 evaluable patients, with 24 (16%) having complete responses. In a safety population of 260 patients treated regardless of TRK fusion status, the most common grade 3 or 4 larotrectinib-related adverse events were increased alanine aminotransferase (eight [3%] of 260 patients), anaemia (six, 2%), and decreased neutrophil count (five [2%]). The most common larotrectinib-related serious adverse events were increased alanine aminotransferase (two [<1%] of 260 patients), increased aspartate aminotransferase (two [<1%]), and nausea (two [<1%]). No treatment-related deaths occurred.

INTERPRETATION

These data confirm that TRK fusions define a unique molecular subgroup of advanced solid tumours for which larotrectinib is highly active. Safety data indicate that long-term administration of larotrectinib is feasible.

FUNDING

Bayer and Loxo Oncology.

High-coverage whole-genome analysis of 1220 cancers reveals hundreds of genes deregulated by rearrangement-mediated cis-regulatory alterations

The impact of somatic structural variants (SVs) on gene expression in cancer is largely unknown. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole-genome sequencing data and RNA sequencing from a common set of 1220 cancer cases, we report hundreds of genes for which the presence within 100 kb of an SV breakpoint associates with altered expression. For the majority of these genes, expression increases rather than decreases with corresponding breakpoint events. Up-regulated cancer-associated genes impacted by this phenomenon include TERT, MDM2, CDK4, ERBB2, CD274, PDCD1LG2, and IGF2. TERT-associated breakpoints involve ~3% of cases, most frequently in liver biliary, melanoma, sarcoma, stomach, and kidney cancers. SVs associated with up-regulation of PD1 and PDL1 genes involve ~1% of non-amplified cases. For many genes, SVs are significantly associated with increased numbers or greater proximity of enhancer regulatory elements near the gene. DNA methylation near the promoter is often increased with nearby SV breakpoint, which may involve inactivation of repressor elements.

Tumor suppressor genes and allele-specific expression: mechanisms and significance

Recent findings indicate that allele-specific expression (ASE) at specific cancer driver gene loci may be of importance in onset/progression of the disease. Of particular interest are loss-of-function (LOF) of tumor suppressor gene (TSGs) alleles. While LOF tumor suppressor mutations are typically considered to be recessive, if these mutant alleles can be significantly differentially expressed relative to wild-type alleles in heterozygotes, the clinical consequences could be significant. LOF TSG alleles are shown to be segregating at high frequencies in world-wide populations of normal/healthy individuals. Matched sets of normal and tumor tissues isolated from 233 cancer patients representing four diverse tumor types demonstrate functionally important changes in patterns of ASE in individuals heterozygous for LOF TSG alleles associated with cancer onset/progression. While a variety of molecular mechanisms were identified as potentially contributing to changes in ASE patterns in cancer, changes in DNA copy number and allele-specific alternative splicing possibly mediated by antisense RNA emerged as predominant factors. In conclusion, LOF TSGs are segregating in human populations at significant frequencies indicating that many otherwise healthy individuals are at elevated risk of developing cancer. Changes in ASE between normal and cancer tissues indicates that LOF TSG alleles may contribute to cancer onset/progression even when heterozygous with wild-type functional alleles.

Somatic gene mutation signatures predict cancer type and prognosis in multiple cancers with pan-cancer 1000 gene panel

Most cancers are caused by somatic mutations. Some common mutations in the same cancer type can form a "signature" to specifically predict the prognosis or to distinguish it from other cancers. In this study, 710 somatic cell mutations were identified in 142 cases, including digestive, lung and urogenital cancers, and the digestive cancers were further divided into liver, stomach, intestinal, esophageal and cardia cancer. The above mutations were located in 166 genes. In addition, a group of high-frequency mutation genes with specific characteristics were screened to form predictive signatures for each cancer. Verification using TCGA suggested that the signatures could predict the stages, progression-free survival, and overall survival of digestive, intestinal, and liver cancers (P < 0.05). The validation cases further confirmed the predictive role of digestive and liver cancers signatures in diagnosis and prognosis. Overall, this study established predictive signatures for different cancer systems and their subtypes. These findings enable a better understanding in cancer genome, and contribute to the personalized diagnosis and treatment.

Telomere Maintenance in Pediatric Cancer

Telomere length has been proposed as a biomarker of biological age and a risk factor for age-related diseases and cancer. Substantial progress has been made in recent decades in understanding the complex molecular relationships in this research field. However, the majority of telomere studies have been conducted in adults. The data on telomere dynamics in pediatric cancers is limited, and interpretation can be challenging, especially in cases where results are contrasting to those in adult entities. This review describes recent advances in the molecular characterization of structure and function of telomeres, regulation of telomerase activity in cancer pathogenesis in general, and highlights the key advances that have expanded our views on telomere biology in pediatric cancer, with special emphasis on the central role of telomere maintenance in neuroblastoma. Furthermore, open questions in the field of telomere maintenance research are discussed in the context of recently published literature.

Global impact of somatic structural variation on the DNA methylome of human cancers

Background

Genomic rearrangements exert a heavy influence on the molecular landscape of cancer. New analytical approaches integrating somatic structural variants (SSVs) with altered gene features represent a framework by which we can assign global significance to a core set of genes, analogous to established methods that identify genes non-randomly targeted by somatic mutation or copy number alteration. While recent studies have defined broad patterns of association involving gene transcription and nearby SSV breakpoints, global alterations in DNA methylation in the context of SSVs remain largely unexplored.

Results

By data integration of whole genome sequencing, RNA sequencing, and DNA methylation arrays from more than 1400 human cancers, we identify hundreds of genes and associated CpG islands (CGIs) for which the nearby presence of a somatic structural variant (SSV) breakpoint is recurrently associated with altered expression or DNA methylation, respectively, independently of copy number alterations. CGIs with SSV-associated increased methylation are predominantly promoter-associated, while CGIs with SSV-associated decreased methylation are enriched for gene body CGIs. Rearrangement of genomic regions normally having higher or lower methylation is often involved in SSV-associated CGI methylation alterations. Across cancers, the overall structural variation burden is associated with a global decrease in methylation, increased expression in methyltransferase genes and DNA damage response genes, and decreased immune cell infiltration.

Conclusion

Genomic rearrangement appears to have a major role in shaping the cancer DNA methylome, to be considered alongside commonly accepted mechanisms including histone modifications and disruption of DNA methyltransferases.