Pan-cancer analysis of whole genomes

CVCDAP: an integrated platform for molecular and clinical analysis of cancer virtual cohorts

Recent large-scale multi-omics studies resulted in quick accumulation of an overwhelming amount of cancer-related data, which provides an unprecedented resource to interrogate diverse questions. While certain existing web servers are valuable and widely used, analysis and visualization functions with regard to re-investigation of these data at cohort level are not adequately addressed. Here, we present CVCDAP, a web-based platform to deliver an interactive and customizable toolbox off the shelf for cohort-level analysis of TCGA and CPTAC public datasets, as well as user uploaded datasets. CVCDAP allows flexible selection of patients sharing common molecular and/or clinical characteristics across multiple studies as a virtual cohort, and provides dozens of built-in customizable tools for seamless genomic, transcriptomic, proteomic and clinical analysis of a single virtual cohort, as well as, to compare two virtual cohorts with relevance. The flexibility and analytic competence of CVCDAP empower experimental and clinical researchers to identify new molecular mechanisms and develop potential therapeutic approaches, by building and analyzing virtual cohorts for their subject of interests. We demonstrate that CVCDAP can conveniently reproduce published findings and reveal novel insights by two applications. The CVCDAP web server is freely available at https://omics.bjcancer.org/cvcdap/.

Pervasive lesion segregation shapes cancer genome evolution

Cancers arise through the acquisition of oncogenic mutations and grow by clonal expansion1,2. Here we reveal that most mutagenic DNA lesions are not resolved into a mutated DNA base pair within a single cell cycle. Instead, DNA lesions segregate, unrepaired, into daughter cells for multiple cell generations, resulting in the chromosome-scale phasing of subsequent mutations. We characterize this process in mutagen-induced mouse liver tumours and show that DNA replication across persisting lesions can produce multiple alternative alleles in successive cell divisions, thereby generating both multiallelic and combinatorial genetic diversity. The phasing of lesions enables accurate measurement of strand-biased repair processes, quantification of oncogenic selection and fine mapping of sister-chromatid-exchange events. Finally, we demonstrate that lesion segregation is a unifying property of exogenous mutagens, including UV light and chemotherapy agents in human cells and tumours, which has profound implications for the evolution and adaptation of cancer genomes.

Navigating the path to distant metastasis

How ‘difficult’ is it for somatic evolution to produce a cell that is capable of leaving the primary tumor and growing in a distant organ? In this issue, Reiter et al. assess genetic diversity across metastatic lesions and identify a tight selective bottleneck preceding distant metastasis.

Mutational signature learning with supervised negative binomial non-negative matrix factorization

MOTIVATION

Understanding the underlying mutational processes of cancer patients has been a long-standing goal in the community and promises to provide new insights that could improve cancer diagnoses and treatments. Mutational signatures are summaries of the mutational processes, and improving the derivation of mutational signatures can yield new discoveries previously obscured by technical and biological confounders. Results from existing mutational signature extraction methods depend on the size of available patient cohort and solely focus on the analysis of mutation count data without considering the exploitation of metadata.

RESULTS

Here we present a supervised method that utilizes cancer type as metadata to extract more distinctive signatures. More specifically, we use a negative binomial non-negative matrix factorization and add a support vector machine loss. We show that mutational signatures extracted by our proposed method have a lower reconstruction error and are designed to be more predictive of cancer type than those generated by unsupervised methods. This design reduces the need for elaborate post-processing strategies in order to recover most of the known signatures unlike the existing unsupervised signature extraction methods. Signatures extracted by a supervised model used in conjunction with cancer-type labels are also more robust, especially when using small and potentially cancer-type limited patient cohorts. Finally, we adapted our model such that molecular features can be utilized to derive an according mutational signature. We used APOBEC expression and MUTYH mutation status to demonstrate the possibilities that arise from this ability. We conclude that our method, which exploits available metadata, improves the quality of mutational signatures as well as helps derive more interpretable representations.

AVAILABILITY AND IMPLEMENTATION

https://github.com/ratschlab/SNBNMF-mutsig-public.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Hypermutation in single-stranded DNA

Regions of genomic DNA can become single-stranded in the course of normal replication and transcription as well as during DNA repair. Abnormal repair and replication intermediates can contain large stretches of persistent single-stranded DNA, which is extremely vulnerable to DNA damaging agents and hypermutation. Since such single-stranded DNA spans only a fraction of the genome at a given instance, hypermutation in these regions leads to tightly-spaced mutation clusters. This phenomenon of hypermutation in single-stranded DNA has been documented in several experimental models as well as in cancer genomes. Recently, hypermutated single-stranded RNA viral genomes also have been documented. Moreover, indications of hypermutation in single-stranded DNA may also be found in the human germline. This review will summarize key current knowledge and the recent developments in understanding the diverse mechanisms and sources of ssDNA hypermutation.

Rethinking carcinogenesis: The detached pericyte hypothesis

The limiting step in cancer prevention is a lack of understanding of cancer biology. This limitation is exacerbated by a focus on the dominant somatic mutation theory (that driver mutations cause cancer) with little consideration of alternative theories of carcinogenesis. The recently proposed detached pericyte hypothesis explains many puzzling phenomena in cancer biology for which the somatic mutation theory offers no obvious explanation. These puzzling phenomena include foreign-body tumorigenesis, the link between denervation and cancer, tumors in transgenic mice that lack the inducing mutation, and non-genotoxic carcinogens. The detached pericyte hypothesis postulates that (1) a carcinogen or chronic inflammation causes pericytes to detach from blood cell walls, (2) some detached pericytes develop into myofibroblasts which alter the extracellular matrix (3) some detached pericytes develop into mesenchymal stem cells, (4) some of the mesenchymal stem cells adhere to the altered extracellular matrix (5) the altered extracellular matrix disrupts regulatory controls, causing the adjacent mesenchymal stem cells to develop into tumors. Results from experimental studies support the detached pericyte hypothesis. If the detached pericyte hypothesis is correct, pericytes should play a key role in metastasis - a testable prediction. Recent experimental results confirm this prediction and motivate a proposed experiment to partially test the detached pericyte hypothesis. If the detached pericyte hypothesis is correct, it could lead to new strategies for cancer prevention.

What will radiation oncology look like in 2050? A look at a changing professional landscape in Europe and beyond

The number of newly diagnosed cancers per year is predicted to almost double in the next two decades worldwide, and it remains unclear if and when this alarming trend will level off or even reverse. As such, cancer is very likely to continue to pose a major threat to human health. Radiation oncology is an indispensable pillar of cancer treatment and a well‐developed discipline. Nevertheless, key trends in cancer research and care, including improved primary prevention, early detection, integrated multidisciplinary approaches, personalized strategies at all levels of care, value‐based assessments of healthcare systems, and global health perspectives, will all shape the future of radiation oncology. Broader scientific advances, such as rapid progress in digitization, automation, and in our biological understanding of cancer, as well as the wider societal view of healthcare systems will also influence radiation oncology and how it is practiced. To stimulate a proactive discussion on how to adapt and reshape our discipline, this review provides some predictions on what the role and practice of radiation oncology might look like in 30 years’ time.

Targeted Therapy in Melanoma and Mechanisms of Resistance

The common mutation BRAFV600 in primary melanomas activates the mitogen-activated protein kinase/extracellular-signal-regulated kinase (MAPK/ERK) pathway and the introduction of proto-oncogene B-Raf (BRAF) and mitogen-activated protein kinase kinase (MEK) inhibitors (BRAFi and MEKi) was a breakthrough in the treatment of these cancers. However, 15–20% of tumors harbor primary resistance to this therapy, and moreover, patients develop acquired resistance to treatment. Understanding the molecular phenomena behind resistance to BRAFi/MEKis is indispensable in order to develop novel targeted therapies. Most often, resistance develops due to either the reactivation of the MAPK/ERK pathway or the activation of alternative kinase signaling pathways including phosphatase and tensin homolog (PTEN), neurofibromin 1 (NF-1) or RAS signaling. The hyperactivation of tyrosine kinase receptors, such as the receptor of the platelet-derived growth factor β (PDFRβ), insulin-like growth factor 1 receptor (IGF-1R) and the receptor for hepatocyte growth factor (HGF), lead to the induction of the AKT/3-phosphoinositol kinase (PI3K) pathway. Another pathway resulting in BRAFi/MEKi resistance is the hyperactivation of epidermal growth factor receptor (EGFR) signaling or the deregulation of microphthalmia-associated transcription factor (MITF).

Visualizing Human Colorectal Cancer Intratumor Heterogeneity with Phylogeography

Phylogeography combines ancestry with location and can be translated to intratumor heterogeneity (ITH) to visualize how tumors spread. ITH is common in human tumors, with many genetic and phenotypic differences between regions. The roles of ITH in progression are uncertain because many subclones lack discernable driver mutations. ITH can be visualized by mapping mutations onto microscopic sections, where subclones are directly associated with phenotypes, especially the deeper areas with the more invasive cells that confer worst clinical outcomes. Instead of a stepwise hierarchy where subclones segregate by phenotype with later branching subclones in more invasive areas, multiple subclones share superficial and invasive phenotype and are jigsaw arrayed in vertical columns. Phylogeography shows that both early and late subclones extend from the surface to the invasive front, suggesting that founder cells start with phenotypic plasticity and essentially all the drivers necessary to rapidly grow into large invasive tumors.

"Right-to-Try" experimental drugs: an overview

The “Right-to-Try” experimental drugs act passed by Donald Trump in 2018 provides an opportunity of early access to experimental drugs for the treatment of life-threatening diseases and a potential boon to many young and under-capitalized biotechnology or pharmaceutical companies. The pros and cons of experimental drugs, including a number of “cutting edge” scientific, clinical, and a number of synergistic approaches such as artificial intelligence, machine learning, big data, data refineries, electronic health records, data driven clinical decisions and risk mitigation are reviewed.

Systematic identification, development, and validation of prognostic biomarkers involving the tumor-immune microenvironment for glioblastoma

Gliomas are infiltrative neoplasms with a highly invasive nature. Due to its distinct genomic, genetic and epigenetic features, the immune prognostic signature (IPS) and immune microenvironment of glioblastoma (GBM) merit further research. We aimed to explore prognosis-related immune genes and develop an IPS model for predicting prognosis in GBM. RNA-sequencing data, as well as clinical information, from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) public cohorts were analyzed. To develop the IPS, least absolute shrinkage and selection operator (LASSO) Cox analysis was performed for immune-related genes that were differentially expressed between GBM and normal tissues. Then, interaction effects of the IPS on the immune microenvironment were systematically analyzed; the precise prognostic model was developed based on the IPS and clinical data and was then further validated. A total of 21 immune prognostic genes were identified based on GBM microenvironment status. An 8-gene IPS was established, and the GBM patients were effectively stratified into low- and high-risk groups in the TCGA cohort as a training set. Univariate and multivariate Cox analyses revealed that IPS was an independent prognostic factor, and the prognostic performance of individual IPS genes was systematically illustrated. In addition, a comprehensive and novel nomogram model was initially established to estimate overall survival in TCGA-GBM patients, and high-risk patients had higher levels of dendritic cell and neutrophil infiltration. Furthermore, the nomogram model was developed and validated in the CGGA validation set. The low-risk IPS was linked to a stronger response to anti-PD-L1 immunotherapy and clinical advantages in the IMvigor210 cohort. This novel IPS with promising biomarkers classifies GBM patients into subgroups with distinct clinical outcomes and immunophenotypes. Our findings and this resource may help to characterize the immune microenvironment, inform cancer immunotherapy and facilitate the development of precision immuno-oncology.

Hot Spot TERT Promoter Mutations Are Rare in Sporadic Pancreatic Neuroendocrine Neoplasms and Associated with Telomere Length and Epigenetic Expression Patterns

Cancer cells activate a telomere maintenance mechanism like telomerase in order to proliferate indefinitely. Telomerase can be reactivated by gain-of-function Telomerase Reverse Transcriptase (TERT) promoter mutations (TPMs) that occur in several cancer subtypes with high incidence and association with diagnosis, prognosis and epigenetics. However, such information about TPMs in sporadic pancreatic neuroendocrine neoplasms (pNENs) including tumor (pNET) and carcinoma (pNEC) is less well defined. We have studied two hot spot TPMs and telomere length (TL) in pNEN and compared the results with clinicopathological information and proliferation-associated miRNA/HDAC expression profiles. DNA was isolated from formalin-fixed paraffin-embedded (FFPE) tissue of 58 sporadic pNEN patients. T allele frequency of C250T and C228T TPM was analyzed by pyrosequencing, relative TL as telomeric content by qPCR. In total, five pNEN cases (9%) including four pNETs and one pNEC were identified with TPMs, four cases with exclusive C250T as predominant TPM and one case with both C250T and C228T. T allele frequencies of DNA isolated from adjacent high tumor cell content FFPE tissue varied considerably, which may indicate TPM tumor heterogeneity. Overall and disease-free survival was not associated with TPM versus wild-type pNEN cases. Binary category analyses indicated a marginally significant relationship between TPM status and longer telomeres (p = 0.086), and changes in expression of miR449a (p = 0.157), HDAC4 (p = 0.146) and HDAC9 (p = 0.149). Future studies with larger patient cohorts are needed to assess the true clinical value of these rare mutations in pNEN.

A Driver Never Works Alone-Interplay Networks of Mutant p53, MYC, RAS, and Other Universal Oncogenic Drivers in Human Cancer

The knowledge accumulating on the occurrence and mechanisms of the activation of oncogenes in human neoplasia necessitates an increasingly detailed understanding of their systemic interactions. None of the known oncogenic drivers work in isolation from the other oncogenic pathways. The cooperation between these pathways is an indispensable element of a multistep carcinogenesis, which apart from inactivation of tumor suppressors, always includes the activation of two or more proto-oncogenes. In this review we focus on representative examples of the interaction of major oncogenic drivers with one another. The drivers are selected according to the following criteria: (1) the highest frequency of known activation in human neoplasia (by mutations or otherwise), (2) activation in a wide range of neoplasia types (universality) and (3) as a part of a distinguishable pathway, (4) being a known cause of phenotypic addiction of neoplastic cells and thus a promising therapeutic target. Each of these universal oncogenic factors—mutant p53, KRAS and CMYC proteins, telomerase ribonucleoprotein, proteasome machinery, HSP molecular chaperones, NF-κB and WNT pathways, AP-1 and YAP/TAZ transcription factors and non-coding RNAs—has a vast network of molecular interrelations and common partners. Understanding this network allows for the hunt for novel therapeutic targets and protocols to counteract drug resistance in a clinical neoplasia treatment.

High-Throughput Sequencing is a Crucial Tool to Investigate the Contribution of Human Endogenous Retroviruses (HERVs) to Human Biology and Development

Human Endogenous retroviruses (HERVs) are remnants of ancient retroviral infections that represent a large fraction of our genome. Their transcriptional activity is finely regulated in early developmental stages and their expression is modulated in different cell types and tissues. Such activity has an impact on human physiology and pathology that is only partially understood up to date. Novel high-throughput sequencing tools have recently allowed for a great advancement in elucidating the various HERV expression patterns in different tissues as well as the mechanisms controlling their transcription, and overall, have helped in gaining better insights in an all-inclusive understanding of the impact of HERVs in biology of the host.

MutSpot: detection of non-coding mutation hotspots in cancer genomes

Recurrence and clustering of somatic mutations (hotspots) in cancer genomes may indicate positive selection and involvement in tumorigenesis. MutSpot performs genome-wide inference of mutation hotspots in non-coding and regulatory DNA of cancer genomes. MutSpot performs feature selection across hundreds of epigenetic and sequence features followed by estimation of position- and patient-specific background somatic mutation probabilities. MutSpot is user-friendly, works on a standard workstation, and scales to thousands of cancer genomes.

Ancestry-specific predisposing germline variants in cancer

BACKGROUND

Distinct prevalence of inherited genetic predisposition may partially explain the difference of cancer risks across ancestries. Ancestry-specific analyses of germline genomes are required to inform cancer genetic risk and prognosis of diverse populations.

METHODS

We conducted analyses using germline and somatic sequencing data generated by The Cancer Genome Atlas. Collapsing pathogenic and likely pathogenic variants to cancer predisposition genes (CPG), we analyzed the association between CPGs and cancer types within ancestral groups. We also identified the predisposition-associated two-hit events and gene expression effects in tumors.

RESULTS

Genetic ancestry analysis classified the cohort of 9899 cancer cases into individuals of primarily European (N = 8184, 82.7%), African (N = 966, 9.8%), East Asian (N = 649, 6.6%), South Asian (N = 48, 0.5%), Native/Latin American (N = 41, 0.4%), and admixed (N = 11, 0.1%) ancestries. In the African ancestry, we discovered a potentially novel association of BRCA2 in lung squamous cell carcinoma (OR = 41.4 [95% CI, 6.1-275.6]; FDR = 0.002) previously identified in Europeans, along with a known association of BRCA2 in ovarian serous cystadenocarcinoma (OR = 8.5 [95% CI, 1.5-47.4]; FDR = 0.045). In the East Asian ancestry, we discovered one previously known association of BRIP1 in stomach adenocarcinoma (OR = 12.8 [95% CI, 1.8-90.8]; FDR = 0.038). Rare variant burden analysis further identified 7 suggestive associations in African ancestry individuals previously described in European ancestry, including SDHB in pheochromocytoma and paraganglioma, ATM in prostate adenocarcinoma, VHL in kidney renal clear cell carcinoma, FH in kidney renal papillary cell carcinoma, and PTEN in uterine corpus endometrial carcinoma. Most predisposing variants were found exclusively in one ancestry in the TCGA and gnomAD datasets. Loss of heterozygosity was identified for 7 out of the 15 African ancestry carriers of predisposing variants. Further, tumors from the SDHB or BRCA2 carriers showed simultaneous allelic-specific expression and low gene expression of their respective affected genes, and FH splice-site variant carriers showed mis-splicing of FH.

CONCLUSIONS

While several CPGs are shared across patients, many pathogenic variants are found to be ancestry-specific and trigger somatic effects. Studies using larger cohorts of diverse ancestries are required to pinpoint ancestry-specific genetic predisposition and inform genetic screening strategies.

Chromosome Abnormalities: New Insights into Their Clinical Significance in Cancer

Chromosomal abnormalities, consisting of numerical and structural chromosome abnormalities, are a common characteristic of cancer. Numerical chromosome abnormalities, mainly including aneuploidy and chromosome instability, are caused by chromosome segregation errors in mitosis, whereas structural chromosome abnormalities are a consequence of DNA damage and comprise focal/arm-level chromosome gain or loss. Recent advances have started to unveil the mechanisms by which chromosomal abnormalities can facilitate tumorigenesis and change the cellular fitness and the expression or function of RNAs and proteins. Accumulating evidence suggests that chromosome abnormalities represent a genomic signature that is linked to cancer prognosis and reaction to chemotherapy and immunotherapy. In this review, we discuss the most recent findings on the role of chromosome abnormalities in tumorigenesis and cancer progression, with a particular emphasis on how aneuploidy and chromosome instability influence cancer therapy and prognosis. We also highlight the distribution and clinical application of the structural chromosome abnormalities in various cancer types. A better understanding of the role of chromosome abnormalities will be beneficial to the development of precision oncology and suggest future directions for the field.

The Hippo Pathway as a Driver of Select Human Cancers

The Hippo pathway regulates myriad biological processes in diverse species and is a key cancer signaling network in humans. Although Hippo has been linked to multiple aspects of cancer, its role in this disease is incompletely understood. Large-scale pan-cancer analyses of core Hippo pathway genes reveal that the pathway is mutated at a high frequency only in select human cancers, including malignant mesothelioma and meningioma. Hippo pathway deregulation is also enriched in squamous epithelial cancers. We discuss cancer-related functions of the Hippo pathway and potential explanations for the cancer-restricted mutation profile of core Hippo pathway genes. Greater understanding of Hippo pathway deregulation in cancers will be essential to guide the imminent use of Hippo-targeted therapies.

Extreme differences between human germline and tumor mutation densities are driven by ancestral human-specific deviations

Mutations do not accumulate uniformly across the genome. Human germline and tumor mutation density correlate poorly, and each is associated with different genomic features. Here, we use non-human great ape (NHGA) germlines to determine human germline- and tumor-specific deviations from an ancestral-like great ape genome-wide mutational landscape. Strikingly, we find that the distribution of mutation densities in tumors presents a stronger correlation with NHGA than with human germlines. This effect is driven by human-specific differences in the distribution of mutations at non-CpG sites. We propose that ancestral human demographic events, together with the human-specific mutation slowdown, disrupted the human genome-wide distribution of mutation densities. Tumors partially recover this distribution by accumulating preneoplastic-like somatic mutations. Our results highlight the potential utility of using NHGA population data, rather than human controls, to establish the expected mutational background of healthy somatic cells.

Germline variant burden in cancer genes correlates with age at diagnosis and somatic mutation burden

Cancers harbor many somatic mutations and germline variants, we hypothesized that the combined effect of germline variants that alter the structure, expression, or function of protein-coding regions of cancer-biology related genes (gHFI) determines which and how many somatic mutations (sM) must occur for malignant transformation. We show that gHFI and sM affect overlapping genes and the average number of gHFI in cancer hallmark genes is higher in patients who develop cancer at a younger age (r = -0.77, P = 0.0051), while the average number of sM increases in increasing age groups (r = 0.92, P = 0.000073). A strong negative correlation exists between average gHFI and average sM burden in increasing age groups (r = -0.70, P = 0.017). In early-onset cancers, the larger gHFI burden in cancer genes suggests a greater contribution of germline alterations to the transformation process while late-onset cancers are more driven by somatic mutations.

In vivo CRISPR screens reveal potent driver mutations in head and neck cancers

We have recently tested the transforming potential of 484 'long-tail' genes, which are recurrently albeit infrequently mutated in head and neck cancers (HNSCC). We identified 15 novel tumor suppressors and our top hits converge on regulating the NOTCH signaling pathway. Therapeutic approaches activating NOTCH signaling could be a promising strategy to treat two-thirds of human HNSCC patients.

Molecular markers and targeted therapy in pediatric low-grade glioma

INTRODUCTION

Recently discovered molecular alterations in pediatric low-grade glioma have helped to refine the classification of these tumors and offered novel targets for therapy. Genetic aberrations may combine with histopathology to offer new insights into glioma classification, gliomagenesis and prognosis. Therapies targeting common genetic aberrations in the MAPK pathway offer a novel mechanism of tumor control that is currently under study.

METHODS

We have reviewed common molecular alterations found in pediatric low-grade glioma as well as recent clinical trials of MEK and BRAF inhibitors.

RESULTS

In this topic review, we examine the current understanding of molecular alterations in pediatric low-grade glioma, as well as their role in diagnosis, prognosis and therapy. We summarize current data on the efficacy of targeted therapies in pediatric low-grade gliomas, as well as the many unanswered questions that these new discoveries and therapies raise.

CONCLUSIONS

The identification of driver alterations in pediatric low-grade glioma and the development of targeted therapies have opened new therapeutic avenues for patients with low-grade gliomas.

Sharing Is Caring-Data Sharing Initiatives in Healthcare

In recent years, more and more health data are being generated. These data come not only from professional health systems, but also from wearable devices. All these 'big data' put together can be utilized to optimize treatments for each unique patient ('precision medicine'). For this to be possible, it is necessary that hospitals, academia and industry work together to bridge the 'valley of death' of translational medicine. However, hospitals and academia often are reluctant to share their data with other parties, even though the patient is actually the owner of his/her own health data. Academic hospitals usually invest a lot of time in setting up clinical trials and collecting data, and want to be the first ones to publish papers on this data. There are some publicly available datasets, but these are usually only shared after study (and publication) completion, which means a severe delay of months or even years before others can analyse the data. One solution is to incentivize the hospitals to share their data with (other) academic institutes and the industry. Here, we show an analysis of the current literature around data sharing, and we discuss five aspects of data sharing in the medical domain: publisher requirements, data ownership, growing support for data sharing, data sharing initiatives and how the use of federated data might be a solution. We also discuss some potential future developments around data sharing, such as medical crowdsourcing and data generalists.

Transcription-coupled repair and mismatch repair contribute towards preserving genome integrity at mononucleotide repeat tracts

The mechanisms that underpin how insertions or deletions (indels) become fixed in DNA have primarily been ascribed to replication-related and/or double-strand break (DSB)-related processes. Here, we introduce a method to evaluate indels, orientating them relative to gene transcription. In so doing, we reveal a number of surprising findings: First, there is a transcriptional strand asymmetry in the distribution of mononucleotide repeat tracts in the reference human genome. Second, there is a strong transcriptional strand asymmetry of indels across 2,575 whole genome sequenced human cancers. We suggest that this is due to the activity of transcription-coupled nucleotide excision repair (TC-NER). Furthermore, TC-NER interacts with mismatch repair (MMR) under physiological conditions to produce strand bias. Finally, we show how insertions and deletions differ in their dependencies on these repair pathways. Our analytical approach reveals insights into the contribution of DNA repair towards indel mutagenesis in human cells.

Timing the initiation of multiple myeloma

The evolution and progression of multiple myeloma and its precursors over time is poorly understood. Here, we investigate the landscape and timing of mutational processes shaping multiple myeloma evolution in a large cohort of 89 whole genomes and 973 exomes. We identify eight processes, including a mutational signature caused by exposure to melphalan. Reconstructing the chronological activity of each mutational signature, we estimate that the initial transformation of a germinal center B-cell usually occurred during the first 2nd-3rd decades of life. We define four main patterns of activation-induced deaminase (AID) and apolipoprotein B mRNA editing catalytic polypeptide-like (APOBEC) mutagenesis over time, including a subset of patients with evidence of prolonged AID activity during the pre-malignant phase, indicating antigen-responsiveness and germinal center reentry. Our findings provide a framework to study the etiology of multiple myeloma and explore strategies for prevention and early detection.

The PI3K-Akt-mTOR Signaling Pathway in Human Acute Myeloid Leukemia (AML) Cells

Acute myeloid leukemia (AML) is a heterogeneous group of diseases characterized by uncontrolled proliferation of hematopoietic stem cells in the bone marrow. Malignant cell growth is characterized by disruption of normal intracellular signaling, caused by mutations or aberrant external signaling. The phosphoinositide 3-kinase (PI3K)-Akt-mammalian target of rapamycin (mTOR) pathway (PI3K-Akt-mTOR pathway) is among one of the intracellular pathways aberrantly upregulated in cancers including AML. Activation of this pathway seems important in leukemogenesis, and given the central role of this pathway in metabolism, the bioenergetics of AML cells may depend on downstream signaling within this pathway. Furthermore, observations suggest that constitutive activation of the PI3K-Akt-mTOR pathway differs between patients, and that increased activity within this pathway is an adverse prognostic parameter in AML. Pharmacological targeting of the PI3K-Akt-mTOR pathway with specific inhibitors results in suppression of leukemic cell growth. However, AML patients seem to differ regarding their susceptibility to various small-molecule inhibitors, reflecting biological heterogeneity in the intracellular signaling status. These findings should be further investigated in both preclinical and clinical settings, along with the potential use of this pathway as a prognostic biomarker, both in patients receiving intensive curative AML treatment and in elderly/unfit receiving AML-stabilizing treatment.

Insights into Genetic Susceptibility to Melanoma by Gene Panel Testing: Potential Pathogenic Variants in ACD, ATM, BAP1, and POT1

The contribution of recently established or candidate susceptibility genes to melanoma missing heritability has yet to be determined. Multigene panel testing could increase diagnostic yield and better define the role of candidate genes. We characterized 273 CDKN2A/ARF and CDK4-negative probands through a custom-designed targeted gene panel that included CDKN2A/ARF, CDK4, ACD, BAP1, MITF, POT1, TERF2IP, ATM, and PALB2. Co-segregation, loss of heterozygosity (LOH)/protein expression analysis, and splicing characterization were performed to improve variant classification. We identified 16 (5.9%) pathogenic and likely pathogenic variants in established high/medium penetrance cutaneous melanoma susceptibility genes (BAP1, POT1, ACD, MITF, and TERF2IP), including two novel variants in BAP1 and 4 in POT1. We also found four deleterious and five likely deleterious variants in ATM (3.3%). Thus, including potentially deleterious variants in ATM increased the diagnostic yield to about 9%. Inclusion of rare variants of uncertain significance would increase the overall detection yield to 14%. At least 10% of melanoma missing heritability may be explained through panel testing in our population. To our knowledge, this is the highest frequency of putative ATM deleterious variants reported in melanoma families, suggesting a possible role in melanoma susceptibility, which needs further investigation.

Mechanisms generating cancer genome complexity from a single cell division error

The chromosome breakage-fusion-bridge (BFB) cycle is a mutational process that produces gene amplification and genome instability. Signatures of BFB cycles can be observed in cancer genomes alongside chromothripsis, another catastrophic mutational phenomenon. We explain this association by elucidating a mutational cascade that is triggered by a single cell division error-chromosome bridge formation-that rapidly increases genomic complexity. We show that actomyosin forces are required for initial bridge breakage. Chromothripsis accumulates, beginning with aberrant interphase replication of bridge DNA. A subsequent burst of DNA replication in the next mitosis generates extensive DNA damage. During this second cell division, broken bridge chromosomes frequently missegregate and form micronuclei, promoting additional chromothripsis. We propose that iterations of this mutational cascade generate the continuing evolution and subclonal heterogeneity characteristic of many human cancers.

Mutation signatures specific to DNA alkylating agents in yeast and cancers

Alkylation is one of the most ubiquitous forms of DNA lesions. However, the motif preferences and substrates for the activity of the major types of alkylating agents defined by their nucleophilic substitution reactions (SN1 and SN2) are still unclear. Utilizing yeast strains engineered for large-scale production of single-stranded DNA (ssDNA), we probed the substrate specificity, mutation spectra and signatures associated with DNA alkylating agents. We determined that SN1-type agents preferably mutagenize double-stranded DNA (dsDNA), and the mutation signature characteristic of the activity of SN1-type agents was conserved across yeast, mice and human cancers. Conversely, SN2-type agents preferably mutagenize ssDNA in yeast. Moreover, the spectra and signatures derived from yeast were detectable in lung cancers, head and neck cancers and tumors from patients exposed to SN2-type alkylating chemicals. The estimates of mutation loads associated with the SN2-type alkylation signature were higher in lung tumors from smokers than never-smokers, pointing toward the mutagenic activity of the SN2-type alkylating carcinogens in cigarettes. In summary, our analysis of mutations in yeast strains treated with alkylating agents, as well as in whole-exome and whole-genome-sequenced tumors identified signatures highly specific to alkylation mutagenesis and indicate the pervasive nature of alkylation-induced mutagenesis in cancers.

Telomere dysfunction cooperates with epigenetic alterations to impair murine embryonic stem cell fate commitment

The precise relationship between epigenetic alterations and telomere dysfunction is still an extant question. Previously, we showed that eroded telomeres lead to differentiation instability in murine embryonic stem cells (mESCs) via DNA hypomethylation at pluripotency-factor promoters. Here, we uncovered that telomerase reverse transcriptase null (Tert^-/-) mESCs exhibit genome-wide alterations in chromatin accessibility and gene expression during differentiation. These changes were accompanied by an increase of H3K27me3 globally, an altered chromatin landscape at the Pou5f1/Oct4 promoter, and a refractory response to differentiation cues. Inhibition of the Polycomb Repressive Complex 2 (PRC2), an H3K27 tri-methyltransferase, exacerbated the impairment in differentiation and pluripotency gene repression in Tert^-/-mESCs but not wild-type mESCs, whereas inhibition of H3K27me3 demethylation led to a partial rescue of the Tert^-/- phenotype. These data reveal a new interdependent relationship between H3K27me3 and telomere integrity in stem cell lineage commitment that may have implications in aging and cancer.

RET Gene Fusions in Malignancies of the Thyroid and Other Tissues

Following the identification of the BCR-ABL1 (Breakpoint Cluster Region-ABelson murine Leukemia) fusion in chronic myelogenous leukemia, gene fusions generating chimeric oncoproteins have been recognized as common genomic structural variations in human malignancies. This is, in particular, a frequent mechanism in the oncogenic conversion of protein kinases. Gene fusion was the first mechanism identified for the oncogenic activation of the receptor tyrosine kinase RET (REarranged during Transfection), initially discovered in papillary thyroid carcinoma (PTC). More recently, the advent of highly sensitive massive parallel (next generation sequencing, NGS) sequencing of tumor DNA or cell-free (cfDNA) circulating tumor DNA, allowed for the detection of RET fusions in many other solid and hematopoietic malignancies. This review summarizes the role of RET fusions in the pathogenesis of human cancer.

Differential expression of MAGEA6 toggles autophagy to promote pancreatic cancer progression

The melanoma-associated antigen family A (MAGEA) antigens are expressed in a wide variety of malignant tumors but not in adult somatic cells, rendering them attractive targets for cancer immunotherapy. Here we show that a number of cancer-associated MAGEA mutants that undergo proteasome-dependent degradation in vitro could negatively impact their utility as immunotherapeutic targets. Importantly, in pancreatic ductal adenocarcinoma cell models, MAGEA6 suppresses macroautophagy (autophagy). The inhibition of autophagy is released upon MAGEA6 degradation, which can be induced by nutrient deficiency or by acquisition of cancer-associated mutations. Using xenograft mouse models, we demonstrated that inhibition of autophagy is critical for tumor initiation whereas reinstitution of autophagy as a consequence of MAGEA6 degradation contributes to tumor progression. These findings could inform cancer immunotherapeutic strategies for targeting MAGEA antigens and provide mechanistic insight into the divergent roles of MAGEA6 during pancreatic cancer initiation and progression.

Computational Oncology in the Multi-Omics Era: State of the Art

Cancer is the quintessential complex disease. As technologies evolve faster each day, we are able to quantify the different layers of biological elements that contribute to the emergence and development of malignancies. In this multi-omics context, the use of integrative approaches is mandatory in order to gain further insights on oncological phenomena, and to move forward toward the precision medicine paradigm. In this review, we will focus on computational oncology as an integrative discipline that incorporates knowledge from the mathematical, physical, and computational fields to further the biomedical understanding of cancer. We will discuss the current roles of computation in oncology in the context of multi-omic technologies, which include: data acquisition and processing; data management in the clinical and research settings; classification, diagnosis, and prognosis; and the development of models in the research setting, including their use for therapeutic target identification. We will discuss the machine learning and network approaches as two of the most promising emerging paradigms, in computational oncology. These approaches provide a foundation on how to integrate different layers of biological description into coherent frameworks that allow advances both in the basic and clinical settings.

Genetics and Genomics of Breast Cancer: update and translational perspectives

In the recent years the rapid scientific innovation in the evaluation of the individual's genome have allowed the identification of variants associated with the onset, treatment and prognosis of various pathologies including cancer, and with a potential impact in the assessment of therapy responses. Despite the analysis and interpretation of genomic information is considered incomplete, in many cases the identification of specific genomic profile has allowed the stratification of subgroups of patients characterized by a better response to drug therapies. Individual genome analysis has changed profoundly the diagnostic and therapeutic approach of breast cancer in the last 15 years by identifying selective molecular lesions that drive the development of neoplasms, showing that each tumor has its own genomic signature, with some specific features and some features common to several sub-types. Several personalized therapies have been (and still are being) developed showing a remarkable efficacy in the treatment of breast cancer.

Germline Elongator mutations in Sonic Hedgehog medulloblastoma

Cancer genomics has revealed many genes and core molecular processes that contribute to human malignancies, but the genetic and molecular bases of many rare cancers remains unclear. Genetic predisposition accounts for 5 to 10% of cancer diagnoses in children1,2, and genetic events that cooperate with known somatic driver events are poorly understood. Pathogenic germline variants in established cancer predisposition genes have been recently identified in 5% of patients with the malignant brain tumour medulloblastoma3. Here, by analysing all protein-coding genes, we identify and replicate rare germline loss-of-function variants across ELP1 in 14% of paediatric patients with the medulloblastoma subgroup Sonic Hedgehog (MBSHH). ELP1 was the most common medulloblastoma predisposition gene and increased the prevalence of genetic predisposition to 40% among paediatric patients with MBSHH. Parent-offspring and pedigree analyses identified two families with a history of paediatric medulloblastoma. ELP1-associated medulloblastomas were restricted to the molecular SHHα subtype4 and characterized by universal biallelic inactivation of ELP1 owing to somatic loss of chromosome arm 9q. Most ELP1-associated medulloblastomas also exhibited somatic alterations in PTCH1, which suggests that germline ELP1 loss-of-function variants predispose individuals to tumour development in combination with constitutive activation of SHH signalling. ELP1 is the largest subunit of the evolutionarily conserved Elongator complex, which catalyses translational elongation through tRNA modifications at the wobble (U34) position5,6. Tumours from patients with ELP1-associated MBSHH were characterized by a destabilized Elongator complex, loss of Elongator-dependent tRNA modifications, codon-dependent translational reprogramming, and induction of the unfolded protein response, consistent with loss of protein homeostasis due to Elongator deficiency in model systems7-9. Thus, genetic predisposition to proteome instability may be a determinant in the pathogenesis of paediatric brain cancers. These results support investigation of the role of protein homeostasis in other cancer types and potential for therapeutic interference.

Encapsulation for Cancer Therapy

The current rapid advancement of numerous nanotechnology tools is being employed in treatment of many terminal diseases such as cancer. Nanocapsules (NCs) containing an anti-cancer drug offer a very promising alternative to conventional treatments, mostly due to their targeted delivery and precise action, and thereby they can be used in distinct applications: as biosensors or in medical imaging, allowing for cancer detection as well as agents/carriers in targeted drug delivery. The possibility of using different systems-inorganic nanoparticles, dendrimers, proteins, polymeric micelles, liposomes, carbon nanotubes (CNTs), quantum dots (QDs), biopolymeric nanoparticles and their combinations-offers multiple benefits to early cancer detection as well as controlled drug delivery to specific locations. This review focused on the key and recent progress in the encapsulation of anticancer drugs that include methods of preparation, drug loading and drug release mechanism on the presented nanosystems. Furthermore, the future directions in applications of various nanoparticles are highlighted.

Elucidation of Functional Roles of Sialic Acids in Cancer Migration

Sialic acids (SA), negatively charged nine-carbon sugars, have long been implicated in cancer metastasis since 1960's but its detailed functional roles remain elusive. We present a computational analysis of transcriptomic data of cancer vs. control tissues of eight types in TCGA, aiming to elucidate the possible reason for the increased production and utilization of SAs in cancer and their possible driving roles in cancer migration. Our analyses have revealed for all cancer types: (1) the synthesis and deployment enzymes of SAs are persistently up-regulated throughout the progression for all but one cancer type; and (2) gangliosides, of which SAs are part, tend to converge to specific types that allow SAs to pack at high densities on cancer cell surface as a cancer advances. Statistical and modeling analyses suggest that (i) a highly plausible reason for the increased syntheses of SAs is to produce net protons, used for neutralizing the OH⁻ persistently generated by elevated intracellular iron metabolism coupled with chronic inflammation in cancer tissues; (ii) the level of SA accumulation on cancer cell surface strongly correlates with the stage of cancer migration, as well as multiple migration-related characteristics such as altered cell-cell adhesion, mechanical stress, cell protrusion, and contraction; and (iii) the pattern of SA deployment correlates with the 5-year survival rate of a cancer type. Overall, our study provides strong evidence for that the continuous accumulation of SAs on cancer cell surface gives rise to increasingly stronger cell-cell repulsion due to their negative charges, leading to cell deformation by electrostatic force-induced mechanical compression, which is known to be able to drive cancer cell migration established by recent studies.

The genome-wide landscape of C:G > T:A polymorphism at the CpG contexts in the human population

BACKGROUND

The C:G > T:A substitution at the CpG dinucleotide contexts is the most frequent substitution type in genome evolution. The mutational process is obviously ongoing in the human germline; however, its impact on common and rare genomic polymorphisms has not been comprehensively investigated yet. Here we observed the landscape and dynamics of C:G > T:A substitutions from population-scale human genome sequencing datasets including ~ 4300 whole-genomes from the 1000 Genomes and the pan-cancer analysis of whole genomes (PCAWG) Project and ~ 60,000 whole-exomes from the Exome Aggregation Consortium (ExAC) database.

RESULTS

Of the 28,084,558 CpG sites in the human reference genome, 26.0% show C:G > T:A substitution in the dataset. Remarkably, CpGs in CpG islands (CGIs) have a much lower frequency of such mutations (5.6%). Interestingly, the mutation frequency of CGIs is not uniform with a significantly higher C:G > T:A substitution rate for intragenic CGIs compared to other types. For non-CGI CpGs, the mutation rate was positively correlated with the distance from the nearest CGI up to 2 kb. Finally, we found the impact of negative selection for coding CpG mutations resulting in amino acid change.

CONCLUSIONS

This study provides the first unbiased rate of C:G > T:A substitution at the CpG dinucleotide contexts, using population-scale human genome sequencing data. Our findings provide insights into the dynamics of the mutation acquisition in the human genome.

Chromosome Instability; Implications in Cancer Development, Progression, and Clinical Outcomes

Chromosome instability (CIN) refers to an ongoing rate of chromosomal changes and is a driver of genetic, cell-to-cell heterogeneity. It is an aberrant phenotype that is intimately associated with cancer development and progression. The presence, extent, and level of CIN has tremendous implications for the clinical management and outcomes of those living with cancer. Despite its relevance in cancer, there is still extensive misuse of the term CIN, and this has adversely impacted our ability to identify and characterize the molecular determinants of CIN. Though several decades of genetic research have provided insight into CIN, the molecular determinants remain largely unknown, which severely limits its clinical potential. In this review, we provide a definition of CIN, describe the two main types, and discuss how it differs from aneuploidy. We subsequently detail its impact on cancer development and progression, and describe how it influences metastatic potential with reference to cancer prognosis and outcomes. Finally, we end with a discussion of how CIN induces genetic heterogeneity to influence the use and efficacy of several precision medicine strategies, including patient and risk stratification, as well as its impact on the acquisition of drug resistance and disease recurrence.

OncoOmics approaches to reveal essential genes in breast cancer: a panoramic view from pathogenesis to precision medicine

Breast cancer (BC) is the leading cause of cancer-related death among women and the most commonly diagnosed cancer worldwide. Although in recent years large-scale efforts have focused on identifying new therapeutic targets, a better understanding of BC molecular processes is required. Here we focused on elucidating the molecular hallmarks of BC heterogeneity and the oncogenic mutations involved in precision medicine that remains poorly defined. To fill this gap, we established an OncoOmics strategy that consists of analyzing genomic alterations, signaling pathways, protein-protein interactome network, protein expression, dependency maps in cell lines and patient-derived xenografts in 230 previously prioritized genes to reveal essential genes in breast cancer. As results, the OncoOmics BC essential genes were rationally filtered to 140. mRNA up-regulation was the most prevalent genomic alteration. The most altered signaling pathways were associated with basal-like and Her2-enriched molecular subtypes. RAC1, AKT1, CCND1, PIK3CA, ERBB2, CDH1, MAPK14, TP53, MAPK1, SRC, RAC3, BCL2, CTNNB1, EGFR, CDK2, GRB2, MED1 and GATA3 were essential genes in at least three OncoOmics approaches. Drugs with the highest amount of clinical trials in phases 3 and 4 were paclitaxel, docetaxel, trastuzumab, tamoxifen and doxorubicin. Lastly, we collected ~3,500 somatic and germline oncogenic variants associated with 50 essential genes, which in turn had therapeutic connectivity with 73 drugs. In conclusion, the OncoOmics strategy reveals essential genes capable of accelerating the development of targeted therapies for precision oncology.

Comprehensive analysis of indels in whole-genome microsatellite regions and microsatellite instability across 21 cancer types

Microsatellites are repeats of 1- to 6-bp units, and approximately 10 million microsatellites have been identified across the human genome. Microsatellites are vulnerable to DNA mismatch errors and have thus been used to detect cancers with mismatch repair deficiency. To reveal the mutational landscape of microsatellite repeat regions at the genome level, we analyzed approximately 20.1 billion microsatellites in 2717 whole genomes of pan-cancer samples across 21 tissue types. First, we developed a new insertion and deletion caller (MIMcall) that takes into consideration the error patterns of different types of microsatellites. Among the 2717 pan-cancer samples, our analysis identified 31 samples, including colorectal, uterus, and stomach cancers, with a higher proportion of mutated microsatellite (≥0.03), which we defined as microsatellite instability (MSI) cancers of genome-wide level. Next, we found 20 highly mutated microsatellites that can be used to detect MSI cancers with high sensitivity. Third, we found that replication timing and DNA shape were significantly associated with mutation rates of microsatellites. Last, analysis of mutations in mismatch repair genes showed that somatic SNVs and short indels had larger functional impacts than germline mutations and structural variations. Our analysis provides a comprehensive picture of mutations in the microsatellite regions and reveals possible causes of mutations, as well as provides a useful marker set for MSI detection.

Nucleosome positioning stability is a modulator of germline mutation rate variation across the human genome

Nucleosome organization has been suggested to affect local mutation rates in the genome. However, the lack of de novo mutation and high-resolution nucleosome data has limited the investigation of this hypothesis. Additionally, analyses using indirect mutation rate measurements have yielded contradictory and potentially confounding results. Here, we combine data on >300,000 human de novo mutations with high-resolution nucleosome maps and find substantially elevated mutation rates around translationally stable (‘strong’) nucleosomes. We show that the mutational mechanisms affected by strong nucleosomes are low-fidelity replication, insufficient mismatch repair and increased double-strand breaks. Strong nucleosomes preferentially locate within young SINE/LINE transposons, suggesting that when subject to increased mutation rates, transposons are then more rapidly inactivated. Depletion of strong nucleosomes in older transposons suggests frequent positioning changes during evolution. The findings have important implications for human genetics and genome evolution.

Nucleosome organization has been suggested to affect local mutation rates in the genome. Here, the authors analyse data on >300,000 human de novo mutations and high-resolution nucleosome maps and provide evidence that nucleosome positioning stability modulates germline mutation rate variation across the human genome.

Genomic data sharing in Europe is stumbling-Could a code of conduct prevent its fall?

Genomic data sharing is becoming more important as scientists join forces across borders in biomedical research for the benefit of patients and society. The EU's General Data Protection Regulation (GDPR) helps simplify sharing of such data at the European and international level. However, initial optimism has dried up as EU member states go their own ways in implementing the GDPR into national laws, and as legal cases challenging data sharing reach courts. Codes of conduct could facilitate data sharing in Europe and better connect it to global health research. This commentary explains the potential of codes of conduct for addressees and drafters. Codes are no panacea though; other measures may be necessary to ensure that Europe remains collaborative and competitive in biomedical research. Nevertheless, codes of conduct would bring immediate benefits and, in the long term, could foster a true European ecosystem for joint biomedical research and easier international data sharing.