Systematic analysis of noncoding somatic mutations and gene expression alterations across 14 tumor types. Nat Genet. 2014;46:1258-1263. [PMID: 25383969 DOI: 10.1038/ng.3141]

Elevated pyrimidine dimer formation at distinct genomic bases underlies promoter mutation hotspots in UV-exposed cancers

Sequencing of whole cancer genomes has revealed an abundance of recurrent mutations in gene-regulatory promoter regions, in particular in melanoma where strong mutation hotspots are observed adjacent to ETS-family transcription factor (TF) binding sites. While sometimes interpreted as functional driver events, these mutations are commonly believed to be due to locally inhibited DNA repair. Here, we first show that low-dose UV light induces mutations preferably at a known ETS promoter hotspot in cultured cells even in the absence of global or transcription-coupled nucleotide excision repair (NER). Further, by genome-wide mapping of cyclobutane pyrimidine dimers (CPDs) shortly after UV exposure and thus before DNA repair, we find that ETS-related mutation hotspots exhibit strong increases in CPD formation efficacy in a manner consistent with tumor mutation data at the single-base level. Analysis of a large whole genome cohort illustrates the widespread contribution of this effect to recurrent mutations in melanoma. While inhibited NER underlies a general increase in somatic mutation burden in regulatory elements including ETS sites, our data supports that elevated DNA damage formation at specific genomic bases is at the core of the prominent promoter mutation hotspots seen in skin cancers, thus explaining a key phenomenon in whole-genome cancer analyses.

The Identification and Interpretation of cis-Regulatory Noncoding Mutations in Cancer

In the need to characterise the genomic landscape of cancers and to establish novel biomarkers and therapeutic targets, studies have largely focused on the identification of driver mutations within the protein-coding gene regions, where the most pathogenic alterations are known to occur. However, the noncoding genome is significantly larger than its protein-coding counterpart, and evidence reveals that regulatory sequences also harbour functional mutations that significantly affect the regulation of genes and pathways implicated in cancer. Due to the sheer number of noncoding mutations (NCMs) and the limited knowledge of regulatory element functionality in cancer genomes, differentiating pathogenic mutations from background passenger noise is particularly challenging technically and computationally. Here we review various up-to-date high-throughput sequencing data/studies and in silico methods that can be employed to interrogate the noncoding genome. We aim to provide an overview of available data resources as well as computational and molecular techniques that can help and guide the search for functional NCMs in cancer genomes.

Recurrent mutations at estrogen receptor binding sites alter chromatin topology and distal gene expression in breast cancer

BACKGROUND

The mutational processes underlying non-coding cancer mutations and their biological significance in tumor evolution are poorly understood. To get better insights into the biological mechanisms of mutational processes in breast cancer, we integrate whole-genome level somatic mutations from breast cancer patients with chromatin states and transcription factor binding events.

RESULTS

We discover that a large fraction of non-coding somatic mutations in estrogen receptor (ER)-positive breast cancers are confined to ER binding sites. Notably, the highly mutated estrogen receptor binding sites are associated with more frequent chromatin loop contacts and the associated distal genes are expressed at higher level. To elucidate the functional significance of these non-coding mutations, we focus on two of the recurrently mutated estrogen receptor binding sites. Our bioinformatics and biochemical analysis suggest loss of DNA-protein interactions due to the recurrent mutations. Through CRISPR interference, we find that the recurrently mutated regulatory element at the LRRC3C-GSDMA locus impacts the expression of multiple distal genes. Using a CRISPR base editor, we show that the recurrent C→T conversion at the ZNF143 locus results in decreased TF binding, increased chromatin loop formation, and increased expression of multiple distal genes. This single point mutation mediates reduced response to estradiol-induced cell proliferation but increased resistance to tamoxifen-induced growth inhibition.

CONCLUSIONS

Our data suggest that ER binding is associated with localized accumulation of somatic mutations, some of which affect chromatin architecture, distal gene expression, and cellular phenotypes in ER-positive breast cancer.

Association analysis using somatic mutations

Somatic mutations drive the growth of tumor cells and are pivotal biomarkers for many cancer treatments. Genetic association analysis using somatic mutations is an effective approach to study the functional impact of somatic mutations. However, standard regression methods are not appropriate for somatic mutation association studies because somatic mutation calls often have non-ignorable false positive rate and/or false negative rate. While large scale association analysis using somatic mutations becomes feasible recently—thanks for the improvement of sequencing techniques and the reduction of sequencing cost—there is an urgent need for a new statistical method designed for somatic mutation association analysis. We propose such a method with computationally efficient software implementation: Somatic mutation Association test with Measurement Errors (SAME). SAME accounts for somatic mutation calling uncertainty using a likelihood based approach. It can be used to assess the associations between continuous/dichotomous outcomes and individual mutations or gene-level mutations. Through simulation studies across a wide range of realistic scenarios, we show that SAME can significantly improve statistical power than the naive generalized linear model that ignores mutation calling uncertainty. Finally, using the data collected from The Cancer Genome Atlas (TCGA) project, we apply SAME to study the associations between somatic mutations and gene expression in 12 cancer types, as well as the associations between somatic mutations and colon cancer subtype defined by DNA methylation data. SAME recovered some interesting findings that were missed by the generalized linear model. In addition, we demonstrated that mutation-level and gene-level analyses are often more appropriate for oncogene and tumor-suppressor gene, respectively.

Cancer is a genetic disease that is driven by the accumulation of somatic mutations. Association studies using somatic mutations is a powerful approach to identify the potential impact of somatic mutations on molecular or clinical features. One challenge for such tasks is the non-ignorable somatic mutation calling errors. We have developed a statistical method to address this challenge and applied our method to study the gene expression traits associated with somatic mutations in 12 cancer types. Our results show that some somatic mutations affect gene expression in several cancer types. In particular, we show that the associations between gene expression traits and TP53 gene level mutation reveal some similarities across a few cancer types.

Advances in genomic hepatocellular carcinoma research

Background

Hepatocellular carcinoma (HCC) is the cancer with the second highest mortality in the world due to its late presentation and limited treatment options. As such, there is an urgent need to identify novel biomarkers for early diagnosis and to develop novel therapies. The availability of next-generation sequencing (NGS) data from tumors of liver cancer patients has provided us with invaluable resources to better understand HCC through the integration of data from different sources to facilitate the identification of promising biomarkers or therapeutic targets.

Findings

Here, we review key insights gleaned from more than 20 NGS studies of HCC tumor samples, comprising approximately 582 whole genomes and 1,211 whole exomes mainly from the East Asian population. Through consolidation of reported somatic mutations from multiple studies, we identified genes with different types of somatic mutations, including single nucleotide variations, insertion/deletions, structural variations, and copy number alterations as well as genes with multiple frequent viral integration. Pathway analysis showed that this curated list of somatic mutations is critically involved in cancer-related pathways, viral carcinogenesis, and signaling pathways. Lastly, we addressed the future directions of HCC research as more NGS datasets become available.

Conclusions

Our review is a comprehensive resource for the current NGS research in HCC, consolidating published articles, potential gene candidates, and their related biological pathways.

HOXA9 Reprograms the Enhancer Landscape to Promote Leukemogenesis

Aberrant expression of HOXA9 is a prominent feature of acute leukemia driven by diverse oncogenes. Here we show that HOXA9 overexpression in myeloid and B progenitor cells leads to significant enhancer reorganizations with prominent emergence of leukemia-specific de novo enhancers. Alterations in the enhancer landscape lead to activation of an ectopic embryonic gene program. We show that HOXA9 functions as a pioneer factor at de novo enhancers and recruits CEBPα and the MLL3/MLL4 complex. Genetic deletion of MLL3/MLL4 blocks histone H3K4 methylation at de novo enhancers and inhibits HOXA9/MEIS1-mediated leukemogenesis in vivo. These results suggest that therapeutic targeting of HOXA9-dependent enhancer reorganization can be an effective therapeutic strategy in acute leukemia with HOXA9 overexpression.

A pan-cancer atlas of cancer hallmark-associated candidate driver lncRNAs

Substantial cancer genome sequencing efforts have discovered many important driver genes contributing to tumorigenesis. However, very little is known about the genetic alterations of long non‐coding RNAs (lncRNAs) in cancer. Thus, there is a need for systematic surveys of driver lncRNAs. Through integrative analysis of 5918 tumors across 11 cancer types, we revealed that lncRNAs have undergone dramatic genomic alterations, many of which are mutually exclusive with well‐known cancer genes. Using the hypothesis of functional redundancy of mutual exclusivity, we developed a computational framework to identify driver lncRNAs associated with different cancer hallmarks. Applying it to pan‐cancer data, we identified 378 candidate driver lncRNAs whose genomic features highly resemble the known cancer driver genes (e.g. high conservation and early replication). We further validated the candidate driver lncRNAs involved in ‘Tissue Invasion and Metastasis’ in lung adenocarcinoma and breast cancer, and also highlighted their potential roles in improving clinical outcomes. In summary, we have generated a comprehensive landscape of cancer candidate driver lncRNAs that could act as a starting point for future functional explorations, as well as the identification of biomarkers and lncRNA‐based target therapy.

Promoter capture Hi-C-based identification of recurrent noncoding mutations in colorectal cancer

Efforts are being directed to systematically analyze the non-coding regions of the genome for cancer-driving mutations^1-6. cis-regulatory elements (CREs) represent a highly enriched subset of the non-coding regions of the genome in which to search for such mutations. Here we use high-throughput chromosome conformation capture techniques (Hi-C) for 19,023 promoter fragments to catalog the regulatory landscape of colorectal cancer in cell lines, mapping CREs and integrating these with whole-genome sequence and expression data from The Cancer Genome Atlas^7,8. We identify a recurrently mutated CRE interacting with the ETV1 promoter affecting gene expression. ETV1 expression influences cell viability and is associated with patient survival. We further refine our understanding of the regulatory effects of copy-number variations, showing that RASL11A is targeted by a previously identified enhancer amplification¹. This study reveals new insights into the complex genetic alterations driving tumor development, providing a paradigm for employing chromosome conformation capture to decipher non-coding CREs relevant to cancer biology.

Noncanonical secondary structures arising from non-B DNA motifs are determinants of mutagenesis

Somatic mutations show variation in density across cancer genomes. Previous studies have shown that chromatin organization and replication time domains are correlated with, and thus predictive of, this variation. Here, we analyze 1809 whole-genome sequences from 10 cancer types to show that a subset of repetitive DNA sequences, called non-B motifs that predict noncanonical secondary structure formation can independently account for variation in mutation density. Combined with epigenetic factors and replication timing, the variance explained can be improved to 43%-76%. Approximately twofold mutation enrichment is observed directly within non-B motifs, is focused on exposed structural components, and is dependent on physical properties that are optimal for secondary structure formation. Therefore, there is mounting evidence that secondary structures arising from non-B motifs are not simply associated with increased mutation density-they are possibly causally implicated. Our results suggest that they are determinants of mutagenesis and increase the likelihood of recurrent mutations in the genome. This analysis calls for caution in the interpretation of recurrent mutations and highlights the importance of taking non-B motifs that can simply be inferred from the reference sequence into consideration in background models of mutability henceforth.

Transcriptome analysis of papillary thyroid cancer harboring telomerase reverse transcriptase promoter mutation

BACKGROUND

Telomerase reverse transcriptase (TERT) promoter mutations have recently been identified as an important prognostic factor in thyroid cancer. Studies suggest that TERT may have noncanonical functions beyond telomere maintenance.

METHODS

Clinicopathological information and transcriptome data for papillary thyroid carcinoma (PTC) samples were obtained from The Cancer Genome Atlas (TCGA). Propensity score matching was performed to adjust for potential confounding variables between the TERT promoter wild-type group and the mutant group. Gene expression data of 36 patients in the mutant group were systemically compared to those of 72 patients in the wild-type group.

RESULTS

Tumors with TERT promoter mutations had a higher TERT expression. Pathways central to DNA damage responses and cell cycle regulation were significantly enriched among 888 upregulated genes. Transporter and metabolic activities were overrepresented among 799 downregulated genes. There was no difference in the expression of most of the thyroid differentiation genes.

CONCLUSION

The TERT promoter mutations were associated with proliferative and metabolic alterations in PTC.

Realizing the significance of noncoding functionality in clinical genomics

Clinical genomics promises unprecedented precision in understanding the genetic basis of disease. Understanding the impact of variation across the genome is required to realize this potential. Currently, clinical genomics analyses focus on protein-coding genes. However, the noncoding genome is substantially larger than the protein-coding counterpart, and contains structural, regulatory, and transcribed information that needs to be incorporated into genome annotations if the full extent of the opportunity to use genomic information in healthcare is to be realized. This article reviews the challenges and opportunities in unlocking the clinical significance of coding and noncoding genomic information and translating its utility in practice.

Most of the DNA in the genome does not consist of genes that code for proteins, and understanding the function of these less examined parts of our genetic material is essential to fully understand human development and disease. Brian Gloss and Marcel Dinger at the Garvan Institute of Medical Research in Sydney, Australia, review the challenges and opportunities in unraveling the clinical significance of all parts of our DNA. Many regions of DNA that do not encode protein molecules perform crucial functions in regulating the activity and interactions of the protein-coding genes. Variations in these regions may significantly influence the risks and causes of disease. Studying all parts of the genome will be critical for ensuring that the powerful modern techniques of genetic analysis have maximal impact on healthcare.

ETS transcription factors induce a unique UV damage signature that drives recurrent mutagenesis in melanoma

Recurrent mutations are frequently associated with transcription factor (TF) binding sites (TFBS) in melanoma, but the mechanism driving mutagenesis at TFBS is unclear. Here, we use a method called CPD-seq to map the distribution of UV-induced cyclobutane pyrimidine dimers (CPDs) across the human genome at single nucleotide resolution. Our results indicate that CPD lesions are elevated at active TFBS, an effect that is primarily due to E26 transformation-specific (ETS) TFs. We show that ETS TFs induce a unique signature of CPD hotspots that are highly correlated with recurrent mutations in melanomas, despite high repair activity at these sites. ETS1 protein renders its DNA binding targets extremely susceptible to UV damage in vitro, due to binding-induced perturbations in the DNA structure that favor CPD formation. These findings define a mechanism responsible for recurrent mutations in melanoma and reveal that DNA binding by ETS TFs is inherently mutagenic in UV-exposed cells.

Many factors contribute to mutation hotspots in cancer cells. Here the authors map UV damage at single-nucleotide resolution across the human genome and find that binding sites of ETS transcription factors are especially prone to forming UV lesions, leading to mutation hotspots in melanoma.

Genome-wide multi-omics profiling of the 8p11-p12 amplicon in breast carcinoma

Genomic instability contributes to the neoplastic phenotype by deregulating key cancer-related genes, which in turn can have a detrimental effect on patient outcome. DNA amplification of the 8p11-p12 genomic region has clinical and biological implications in multiple malignancies, including breast carcinoma where the amplicon has been associated with tumor progression and poor prognosis. However, oncogenes driving increased cancer-related death and recurrent genetic features associated with the 8p11-p12 amplicon remain to be identified. In this study, DNA copy number and transcriptome profiling data for 229 primary invasive breast carcinomas (corresponding to 185 patients) were evaluated in conjunction with clinicopathological features to identify putative oncogenes in 8p11-p12 amplified samples. Illumina paired-end whole transcriptome sequencing and whole-genome SNP genotyping were subsequently performed on 23 samples showing high-level regional 8p11-p12 amplification to characterize recurrent genetic variants (SNPs and indels), expressed gene fusions, gene expression profiles and allelic imbalances. We now show previously undescribed chromothripsis-like patterns spanning the 8p11-p12 genomic region and allele-specific DNA amplification events. In addition, recurrent amplification-specific genetic features were identified, including genetic variants in the HIST1H1E and UQCRHL genes and fusion transcripts containing MALAT1 non-coding RNA, which is known to be a prognostic indicator for breast cancer and stimulated by estrogen. In summary, these findings highlight novel candidate targets for improved treatment of 8p11-p12 amplified breast carcinomas.

A site specific model and analysis of the neutral somatic mutation rate in whole-genome cancer data

Background

Detailed modelling of the neutral mutational process in cancer cells is crucial for identifying driver mutations and understanding the mutational mechanisms that act during cancer development. The neutral mutational process is very complex: whole-genome analyses have revealed that the mutation rate differs between cancer types, between patients and along the genome depending on the genetic and epigenetic context. Therefore, methods that predict the number of different types of mutations in regions or specific genomic elements must consider local genomic explanatory variables. A major drawback of most methods is the need to average the explanatory variables across the entire region or genomic element. This procedure is particularly problematic if the explanatory variable varies dramatically in the element under consideration.

Results

To take into account the fine scale of the explanatory variables, we model the probabilities of different types of mutations for each position in the genome by multinomial logistic regression. We analyse 505 cancer genomes from 14 different cancer types and compare the performance in predicting mutation rate for both regional based models and site-specific models. We show that for 1000 randomly selected genomic positions, the site-specific model predicts the mutation rate much better than regional based models.

We use a forward selection procedure to identify the most important explanatory variables. The procedure identifies site-specific conservation (phyloP), replication timing, and expression level as the best predictors for the mutation rate. Finally, our model confirms and quantifies certain well-known mutational signatures.

Conclusion

We find that our site-specific multinomial regression model outperforms the regional based models. The possibility of including genomic variables on different scales and patient specific variables makes it a versatile framework for studying different mutational mechanisms. Our model can serve as the neutral null model for the mutational process; regions that deviate from the null model are candidates for elements that drive cancer development.

Electronic supplementary material

The online version of this article (10.1186/s12859-018-2141-2) contains supplementary material, which is available to authorized users.

A global transcriptional network connecting noncoding mutations to changes in tumor gene expression

Although cancer genomes are replete with noncoding mutations, the effects of these mutations remain poorly characterized. Here we perform an integrative analysis of 930 tumor whole genomes and matched transcriptomes, identifying a network of 193 noncoding loci in which mutations disrupt target gene expression. These “somatic eQTLs” (expression Quantitative Trait Loci) are frequently mutated in specific cancer tissues, and the majority can be validated in an independent cohort of 3,382 tumors. Among these, we find that the effects of noncoding mutations on DAAM1, MTG2 and HYI transcription are recapitulated in multiple cancer cell lines, and that increasing DAAM1 expression leads to invasive cell migration. Collectively the noncoding loci converge on a set of core pathways, permitting a classification of tumors into pathway-based subtypes. The somatic eQTL network is disrupted in 88% of tumors, suggesting widespread impact of noncoding mutations in cancer.

Mechanisms of human telomerase reverse transcriptase (hTERT) regulation: clinical impacts in cancer

Background

Limitless self-renewal is one of the hallmarks of cancer and is attained by telomere maintenance, essentially through telomerase (hTERT) activation. Transcriptional regulation of hTERT is believed to play a major role in telomerase activation in human cancers.

Main body

The dominant interest in telomerase results from its role in cancer. The role of telomeres and telomere maintenance mechanisms is well established as a major driving force in generating chromosomal and genomic instability. Cancer cells have acquired the ability to overcome their fate of senescence via telomere length maintenance mechanisms, mainly by telomerase activation.

hTERT expression is up-regulated in tumors via multiple genetic and epigenetic mechanisms including hTERT amplifications, hTERT structural variants, hTERT promoter mutations and epigenetic modifications through hTERT promoter methylation. Genetic (hTERT promoter mutations) and epigenetic (hTERT promoter methylation and miRNAs) events were shown to have clinical implications in cancers that depend on hTERT activation. Knowing that telomeres are crucial for cellular self-renewal, the mechanisms responsible for telomere maintenance have a crucial role in cancer diseases and might be important oncological biomarkers. Thus, rather than quantifying TERT expression and its correlation with telomerase activation, the discovery and the assessment of the mechanisms responsible for TERT upregulation offers important information that may be used for diagnosis, prognosis, and treatment monitoring in oncology. Furthermore, a better understanding of these mechanisms may promote their translation into effective targeted cancer therapies.

Conclusion

Herein, we reviewed the underlying mechanisms of hTERT regulation, their role in oncogenesis, and the potential clinical applications in telomerase-dependent cancers.

Whole genome sequencing analysis for cancer genomics and precision medicine

Explosive advances in next-generation sequencer (NGS) and computational analyses have enabled exploration of somatic protein-altered mutations in most cancer types, with coding mutation data intensively accumulated. However, there is limited information on somatic mutations in non-coding regions, including introns, regulatory elements and non-coding RNA. Structural variants and pathogen in cancer genomes remain widely unexplored. Whole genome sequencing (WGS) approaches can be used to comprehensively explore all types of genomic alterations in cancer and help us to better understand the whole landscape of driver mutations and mutational signatures in cancer genomes and elucidate the functional or clinical implications of these unexplored genomic regions and mutational signatures. This review describes recently developed technical approaches for cancer WGS and the future direction of cancer WGS, and discusses its utility and limitations as an analysis platform and for mutation interpretation for cancer genomics and cancer precision medicine. Taking into account the diversity of cancer genomes and phenotypes, interpretation of abundant mutation information from WGS, especially non-coding and structure variants, requires the analysis of large-scale WGS data integrated with RNA-Seq, epigenomics, immuno-genomic and clinic-pathological information.

Thyroid transcription factor FOXE1 interacts with ETS factor ELK1 to co-regulate TERT

BACKGROUND

Although FOXE1 was initially recognized for its role in thyroid organogenesis, more recently a strong association has been identified between the FOXE1 locus and thyroid cancer. The role of FOXE1 in adult thyroid, and in particular regarding cancer risk, has not been well established. We hypothesised that discovering key FOXE1 transcriptional partners would in turn identify regulatory pathways relevant to its role in oncogenesis.

RESULTS

In a transcription factor-binding array, ELK1 was identified to bind FOXE1. We confirmed this physical association in heterologously transfected cells by IP and mammalian two-hybrid assays. In thyroid tissue, endogenous FOXE1 was shown to bind ELK1, and using ChIP assays these factors bound thyroid-relevant gene promoters TPO and TERT in close proximity to each other. Using a combination of electromobility shift assays, TERT promoter assays and siRNA-silencing, we found that FOXE1 positively regulated TERT expression in a manner dependent upon its association with ELK1. Treating heterologously transfected thyroid cells with MEK inhibitor U0126 inhibited FOXE1-ELK1 interaction, and reduced TERT and TPO promoter activity.

METHODOLOGY

We investigated FOXE1 interactions within in vitro thyroid cell models and human thyroid tissue using a combination of immunoprecipitation (IP), chromatin IP (ChIP) and gene reporter assays.

CONCLUSIONS

FOXE1 interacts with ELK1 on thyroid relevant gene promoters, establishing a new regulatory pathway for its role in adult thyroid function. Co-regulation of TERT suggests a mechanism by which allelic variants in/near FOXE1 are associated with thyroid cancer risk.

Telomere Length Dynamics and the Evolution of Cancer Genome Architecture

Telomeres are progressively eroded during repeated rounds of cell division due to the end replication problem but also undergo additional more substantial stochastic shortening events. In most cases, shortened telomeres induce a cell-cycle arrest or trigger apoptosis, although for those cells that bypass such signals during tumour progression, a critical length threshold is reached at which telomere dysfunction may ensue. Dysfunction of the telomere nucleoprotein complex can expose free chromosome ends to the DNA double-strand break (DSB) repair machinery, leading to telomere fusion with both telomeric and non-telomeric loci. The consequences of telomere fusions in promoting genome instability have long been appreciated through the breakage-fusion-bridge (BFB) cycle mechanism, although recent studies using high-throughput sequencing technologies have uncovered evidence of involvement in a wider spectrum of genomic rearrangements including chromothripsis. A critical step in cancer progression is the transition of a clone to immortality, through the stabilisation of the telomere repeat array. This can be achieved via the reactivation of telomerase, or the induction of the alternative lengthening of telomeres (ALT) pathway. Whilst telomere dysfunction may promote genome instability and tumour progression, by limiting the replicative potential of a cell and enforcing senescence, telomere shortening can act as a tumour suppressor mechanism. However, the burden of senescent cells has also been implicated as a driver of ageing and age-related pathology, and in the promotion of cancer through inflammatory signalling. Considering the critical role of telomere length in governing cancer biology, we review questions related to the prognostic value of studying the dynamics of telomere shortening and fusion, and discuss mechanisms and consequences of telomere-induced genome rearrangements.

Identification of Single Nucleotide Non-coding Driver Mutations in Cancer

Recent whole-genome sequencing studies have identified millions of somatic variants present in tumor samples. Most of these variants reside in non-coding regions of the genome potentially affecting transcriptional and post-transcriptional gene regulation. Although a few hallmark examples of driver mutations in non-coding regions have been reported, the functional role of the vast majority of somatic non-coding variants remains to be determined. This is because the few driver variants in each sample must be distinguished from the thousands of passenger variants and because the logic of regulatory element function has not yet been fully elucidated. Thus, variants prioritized based on mutational burden and location within regulatory elements need to be validated experimentally. This is generally achieved by combining assays that measure physical binding, such as chromatin immunoprecipitation, with those that determine regulatory activity, such as luciferase reporter assays. Here, we present an overview of in silico approaches used to prioritize somatic non-coding variants and the experimental methods used for functional validation and characterization.

Combining molecular and immunohistochemical analyses of key drivers in primary melanomas: interplay between germline and somatic variations

Due to the high mutational somatic burden of Cutaneous Malignant Melanoma (CMM) a thorough profiling of the driver mutations and their interplay is necessary to explain the timing of tumorigenesis or for the identification of actionable genetic events. The aim of this study was to establish the mutation rate of some of the key drivers in melanoma tumorigenesis combining molecular analyses and/or immunohistochemistry in 93 primary CMMs from an Italian cohort also characterized for germline status, and to investigate an interplay between germline and somatic variants. BRAF mutations were present in 68% of cases, while CDKN2A germline mutations were found in 16 % and p16 loss in tissue was found in 63%. TERT promoter somatic mutations were detected in 38% of cases while the TERT -245T>C polymorphism was found in 51% of cases. NRAS mutations were found in 39% of BRAF negative or undetermined cases. NF1 was expressed in all cases analysed. MC1R variations were both considered as a dichotomous variable or scored. While a positive, although not significant association between CDKN2A germline mutations, but not MC1R variants, and BRAF somatic mutation was found, we did not observe other associations between germline and somatic events. A yet undescribed inverse correlation between TERT -245T>C polymorphism and the presence of BRAF mutation was found. It is possible to hypothesize that -245T>C polymorphism could be included in those genotypes which may influence the occurrence of BRAF mutations. Further studies are needed to investigate the role of -245T>C polymorphism as a germline predictor of BRAF somatic mutation status.

Pan-cancer screen for mutations in non-coding elements with conservation and cancer specificity reveals correlations with expression and survival

Cancer develops by accumulation of somatic driver mutations, which impact cellular function. Mutations in non-coding regulatory regions can now be studied genome-wide and further characterized by correlation with gene expression and clinical outcome to identify driver candidates. Using a new two-stage procedure, called ncDriver, we first screened 507 ICGC whole-genomes from 10 cancer types for non-coding elements, in which mutations are both recurrent and have elevated conservation or cancer specificity. This identified 160 significant non-coding elements, including the TERT promoter, a well-known non-coding driver element, as well as elements associated with known cancer genes and regulatory genes (e.g., PAX5, TOX3, PCF11, MAPRE3). However, in some significant elements, mutations appear to stem from localized mutational processes rather than recurrent positive selection in some cases. To further characterize the driver potential of the identified elements and shortlist candidates, we identified elements where presence of mutations correlated significantly with expression levels (e.g., TERT and CDH10) and survival (e.g., CDH9 and CDH10) in an independent set of 505 TCGA whole-genome samples. In a larger pan-cancer set of 4128 TCGA exomes with expression profiling, we identified mutational correlation with expression for additional elements (e.g., near GATA3, CDC6, ZNF217, and CTCF transcription factor binding sites). Survival analysis further pointed to MIR122, a known marker of poor prognosis in liver cancer. In conclusion, the screen for significant mutation patterns coupled with correlative mutational analysis identified new individual driver candidates and suggest that some non-coding mutations recurrently affect expression and play a role in cancer development.

Mutations in the “non-coding” part of the genome have been identified that could be involved in driving cancer development. Jakob Pedersen, Henrik Hornshøj and colleagues from Aarhus University Hospital in Denmark and MIT in the United States developed a two-stage procedure to identify elements that could be driving cancer development in the part of DNA that does not code for proteins. They conducted statisical analyses on catalogs of tumor genomes to identify recurrent mutations. They then evaluated how specific these mutations were to different cancer types, their predicted functional impact, and their association with gene expression and patient survival. The analyses identified mutations in the non-coding part of cancer genomes that could be driving tumor development, but further analyses on larger sample sets need to be conducted to validate the results, which could provide a basis for biomarker discovery and precision medical treatment.

Precision oncology in the age of integrative genomics

Precision oncology applies genomic and other molecular analyses of tumor biopsies to improve the diagnosis and treatment of cancers. In addition to identifying therapeutic options, precision oncology tracks the response of a tumor to an intervention at the molecular level and detects drug resistance and the mechanisms by which it occurs. Integrative genomics can include sequencing specific panels of genes, exomes, or the entire triad of the patient's germline, tumor exome, and tumor transcriptome. Although the capabilities of sequencing technologies continue to improve, widespread adoption of genomics-driven precision oncology in the clinic has been held back by logistical, regulatory, financial, and ethical considerations. Nevertheless, integrative clinical sequencing programs applied at the point of care have the potential to improve the clinical management of cancer patients.

Individualized network-based drug repositioning infrastructure for precision oncology in the panomics era

Advances in next-generation sequencing technologies have generated the data supporting a large volume of somatic alterations in several national and international cancer genome projects, such as The Cancer Genome Atlas and the International Cancer Genome Consortium. These cancer genomics data have facilitated the revolution of a novel oncology drug discovery paradigm from candidate target or gene studies toward targeting clinically relevant driver mutations or molecular features for precision cancer therapy. This focuses on identifying the most appropriately targeted therapy to an individual patient harboring a particularly genetic profile or molecular feature. However, traditional experimental approaches that are used to develop new chemical entities for targeting the clinically relevant driver mutations are costly and high-risk. Drug repositioning, also known as drug repurposing, re-tasking or re-profiling, has been demonstrated as a promising strategy for drug discovery and development. Recently, computational techniques and methods have been proposed for oncology drug repositioning and identifying pharmacogenomics biomarkers, but overall progress remains to be seen. In this review, we focus on introducing new developments and advances of the individualized network-based drug repositioning approaches by targeting the clinically relevant driver events or molecular features derived from cancer panomics data for the development of precision oncology drug therapies (e.g. one-person trials) to fully realize the promise of precision medicine. We discuss several potential challenges (e.g. tumor heterogeneity and cancer subclones) for precision oncology. Finally, we highlight several new directions for the precision oncology drug discovery via biotherapies (e.g. gene therapy and immunotherapy) that target the 'undruggable' cancer genome in the functional genomics era.

Circular RNA expression is abundant and correlated to aggressiveness in early-stage bladder cancer

The functions and biomarker potential of circular RNAs (circRNAs) in various cancer types are a rising field of study, as emerging evidence relates circRNAs to tumorigenesis. Here, we profiled the expression of circRNAs in 457 tumors from patients with non-muscle-invasive bladder cancer (NMIBC). We show that a set of highly expressed circRNAs have conserved core splice sites, are associated with Alu repeats, and enriched with Synonymous Constraint Elements as well as microRNA target sites. We identified 113 abundant circRNAs that are differentially expressed between high and low-risk tumor subtypes. Analysis of progression-free survival revealed 13 circRNAs, among them circHIPK3 and circCDYL, where expression correlated with progression independently of the linear transcript and the host gene. In summary, our results demonstrate that abundant circRNAs possess multiple biological features, distinguishing them from low-expressed circRNAs and non-circularized exons, and suggest that circRNAs might serve as a new class of prognostic biomarkers in NMIBC.

Expression levels of non-coding “circular” RNA molecules could be used as a prognostic biomarker for patients with early-stage bladder cancer. A team led by Trine Line Hauge Okholm and Jakob Skou Pedersen from Aarhus University Hospital, Denmark, profiled the expression of these loop-forming, potentially gene-regulating RNAs in biopsied tumor samples from 457 patients with bladder cancer that had not invaded nearby muscle tissue. They identified a suite of 113 circular RNAs that were abundant and differentially expressed between patients with different molecular subtypes of bladder cancer. The researchers also found a smaller set of 13 circular RNAs for which expression levels correlated with disease progression. These non-coding RNA molecules, by indicating likely patient outcomes, could potentially serve as future diagnostic aids to inform treatment strategies and decisions.

Understanding the Molecular Genetics of Basal Cell Carcinoma

Basal cell carcinoma (BCC) is the most common human cancer and represents a growing public health care problem. Several tumor suppressor genes and proto-oncogenes have been implicated in BCC pathogenesis, including the key components of the Hedgehog pathway, PTCH1 and SMO, the TP53 tumor suppressor, and members of the RAS proto-oncogene family. Aberrant activation of the Hedgehog pathway represents the molecular driver in basal cell carcinoma pathogenesis, with the majority of BCCs carrying somatic point mutations, mainly ultraviolet (UV)-induced, and/or copy-loss of heterozygosis in the PTCH1 gene. Recent advances in sequencing technology allowed genome-scale approaches to mutation discovery, identifying new genes and pathways potentially involved in BCC carcinogenesis. Mutational and functional analysis suggested PTPN14 and LATS1, both effectors of the Hippo–YAP pathway, and MYCN as new BCC-associated genes. In addition, emerging reports identified frequent non-coding mutations within the regulatory promoter sequences of the TERT and DPH3-OXNAD1 genes. Thus, it is clear that a more complex genetic network of cancer-associated genes than previously hypothesized is involved in BCC carcinogenesis, with a potential impact on the development of new molecular targeted therapies. This article reviews established knowledge and new hypotheses regarding the molecular genetics of BCC pathogenesis.

Universal Patterns of Selection in Cancer and Somatic Tissues

Cancer develops as a result of somatic mutation and clonal selection, but quantitative measures of selection in cancer evolution are lacking. We adapted methods from molecular evolution and applied them to 7,664 tumors across 29 cancer types. Unlike species evolution, positive selection outweighs negative selection during cancer development. On average, <1 coding base substitution/tumor is lost through negative selection, with purifying selection almost absent outside homozygous loss of essential genes. This allows exome-wide enumeration of all driver coding mutations, including outside known cancer genes. On average, tumors carry ∼4 coding substitutions under positive selection, ranging from <1/tumor in thyroid and testicular cancers to >10/tumor in endometrial and colorectal cancers. Half of driver substitutions occur in yet-to-be-discovered cancer genes. With increasing mutation burden, numbers of driver mutations increase, but not linearly. We systematically catalog cancer genes and show that genes vary extensively in what proportion of mutations are drivers versus passengers.

Genomic Instability of iPSCs: Challenges Towards Their Clinical Applications

Induced pluripotent stem cells (iPSCs) are a type of pluripotent stem cells generated directly from mature cells through the introduction of key transcription factors. iPSCs can be propagated and differentiated into many cell types in the human body, holding enormous potential in the field of regenerative medicine. However, genomic instability of iPSCs has been reported with the advent of high-throughput technologies such as next-generation sequencing. The presence of genetic variations in iPSCs has raised serious safety concerns, hampering the advancement of iPSC-based novel therapies. Here we summarize our current knowledge on genomic instability of iPSCs, with a particular focus on types of genetic variations and their origins. Importantly, it remains elusive whether genetic variations in iPSCs can be an actual risk factor for adverse effects including malignant outgrowth. Furthermore, we discuss novel approaches to generate iPSCs with fewer genetic variations. Lastly, we outline the safety issues and monitoring strategies of iPSCs in clinical settings.

Reduced mutation rate in exons due to differential mismatch repair

While recent studies have identified higher than anticipated heterogeneity of mutation rate across genomic regions, mutations in exons and introns are assumed to be generated at the same rate. Here we find fewer somatic mutations in exons than expected from their sequence content and demonstrate that this is not due to purifying selection. Instead, we show that it is caused by higher mismatch-repair activity in exonic than in intronic regions. Our findings have important implications for understanding of mutational and DNA repair processes and knowledge of the evolution of eukaryotic genes, and they have practical ramifications for the study of evolution of both tumors and species.

Genomic Hallmarks of Thyroid Neoplasia

The genomic landscape of thyroid cancers that are derived from follicular cells has been substantially elucidated through the coordinated application of high-throughput genomic technologies. Here, I review the common genetic alterations across the spectrum of thyroid neoplasia and present the resulting model of thyroid cancer initiation and progression. This model illustrates the striking correlation between tumor differentiation and overall somatic mutational burden, which also likely explains the highly variable clinical behavior and outcome of patients with thyroid cancers. These advances are yielding critical insights into thyroid cancer pathogenesis, which are being leveraged for the development of new diagnostic tools, prognostic and predictive biomarkers, and novel therapeutic approaches.

Revealing the Determinants of Widespread Alternative Splicing Perturbation in Cancer

It is increasingly appreciated that alternative splicing plays a key role in generating functional specificity and diversity in cancer. However, the mechanisms by which cancer mutations perturb splicing remain unknown. Here, we developed a network-based strategy, DrAS-Net, to investigate more than 2.5 million variants across cancer types and link somatic mutations with cancer-specific splicing events. We identified more than 40,000 driver variant candidates and their 80,000 putative splicing targets deregulated in 33 cancer types and inferred their functional impact. Strikingly, tumors with splicing perturbations show reduced expression of immune system-related genes and increased expression of cell proliferation markers. Tumors harboring different mutations in the same gene often exhibit distinct splicing perturbations. Further stratification of 10,000 patients based on their mutation-splicing relationships identifies subtypes with distinct clinical features, including survival rates. Our work reveals how single-nucleotide changes can alter the repertoires of splicing isoforms, providing insights into oncogenic mechanisms for precision medicine.

The MeLiM Minipig: An Original Spontaneous Model to Explore Cutaneous Melanoma Genetic Basis

Melanoma is the deadliest skin cancer and is a major public health concern with a growing incidence worldwide. As for other complex diseases, animal models are needed in order to better understand the mechanisms leading to pathology, identify potential biomarkers to be used in the clinics, and eventually molecular targets for therapeutic solutions. Cutaneous melanoma, arising from skin melanocytes, is mainly caused by environmental factors such as UV radiation; however a significant genetic component participates in the etiology of the disease. The pig is a recognized model for spontaneous development of melanoma with features similar to the human ones, followed by a complete regression and a vitiligo-like depigmentation. Three different pig models (MeLiM, Sinclair, and MMS-Troll) have been maintained through the last decades, and different genetic studies have evidenced a complex inheritance of the disease. As in humans, pigmentation seems to play a prominent role, notably through MC1R and MITF signaling. Conversely, cell cycle genes as CDKN2A and CDK4 have been excluded as predisposing for melanoma in MeLiM. So far, only sparse studies have focused on somatic changes occurring during oncogenesis, and have revealed major cytological changes and a potential dysfunction of the telomere maintenance system. Finally, the spontaneous tumor progression and regression occurring in these models could shed light on the interplay between endogenous retroviruses, melanomagenesis, and adaptive immune response.

Functional assessment of CTCF sites at cytokine-sensing mammary enhancers using CRISPR/Cas9 gene editing in mice

The zinc finger protein CTCF has been invoked in establishing boundaries between genes, thereby controlling spatial and temporal enhancer activities. However, there is limited genetic evidence to support the concept that these boundaries restrict the search space of enhancers. We have addressed this question in the casein locus containing five mammary and two non-mammary genes under the control of at least seven putative enhancers. We have identified two CTCF binding sites flanking the locus and two associated with a super-enhancer. Individual deletion of these sites from the mouse genome did not alter expression of any of the genes. However, deletion of the border CTCF site separating the Csn1s1 mammary enhancer from neighboring genes resulted in the activation of Sult1d1 at a distance of more than 95 kb but not the more proximal and silent Sult1e1 gene. Loss of this CTCF site led to de novo interactions between the Sult1d1 promoter and several enhancers in the casein locus. Our study demonstrates that only one out of the four CTCF sites in the casein locus had a measurable in vivo activity. Studies on additional loci are needed to determine the biological role of CTCF sites associated with enhancers.

Identifying DNase I hypersensitive sites as driver distal regulatory elements in breast cancer

Efforts to identify driver mutations in cancer have largely focused on genes, whereas non-coding sequences remain relatively unexplored. Here we develop a statistical method based on characteristics known to influence local mutation rate and a series of enrichment filters in order to identify distal regulatory elements harboring putative driver mutations in breast cancer. We identify ten DNase I hypersensitive sites that are significantly mutated in breast cancers and associated with the aberrant expression of neighboring genes. A pan-cancer analysis shows that three of these elements are significantly mutated across multiple cancer types and have mutation densities similar to protein-coding driver genes. Functional characterization of the most highly mutated DNase I hypersensitive sites in breast cancer (using in silico and experimental approaches) confirms that they are regulatory elements and affect the expression of cancer genes. Our study suggests that mutations of regulatory elements in tumors likely play an important role in cancer development.

Cancer driver mutations can occur within noncoding genomic sequences. Here, the authors develop a statistical approach to identify candidate noncoding driver mutations in DNase I hypersensitive sites in breast cancer and experimentally demonstrate they are regulatory elements of known cancer genes.

Overexpressed somatic alleles are enriched in functional elements in Breast Cancer

Asymmetric allele content in the transcriptome can be indicative of functional and selective features of the underlying genetic variants. Yet, imbalanced alleles, especially from diploid genome regions, are poorly explored in cancer. Here we systematically quantify and integrate the variant allele fraction from corresponding RNA and DNA sequence data from patients with breast cancer acquired through The Cancer Genome Atlas (TCGA). We test for correlation between allele prevalence and functionality in known cancer-implicated genes from the Cancer Gene Census (CGC). We document significant allele-preferential expression of functional variants in CGC genes and across the entire dataset. Notably, we find frequent allele-specific overexpression of variants in tumor-suppressor genes. We also report a list of over-expressed variants from non-CGC genes. Overall, our analysis presents an integrated set of features of somatic allele expression and points to the vast information content of the asymmetric alleles in the cancer transcriptome.

Induced Pluripotent Stem Cells Meet Genome Editing

It is extremely rare for a single experiment to be so impactful and timely that it shapes and forecasts the experiments of the next decade. Here, we review how two such experiments-the generation of human induced pluripotent stem cells (iPSCs) and the development of CRISPR/Cas9 technology-have fundamentally reshaped our approach to biomedical research, stem cell biology, and human genetics. We will also highlight the previous knowledge that iPSC and CRISPR/Cas9 technologies were built on as this groundwork demonstrated the need for solutions and the benefits that these technologies provided and set the stage for their success.

Whole-Genome and Epigenomic Landscapes of Etiologically Distinct Subtypes of Cholangiocarcinoma

Cholangiocarcinoma (CCA) is a hepatobiliary malignancy exhibiting high incidence in countries with endemic liver-fluke infection. We analyzed 489 CCAs from 10 countries, combining whole-genome (71 cases), targeted/exome, copy-number, gene expression, and DNA methylation information. Integrative clustering defined 4 CCA clusters-fluke-positive CCAs (clusters 1/2) are enriched in ERBB2 amplifications and TP53 mutations; conversely, fluke-negative CCAs (clusters 3/4) exhibit high copy-number alterations and PD-1/PD-L2 expression, or epigenetic mutations (IDH1/2, BAP1) and FGFR/PRKA-related gene rearrangements. Whole-genome analysis highlighted FGFR2 3' untranslated region deletion as a mechanism of FGFR2 upregulation. Integration of noncoding promoter mutations with protein-DNA binding profiles demonstrates pervasive modulation of H3K27me3-associated sites in CCA. Clusters 1 and 4 exhibit distinct DNA hypermethylation patterns targeting either CpG islands or shores-mutation signature and subclonality analysis suggests that these reflect different mutational pathways. Our results exemplify how genetics, epigenetics, and environmental carcinogens can interplay across different geographies to generate distinct molecular subtypes of cancer.Significance: Integrated whole-genome and epigenomic analysis of CCA on an international scale identifies new CCA driver genes, noncoding promoter mutations, and structural variants. CCA molecular landscapes differ radically by etiology, underscoring how distinct cancer subtypes in the same organ may arise through different extrinsic and intrinsic carcinogenic processes. Cancer Discov; 7(10); 1116-35. ©2017 AACR.This article is highlighted in the In This Issue feature, p. 1047.

Recurrent and functional regulatory mutations in breast cancer

Genomic analysis of tumours has led to the identification of hundreds of cancer genes on the basis of the presence of mutations in protein-coding regions. By contrast, much less is known about cancer-causing mutations in non-coding regions. Here we perform deep sequencing in 360 primary breast cancers and develop computational methods to identify significantly mutated promoters. Clear signals are found in the promoters of three genes. FOXA1, a known driver of hormone-receptor positive breast cancer, harbours a mutational hotspot in its promoter leading to overexpression through increased E2F binding. RMRP and NEAT1, two non-coding RNA genes, carry mutations that affect protein binding to their promoters and alter expression levels. Our study shows that promoter regions harbour recurrent mutations in cancer with functional consequences and that the mutations occur at similar frequencies as in coding regions. Power analyses indicate that more such regions remain to be discovered through deep sequencing of adequately sized cohorts of patients.

Computational Methods for Characterizing Cancer Mutational Heterogeneity

Advances in DNA sequencing technologies have allowed the characterization of somatic mutations in a large number of cancer genomes at an unprecedented level of detail, revealing the extreme genetic heterogeneity of cancer at two different levels: inter-tumor, with different patients of the same cancer type presenting different collections of somatic mutations, and intra-tumor, with different clones coexisting within the same tumor. Both inter-tumor and intra-tumor heterogeneity have crucial implications for clinical practices. Here, we review computational methods that use somatic alterations measured through next-generation DNA sequencing technologies for characterizing tumor heterogeneity and its association with clinical variables. We first review computational methods for studying inter-tumor heterogeneity, focusing on methods that attempt to summarize cancer heterogeneity by discovering pathways that are commonly mutated across different patients of the same cancer type. We then review computational methods for characterizing intra-tumor heterogeneity using information from bulk sequencing data or from single cell sequencing data. Finally, we present some of the recent computational methodologies that have been proposed to identify and assess the association between inter- or intra-tumor heterogeneity with clinical variables.

Mutational Signatures Are Critical for Proper Estimation of Purifying Selection Pressures in Cancer Somatic Mutation Data When Using the dN/dS Metric

Large cancer genome sequencing initiatives have led to the identification of cancer driver genes based on signals of positive selection in somatic mutation data. Additionally, the identification of purifying (negative) selection has the potential to identify essential genes that may be of therapeutic interest. The most widely used way of quantifying selection pressures in protein-coding genes is the dN/dS metric, which compares non-synonymous to synonymous substitution rates. In this study, we examine whether and how this metric is influenced by the mutational processes that have been active during tumor evolution. We use exome sequencing data from six different cancer types from The Cancer Genome Atlas (TCGA) and demonstrate that dN/dS in its basic form, where uniform base substitution probabilities are assumed, is in fact strongly biased by these mutational processes. This is particularly true in malignant melanoma, where the mutational signature is characterized by a high amount of UV-induced cytosine to thymine mutations at dipyrimidine dinucleotides. This increases the likelihood of random synonymous mutations occurring in hydrophobic amino acid codons, leading to reduced dN/dS ratios in genes encoding membrane proteins and falsely suggesting purifying selection in these genes. When this effect is corrected for by taking mutational signature-derived substitution probabilities into account, purifying selection was found to be limited and similar in all cancer types studied. Our results demonstrate that it is crucial to take mutational signatures into account when applying the dN/dS metric to cancer somatic mutation data.

Recurrent noncoding regulatory mutations in pancreatic ductal adenocarcinoma

The contributions of coding mutations to tumorigenesis are relatively well known; however, little is known about somatic alterations in noncoding DNA. Here we describe GECCO (Genomic Enrichment Computational Clustering Operation) to analyze somatic noncoding alterations in 308 pancreatic ductal adenocarcinomas (PDAs) and identify commonly mutated regulatory regions. We find recurrent noncoding mutations to be enriched in PDA pathways, including axon guidance and cell adhesion, and newly identified processes, including transcription and homeobox genes. We identified mutations in protein binding sites correlating with differential expression of proximal genes and experimentally validated effects of mutations on expression. We developed an expression modulation score that quantifies the strength of gene regulation imposed by each class of regulatory elements, and found the strongest elements were most frequently mutated, suggesting a selective advantage. Our detailed single-cancer analysis of noncoding alterations identifies regulatory mutations as candidates for diagnostic and prognostic markers, and suggests new mechanisms for tumor evolution.

A mutated dph3 gene causes sensitivity of Schizosaccharomyces pombe cells to cytotoxic agents

Dph3 is involved in diphthamide modification of the eukaryotic translation elongation factor eEF2 and in Elongator-mediated modifications of tRNAs, where a 5-methoxycarbonyl-methyl moiety is added to wobble uridines. Lack of such modifications affects protein synthesis due to inaccurate translation of mRNAs at ribosomes. We have discovered that integration of markers at the msh3 locus of Schizosaccharomyces pombe impaired the function of the nearby located dph3 gene. Such integrations rendered cells sensitive to the cytotoxic drugs hydroxyurea and methyl methanesulfonate. We constructed dph3 and msh3 strains with mutated ATG start codons (ATGmut), which allowed investigating drug sensitivity without potential interference by marker insertions. The dph3-ATGmut and a dph3::loxP-ura4-loxM gene disruption strain, but not msh3-ATGmut, turned out to be sensitive to hydroxyurea and methyl methanesulfonate, likewise the strains with cassettes integrated at the msh3 locus. The fungicide sordarin, which inhibits diphthamide modified eEF2 of Saccharomyces cerevisiae, barely affected survival of wild type and msh3Δ S. pombe cells, while the dph3Δ mutant was sensitive. The msh3-ATG mutation, but not dph3Δ or the dph3-ATG mutation caused a defect in mating-type switching, indicating that the ura4 marker at the dph3 locus did not interfere with Msh3 function. We conclude that Dph3 is required for cellular resistance to the fungicide sordarin and to the cytotoxic drugs hydroxyurea and methyl methanesulfonate. This is likely mediated by efficient translation of proteins in response to DNA damage and replication stress.

Recurrent promoter mutations in melanoma are defined by an extended context-specific mutational signature

Sequencing of whole tumor genomes holds the promise of revealing functional somatic regulatory mutations, such as those described in the TERT promoter. Recurrent promoter mutations have been identified in many additional genes and appear to be particularly common in melanoma, but convincing functional data such as influence on gene expression has been more elusive. Here, we show that frequently recurring promoter mutations in melanoma occur almost exclusively at cytosines flanked by a distinct sequence signature, TTCCG, with TERT as a notable exception. In active, but not inactive, promoters, mutation frequencies for cytosines at the 5’ end of this ETS-like motif were considerably higher than expected based on a UV trinucleotide mutational signature. Additional analyses solidify this pattern as an extended context-specific mutational signature that mediates an exceptional position-specific vulnerability to UV mutagenesis, arguing against positive selection. We further use ultra-sensitive amplicon sequencing to demonstrate that cell cultures exposed to UV light quickly develop subclonal mutations specifically in affected positions. Our findings have implications for the interpretation of somatic mutations in regulatory regions, and underscore the importance of genomic context and extended sequence patterns to accurately describe mutational signatures in cancer.

Cancer is caused by somatic mutations that alter cell behavior. While such mutations typically occur in protein-coding genes, recent studies describe individual positions in gene regulatory regions (promoters) that are recurrently mutated in many independent tumors. This suggests that positive selection could be acting on these non-coding mutations, and that they may contribute to carcinogenesis. However, proper interpretation of recurrent mutations requires a detailed understanding of how such mutations arise in the absence of selection pressures, referred to as mutational heterogeneity. In this paper, we describe a distinct sequence signature that characterizes nearly all highly recurrent promoter mutations in melanoma. Additional analyses support that this sequence mediates an exceptional local vulnerability to UV-induced mutagenesis, explaining why mutations are frequently observed in these positions. Importantly, cultured cells exposed to UV light quickly developed mutations specifically in the expected sites. Our results have important implications for the interpretation of recurrent somatic mutation patterns in non-coding DNA.

Whole-genome landscapes of major melanoma subtypes

Melanoma of the skin is a common cancer only in Europeans, whereas it arises in internal body surfaces (mucosal sites) and on the hands and feet (acral sites) in people throughout the world. Here we report analysis of whole-genome sequences from cutaneous, acral and mucosal subtypes of melanoma. The heavily mutated landscape of coding and non-coding mutations in cutaneous melanoma resolved novel signatures of mutagenesis attributable to ultraviolet radiation. However, acral and mucosal melanomas were dominated by structural changes and mutation signatures of unknown aetiology, not previously identified in melanoma. The number of genes affected by recurrent mutations disrupting non-coding sequences was similar to that affected by recurrent mutations to coding sequences. Significantly mutated genes included BRAF, CDKN2A, NRAS and TP53 in cutaneous melanoma, BRAF, NRAS and NF1 in acral melanoma and SF3B1 in mucosal melanoma. Mutations affecting the TERT promoter were the most frequent of all; however, neither they nor ATRX mutations, which correlate with alternative telomere lengthening, were associated with greater telomere length. Most melanomas had potentially actionable mutations, most in components of the mitogen-activated protein kinase and phosphoinositol kinase pathways. The whole-genome mutation landscape of melanoma reveals diverse carcinogenic processes across its subtypes, some unrelated to sun exposure, and extends potential involvement of the non-coding genome in its pathogenesis.

Altered TERT promoter and other genomic regulatory elements: occurrence and impact

Study of genetic alterations, inherited or acquired, that increase the risk or drive cancers and many other diseases had remained mostly confined to coding sequences of the human genome. Data from genome wide associations studies, development of the Encyclopedia of DNA Elements (ENCODE), and a spurt in detection of driver somatic mutations have shifted focus towards noncoding regions of the human genome. The majority of genetic variants robustly associated with cancers and other syndromes identified through genome wide studies are located within noncoding regulatory regions of the genome. Genome wide techniques have put an emphasis on the role of three-dimensional chromosomal structures and cis-acting elements in regulations of different genes. The variants within noncoding genomic regions can potentially alter a number of regulatory elements including promoters, enhancers, insulators, noncoding long RNAs and others that affect cancers and various diseases through altered expression of critical genes. With effect of genetic alterations within regulatory elements dependent on other partner molecules like transcription factors and histone marks, an understanding of such modifications can potentially identify extended therapeutic targets. That concept has been augmented by the detection of driver somatic noncoding mutations within the promoter region of the telomerase reverse transcriptase (TERT) gene in different cancers. The acquired somatic noncoding mutations within different regulatory elements are now being reported in different cancers with an increased regularity. In this review we discuss the occurrence and impact of germline and somatic alterations within the TERT promoter and other genomic regulatory elements.

Intrinsic Molecular Processes: Impact on Mutagenesis

Mutations provide resources for genome evolution by generating genetic variability. In addition, mutations act as a driving force leading to disease pathogenesis, and thus have important implications for disease diagnosis, prognosis, and treatment. Understanding the mechanisms underlying how mutations occur is therefore of prime importance for elucidating evolutionary and pathogenic processes. Recent genomics studies have revealed that mutations occur non-randomly across the human genome. In particular, the distribution of mutations is highly associated with intrinsic molecular processes including transcription, chromatin organization, DNA replication timing, and DNA repair. Interplay between intrinsic processes and extrinsic mutagenic exposure may thus imprint a characteristic mutational landscape on tumors. We discuss the impact of intrinsic molecular processes on mutation acquisition in cancer.