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]

Molecular Expression of Some Oncogenes and Predisposing Behaviors Contributing to the Aggressiveness of Prostate Cancer

Background

Prostate cancer is the second most common cancer in men in Iran. It can be treated in the early stages of the disease; therefore, early diagnosis can be lifesaving. The aim of this study was to investigate the molecular expression of some oncogenes and predisposing behaviors contributing to the aggressiveness of prostate cancer.

Methods

In this case-control study, prostate cancer specimens were collected from both patients and healthy volunteers. Several factors such as age, family history, smoking, and stage of the disease, were investigated based on the criteria of this study. Real-time PCR was used to measure the expression of four oncogenes. Statistical analysis of our data was carried out using SPSS software version 22.

Results

The X² test showed that there was a difference in the incidence of prostate cancer in different age groups (X²= 9.30; p= 0.026). Although data analysis by the X² test showed that family history had a significant effect on prostate cancer (X²= 14.43; p= 0.001), smoking did not show a significant effect on the incidence of this disorder (X²= 4.67; p= 0.097). The T2N1M0 stage is the most common form of prostate cancer in patients with family history of prostate cancer and the habit of smoking. Also, the expression of KRAS1P, GLB1L2, SChLAP1 and PACSIN3 oncogenes reduced in prostate cancer samples compared to the control group.

Conclusion

Overall, functional interpretation of gene expression in the prostate tissue can affect tumor progression. Yet, further practical studies are required to reveal the accurate underlying mechanisms.

Cis-regulatory mutations with driver hallmarks in major cancers

Despite the recent availability of complete genome sequences of tumors from thousands of patients, isolating disease-causing (driver) non-coding mutations from the plethora of somatic variants remains challenging, and only a handful of validated examples exist. By integrating whole-genome sequencing, genetic data, and allele-specific gene expression from TCGA, we identified 320 somatic non-coding mutations that affect gene expression in cis (FDR<0.25). These mutations cluster into 47 cis-regulatory elements that modulate expression of their subject genes through diverse molecular mechanisms. We further show that these mutations have hallmark features of non-coding drivers; namely, that they preferentially disrupt transcription factor binding motifs, are associated with a selective advantage, increased oncogene expression and decreased tumor suppressor expression.

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Enrichment of functional non-coding somatic mutations predicts drivers

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Elevated variant allele frequencies are consistent with roles in tumorigenesis

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Putative non-coding drivers disrupt transcription factor binding motifs

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Predicted drivers associate with increased oncogene and decreased TSG expression

Pan-cancer noncoding genomic analysis identifies functional CDC20 promoter mutation hotspots

Noncoding DNA sequences occupy more than 98% of the human genome; however, few cancer noncoding drivers have been identified compared with cancer coding drivers, probably because cancer noncoding drivers have a distinct mutation pattern due to the distinct function of noncoding DNA. Here we performed pan-cancer whole genome mutation analysis to screen for functional noncoding mutations that influence protein factor binding. Recurrent mutations were identified in the promoter of CDC20 gene. These CDC20 promoter hotspot mutations disrupt the binding of ELK4 transcription repressor, lead to the up-regulation of CDC20 transcription. Physiologically ELK4 binds to the unmutated hotspot sites and is involved in DNA damage-induced CDC20 transcriptional repression. Overall, our study not only identifies a detailed mechanism for CDC20 gene deregulation in human cancers but also finds functional noncoding genetic alterations, with implications for the further development of function-based noncoding driver discovery pipelines.

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Pan-cancer noncoding analysis for mutations that influence protein factor binding

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Recurrent mutations were identified in the promoter of CDC20 gene

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Promoter hotspot mutations disrupt ELK4 binding, up-regulate CDC20 transcription

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Promoter hotspot mutation site is involved in DNA damage-induced CDC20 repression

Variable interplay of UV-induced DNA damage and repair at transcription factor binding sites

An abnormally high rate of UV-light related mutations appears at transcription factor binding sites (TFBS) across melanomas. The binding of transcription factors (TFs) to the DNA impairs the repair of UV-induced lesions and certain TFs have been shown to increase the rate of generation of these lesions at their binding sites. However, the precise contribution of these two elements to the increase in mutation rate at TFBS in these malignant cells is not understood. Here, exploiting nucleotide-resolution data, we computed the rate of formation and repair of UV-lesions within the binding sites of TFs of different families. We observed, at certain dipyrimidine positions within the binding site of TFs in the Tryptophan Cluster family, an increased rate of formation of UV-induced lesions, corroborating previous studies. Nevertheless, across most families of TFs, the observed increased mutation rate within the entire DNA region covered by the protein results from the decreased repair efficiency. While the rate of mutations across all TFBS does not agree with the amount of UV-induced lesions observed immediately after UV exposure, it strongly agrees with that observed after 48 h. This corroborates the determinant role of the impaired repair in the observed increase of mutation rate.

Systematic evaluation of the effects of genetic variants on PIWI-interacting RNA expression across 33 cancer types

PIWI-interacting RNAs (piRNAs) are an emerging class of non-coding RNAs involved in tumorigenesis. Expression quantitative trait locus (eQTL) analysis has been demonstrated to help reveal the genetic mechanism of single nucleotide polymorphisms (SNPs) in cancer etiology. However, there are no databases that have been constructed to provide an eQTL analysis between SNPs and piRNA expression. In this study, we collected genotyping and piRNA expression data for 10 997 samples across 33 cancer types from The Cancer Genome Atlas (TCGA). Using linear regression cis-eQTL analysis with adjustment of appropriate covariates, we identified millions of SNP-piRNA pairs in tumor (76 924 831) and normal (24 431 061) tissues. Further, we performed differential expression and survival analyses, and linked the eQTLs to genome-wide association study (GWAS) data to comprehensively decipher the functional roles of identified cis-piRNA eQTLs. Finally, we developed a user-friendly database, piRNA-eQTL (http://njmu-edu.cn:3838/piRNA-eQTL/), to help users query, browse and download corresponding eQTL results. In summary, piRNA-eQTL could serve as an important resource to assist the research community in understanding the roles of genetic variants and piRNAs in the development of cancers.

Telomeres: history, health, and hallmarks of aging

The escalating social and economic burden of an aging world population has placed aging research at center stage. The hallmarks of aging comprise diverse molecular mechanisms and cellular systems that are interrelated and act in concert to drive the aging process. Here, through the lens of telomere biology, we examine how telomere dysfunction may amplify or drive molecular biological processes underlying each hallmark of aging and contribute to development of age-related diseases such as neurodegeneration and cancer. The intimate link of telomeres to aging hallmarks informs preventive and therapeutic interventions designed to attenuate aging itself and reduce the incidence of age-associated diseases.

Discovery of driver non-coding splice-site-creating mutations in cancer

Non-coding mutations can create splice sites, however the true extent of how such somatic non-coding mutations affect RNA splicing are largely unexplored. Here we use the MiSplice pipeline to analyze 783 cancer cases with WGS data and 9494 cases with WES data, discovering 562 non-coding mutations that lead to splicing alterations. Notably, most of these mutations create new exons. Introns associated with new exon creation are significantly larger than the genome-wide average intron size. We find that some mutation-induced splicing alterations are located in genes important in tumorigenesis (ATRX, BCOR, CDKN2B, MAP3K1, MAP3K4, MDM2, SMAD4, STK11, TP53 etc.), often leading to truncated proteins and affecting gene expression. The pattern emerging from these exon-creating mutations suggests that splice sites created by non-coding mutations interact with pre-existing potential splice sites that originally lacked a suitable splicing pair to induce new exon formation. Our study suggests the importance of investigating biological and clinical consequences of noncoding splice-inducing mutations that were previously neglected by conventional annotation pipelines. MiSplice will be useful for automatically annotating the splicing impact of coding and non-coding mutations in future large-scale analyses.

Untangling a complex web: Computational analyses of tumor molecular profiles to decode driver mechanisms

Genome-scale studies focusing on molecular profiling of cancers across tissue types have revealed a plethora of aberrations across the genomic, transcriptomic, and epigenomic scales. The significant molecular heterogeneity across individual tumors even within the same tissue context complicates decoding the key etiologic mechanisms of this disease. Furthermore, it is increasingly likely that biologic mechanisms underlying the pathobiology of cancer involve multiple molecular entities interacting across functional scales. This has motivated the development of computational approaches that integrate molecular measurements with prior biological knowledge in increasingly intricate ways to enable the discovery of driver genomic aberrations across cancers. Here, we review diverse methodological approaches that have powered significant advances in our understanding of the genomic underpinnings of cancer at the cohort and at the individual tumor scales. We outline the key advances and challenges in the computational discovery of cancer mechanisms while motivating the development of systems biology approaches to comprehensively decode the biologic drivers of this complex disease.

Mapping Tumor-Specific Expression QTLs in Impure Tumor Samples

The study of gene expression quantitative trait loci (eQTL) is an effective approach to illuminate the functional roles of genetic variants. Computational methods have been developed for eQTL mapping using gene expression data from microarray or RNA-seq technology. Application of these methods for eQTL mapping in tumor tissues is problematic because tumor tissues are composed of both tumor and infiltrating normal cells (e.g. immune cells) and eQTL effects may vary between tumor and infiltrating normal cells. To address this challenge, we have developed a new method for eQTL mapping using RNA-seq data from tumor samples. Our method separately estimates the eQTL effects in tumor and infiltrating normal cells using both total expression and allele-specific expression (ASE). We demonstrate that our method controls type I error rate and has higher power than some alternative approaches. We applied our method to study RNA-seq data from The Cancer Genome Atlas and illustrated the similarities and differences of eQTL effects in tumor and normal cells.

Functional and genetic determinants of mutation rate variability in regulatory elements of cancer genomes.. [DOI: 10.1101/2020.07.29.226373] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

Background

Cancer genomes are shaped by mutational processes with complex spatial variation at multiple scales. Entire classes of regulatory elements are affected by local variations in mutation frequency. However, the underlying mutational mechanisms with functional and genetic determinants remain poorly understood.

Results

We characterised the mutational landscape of 1.3 million gene regulatory and chromatin architectural elements in 2,419 whole cancer genomes with transcriptional and pathway activity, functional conservation and recurrent driver events. We developed RM2, a statistical model that quantifies mutational enrichment or depletion in classes of genomic elements through genetic, trinucleotide and megabase-scale effects. We report a map of localised mutational processes affecting CTCF binding sites, transcription start sites (TSS) and tissue-specific open-chromatin regions. We show that increased mutational frequency in TSSs correlates with mRNA abundance in most cancer types, while open-chromatin regions are generally enriched in mutations. We identified ∼10,000 CTCF binding sites with core DNA motifs and constitutive binding in 66 cell types that represent focal points of local mutagenesis. We detected site-specific mutational signatures, such as SBS40 in open-chromatin regions in prostate cancer and SBS17b in CTCF binding sites in gastrointestinal cancers. We also proposed candidate drivers of localised mutagenesis: BRAF mutations associate with mutational enrichments at CTCF binding sites in melanoma, and ARID1A mutations with TSS-specific mutations in pancreatic cancer.

Conclusions

Our method and catalogue of localised mutational processes provide novel perspectives to cancer genome evolution, mutagenesis, DNA repair and driver discovery. Functional and genetic correlates of localised mutagenesis provide mechanistic hypotheses for future studies.

Metastatic Melanoma Patient-Derived Xenografts Respond to MDM2 Inhibition as a Single Agent or in Combination with BRAF/MEK Inhibition

PURPOSE

Over 60% of patients with melanoma respond to immune checkpoint inhibitor (ICI) therapy, but many subsequently progress on these therapies. Second-line targeted therapy is based on BRAF mutation status, but no available agents are available for NRAS, NF1, CDKN2A, PTEN, and TP53 mutations. Over 70% of melanoma tumors have activation of the MAPK pathway due to BRAF or NRAS mutations, while loss or mutation of CDKN2A occurs in approximately 40% of melanomas, resulting in unregulated MDM2-mediated ubiquitination and degradation of p53. Here, we investigated the therapeutic efficacy of over-riding MDM2-mediated degradation of p53 in melanoma with an MDM2 inhibitor that interrupts MDM2 ubiquitination of p53, treating tumor-bearing mice with the MDM2 inhibitor alone or combined with MAPK-targeted therapy.

EXPERIMENTAL DESIGN

To characterize the ability of the MDM2 antagonist, KRT-232, to inhibit tumor growth, we established patient-derived xenografts (PDX) from 15 patients with melanoma. Mice were treated with KRT-232 or a combination with BRAF and/or MEK inhibitors. Tumor growth, gene mutation status, as well as protein and protein-phosphoprotein changes, were analyzed.

RESULTS

One-hundred percent of the 15 PDX tumors exhibited significant growth inhibition either in response to KRT-232 alone or in combination with BRAF and/or MEK inhibitors. Only BRAFV600WT tumors responded to KRT-232 treatment alone while BRAFV600E/M PDXs exhibited a synergistic response to the combination of KRT-232 and BRAF/MEK inhibitors.

CONCLUSIONS

KRT-232 is an effective therapy for the treatment of either BRAFWT or PAN WT (BRAFWT, NRASWT) TP53WT melanomas. In combination with BRAF and/or MEK inhibitors, KRT-232 may be an effective treatment strategy for BRAFV600-mutant tumors.

Role of Telomeres and Telomeric Proteins in Human Malignancies and Their Therapeutic Potential

Telomeres are the ends of linear chromosomes comprised of repetitive nucleotide sequences in humans. Telomeres preserve chromosomal stability and genomic integrity. Telomere length shortens with every cell division in somatic cells, eventually resulting in replicative senescence once telomere length becomes critically short. Telomere shortening can be overcome by telomerase enzyme activity that is undetectable in somatic cells, while being active in germline cells, stem cells, and immune cells. Telomeres are bound by a shelterin complex that regulates telomere lengthening as well as protects them from being identified as DNA damage sites. Telomeres are transcribed by RNA polymerase II, and generate a long noncoding RNA called telomeric repeat-containing RNA (TERRA), which plays a key role in regulating subtelomeric gene expression. Replicative immortality and genome instability are hallmarks of cancer and to attain them cancer cells exploit telomere maintenance and telomere protection mechanisms. Thus, understanding the role of telomeres and their associated proteins in cancer initiation, progression and treatment is very important. The present review highlights the critical role of various telomeric components with recently established functions in cancer. Further, current strategies to target various telomeric components including human telomerase reverse transcriptase (hTERT) as a therapeutic approach in human malignancies are discussed.

Discovery of regulatory noncoding variants in individual cancer genomes by using cis-X

We developed cis-X, a computational method for discovering regulatory noncoding variants in cancer by integrating whole-genome and transcriptome sequencing data from a single cancer sample. cis-X first finds aberrantly cis-activated genes that exhibit allele-specific expression accompanied by an elevated outlier expression. It then searches for causal noncoding variants that may introduce aberrant transcription factor binding motifs or enhancer hijacking by structural variations. Analysis of 13 T-lineage acute lymphoblastic leukemias identified a recurrent intronic variant predicted to cis-activate the TAL1 oncogene, a finding validated in vivo by chromatin immunoprecipitation sequencing of a patient-derived xenograft. Candidate oncogenes include the prolactin receptor PRLR activated by a focal deletion that removes a CTCF-insulated neighborhood boundary. cis-X may be applied to pediatric and adult solid tumors that are aneuploid and heterogeneous. In contrast to existing approaches, which require large sample cohorts, cis-X enables the discovery of regulatory noncoding variants in individual cancer genomes.

OncodriveCLUSTL: a sequence-based clustering method to identify cancer drivers

Motivation

Identification of the genomic alterations driving tumorigenesis is one of the main goals in oncogenomics research. Given the evolutionary principles of cancer development, computational methods that detect signals of positive selection in the pattern of tumor mutations have been effectively applied in the search for cancer genes. One of these signals is the abnormal clustering of mutations, which has been shown to be complementary to other signals in the detection of driver genes.

Results

We have developed OncodriveCLUSTL, a new sequence-based clustering algorithm to detect significant clustering signals across genomic regions. OncodriveCLUSTL is based on a local background model derived from the simulation of mutations accounting for the composition of tri- or penta-nucleotide context substitutions observed in the cohort under study. Our method can identify known clusters and bona-fide cancer drivers across cohorts of tumor whole-exomes, outperforming the existing OncodriveCLUST algorithm and complementing other methods based on different signals of positive selection. Our results indicate that OncodriveCLUSTL can be applied to the analysis of non-coding genomic elements and non-human mutations data.

Availability and implementation

OncodriveCLUSTL is available as an installable Python 3.5 package. The source code and running examples are freely available at https://bitbucket.org/bbglab/oncodriveclustl under GNU Affero General Public License.

Supplementary information

Supplementary data are available at Bioinformatics online.

TERT Promoter Mutations and Their Impact on Gene Expression Profile in Papillary Thyroid Carcinoma

BACKGROUND

Telomerase reverse transcriptase promoter (TERTp) mutations are related to a worse prognosis in various malignancies, including papillary thyroid carcinoma (PTC). Since mechanisms responsible for the poorer outcome of TERTp(+) patients are still unknown, searching for molecular consequences of TERTp mutations in PTC was the aim of our study.

METHODS

The studied cohort consisted of 54 PTCs, among them 24 cases with distant metastases. BRAF V600E, RAS, and TERTp mutational status was evaluated in all cases. Differences in gene expression profile between TERTp(+) and TERTp(-) PTCs were examined using microarrays. The evaluation of signaling pathways and gene ontology was based on the Gene Set Enrichment Analysis.

RESULTS

Fifty-nine percent (32/54) of analyzed PTCs were positive for at least one mutation: 27 were BRAF(+), among them eight were TERTp(+), and 1 NRAS(+), whereas five other samples harbored RAS mutations. Expression of four genes significantly differed in BRAF(+)TERTp(+) and BRAF(+)TERTp(-) PTCs. Deregulation of pathways involved in key cell processes was observed.

CONCLUSIONS

TERTp mutations are related to higher PTC aggressiveness. CRABP2 gene was validated as associated with TERTp mutations. However, its potential use in diagnostics or risk stratification in PTC patients needs further studies.

OncoBase: a platform for decoding regulatory somatic mutations in human cancers

Whole-exome and whole-genome sequencing have revealed millions of somatic mutations associated with different human cancers, and the vast majority of them are located outside of coding sequences, making it challenging to directly interpret their functional effects. With the rapid advances in high-throughput sequencing technologies, genome-scale long-range chromatin interactions were detected, and distal target genes of regulatory elements were determined using three-dimensional (3D) chromatin looping. Herein, we present OncoBase (http://www.oncobase.biols.ac.cn/), an integrated database for annotating 81 385 242 somatic mutations in 68 cancer types from more than 120 cancer projects by exploring their roles in distal interactions between target genes and regulatory elements. OncoBase integrates local chromatin signatures, 3D chromatin interactions in different cell types and reconstruction of enhancer-target networks using state-of-the-art algorithms. It employs informative visualization tools to display the integrated local and 3D chromatin signatures and effects of somatic mutations on regulatory elements. Enhancer-promoter interactions estimated from chromatin interactions are integrated into a network diffusion system that quantitatively prioritizes somatic mutations and target genes from a large pool. Thus, OncoBase is a useful resource for the functional annotation of regulatory noncoding regions and systematically benchmarking the regulatory effects of embedded noncoding somatic mutations in human carcinogenesis.

Missing heritability in Parkinson's disease: the emerging role of non-coding genetic variation

Parkinson's disease (PD) is a neurodegenerative disorder caused by a complex interplay of genetic and environmental factors. For the stratification of PD patients and the development of advanced clinical trials, including causative treatments, a better understanding of the underlying genetic architecture of PD is required. Despite substantial efforts, genome-wide association studies have not been able to explain most of the observed heritability. The majority of PD-associated genetic variants are located in non-coding regions of the genome. A systematic assessment of their functional role is hampered by our incomplete understanding of genotype-phenotype correlations, for example through differential regulation of gene expression. Here, the recent progress and remaining challenges for the elucidation of the role of non-coding genetic variants is reviewed with a focus on PD as a complex disease with multifactorial origins. The function of gene regulatory elements and the impact of non-coding variants on them, and the means to map these elements on a genome-wide level, will be delineated. Moreover, examples of how the integration of functional genomic annotations can serve to identify disease-associated pathways and to prioritize disease- and cell type-specific regulatory variants will be given. Finally, strategies for functional validation and considerations for suitable model systems are outlined. Together this emphasizes the contribution of rare and common genetic variants to the complex pathogenesis of PD and points to remaining challenges for the dissection of genetic complexity that may allow for better stratification, improved diagnostics and more targeted treatments for PD in the future.

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.

TERT promoter mutations and telomeres during tumorigenesis

Telomerase regulation and telomere shortening act as a strong tumor suppressor mechanism in human somatic cells. Point mutations in the promoter of telomerase reverse transcriptase (TERT) are the most frequent non-coding mutation in cancer. These TERT promoter mutations (TPMs) create de novo ETS factor binding sites upstream of the start codon of the gene, which can be bound by different ETS factors. TPMs can occur early during tumorigenesis and are thought to be among the first mutations in melanoma, glioblastoma and hepatocellular carcinoma. Despite their association with increased TERT levels, TPMs do not prohibit telomere shortening and TPM-harboring cancers present with short telomeres. Their short telomere length combined with their high prevalence and specificity for cancer makes TPMs an attractive target for future therapeutic exploitation of telomerase inhibition and telomere deprotection-induced cell death.

Differential Allele-Specific Expression Uncovers Breast Cancer Genes Dysregulated by Cis Noncoding Mutations

Identifying cancer-relevant mutations in noncoding regions is challenging due to the large numbers of such mutations, their low levels of recurrence, and difficulties in interpreting their functional impact. To uncover genes that are dysregulated due to somatic mutations in cis, we build upon the concept of differential allele-specific expression (ASE) and introduce methods to identify genes within an individual's cancer whose ASE differs from what is found in matched normal tissue. When applied to breast cancer tumor samples, our methods detect the known allele-specific effects of copy number variation and nonsense-mediated decay. Further, genes that are found to recurrently exhibit differential ASE across samples are cancer relevant. Genes with cis mutations are enriched for differential ASE, and we find 147 potentially functional noncoding mutations cis to genes that exhibit significant differential ASE. We conclude that differential ASE is a promising means for discovering gene dysregulation due to cis noncoding mutations.

Genomic Instability of iPSCs and Challenges in Their Clinical Applications

Generation of human-induced pluripotent stem cells (iPSCs) from somatic cells has opened the possibility to design novel therapeutic approaches. In 2014, the first-in-human clinical trial of iPSC-based therapy was conducted. However, the transplantation for the second patient was discontinued at least in part due to genetic aberrations detected in iPSCs. Moreover, many studies have reported genetic aberrations in iPSCs with the rapid progress in genomic technologies. The presence of genomic instability raises serious safety concerns and can hamper the advancement of iPSC-based therapies. Here, we summarize our current knowledge on genomic instability of iPSCs and challenges in their clinical applications. In view of the recent expansion of stem cell therapies, it is crucial to gain deeper mechanistic insights into the genetic aberrations, ranging from chromosomal aberrations, copy number variations to point mutations. On the basis of their origin, these genetic aberrations in iPSCs can be classified as (i) preexisting mutations in parental somatic cells, (ii) reprogramming-induced mutations, and (iii) mutations that arise during in vitro culture. However, it is still unknown whether these genetic aberrations in iPSCs can be an actual risk factor for adverse effects. Intersection of the genomic data on iPSCs with the patients' clinical follow-up data will help to produce evidence-based criteria for clinical application. Furthermore, we discuss novel approaches to generate iPSCs with fewer genetic aberrations. Better understanding of iPSCs from both basic and clinical aspects will pave the way for iPSC-based therapies.

Pathway and network analysis of more than 2500 whole cancer genomes

The catalog of cancer driver mutations in protein-coding genes has greatly expanded in the past decade. However, non-coding cancer driver mutations are less well-characterized and only a handful of recurrent non-coding mutations, most notably TERT promoter mutations, have been reported. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2658 cancer across 38 tumor types, we perform multi-faceted pathway and network analyses of non-coding mutations across 2583 whole cancer genomes from 27 tumor types compiled by the ICGC/TCGA PCAWG project that was motivated by the success of pathway and network analyses in prioritizing rare mutations in protein-coding genes. While few non-coding genomic elements are recurrently mutated in this cohort, we identify 93 genes harboring non-coding mutations that cluster into several modules of interacting proteins. Among these are promoter mutations associated with reduced mRNA expression in TP53, TLE4, and TCF4. We find that biological processes had variable proportions of coding and non-coding mutations, with chromatin remodeling and proliferation pathways altered primarily by coding mutations, while developmental pathways, including Wnt and Notch, altered by both coding and non-coding mutations. RNA splicing is primarily altered by non-coding mutations in this cohort, and samples containing non-coding mutations in well-known RNA splicing factors exhibit similar gene expression signatures as samples with coding mutations in these genes. These analyses contribute a new repertoire of possible cancer genes and mechanisms that are altered by non-coding mutations and offer insights into additional cancer vulnerabilities that can be investigated for potential therapeutic treatments.

Pan-cancer analysis of whole genomes

Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale1-3. Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter4; identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation5,6; analyses timings and patterns of tumour evolution7; describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity8,9; and evaluates a range of more-specialized features of cancer genomes8,10-18.

Analyses of non-coding somatic drivers in 2,658 cancer whole genomes

The discovery of drivers of cancer has traditionally focused on protein-coding genes1-4. Here we present analyses of driver point mutations and structural variants in non-coding regions across 2,658 genomes from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium5 of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). For point mutations, we developed a statistically rigorous strategy for combining significance levels from multiple methods of driver discovery that overcomes the limitations of individual methods. For structural variants, we present two methods of driver discovery, and identify regions that are significantly affected by recurrent breakpoints and recurrent somatic juxtapositions. Our analyses confirm previously reported drivers6,7, raise doubts about others and identify novel candidates, including point mutations in the 5' region of TP53, in the 3' untranslated regions of NFKBIZ and TOB1, focal deletions in BRD4 and rearrangements in the loci of AKR1C genes. We show that although point mutations and structural variants that drive cancer are less frequent in non-coding genes and regulatory sequences than in protein-coding genes, additional examples of these drivers will be found as more cancer genomes become available.

Genomic basis for RNA alterations in cancer

Transcript alterations often result from somatic changes in cancer genomes1. Various forms of RNA alterations have been described in cancer, including overexpression2, altered splicing3 and gene fusions4; however, it is difficult to attribute these to underlying genomic changes owing to heterogeneity among patients and tumour types, and the relatively small cohorts of patients for whom samples have been analysed by both transcriptome and whole-genome sequencing. Here we present, to our knowledge, the most comprehensive catalogue of cancer-associated gene alterations to date, obtained by characterizing tumour transcriptomes from 1,188 donors of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA)5. Using matched whole-genome sequencing data, we associated several categories of RNA alterations with germline and somatic DNA alterations, and identified probable genetic mechanisms. Somatic copy-number alterations were the major drivers of variations in total gene and allele-specific expression. We identified 649 associations of somatic single-nucleotide variants with gene expression in cis, of which 68.4% involved associations with flanking non-coding regions of the gene. We found 1,900 splicing alterations associated with somatic mutations, including the formation of exons within introns in proximity to Alu elements. In addition, 82% of gene fusions were associated with structural variants, including 75 of a new class, termed 'bridged' fusions, in which a third genomic location bridges two genes. We observed transcriptomic alteration signatures that differ between cancer types and have associations with variations in DNA mutational signatures. This compendium of RNA alterations in the genomic context provides a rich resource for identifying genes and mechanisms that are functionally implicated in cancer.

Candidate Cancer Driver Mutations in Distal Regulatory Elements and Long-Range Chromatin Interaction Networks

A comprehensive catalog of cancer driver mutations is essential for understanding tumorigenesis and developing therapies. Exome-sequencing studies have mapped many protein-coding drivers, yet few non-coding drivers are known because genome-wide discovery is challenging. We developed a driver discovery method, ActiveDriverWGS, and analyzed 120,788 cis-regulatory modules (CRMs) across 1,844 whole tumor genomes from the ICGC-TCGA PCAWG project. We found 30 CRMs with enriched SNVs and indels (FDR < 0.05). These frequently mutated regulatory elements (FMREs) were ubiquitously active in human tissues, showed long-range chromatin interactions and mRNA abundance associations with target genes, and were enriched in motif-rewiring mutations and structural variants. Genomic deletion of one FMRE in human cells caused proliferative deficiencies and transcriptional deregulation of cancer genes CCNB1IP1, CDH1, and CDKN2B, validating observations in FMRE-mutated tumors. Pathway analysis revealed further sub-significant FMREs at cancer genes and processes, indicating an unexplored landscape of infrequent driver mutations in the non-coding genome.

Recurrent somatic mutations reveal new insights into consequences of mutagenic processes in cancer

The sheer size of the human genome makes it improbable that identical somatic mutations at the exact same position are observed in multiple tumours solely by chance. The scarcity of cancer driver mutations also precludes positive selection as the sole explanation. Therefore, recurrent mutations may be highly informative of characteristics of mutational processes. To explore the potential, we use recurrence as a starting point to cluster >2,500 whole genomes of a pan-cancer cohort. We describe each genome with 13 recurrence-based and 29 general mutational features. Using principal component analysis we reduce the dimensionality and create independent features. We apply hierarchical clustering to the first 18 principal components followed by k-means clustering. We show that the resulting 16 clusters capture clinically relevant cancer phenotypes. High levels of recurrent substitutions separate the clusters that we link to UV-light exposure and deregulated activity of POLE from the one representing defective mismatch repair, which shows high levels of recurrent insertions/deletions. Recurrence of both mutation types characterizes cancer genomes with somatic hypermutation of immunoglobulin genes and the cluster of genomes exposed to gastric acid. Low levels of recurrence are observed for the cluster where tobacco-smoke exposure induces mutagenesis and the one linked to increased activity of cytidine deaminases. Notably, the majority of substitutions are recurrent in a single tumour type, while recurrent insertions/deletions point to shared processes between tumour types. Recurrence also reveals susceptible sequence motifs, including TT[C>A]TTT and AAC[T>G]T for the POLE and 'gastric-acid exposure' clusters, respectively. Moreover, we refine knowledge of mutagenesis, including increased C/G deletion levels in general for lung tumours and specifically in midsize homopolymer sequence contexts for microsatellite instable tumours. Our findings are an important step towards the development of a generic cancer diagnostic test for clinical practice based on whole-genome sequencing that could replace multiple diagnostics currently in use.

ncdDetect2: improved models of the site-specific mutation rate in cancer and driver detection with robust significance evaluation

Motivation

Understanding the mutational processes that act during cancer development is a key topic of cancer biology. Nevertheless, much remains to be learned, as a complex interplay of processes with dependencies on a range of genomic features creates highly heterogeneous cancer genomes. Accurate driver detection relies on unbiased models of the mutation rate that also capture rate variation from uncharacterized sources.

Results

Here, we analyse patterns of observed-to-expected mutation counts across 505 whole cancer genomes, and find that genomic features missing from our mutation-rate model likely operate on a megabase length scale. We extend our site-specific model of the mutation rate to include the additional variance from these sources, which leads to robust significance evaluation of candidate cancer drivers. We thus present ncdDetect v.2, with greatly improved cancer driver detection specificity. Finally, we show that ranking candidates by their posterior mean value of their effect sizes offers an equivalent and more computationally efficient alternative to ranking by their P-values.

Availability and implementation

ncdDetect v.2 is implemented as an R-package and is freely available at http://github.com/TobiasMadsen/ncdDetect2

Supplementary information

Supplementary data are available at Bioinformatics online.

Intragenomic variability and extended sequence patterns in the mutational signature of ultraviolet light

Mutational signatures have emerged as essential tools in cancer genomics, providing clinically relevant insights as well as accurate background models needed when assessing signals of selection in cancer. Here, we observe that the mutational signature of ultraviolet (UV) light varies across chromatin states, highlighting a previously unappreciated aspect of mutational signatures. Our results imply that locally derived, rather than genome-wide or exome-wide, signatures are more accurate, which is of relevance in situations such as cancer driver gene detection, where correct modelling of signatures and expected mutation rates is critical. We also show that incorporation of longer contextual patterns into the signature further improves modeling of UV mutations.

Mutational signatures can reveal properties of underlying mutational processes and are important when assessing signals of selection in cancer. Here, we describe the sequence characteristics of mutations induced by ultraviolet (UV) light, a major mutagen in several human cancers, in terms of extended (longer than trinucleotide) patterns as well as variability of the signature across chromatin states. Promoter regions display a distinct UV signature with reduced TCG > TTG transitions, and genome-wide mapping of UVB-induced DNA photoproducts (pyrimidine dimers) showed that this may be explained by decreased damage formation at hypomethylated promoter CpG sites. Further, an extended signature model encompassing additional information from longer contextual patterns improves modeling of UV mutations, which may enhance discrimination between drivers and passenger events. Our study presents a refined picture of the UV signature and underscores that the characteristics of a single mutational process may vary across the genome.

Comprehensive Characterization of Somatic Mutations Impacting lncRNA Expression for Pan-Cancer

Somatic mutations have long been recognized as an important feature of cancer. However, analysis of somatic mutations, to date, has focused almost entirely on the protein coding regions of the genome. The potential roles of somatic mutations in human long noncoding RNAs (lncRNAs) are therefore largely unknown, particularly their functional significance across different cancer types. In this study, we characterized some lncRNAs whose expression was affected by somatic mutations (defined as MutLncs) and constructed global MutLnc landscapes across 17 cancer types by systematically integrating multiple levels of data. MutLncs were commonly downregulated and carried low mutation frequencies and non-silent mutations in most cancer types. Co-occurrence analysis in pan-cancer highlighted combined patterns of specific MutLncs, suggesting that a number of MutLncs influence diverse cancer types through combination effects. Several conserved and cancer-specific functions of MutLncs were determined. We further explored the somatic mutations affecting lncRNA expression via mixed and unmixed effects, which led to specific functions in pan-cancer. Survival analysis indicated that MutLncs and co-occurrence pairs can potentially serve as cancer biomarkers. Clarification of the specific roles of MutLncs in human cancers could be beneficial for understanding the molecular pathogenesis of different cancer types and developing the appropriate treatments.

Mapping and Making Sense of Noncoding Mutations in the Genome

Whole-genome sequencing efforts of tumors and normal tissues have identified numerous genetic mutations, both somatic and germline, that do not overlap with coding genomic sequences. Attributing a functional role to these noncoding mutations and characterizing them using experimental methods has been more challenging compared with coding mutations. In this review, we provide a brief introduction to the world of noncoding mutations. We discuss recent progress in identifying noncoding mutations and the analytic and experimental approaches utilized to interpret their functional roles. We also highlight the potential mechanisms by which a noncoding mutation may exert its effect and discuss future challenges and opportunities.

Scarcity of Recurrent Regulatory Driver Mutations in Colorectal Cancer Revealed by Targeted Deep Sequencing

Background

Genetic testing of cancer samples primarily focuses on protein-coding regions, despite most mutations arising in noncoding DNA. Noncoding mutations can be pathogenic if they disrupt gene regulation, but the benefits of assessing promoter mutations in driver genes by panel testing has not yet been established. This is especially the case in colorectal cancer, for which few putative driver variants at regulatory elements have been reported.

Methods

We designed a unique target capture sequencing panel of 39 colorectal cancer driver genes and their promoters, together with more than 35 megabases of regulatory elements focusing on gene promoters. Using this panel, we sequenced 95 colorectal cancer and matched normal samples at high depth, averaging 170× and 82× coverage, respectively.

Results

Our target capture sequencing design enabled improved coverage and variant detection across captured regions. We found cases with hereditary defects in mismatch and base excision repair due to deleterious germline coding variants, and we identified mutational spectra consistent with these repair deficiencies. Focusing on gene promoters and other regulatory regions, we found little evidence for base or region-specific recurrence of functional somatic mutations. Promoter elements, including TERT, harbored few mutations, with none showing strong functional evidence. Recurrent regulatory mutations were rare in our sequenced regions in colorectal cancer, though we highlight some candidate mutations for future functional studies.

Conclusions

Our study supports recent findings that regulatory driver mutations are rare in many cancer types and suggests that the inclusion of promoter regions into cancer panel testing is currently likely to have limited clinical utility in colorectal cancer.

Somatic and Germline Mutation Periodicity Follow the Orientation of the DNA Minor Groove around Nucleosomes

Mutation rates along the genome are highly variable and influenced by several chromatin features. Here, we addressed how nucleosomes, the most pervasive chromatin structure in eukaryotes, affect the generation of mutations. We discovered that within nucleosomes, the somatic mutation rate across several tumor cohorts exhibits a strong 10 base pair (bp) periodicity. This periodic pattern tracks the alternation of the DNA minor groove facing toward and away from the histones. The strength and phase of the mutation rate periodicity are determined by the mutational processes active in tumors. We uncovered similar periodic patterns in the genetic variation among human and Arabidopsis populations, also detectable in their divergence from close species, indicating that the same principles underlie germline and somatic mutation rates. We propose that differential DNA damage and repair processes dependent on the minor groove orientation in nucleosome-bound DNA contribute to the 10-bp periodicity in AT/CG content in eukaryotic genomes.

Dissecting the sources of gene expression variation in a pan-cancer analysis identifies novel regulatory mutations

Although the catalog of cancer-associated mutations in protein-coding regions is nearly complete for all major cancer types, an assessment of regulatory changes in cancer genomes and their clinical significance remain largely preliminary. Adopting bottom-up approach, we quantify the effects of different sources of gene expression variation in a cohort of 3899 samples from 10 cancer types. We find that copy number alterations, epigenetic changes, transcription factors and microRNAs collectively explain, on average, only 31–38% and 18–26% expression variation for cancer-associated and other genes, respectively, and that among these factors copy number alteration has the highest effect. We show that the genes with systematic, large expression variation that could not be attributed to these factors are enriched for pathways related to cancer hallmarks. Integrating whole genome sequencing data and focusing on genes with systematic expression variation we identify novel, recurrent regulatory mutations affecting known cancer genes such as NKX2-1 and GRIN2D in multiple cancer types. Nonetheless, at a genome-wide scale proportions of gene expression variation attributed to recurrent point mutations appear to be modest so far, especially when compared to that attributed to copy number changes – a pattern different from that observed for other complex diseases and traits. We suspect that, owing to plasticity and redundancy in biological pathways, regulatory alterations show complex combinatorial patterns, modulating gene expression in cancer genomes at a finer scale.

Identifying mutual exclusivity across cancer genomes: computational approaches to discover genetic interaction and reveal tumor vulnerability

Systematic sequencing of cancer genomes has revealed prevalent heterogeneity, with patients harboring various combinatorial patterns of genetic alteration. In particular, a phenomenon that a group of genes exhibits mutually exclusive patterns has been widespread across cancers, covering a broad spectrum of crucial cancer pathways. Recently, there is considerable evidence showing that, mutual exclusivity reflects alternative functions in tumor initiation and progression, or suggests adverse effects of their concurrence. Given its importance, numerous computational approaches have been proposed to study mutual exclusivity using genomic profiles alone, or by integrating networks and phenotypes. Some of them have been routinely used to explore genetic associations, which lead to a deeper understanding of carcinogenic mechanisms and reveals unexpected tumor vulnerabilities. Here, we present an overview of mutual exclusivity from the perspective of cancer genome. We describe the common hypothesis underlying mutual exclusivity, summarize the strategies for the identification of significant mutually exclusive patterns, compare the performance of representative algorithms from simulated data sets and discuss their common confounders.

Integrative Analysis of Somatic Mutations in Non-coding Regions Altering RNA Secondary Structures in Cancer Genomes

RNA secondary structure may influence many cellular processes, including RNA processing, stability, localization, and translation. Single-nucleotide variations (SNVs) that alter RNA secondary structure, referred to as riboSNitches, are potentially causative of human diseases, especially in untranslated regions (UTRs) and noncoding RNAs (ncRNAs). The functions of somatic mutations that act as riboSNitches in cancer development remain poorly understood. In this study, we developed a computational pipeline called SNIPER (riboSNitch-enriched or depleted elements in cancer genomes), which employs MeanDiff and EucDiff to detect riboSNitches and then identifies riboSNitch-enriched or riboSNitch-depleted non-coding elements across tumors. SNIPER is available at github: https://github.com/suzhixi/SNIPER/. We found that riboSNitches were more likely to be pathogenic. Moreover, we predicted several UTRs and lncRNAs (long non-coding RNA) that significantly enriched or depleted riboSNitches in cancer genomes, indicative of potential cancer driver or essential noncoding elements. Our study highlights the possibly neglected importance of RNA secondary structure in cancer genomes and provides a new strategy to identify new cancer-associated genes.

Identification of Cancer Drivers at CTCF Insulators in 1,962 Whole Genomes

Recent studies have shown that mutations at non-coding elements, such as promoters and enhancers, can act as cancer drivers. However, an important class of non-coding elements, namely CTCF insulators, has been overlooked in the previous driver analyses. We used insulator annotations from CTCF and cohesin ChIA-PET and analyzed somatic mutations in 1,962 whole genomes from 21 cancer types. Using the heterogeneous patterns of transcription-factor-motif disruption, functional impact, and recurrence of mutations, we developed a computational method that revealed 21 insulators showing signals of positive selection. In particular, mutations in an insulator in multiple cancer types, including 16% of melanoma samples, are associated with TGFB1 up-regulation. Using CRISPR-Cas9, we find that alterations at two of the most frequently mutated regions in this insulator increase cell growth by 40%-50%, supporting the role of this boundary element as a cancer driver. Thus, our study reveals several CTCF insulators as putative cancer drivers.

Mutational signatures of redox stress in yeast single-strand DNA and of aging in human mitochondrial DNA share a common feature

Redox stress is a major hallmark of cancer. Analysis of thousands of sequenced cancer exomes and whole genomes revealed distinct mutational signatures that can be attributed to specific sources of DNA lesions. Clustered mutations discovered in several cancer genomes were linked to single-strand DNA (ssDNA) intermediates in various processes of DNA metabolism. Previously, only one clustered mutational signature had been clearly associated with a subclass of ssDNA-specific apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like (APOBEC) cytidine deaminases. Others remain to be elucidated. We report here deciphering of the mutational spectra and mutational signature of redox stress in ssDNA of budding yeast and the signature of aging in human mitochondrial DNA. We found that the predominance of C to T substitutions is a common feature of both signatures. Measurements of the frequencies of hydrogen peroxide-induced mutations in proofreading-defective yeast mutants supported the conclusion that hydrogen peroxide-induced mutagenesis is not the result of increased DNA polymerase misincorporation errors but rather is caused by direct damage to DNA. Proteins involved in modulation of chromatin status play a significant role in prevention of redox stress-induced mutagenesis, possibly by facilitating protection through modification of chromatin structure. These findings provide an opportunity for the search and identification of the mutational signature of redox stress in cancers and in other pathological conditions and could potentially be used for informing therapeutic decisions. In addition, the discovery of such signatures that may be present in related organisms should also advance our understanding of evolution.

The Untranslated Regions of mRNAs in Cancer

The 5' and 3' untranslated regions (UTRs) regulate crucial aspects of post-transcriptional gene regulation that are necessary for the maintenance of cellular homeostasis. When these processes go awry through mutation or misexpression of certain regulatory elements, the subsequent deregulation of oncogenic gene expression can drive or enhance cancer pathogenesis. Although the number of known cancer-related mutations in UTR regulatory elements has recently increased markedly as a result of advances in whole-genome sequencing, little is known about how the majority of these genetic aberrations contribute functionally to disease. In this review we explore the regulatory functions of UTRs, how they are co-opted in cancer, new technologies to interrogate cancerous UTRs, and potential therapeutic opportunities stemming from these regions.

DNA polymerase η contributes to genome-wide lagging strand synthesis

DNA polymerase η (pol η) is best known for its ability to bypass UV-induced thymine-thymine (T-T) dimers and other bulky DNA lesions, but pol η also has other cellular roles. Here, we present evidence that pol η competes with DNA polymerases α and δ for the synthesis of the lagging strand genome-wide, where it also shows a preference for T-T in the DNA template. Moreover, we found that the C-terminus of pol η, which contains a PCNA-Interacting Protein motif is required for pol η to function in lagging strand synthesis. Finally, we provide evidence that a pol η dependent signature is also found to be lagging strand specific in patients with skin cancer. Taken together, these findings provide insight into the physiological role of DNA synthesis by pol η and have implications for our understanding of how our genome is replicated to avoid mutagenesis, genome instability and cancer.

Recurrent Noncoding Mutations in Skin Cancers: UV Damage Susceptibility or Repair Inhibition as Primary Driver?

Somatic mutations arising in human skin cancers are heterogeneously distributed across the genome, meaning that certain genomic regions (e.g., heterochromatin or transcription factor binding sites) have much higher mutation densities than others. Regional variations in mutation rates are typically not a consequence of selection, as the vast majority of somatic mutations in skin cancers are passenger mutations that do not promote cell growth or transformation. Instead, variations in DNA repair activity, due to chromatin organization and transcription factor binding, have been proposed to be a primary driver of mutational heterogeneity in melanoma. However, as discussed in this review here, recent studies indicate that chromatin organization and transcription factor binding also significantly modulate the rate at which UV lesions form in DNA. The authors propose that local variations in lesion susceptibility may be an important driver of mutational hotspots in melanoma and other skin cancers, particularly at binding sites for ETS transcription factors.

Iron addiction with ferroptosis-resistance in asbestos-induced mesothelial carcinogenesis: Toward the era of mesothelioma prevention

Cancer is the primary cause of human mortality in most countries. This tendency has increased as various medical therapeutics have advanced, which suggests that we cannot escape carcinogenesis, although the final outcome may be modified by exposomes and statistics. Cancer is classified by its cellular differentiation. Mesothelial cells are distinct in that they line somatic cavities, facilitating the smooth movement of organs, but are not exposed to the external environment. Malignant mesothelioma, or simply mesothelioma, develops either in the pleural, peritoneal or pericardial cavities, or in the tunica vaginalis testes. Mesothelioma has been a relatively rare cancer but is socially important due to its association with asbestos exposure, caused by modern industrial development. The major pathogenic mechanisms include oxidative stress either via catalytic reactions against the asbestos surface or frustrated phagocytosis of macrophages, and specific adsorption of hemoglobin and histones by asbestos fibers in the presence of phagocytic activity of mesothelial cells. Multiwall carbon nanotubes of ~50 nm-diameter, additionally adsorbing transferrin, are similarly carcinogenic to mesothelial cells in rodents and were thus classified as Group 2B carcinogens. Genetic alterations found in human and rat mesothelioma notably contain changes found in other excess iron-induced carcinogenesis models. Phlebotomy and iron chelation therapies have been successful in the prevention of mesothelioma in rats. Alternatively, loading of oxidative stress by non-thermal plasma to mesothelioma cells causes ferroptosis. Therefore, carcinogenesis by foreign fibrous inorganic materials may overlap the uncovered molecular mechanisms of birth of life and its evolution.

Molecular Genomic Profiling of Melanocytic Nevi

The benign melanocytic nevus is the most common tumor in humans and rarely transforms into cutaneous melanoma. Elucidation of the nevus genome is required to better understand the molecular steps of progression to melanoma. We performed whole genome sequencing on a series of 14 benign melanocytic nevi consisting of both congenital and acquired types. All nevi had driver mutations in the MAPK signaling pathway, either BRAF V600E or NRAS Q61R/L. No additional definite driver mutations were identified. Somatic mutations in nevi with higher mutation loads showed a predominance of mutational signatures 7a and 7b, consistent with UVR exposure, whereas nevi with lower mutation loads (including all three congenital nevi) had a predominance of the ubiquitous signatures 1 and 5. Two nevi had mutations in promoter regions predicted to bind E26 transformation-specific family transcription factors, as well as subclonal mutations in the TERT promoter. This paper presents whole genome data from melanocytic nevi. We confirm that UVR is involved in the etiology of a subset of nevi. This study also establishes that TERT promoter mutations are present in morphologically benign skin nevi in subclonal populations, which has implications regarding the interpretation of this emerging biomarker in sensitive assays.

Mismatch repair-signature mutations activate gene enhancers across human colorectal cancer epigenomes

Commonly-mutated genes have been found for many cancers, but less is known about mutations in cis-regulatory elements. We leverage gains in tumor-specific enhancer activity, coupled with allele-biased mutation detection from H3K27ac ChIP-seq data, to pinpoint potential enhancer-activating mutations in colorectal cancer (CRC). Analysis of a genetically-diverse cohort of CRC specimens revealed that microsatellite instable (MSI) samples have a high indel rate within active enhancers. Enhancers with indels show evidence of positive selection, increased target gene expression, and a subset is highly recurrent. The indels affect short homopolymer tracts of A/T and increase affinity for FOX transcription factors. We further demonstrate that signature mismatch-repair (MMR) mutations activate enhancers using a xenograft tumor metastasis model, where mutations are induced naturally via CRISPR/Cas9 inactivation of MLH1 prior to tumor cell injection. Our results suggest that MMR signature mutations activate enhancers in CRC tumor epigenomes to provide a selective advantage.

TERT gene: its function and dysregulation in cancer

In this review, we summarise the function and structure of telomerase reverse transcriptase (TERT) in humans, including its regulation. The dysregulation of telomerase through TERT promoter mutations across a range of cancers is discussed. The molecular mechanism activated by TERT promoter mutations is outlined. Finally, the timing of TERT promoter mutations during carcinogenesis is reviewed in the context of their potential utility as clinical biomarkers of malignant transformation.