Oncogene-Driven Non-Small Cell Lung Cancers in Patients with a History of Smoking Lack Smoking-Induced Mutations.

Non-small cell lung cancers (NSCLC) in nonsmokers are mostly driven by mutations in the oncogenes EGFR, ERBB2, and MET and fusions involving ALK and RET. In addition to occurring in nonsmokers, alterations in these "nonsmoking-related oncogenes" (NSRO) also occur in smokers. To better understand the clonal architecture and genomic landscape of NSRO-driven tumors in smokers compared with typical-smoking NSCLCs, we investigated genomic and transcriptomic alterations in 173 tumor sectors from 48 NSCLC patients. NSRO-driven NSCLCs in smokers and nonsmokers had similar genomic landscapes. Surprisingly, even in patients with prominent smoking histories, the mutational signature caused by tobacco smoking was essentially absent in NSRO-driven NSCLCs, which was confirmed in two large NSCLC data sets from other geographic regions. However, NSRO-driven NSCLCs in smokers had higher transcriptomic activities related to the regulation of the cell cycle. These findings suggest that, whereas the genomic landscape is similar between NSRO-driven NSCLC in smokers and nonsmokers, smoking still affects the tumor phenotype independently of genomic alterations. SIGNIFICANCE: Non-small cell lung cancers driven by nonsmoking-related oncogenes do not harbor genomic scars caused by smoking regardless of smoking history, indicating that the impact of smoking on these tumors is mainly nongenomic.

Deep whole-genome analysis of 494 hepatocellular carcinomas.

Over half of hepatocellular carcinoma (HCC) cases diagnosed worldwide are in China1-3. However, whole-genome analysis of hepatitis B virus (HBV)-associated HCC in Chinese individuals is limited4-8, with current analyses of HCC mainly from non-HBV-enriched populations9,10. Here we initiated the Chinese Liver Cancer Atlas (CLCA) project and performed deep whole-genome sequencing (average depth, 120×) of 494 HCC tumours. We identified 6 coding and 28 non-coding previously undescribed driver candidates. Five previously undescribed mutational signatures were found, including aristolochic-acid-associated indel and doublet base signatures, and a single-base-substitution signature that we termed SBS_H8. Pentanucleotide context analysis and experimental validation confirmed that SBS_H8 was distinct to the aristolochic-acid-associated SBS22. Notably, HBV integrations could take the form of extrachromosomal circular DNA, resulting in elevated copy numbers and gene expression. Our high-depth data also enabled us to characterize subclonal clustered alterations, including chromothripsis, chromoplexy and kataegis, suggesting that these catastrophic events could also occur in late stages of hepatocarcinogenesis. Pathway analysis of all classes of alterations further linked non-coding mutations to dysregulation of liver metabolism. Finally, we performed in vitro and in vivo assays to show that fibrinogen alpha chain (FGA), determined as both a candidate coding and non-coding driver, regulates HCC progression and metastasis. Our CLCA study depicts a detailed genomic landscape and evolutionary history of HCC in Chinese individuals, providing important clinical implications.

mSigHdp: hierarchical Dirichlet process mixture modeling for mutational signature discovery.

Mutational signatures are characteristic patterns of mutations caused by endogenous or exogenous mutational processes. These signatures can be discovered by analyzing mutations in large sets of samples-usually somatic mutations in tumor samples. Most programs for discovering mutational signatures are based on non-negative matrix factorization (NMF). Alternatively, signatures can be discovered using hierarchical Dirichlet process (HDP) mixture models, an approach that has been less explored. These models assign mutations to clusters and view each cluster as being generated from the signature of a particular mutational process. Here, we describe mSigHdp, an improved approach to using HDP mixture models to discover mutational signatures. We benchmarked mSigHdp and state-of-the-art NMF-based approaches on four realistic synthetic data sets. These data sets encompassed 18 cancer types. In total, they contained 3.5 × 107 single-base-substitution mutations representing 32 signatures and 6.1 × 106 small insertion and deletion mutations representing 13 signatures. For three of the four data sets, mSigHdp had the best positive predictive value for discovering mutational signatures, and for all four data sets, it had the best true positive rate. Its CPU usage was similar to that of the NMF-based approaches. Thus, mSigHdp is an important and practical addition to the set of tools available for discovering mutational signatures.

Uncovering novel mutational signatures by de novo extraction with SigProfilerExtractor.

Mutational signature analysis is commonly performed in cancer genomic studies. Here, we present SigProfilerExtractor, an automated tool for de novo extraction of mutational signatures, and benchmark it against another 13 bioinformatics tools by using 34 scenarios encompassing 2,500 simulated signatures found in 60,000 synthetic genomes and 20,000 synthetic exomes. For simulations with 5% noise, reflecting high-quality datasets, SigProfilerExtractor outperforms other approaches by elucidating between 20% and 50% more true-positive signatures while yielding 5-fold less false-positive signatures. Applying SigProfilerExtractor to 4,643 whole-genome- and 19,184 whole-exome-sequenced cancers reveals four novel signatures. Two of the signatures are confirmed in independent cohorts, and one of these signatures is associated with tobacco smoking. In summary, this report provides a reference tool for analysis of mutational signatures, a comprehensive benchmarking of bioinformatics tools for extracting signatures, and several novel mutational signatures, including one putatively attributed to direct tobacco smoking mutagenesis in bladder tissues.

Acetyl-CoA metabolism drives epigenome change and contributes to carcinogenesis risk in fatty liver disease.

BACKGROUND: The incidence of non-alcoholic fatty liver disease (NAFLD)-associated hepatocellular carcinoma (HCC) is increasing worldwide, but the steps in precancerous hepatocytes which lead to HCC driver mutations are not well understood. Here we provide evidence that metabolically driven histone hyperacetylation in steatotic hepatocytes can increase DNA damage to initiate carcinogenesis. METHODS: Global epigenetic state was assessed in liver samples from high-fat diet or high-fructose diet rodent models, as well as in cultured immortalized human hepatocytes (IHH cells). The mechanisms linking steatosis, histone acetylation and DNA damage were investigated by computational metabolic modelling as well as through manipulation of IHH cells with metabolic and epigenetic inhibitors. Chromatin immunoprecipitation and next-generation sequencing (ChIP-seq) and transcriptome (RNA-seq) analyses were performed on IHH cells. Mutation locations and patterns were compared between the IHH cell model and genome sequence data from preneoplastic fatty liver samples from patients with alcohol-related liver disease and NAFLD. RESULTS: Genome-wide histone acetylation was increased in steatotic livers of rodents fed high-fructose or high-fat diet. In vitro, steatosis relaxed chromatin and increased DNA damage marker γH2AX, which was reversed by inhibiting acetyl-CoA production. Steatosis-associated acetylation and γH2AX were enriched at gene clusters in telomere-proximal regions which contained HCC tumour suppressors in hepatocytes and human fatty livers. Regions of metabolically driven epigenetic change also had increased levels of DNA mutation in non-cancerous tissue from NAFLD and alcohol-related liver disease patients. Finally, genome-scale network modelling indicated that redox balance could be a key contributor to this mechanism. CONCLUSIONS: Abnormal histone hyperacetylation facilitates DNA damage in steatotic hepatocytes and is a potential initiating event in hepatocellular carcinogenesis.

Accuracy of mutational signature software on correlated signatures.

Mutational signatures are characteristic patterns of mutations generated by exogenous mutagens or by endogenous mutational processes. Mutational signatures are important for research into DNA damage and repair, aging, cancer biology, genetic toxicology, and epidemiology. Unsupervised learning can infer mutational signatures from the somatic mutations in large numbers of tumors, and separating correlated signatures is a notable challenge for this task. To investigate which methods can best meet this challenge, we assessed 18 computational methods for inferring mutational signatures on 20 synthetic data sets that incorporated varying degrees of correlated activity of two common mutational signatures. Performance varied widely, and four methods noticeably outperformed the others: hdp (based on hierarchical Dirichlet processes), SigProExtractor (based on multiple non-negative matrix factorizations over resampled data), TCSM (based on an approach used in document topic analysis), and mutSpec.NMF (also based on non-negative matrix factorization). The results underscored the complexities of mutational signature extraction, including the importance and difficulty of determining the correct number of signatures and the importance of hyperparameters. Our findings indicate directions for improvement of the software and show a need for care when interpreting results from any of these methods, including the need for assessing sensitivity of the results to input parameters.

Recurrent mutations in topoisomerase IIα cause a previously undescribed mutator phenotype in human cancers.

Topoisomerases nick and reseal DNA to relieve torsional stress associated with transcription and replication and to resolve structures such as knots and catenanes. Stabilization of the yeast Top2 cleavage intermediates is mutagenic in yeast, but whether this extends to higher eukaryotes is less clear. Chemotherapeutic topoisomerase poisons also elevate cleavage, resulting in mutagenesis. Here, we describe p.K743N mutations in human topoisomerase hTOP2α and link them to a previously undescribed mutator phenotype in cancer. Overexpression of the orthologous mutant protein in yeast generated a characteristic pattern of 2- to 4-base pair (bp) duplications resembling those in tumors with p.K743N. Using mutant strains and biochemical analysis, we determined the genetic requirements of this mutagenic process and showed that it results from trapping of the mutant yeast yTop2 cleavage complex. In addition to 2- to 4-bp duplications, hTOP2α p.K743N is also associated with deletions that are absent in yeast. We call the combined pattern of duplications and deletions ID_TOP2α. All seven tumors carrying the hTOP2α p.K743N mutation showed ID_TOP2α, while it was absent from all other tumors examined (n = 12,269). Each tumor with the ID_TOP2α signature had indels in several known cancer genes, which included frameshift mutations in tumor suppressors PTEN and TP53 and an activating insertion in BRAF. Sequence motifs found at ID_TOP2α mutations were present at 80% of indels in cancer-driver genes, suggesting that ID_TOP2α mutagenesis may contribute to tumorigenesis. The results reported here shed further light on the role of topoisomerase II in genome instability.

Mutational processes in cancer preferentially affect binding of particular transcription factors.

Protein binding microarrays provide comprehensive information about the DNA binding specificities of transcription factors (TFs), and can be used to quantitatively predict the effects of DNA sequence variation on TF binding. There has also been substantial progress in dissecting the patterns of mutations, i.e., the "mutational signatures", generated by different mutational processes. By combining these two layers of information we can investigate whether certain mutational processes tend to preferentially affect binding of particular classes of TFs. Such preferential alterations of binding might predispose to particular oncogenic pathways. We developed and implemented a method, termed "Signature-QBiC", that integrates protein binding microarray data with the signatures of mutational processes, with the aim of predicting which TFs' binding profiles are preferentially perturbed by particular mutational processes. We used Signature-QBiC to predict the effects of 47 signatures of mutational processes on 582 human TFs. Pathway analysis showed that binding of TFs involved in NOTCH1 signaling is strongly affected by the signatures of several mutational processes, including exposure to ultraviolet radiation. Additionally, toll-like-receptor signaling pathways are also vulnerable to disruption by this exposure. This study provides a novel overview of the effects of mutational processes on TF binding and the potential of these processes to activate oncogenic pathways through mutating TF binding sites.

Enhancer-derived long non-coding RNAs CCAT1 and CCAT2 at rs6983267 has limited predictability for early stage colorectal carcinoma metastasis.

Up-regulation of long non-coding RNAs (lncRNAs), colon-cancer associated transcript (CCAT) 1 and 2, was associated with worse prognosis in colorectal cancer (CRC). Nevertheless, their role in predicting metastasis in early-stage CRC is unclear. We measured the expression of CCAT1, CCAT2 and their oncotarget, c-Myc, in 150 matched mucosa-tumour samples of early-stage microsatellite-stable Chinese CRC patients with definitive metastasis status by multiplex real-time RT-PCR assay. Expression of CCAT1, CCAT2 and c-Myc were significantly up-regulated in the tumours compared to matched mucosa (p < 0.0001). The expression of c-Myc in the tumours was significantly correlated to time to metastasis [hazard ratio = 1.47 (1.10-1.97)] and the risk genotype (GG) of rs6983267, located within CCAT2. Expression of c-Myc and CCAT2 in the tumour were also significantly up-regulated in metastasis-positive compared to metastasis-negative patients (p = 0.009 and p = 0.04 respectively). Nevertheless, integrating the expression of CCAT1 and CCAT2 by the Random Forest classifier did not improve the predictive values of ColoMet19, the mRNA-based predictor for metastasis previously developed on the same series of tumours. The role of these two lncRNAs is probably mitigated via their oncotarget, c-Myc, which was not ranked high enough previously to be included in ColoMet19.

The mutational landscape of early- and typical-onset oral tongue squamous cell carcinoma.

BACKGROUND: The incidence of oral tongue squamous cell carcinoma (OTSCC) is increasing among younger birth cohorts. The etiology of early-onset OTSCC (diagnosed before the age of 50 years) and cancer driver genes remain largely unknown. METHODS: The Sequencing Consortium of Oral Tongue Cancer was established through the pooling of somatic mutation data of oral tongue cancer specimens (n = 227 [107 early-onset cases]) from 7 studies and The Cancer Genome Atlas. Somatic mutations at microsatellite loci and Catalog of Somatic Mutations in Cancer mutation signatures were identified. Cancer driver genes were identified with the MutSigCV and WITER algorithms. Mutation comparisons between early- and typical-onset OTSCC were evaluated via linear regression with adjustments for patient-related factors. RESULTS: Two novel driver genes (ATXN1 and CDC42EP1) and 5 previously reported driver genes (TP53, CDKN2A, CASP8, NOTCH1, and FAT1) were identified. Six recurrent mutations were identified, with 4 occurring in TP53. Early-onset OTSCC had significantly fewer nonsilent mutations even after adjustments for tobacco use. No associations of microsatellite locus mutations and mutation signatures with the age of OTSCC onset were observed. CONCLUSIONS: This international, multicenter consortium is the largest study to characterize the somatic mutational landscape of OTSCC and the first to suggest differences by age of onset. This study validates multiple previously identified OTSCC driver genes and proposes 2 novel cancer driver genes. In analyses by age, early-onset OTSCC had a significantly smaller somatic mutational burden that was not explained by differences in tobacco use. LAY SUMMARY: This study identifies 7 specific areas in the human genetic code that could be responsible for promoting the development of tongue cancer. Tongue cancer in young patients (under the age of 50 years) has fewer overall changes to the genetic code in comparison with tongue cancer in older patients, but the authors do not think that this is due to differences in smoking rates between the 2 groups. The cause of increasing cases of tongue cancer in young patients remains unclear.

A tumor-associated splice-isoform of MAP2K7 drives dedifferentiation in MBNL1-low cancers via JNK activation.

Master splicing regulator MBNL1 shapes large transcriptomic changes that drive cellular differentiation during development. Here we demonstrate that MBNL1 is a suppressor of tumor dedifferentiation. We surveyed MBNL1 expression in matched tumor/normal pairs across The Cancer Genome Atlas and found that MBNL1 was down-regulated in several common cancers. Down-regulation of MBNL1 predicted poor overall survival in breast, lung, and stomach adenocarcinomas and increased relapse and distant metastasis in triple-negative breast cancer. Down-regulation of MBNL1 led to increased tumorigenic and stem/progenitor-like properties in vitro and in vivo. A discrete set of alternative splicing events (ASEs) are shared between MBNL1-low cancers and embryonic stem cells including a MAP2K7∆exon2 splice variant that leads to increased stem/progenitor-like properties via JNK activation. Accordingly, JNK inhibition is capable of reversing MAP2K7∆exon2-driven tumor dedifferentiation in MBNL1-low cancer cells. Our work elucidates an alternative-splicing mechanism that drives tumor dedifferentiation and identifies biomarkers that predict enhanced susceptibility to JNK inhibition.

Characterization of colibactin-associated mutational signature in an Asian oral squamous cell carcinoma and in other mucosal tumor types.

Mutational signatures can reveal the history of mutagenic processes that cells were exposed to before and during tumorigenesis. We expect that as-yet-undiscovered mutational processes will shed further light on mutagenesis leading to carcinogenesis. With this in mind, we analyzed the mutational spectra of 36 Asian oral squamous cell carcinomas. The mutational spectra of two samples from patients who presented with oral bacterial infections showed novel mutational signatures. One of these novel signatures, SBS_AnT, is characterized by a preponderance of thymine mutations, strong transcriptional strand bias, and enrichment for adenines in the 4 bp 5' of mutation sites. The mutational signature described in this manuscript was shown to be caused by colibactin, a bacterial mutagen produced by E. coli carrying the pks-island. Examination of publicly available sequencing data revealed SBS_AnT in 25 tumors from several mucosal tissue types, expanding the list of tissues in which this mutational signature is observed.

Toward clinical understanding of aristolochic acid upper-tract urothelial carcinoma.

A cluster of patients poisoned by herbal medicine in the 1990s revealed that aristolochic acid (AA) causes kidney failure and upper tract urothelial carcinoma (UTUC). Recent research demonstrated that this was not an isolated incident; on the contrary, AA exposure is widespread in East Asia. This editorial highlights research by Lu and colleagues that investigates clinical characteristics of AA and non-AA UTUCs from 90 patients in Beijing based on the AA mutational signature. The study also detected AA mutations in non-tumor tissue of AA exposed patients and showed that AA mutations can be detected in urine, which might form the basis for non-invasive tests for AA exposure.

Lack of Targetable FGFR2 Fusions in Endemic Fluke-Associated Cholangiocarcinoma.

PURPOSE: Cholangiocarcinoma (CCA) remains a disease with poor prognosis and limited therapeutic options. Identification of driver genetic alterations may lead to the discovery of more effective targeted therapies. CCAs harboring FGFR2 fusions have recently demonstrated promising responses to FGFR inhibitors, highlighting their potential relevance as predictive biomarkers. CCA incidence is high in the northeast of Thailand and its neighboring countries because of chronic infection with the liver fluke Opisthorchis viverrini (Ov). However, there are currently no available data on the prevalence of FGFR alterations in fluke-associated CCA in endemic countries. MATERIALS AND METHODS: In this study, we performed anchored multiplex polymerase chain reaction target enrichment RNA sequencing of FGFR1-3, validated by fluorescence in situ hybridization and Sanger sequencing, in 121 Ov-associated and 95 non-Ov-associated CCA tumors. RESULTS: Compared with non-fluke-associated CCA (11/95; 11.6%), FGFR2 fusions were significantly less common in fluke-associated CCA (1/121; 0.8%; P = .0006). All FGFR fusions were detected exclusively in intrahepatic CCAs and were mutually exclusive with KRAS/ERBB2/BRAF/FGFR mutations, pointing to their potential roles as oncogenic drivers. CONCLUSION: FGFR2 fusions are rare in fluke-associated CCA, underscoring how distinct etiologies may affect molecular landscapes in tumors and highlighting the need to discover other actionable genomic alterations in endemic fluke-associated CCA.

SRSF1 mediates cytokine-induced impaired imatinib sensitivity in chronic myeloid leukemia.

Patients with chronic myeloid leukemia (CML) who are treated with tyrosine kinase inhibitors (TKIs) experience significant heterogeneity regarding depth and speed of responses. Factors intrinsic and extrinsic to CML cells contribute to response heterogeneity and TKI resistance. Among extrinsic factors, cytokine-mediated TKI resistance has been demonstrated in CML progenitors, but the underlying mechanisms remain obscure. Using RNA-sequencing, we identified differentially expressed splicing factors in primary CD34+ chronic phase (CP) CML progenitors and controls. We found SRSF1 expression to be increased as a result of both BCR-ABL1- and cytokine-mediated signaling. SRSF1 overexpression conferred cytokine independence to untransformed hematopoietic cells and impaired imatinib sensitivity in CML cells, while SRSF1 depletion in CD34+ CP CML cells prevented the ability of extrinsic cytokines to decrease imatinib sensitivity. Mechanistically, PRKCH and PLCH1 were upregulated by elevated SRSF1 levels, and contributed to impaired imatinib sensitivity. Importantly, very high SRSF1 levels in the bone marrow of CML patients at presentation correlated with poorer clinical TKI responses. In summary, we find SRSF1 levels to be maintained in CD34+ CP CML progenitors by cytokines despite effective BCR-ABL1 inhibition, and that elevated levels promote impaired imatinib responses. Together, our data support an SRSF1/PRKCH/PLCH1 axis in contributing to cytokine-induced impaired imatinib sensitivity in CML.

The repertoire of mutational signatures in human cancer.

Somatic mutations in cancer genomes are caused by multiple mutational processes, each of which generates a characteristic mutational signature1. Here, as part of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium2 of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA), we characterized mutational signatures using 84,729,690 somatic mutations from 4,645 whole-genome and 19,184 exome sequences that encompass most types of cancer. We identified 49 single-base-substitution, 11 doublet-base-substitution, 4 clustered-base-substitution and 17 small insertion-and-deletion signatures. The substantial size of our dataset, compared with previous analyses3-15, enabled the discovery of new signatures, the separation of overlapping signatures and the decomposition of signatures into components that may represent associated-but distinct-DNA damage, repair and/or replication mechanisms. By estimating the contribution of each signature to the mutational catalogues of individual cancer genomes, we revealed associations of signatures to exogenous or endogenous exposures, as well as to defective DNA-maintenance processes. However, many signatures are of unknown cause. This analysis provides a systematic perspective on the repertoire of mutational processes that contribute to the development of human cancer.

A functional network of gastric-cancer-associated splicing events controlled by dysregulated splicing factors.

Comprehensive understanding of aberrant splicing in gastric cancer is lacking. We RNA-sequenced 19 gastric tumor-normal pairs and identified 118 high-confidence tumor-associated (TA) alternative splicing events (ASEs) based on high-coverage sequencing and stringent filtering, and also identified 8 differentially expressed splicing factors (SFs). The TA ASEs occurred in genes primarily involved in cytoskeletal organization. We constructed a correlative network between TA ASE splicing ratios and SF expression, replicated it in independent gastric cancer data from The Cancer Genome Atlas and experimentally validated it by knockdown of the nodal SFs (PTBP1, ESRP2 and MBNL1). Each SF knockdown drove splicing alterations in several corresponding TA ASEs and led to alterations in cellular migration consistent with the role of TA ASEs in cytoskeletal organization. We have therefore established a robust network of dysregulated splicing associated with tumor invasion in gastric cancer. Our work is a resource for identifying oncogenic splice forms, SFs and splicing-generated tumor antigens as biomarkers and therapeutic targets.