mSignatureDB: a database for deciphering mutational signatures in human cancers

Mutational profile evaluates metastatic capacity of Chinese colorectal cancer patients, revealed by whole-exome sequencing

Colorectal cancer (CRC) is the third most common cancer and the prevalence rate of CRC is increasing in the China. In this study, whole-exome sequencing (WES) was performed on primary tissues of 47 CRC Chinese patients including 22 metastatic and 25 non-metastatic patients. By comparison with data from western colorectal cancer patients in the Cancer Genome Atlas (TCGA), we identified a number of genes that are more likely to be mutated in Chinese colorectal cancer patients, such as MUC12, MUC12, MUC2, MUC4, HYDIN and KMT2C. Interestingly, MUC family genes including MUC12, MUC2 and MUC4, have mutation rates of >20%, while the mutation frequency was extremely low in western colorectal cancer patients, which were <3% in TCGA and 0% in Memorial Sloan Kettering Cancer Center (MSKCC). We detected metastasis-specific mutated genes including TCF7L2, MST1L, HRNR and SMAD4, while MUC4, NEB, FLG and RFPL4A alteration is more prevalent in the non-metastasis group. Further analysis reveals mutation genes in metastasis group are more focus in the Wnt and Hippo signaling pathway. APC, SMAD4 and TCF7L2 accounted for the major genetic abnormalities in this pathway. In conclusion, this study identified the unique characteristics of gene mutations in Chinese patients with colorectal cancer, and is a valuable reference for personalized treatment in Chinese CRC patients.

Microsatellite Instability and Mismatch Repair Deficiency Define a Distinct Subset of Lung Cancers Characterized by Smoking Exposure, High Tumor Mutational Burden, and Recurrent Somatic MLH1 Inactivation

INTRODUCTION

Microsatellite instability (MSI) and mismatch repair (MMR) deficiency represent a distinct oncogenic process and predict response to immune checkpoint inhibitors (ICIs). The clinicopathologic features of MSI-high (MSI-H) and MMR deficiency (MMR-D) in lung cancers remain poorly characterized.

METHODS

MSI status from 5171 patients with NSCLC and 315 patients with SCLC was analyzed from targeted next-generation sequencing data using two validated bioinformatic pipelines.

RESULTS

MSI-H and MMR-D were identified in 21 patients with NSCLC (0.41%) and six patients with SCLC (1.9%). Notably, all patients with NSCLC had a positive smoking history, including 11 adenocarcinomas. Compared with microsatellite stable cases, MSI-H was associated with exceptionally high tumor mutational burden (37.4 versus 8.5 muts/Mb, p < 0.0001), MMR mutational signatures (43% versus 0%, p < 0.0001), and somatic biallelic alterations in MLH1 (52% versus 0%, p < 0.0001). Loss of MLH1 and PMS2 expression by immunohistochemistry was found in MLH1 altered and wild-type cases. Similarly, the majority of patients with MSI-H SCLC had evidence of MLH1 inactivation, including two with MLH1 promoter hypermethylation. A single patient with NSCLC with a somatic MSH2 mutation had Lynch syndrome as confirmed by the presence of a germline MSH2 mutation. Among patients with advanced MSI-H lung cancers treated with ICIs, durable clinical benefit was observed in three of eight patients with NSCLC and two of two patients with SCLC. In NSCLC, STK11, KEAP1, and JAK1 were mutated in nonresponders but wild type in responders.

CONCLUSIONS

We present a comprehensive clinicogenomic landscape of MSI-H lung cancers and reveal that MSI-H defines a rare subset of lung cancers associated with smoking, high tumor mutational burden, and MLH1 inactivation. Although durable clinical benefit to ICI was observed in some patients, the broad range of responses suggests that clinical activity may be modulated by co-mutational landscapes.

Non-BRCA1/BRCA2 high-risk familial breast cancers are not associated with a high prevalence of BRCAness

BACKGROUND

Familial breast cancer is in most cases unexplained due to the lack of identifiable pathogenic variants in the BRCA1 and BRCA2 genes. The somatic mutational landscape and in particular the extent of BRCA-like tumour features (BRCAness) in these familial breast cancers where germline BRCA1 or BRCA2 mutations have not been identified is to a large extent unknown.

METHODS

We performed whole-genome sequencing on matched tumour and normal samples from high-risk non-BRCA1/BRCA2 breast cancer families to understand the germline and somatic mutational landscape and mutational signatures. We measured BRCAness using HRDetect. As a comparator, we also analysed samples from BRCA1 and BRCA2 germline mutation carriers.

RESULTS

We noted for non-BRCA1/BRCA2 tumours, only a small proportion displayed high HRDetect scores and were characterized by concomitant promoter hypermethylation or in one case a RAD51D splice variant previously reported as having unknown significance to potentially explain their BRCAness. Another small proportion showed no features of BRCAness but had mutationally active tumours. The remaining tumours lacked features of BRCAness and were mutationally quiescent.

CONCLUSIONS

A limited fraction of high-risk familial non-BRCA1/BRCA2 breast cancer patients is expected to benefit from treatment strategies against homologue repair deficient cancer cells.

Molecular Pathology of Lung Cancer

This overview of the molecular pathology of lung cancer includes a review of the most salient molecular alterations of the genome, transcriptome, and the epigenome. The insights provided by the growing use of next-generation sequencing (NGS) in lung cancer will be discussed, and interrelated concepts such as intertumor heterogeneity, intratumor heterogeneity, tumor mutational burden, and the advent of liquid biopsy will be explored. Moreover, this work describes how the evolving field of molecular pathology refines the understanding of different histologic phenotypes of non-small-cell lung cancer (NSCLC) and the underlying biology of small-cell lung cancer. This review will provide an appreciation for how ongoing scientific findings and technologic advances in molecular pathology are crucial for development of biomarkers, therapeutic agents, clinical trials, and ultimately improved patient care.

Premetastatic shifts of endogenous and exogenous mutational processes support consolidative therapy in EGFR-driven lung adenocarcinoma

The progression of cancer is an evolutionary process that is challenging to assess between sampling timepoints. However, investigation of cancer evolution over specific time periods is crucial to the elucidation of key events such as the acquisition of therapeutic resistance and subsequent fatal metastatic spread of therapy-resistant cell populations. Here we apply mutational signature analyses within clinically annotated cancer chronograms to detect and describe the shifting mutational processes caused by both endogenous (e.g. mutator gene mutation) and exogenous (e.g. mutagenic therapeutics) factors between tumor sampling timepoints. In one patient, we find that cisplatin therapy can introduce mutations that confer genetic resistance to subsequent targeted therapy with Erlotinib. In another patient, we trace detection of defective mismatch-repair associated mutational signature SBS3 to the emergence of known driver mutation CTNNB1 S37C. In both of these patients, metastatic lineages emerged from a single ancestral lineage that arose during therapy-a finding that argues for the consideration of local consolidative therapy over other therapeutic approaches in EGFR-positive non-small cell lung cancer. Broadly, these results demonstrate the utility of phylogenetic analysis that incorporates clinical time course and mutational signature deconvolution to inform therapeutic decision making and retrospective assessment of disease etiology.

Single-cell analysis of human non-small cell lung cancer lesions refines tumor classification and patient stratification

Immunotherapy is a mainstay of non-small cell lung cancer (NSCLC) management. While tumor mutational burden (TMB) correlates with response to immunotherapy, little is known about the relationship between the baseline immune response and tumor genotype. Using single-cell RNA sequencing, we profiled 361,929 cells from 35 early-stage NSCLC lesions. We identified a cellular module consisting of PDCD1⁺CXCL13⁺ activated T cells, IgG⁺ plasma cells, and SPP1⁺ macrophages, referred to as the lung cancer activation module (LCAM^hi). We confirmed LCAM^hi enrichment in multiple NSCLC cohorts, and paired CITE-seq established an antibody panel to identify LCAM^hi lesions. LCAM presence was found to be independent of overall immune cell content and correlated with TMB, cancer testis antigens, and TP53 mutations. High baseline LCAM scores correlated with enhanced NSCLC response to immunotherapy even in patients with above median TMB, suggesting that immune cell composition, while correlated with TMB, may be a nonredundant biomarker of response to immunotherapy.

Monoallelic deleterious MUTYH germline variants as a driver for tumorigenesis

MUTYH encodes a glycosylase involved in the base excision repair of DNA. Biallelic pathogenic germline variants in MUTYH cause an autosomal recessive condition known as MUTYH-associated adenomatous polyposis and consequently increase the risk of colorectal cancer. However, reports of increased cancer risk in individuals carrying only one defective MUTYH allele are controversial and based on studies involving few individuals. Here, we describe a comprehensive investigation of monoallelic pathogenic MUTYH germline variants in 10,389 cancer patients across 33 different tumour types and 117,000 healthy individuals. Our results indicate that monoallelic pathogenic MUTYH germline variants can lead to tumorigenesis through a mechanism of somatic loss of heterozygosity of the functional MUTYH allele in the tumour. We confirmed that the frequency of monoallelic pathogenic MUTYH germline variants is higher in individuals with cancer than in the general population, although this frequency is not homogeneous among tumour types. We also demonstrated that the MUTYH mutational signature is present only in tumours with loss of the functional allele and found that the characteristic MUTYH base substitution (C>A) increases stop-codon generation. We identified key genes that are affected during tumorigenesis. In conclusion, we propose that carriers of the monoallelic pathogenic MUTYH germline variant are at a higher risk of developing tumours, especially those with frequent loss of heterozygosity events, such as adrenal adenocarcinoma, although the overall risk is still low. © 2021 The Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Whole-exome Sequencing of Epstein-Barr Virus-associated Pulmonary Carcinoma With Low Lymphocytic Infiltration Shows Molecular Features Similar to Those of Classic Pulmonary Lymphoepithelioma-like Carcinoma: Evidence to Support Grouping Together as One Disease Entity

Pulmonary lymphoepithelioma-like carcinoma (LELC) is a distinct type of Epstein-Barr virus (EBV)-associated non-small cell carcinoma characterized by a syncytial growth pattern with heavy lymphocytic infiltration. We recently identified a group of non-small cell carcinomas, which are also associated with EBV but lack significant lymphocytic infiltration. These EBV-associated pulmonary carcinomas with low lymphocytic infiltration morphologically resemble nonkeratinizing squamous cell carcinoma, but their patient characteristics are more similar to those of LELC, including female sex and nonsmoking status. To clarify the relationships between these disease entities, in this study, we explored the molecular characteristics of the EBV-associated carcinomas with low lymphocytic infiltration using whole-exome sequencing and compared their molecular profiles with those of classic LELC and pulmonary squamous cell carcinoma. We demonstrate that the molecular characteristics of EBV-associated carcinomas with low lymphocytic infiltration are highly similar to those of classic LELC. Both show low tumor mutational burden, lack of commonly mutated driver genes in other types of non-small cell lung cancer, similar mutational signature involving APOBEC-related mutations, and enrichment of CD274 (programmed death-ligand 1) amplification. These molecular characteristics are very different from those of pulmonary squamous cell carcinoma. The unique patient demographics and molecular characteristics shared by EBV-associated carcinomas with low lymphocytic infiltration and classic LELC suggest that these tumors represent one single disease entity defined by EBV association. This study supports the proposal for the usage of the term "EBV-associated pulmonary carcinoma" to encompass the entire morphologic spectrum of this distinct EBV-associated disease entity.

Recognizing Pattern and Rule of Mutation Signatures Corresponding to Cancer Types

Cancer has been generally defined as a cluster of systematic malignant pathogenesis involving abnormal cell growth. Genetic mutations derived from environmental factors and inherited genetics trigger the initiation and progression of cancers. Although several well-known factors affect cancer, mutation features and rules that affect cancers are relatively unknown due to limited related studies. In this study, a computational investigation on mutation profiles of cancer samples in 27 types was given. These profiles were first analyzed by the Monte Carlo Feature Selection (MCFS) method. A feature list was thus obtained. Then, the incremental feature selection (IFS) method adopted such list to extract essential mutation features related to 27 cancer types, find out 207 mutation rules and construct efficient classifiers. The top 37 mutation features corresponding to different cancer types were discussed. All the qualitatively analyzed gene mutation features contribute to the distinction of different types of cancers, and most of such mutation rules are supported by recent literature. Therefore, our computational investigation could identify potential biomarkers and prediction rules for cancers in the mutation signature level.

Recruitment of KMT2C/MLL3 to DNA Damage Sites Mediates DNA Damage Responses and Regulates PARP Inhibitor Sensitivity in Cancer

When recruited to promoters, histone 3 lysine 4 (H3K4) methyltransferases KMT2 (KMT2A-D) activate transcription by opening chromatin through H3K4 methylation. Here, we report that KMT2 mutations occur frequently in non-small cell lung cancer (NSCLC) and are associated with high mutation loads and poor survival. KMT2C regulated DNA damage responses (DDR) through direct recruitment to DNA damage sites by Ago2 and small noncoding DNA damage response RNA, where it mediates H3K4 methylation, chromatin relaxation, secondary recruitment of DDR factors, and amplification of DDR signals along chromatin. Furthermore, by disrupting homologous recombination (HR)-mediated DNA repair, KMT2C/D mutations sensitized NSCLC to Poly(ADP-ribose) polymerase inhibitors (PARPi), whose efficacy is unclear in NSCLC due to low BRCA1/2 mutation rates. These results demonstrate a novel, transcription-independent role of KMT2C in DDR and identify high-frequency KMT2C/D mutations as much-needed biomarkers for PARPi therapies in NSCLC and other cancers with infrequent BRCA1/2 mutations. SIGNIFICANCE: This study uncovers a critical role for KMT2C in DDR via direct recruitment to DNA damage sites, identifying high-frequency KMT2C/D mutations as biomarkers for response to PARP inhibition in cancer.

Identification of combinations of somatic mutations that predict cancer survival and immunotherapy benefit

Cancer evolves through the accumulation of somatic mutations over time. Although several methods have been developed to characterize mutational processes in cancers, these have not been specifically designed to identify mutational patterns that predict patient prognosis. Here we present CLICnet, a method that utilizes mutational data to cluster patients by survival rate. CLICnet employs Restricted Boltzmann Machines, a type of generative neural network, which allows for the capture of complex mutational patterns associated with patient survival in different cancer types. For some cancer types, clustering produced by CLICnet also predicts benefit from anti-PD1 immune checkpoint blockade therapy, whereas for other cancer types, the mutational processes associated with survival are different from those associated with the improved anti-PD1 survival benefit. Thus, CLICnet has the ability to systematically identify and catalogue combinations of mutations that predict cancer survival, unveiling intricate associations between mutations, survival, and immunotherapy benefit.

Comprehensive functional genomic analyses link APC somatic mutation and mRNA-miRNA networks to the clinical outcome of stage-III colorectal cancer patients

Background

Colorectal cancer (CRC) is a major health concern globally, but exhibits regional and/or environmental distinctions in terms of outcome especially for patients with stage III CRC.

Methods

From 2014 to 2016, matched pairs of tumor and adjacent normal tissue samples from 60 patients with stage I–IV CRC from Chang Gung Memorial Hospital in Taiwan were analyzed using next-generation sequencing. The DNA, mRNA, and miRNA sequences of paired tumor tissues were profiled. An observational study with survival analysis was done. Online datasets of The Cancer Genome Atlas (TCGA) and The International Cancer Genome Consortium (ICGC) were also integrated and compared.

Results

The gene that exhibited the highest mutation rate was adenomatous polyposis coli (APC) (75.0%), followed by TP53 (70.0%), KRAS (56.6%), and TTN (48.3%). APC was also the most frequently mutated gene in TCGA and ICGC datasets. Surprisingly, for non-metastatic cases (stages I-III), CRC patients with mutated APC had better outcome in terms of overall survival (p = 0.041) and recurrence free survival (p = 0.0048). Particularly for stage III CRC, the overall survival rate was 94.4% and 67.7%, respectively (p = 0.018), and the recurrence free survival rate was 94.4% and 16.7%, respectively (p = 0.00044). Further clinical and gene expression analyses revealed that the APC wt specimens to a greater extent exhibit poor differentiation state as well as EGFR upregulation, providing molecular basis for the poor prognosis of these patients. Finally, based on integrated transcriptome analysis, we constructed the mRNA-miRNA networks underlying disease recurrence of the stage III CRC and uncovered potential therapeutic targets for this clinical condition.

Conclusion

For stage III CRC, patients with mutated APC had better overall and recurrence free survival.

MYBL2-Driven Transcriptional Programs Link Replication Stress and Error-prone DNA Repair With Genomic Instability in Lung Adenocarcinoma

It has long been recognized that defects in cell cycle checkpoint and DNA repair pathways give rise to genomic instability, tumor heterogeneity, and metastasis. Despite this knowledge, the transcription factor-mediated gene expression programs that enable survival and proliferation in the face of enormous replication stress and DNA damage have remained elusive. Using robust omics data from two independent studies, we provide evidence that a large cohort of lung adenocarcinomas exhibit significant genome instability and overexpress the DNA damage responsive transcription factor MYB proto-oncogene like 2 (MYBL2). Across two studies, elevated MYBL2 expression was a robust marker of poor overall survival and disease-free survival outcomes, regardless of disease stage. Clinically, elevated MYBL2 expression identified patients with aggressive early onset disease, increased lymph node involvement, and increased incidence of distant metastases. Analysis of genomic sequencing data demonstrated that MYBL2 High lung adenocarcinomas had elevated somatic mutation burden, widespread chromosomal alterations, and alterations in single-strand DNA break repair pathways. In this study, we provide evidence that impaired single-strand break repair, combined with a loss of cell cycle regulators TP53 and RB1, give rise to MYBL2-mediated transcriptional programs. Omics data supports a model wherein tumors with significant genomic instability upregulate MYBL2 to drive genes that control replication stress responses, promote error-prone DNA repair, and antagonize faithful homologous recombination repair. Our study supports the use of checkpoint kinase 1 (CHK1) pharmacological inhibitors, in targeted MYBL2 High patient cohorts, as a future therapy to improve lung adenocarcinoma patient outcomes.

Analysis of mutational signatures with yet another package for signature analysis

Different mutational processes leave characteristic patterns of somatic mutations in the genome that can be identified as mutational signatures. Determining the contributions of mutational signatures to cancer genomes allows not only to reconstruct the etiology of somatic mutations, but can also be used for improved tumor classification and support therapeutic decisions. We here present the R package yet another package for signature analysis (YAPSA) to deconvolute the contributions of mutational signatures to tumor genomes. YAPSA provides in-built collections from the COSMIC and PCAWG SNV signature sets as well as the PCAWG Indel signatures and employs signature-specific cutoffs to increase sensitivity and specificity. Furthermore, YAPSA allows to determine 95% confidence intervals for signature exposures, to perform constrained stratified signature analyses to obtain enrichment and depletion patterns of the identified signatures and, when applied to whole exome sequencing data, to correct for the triplet content of individual target capture kits. With this functionality, YAPSA has proved to be a valuable tool for analysis of mutational signatures in molecular tumor boards in a precision oncology context. YAPSA is available at R/Bioconductor (http://bioconductor.org/packages/3.12/bioc/html/YAPSA.html).

Two novel cell culture models of buccal mucosal oral cancer from patients with no risk-habits of tobacco smoking or chewing

OBJECTIVE

Tobacco consumption is one of the major etiological factors for oral cancer, but it also develops in non-tobacco users, with unknown etiologies. Cellular models for tobacco associated oral cancer are available, however; reports of cellular models for studying non-tobacco associated oral cancer are limiting. We report here the establishment and characterization of two novel buccal mucosal cancer cell lines 'GBC02' and 'GBC035' derived from non-tobacco users.

MATERIALS AND METHODS

Short tandem repeats (STR) profiling, Next-generation sequencing for whole-genome, exome and copy number alterations, immunofluorescence, flow-cytometry, proliferation, live-cell chemotaxis, 3D-spheroid formation, chemotherapy response, gene-expression microarray, gene-set enrichment analysis and xenograft development were performed.

RESULTS

Sources of the established cultures were matched to their donors through STR profiling. Genome sequence analysis revealed somatic mutations in TP53, CASP8, CDKN2A for GBC02 with deletions and amplifications encompassing CDKN2A, FAT1 and CCND1, PIK3CA, SOX2, EGFR, MYC genes, respectively. GBC035 harbored mutations in FAT1, NOTCH1, HRAS, CDKN2A, HLA-B, HLA-A genes. While GBC035 cells showed higher E-Cadherin positive cell-cell junctions and collective cell migration in chemotaxis; GBC02 cells were vimentin-positive and demonstrated individual cell migration. Further, exhibiting their relevance to preclinical research, GBC02 3D-spheroids demonstrated enrichment of development-related gene-signatures in microarray transcriptome analysis and were resistant to Cisplatin, but showed sensitivity to cancer stem cells-targeting drug, Salinomycin. Additionally, tumorigenic ability of GBC02 was demonstrated.

CONCLUSIONS

Altogether, we present here comprehensively characterized unique cell lines established from non-tobacco associated tumors, which may serve as models for preclinical investigations of oral cancers caused independent of tobacco usage.

Upregulation of centromere protein M promotes tumorigenesis: A potential predictive target for cancer in humans

Centromere protein M (CENPM), a protein required for chromosome separation, is involved in in mitosis. However, little has been reported about the roles of CENPM in various types of cancer. The present study identified that the mRNA expression levels of CENPM were significantly upregulated in 14 types of human cancer and identified a positive association between CENPM mRNA expression and patient mortality using the Oncomine, Gene Expression Profiling Interactive Analysis, Human Protein Atlas and Kaplan‑Meier Plotter databases. A protein interaction network constructed with CENPM‑interacting genes obtained from the cBioPortal demonstrated that nine genes participating in the cell cycle served key roles in the function of CENPM. Cell cycle analysis, reverse transcription‑quantitative polymerase chain reaction, a Cell Counting Kit‑8‑based proliferation assay and a terminal deoxynucleotidyl transferase dUTP nick end labelling assay further revealed the tumorigenic and carcinogenic roles of CENPM in vitro. In addition, it was identified that the mRNA expression levels of five of the nine identified genes were significantly associated with CENPM in MCF7 cells and that CENPM was rarely mutated among various types of human cancer. In conclusion, the data from the present study revealed that CENPM exerted its pro‑tumorigenic function by regulating cell cycle‑associated protein expression and suggested that CENPM could be used as a prognostic marker for breast cancer.

MutSignatures: an R package for extraction and analysis of cancer mutational signatures

Cancer cells accumulate somatic mutations as result of DNA damage, inaccurate repair and other mechanisms. Different genetic instability processes result in characteristic non-random patterns of DNA mutations, also known as mutational signatures. We developed mutSignatures, an integrated R-based computational framework aimed at deciphering DNA mutational signatures. Our software provides advanced functions for importing DNA variants, computing mutation types, and extracting mutational signatures via non-negative matrix factorization. Specifically, mutSignatures accepts multiple types of input data, is compatible with non-human genomes, and supports the analysis of non-standard mutation types, such as tetra-nucleotide mutation types. We applied mutSignatures to analyze somatic mutations found in smoking-related cancer datasets. We characterized mutational signatures that were consistent with those reported before in independent investigations. Our work demonstrates that selected mutational signatures correlated with specific clinical and molecular features across different cancer types, and revealed complementarity of specific mutational patterns that has not previously been identified. In conclusion, we propose mutSignatures as a powerful open-source tool for detecting the molecular determinants of cancer and gathering insights into cancer biology and treatment.

p31comet promotes homologous recombination by inactivating REV7 through the TRIP13 ATPase

The repair of DNA double strand breaks (DSBs) that arise from external mutagenic agents and routine cellular processes is essential for life. DSBs are repaired by two major pathways, homologous recombination (HR) and classical nonhomologous end joining (C-NHEJ). DSB repair pathway choice is largely dictated at the step of 5'-3' DNA end resection, which is promoted during S phase, in part by BRCA1. Opposing end resection is the 53BP1 protein, which recruits the ssDNA-binding REV7-Shieldin complex to favor C-NHEJ repair. We recently identified TRIP13 as a proresection factor that remodels REV7, causing its dissociation from the Shieldin subunit SHLD3. Here, we identify p31^comet, a negative regulator of MAD2 and the spindle assembly checkpoint, as an important mediator of the TRIP13-REV7 interaction. p31^comet binds to the REV7-Shieldin complex in cells, promotes REV7 inactivation, and causes PARP inhibitor resistance. p31^comet also participates in the extraction of REV7 from the chromatin. Furthermore, p31^comet can counteract REV7 function in translesion synthesis (TLS) by releasing it from REV3 in the Pol ζ complex. Finally, p31^comet, like TRIP13, is overexpressed in many cancers and this correlates with poor prognosis. Thus, we reveal a key player in the regulation of HR and TLS with significant clinical implications.

From tobacco smoking to cancer mutational signature: a mediation analysis strategy to explore the role of epigenetic changes

Background

Tobacco smoking is associated with a unique mutational signature in the human cancer genome. It is unclear whether tobacco smoking-altered DNA methylations and gene expressions affect smoking-related mutational signature.

Methods

We systematically analyzed the smoking-related DNA methylation sites reported from five previous casecontrol studies in peripheral blood cells to identify possible target genes. Using the mediation analysis approach, we evaluated whether the association of tobacco smoking with mutational signature is mediated through altered DNA methylation and expression of these target genes in lung adenocarcinoma tumor tissues.

Results

Based on data obtained from 21,108 blood samples, we identified 374 smoking-related DNA methylation sites, annotated to 248 target genes. Using data from DNA methylations, gene expressions and smoking-related mutational signature generated from ~ 7700 tumor tissue samples across 26 cancer types from The Cancer Genome Atlas (TCGA), we found 11 of the 248 target genes whose expressions were associated with smoking-related mutational signature at a Bonferroni-correction P < 0.001. This included four for head and neck cancer, and seven for lung adenocarcinoma. In lung adenocarcinoma, our results showed that smoking increased the expression of three genes, AHRR, GPR15, and HDGF, and decreased the expression of two genes, CAPN8, and RPS6KA1, which were consequently associated with increased smoking-related mutational signature. Additional evidence showed that the elevated expression of AHRR and GPR15 were associated with smoking-altered hypomethylations at cg14817490 and cg19859270, respectively, in lung adenocarcinoma tumor tissues. Lastly, we showed that decreased expression of RPS6KA1, were associated with poor survival of lung cancer patients.

Conclusions

Our findings provide novel insight into the contributions of tobacco smoking to carcinogenesis through the underlying mechanisms of the elevated mutational signature by altered DNA methylations and gene expressions.

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

MOTIVATION

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

RESULTS

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

AVAILABILITY AND IMPLEMENTATION

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

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Distinct immune evasion in APOBEC-enriched, HPV-negative HNSCC

Immune checkpoint inhibition leads to response in some patients with head and neck squamous cell carcinoma (HNSCC). Robust biomarkers are lacking to date. We analyzed viral status, gene expression signatures, mutational load and mutational signatures in whole exome and RNA-sequencing data of the HNSCC TCGA dataset (n = 496) and a validation set (DKTK MASTER cohort, n = 10). Public single-cell gene expression data from 17 HPV-negative HNSCC were separately reanalyzed. APOBEC3-associated TCW motif mutations but not total single nucleotide variant burden were significantly associated with inflammation. This association was restricted to HPV-negative HNSCC samples. An APOBEC-enriched, HPV-negative subgroup was identified, that showed higher T-cell inflammation and immune checkpoint expression, as well as expression of APOBEC3 genes. Mutations in immune-evasion pathways were also enriched in these tumors. Analysis of single-cell sequencing data identified expression of APOBEC3B and 3C genes in malignant cells. We identified an APOBEC-enriched subgroup of HPV-negative HNSCC with a distinct immunogenic phenotype, potentially mediating response to immunotherapy.

Origins and characterization of variants shared between databases of somatic and germline human mutations

Background

Mutations arise in the human genome in two major settings: the germline and the soma. These settings involve different inheritance patterns, time scales, chromatin structures, and environmental exposures, all of which impact the resulting distribution of substitutions. Nonetheless, many of the same single nucleotide variants (SNVs) are shared between germline and somatic mutation databases, such as between the gnomAD database of 120,000 germline exomes and the TCGA database of 10,000 somatic exomes. Here, we sought to explain this overlap.

Results

After strict filtering to exclude common germline polymorphisms and sites with poor coverage or mappability, we found 336,987 variants shared between the somatic and germline databases. A uniform statistical model explains 34% of these shared variants; a model that incorporates the varying mutation rates of the basic mutation types explains another 50% of shared variants; and a model that includes extended nucleotide contexts (e.g. surrounding 3 bases on either side) explains an additional 4% of shared variants. Analysis of read depth finds mixed evidence that up to 4% of the shared variants may represent germline variants leaked into somatic call sets. 9% of the shared variants are not explained by any model. Sequencing errors and convergent evolution did not account for these. We surveyed other factors as well: Cancers driven by endogenous mutational processes share a greater fraction of variants with the germline, and recently derived germline variants were more likely to be somatically shared than were ancient germline ones.

Conclusions

Overall, we find that shared variants largely represent bona fide biological occurrences of the same variant in the germline and somatic setting and arise primarily because DNA has some of the same basic chemical vulnerabilities in either setting. Moreover, we find mixed evidence that somatic call-sets leak appreciable numbers of germline variants, which is relevant to genomic privacy regulations. In future studies, the similar chemical vulnerability of DNA between the somatic and germline settings might be used to help identify disease-related genes by guiding the development of background-mutation models that are informed by both somatic and germline patterns of variation.

Genomic landscape of platinum resistant and sensitive testicular cancers

While most testicular germ cell tumours (TGCTs) exhibit exquisite sensitivity to platinum chemotherapy, ~10% are platinum resistant. To gain insight into the underlying mechanisms, we undertake whole exome sequencing and copy number analysis in 40 tumours from 26 cases with platinum-resistant TGCT, and combine this with published genomic data on an additional 624 TGCTs. We integrate analyses for driver mutations, mutational burden, global, arm-level and focal copy number (CN) events, and SNV and CN signatures. Albeit preliminary and observational in nature, these analyses provide support for a possible mechanistic link between early driver mutations in RAS and KIT and the widespread copy number events by which TGCT is characterised.

Interplay between DNA damage repair and apoptosis shapes cancer evolution through aneuploidy and microsatellite instability

Driver mutations and chromosomal aneuploidy are major determinants of tumorigenesis that exhibit complex relationships. Here, we identify associations between driver mutations and chromosomal aberrations that define two tumor clusters, with distinct regimes of tumor evolution underpinned by unique sets of mutations in different components of DNA damage response. Gastrointestinal and endometrial tumors comprise a separate cluster for which chromosomal-arm aneuploidy and driver mutations are mutually exclusive. The landscape of driver mutations in these tumors is dominated by mutations in DNA repair genes that are further linked to microsatellite instability. The rest of the cancer types show a positive association between driver mutations and aneuploidy, and a characteristic set of mutations that involves primarily genes for components of the apoptotic machinery. The distinct sets of mutated genes derived here show substantial prognostic power and suggest specific vulnerabilities of different cancers that might have therapeutic potential.

Higher prevalence of homologous recombination deficiency in tumors from African Americans versus European Americans

To improve our understanding of longstanding disparities in incidence and mortality in lung cancer across ancestry, we performed a systematic comparative analysis of molecular features in tumors from African Americans (AAs) and European Americans (EAs). We find that lung squamous cell carcinoma tumors from AAs exhibit higher genomic instability-the proportion of non-diploid genome-aggressive molecular features such as chromothripsis and higher homologous recombination deficiency (HRD). In The Cancer Genome Atlas, we demonstrate that high genomic instability, HRD and chromothripsis among tumors from AAs is found across many cancer types. The prevalence of germline HRD (that is, the total number of pathogenic variants in homologous recombination genes) is higher in tumors from AAs, suggesting that the somatic differences observed have genetic ancestry origins. We also identify AA-specific copy-number-based arm-, focal- and gene-level recurrent features in lung cancer, including higher frequencies of PTEN deletion and KRAS amplification. These results highlight the importance of including under-represented populations in genomics research.

TRIP13 regulates DNA repair pathway choice through REV7 conformational change

DNA double-strand breaks (DSBs) are repaired through homology-directed repair (HDR) or non-homologous end joining (NHEJ). BRCA1/2-deficient cancer cells cannot perform HDR, conferring sensitivity to poly(ADP-ribose) polymerase inhibitors (PARPi). However, concomitant loss of the pro-NHEJ factors 53BP1, RIF1, REV7-Shieldin (SHLD1-3) or CST-DNA polymerase alpha (Pol-α) in BRCA1-deficient cells restores HDR and PARPi resistance. Here, we identify the TRIP13 ATPase as a negative regulator of REV7. We show that REV7 exists in active 'closed' and inactive 'open' conformations, and TRIP13 catalyses the inactivating conformational change, thereby dissociating REV7-Shieldin to promote HDR. TRIP13 similarly disassembles the REV7-REV3 translesion synthesis (TLS) complex, a component of the Fanconi anaemia pathway, inhibiting error-prone replicative lesion bypass and interstrand crosslink repair. Importantly, TRIP13 overexpression is common in BRCA1-deficient cancers, confers PARPi resistance and correlates with poor prognosis. Thus, TRIP13 emerges as an important regulator of DNA repair pathway choice-promoting HDR, while suppressing NHEJ and TLS.

Molecular Profiles and Metastasis Markers in Chinese Patients with Gastric Carcinoma

The goal of this work was to investigate the molecular profiles and metastasis markers in Chinese patients with gastric carcinoma (GC). In total, we performed whole exome sequencing (WES) on 74 GC patients with tumor and adjacent normal formalin-fixed, paraffin-embedded (FFPE) tissue samples. The mutation spectrum of these samples showed a high concordance with TCGA and other studies on GC. PTPRT is significantly associated with metastasis of GC, suggesting its predictive role in metastasis of GC. Patients carrying BRCA2 mutations tend not to metastasize, which may be related to their sensitivity to chemotherapy. Mutations in MACF1, CDC27, HMCN1, CDH1 and PDZD2 were moderately enriched in peritoneal metastasis (PM) samples. Furthermore, we found two genomic regions (1p36.21 and Xq26.3) were associated with PM of GC, and patients with amplification of 1p36.21 and Xq26.3 have a worse prognosis (P = 0.002, 0.01, respectively). Our analysis provides GC patients with potential markers for single and combination therapies.

Computational tools to detect signatures of mutational processes in DNA from tumours: A review and empirical comparison of performance

Mutational signatures refer to patterns in the occurrence of somatic mutations that might be uniquely ascribed to particular mutational process. Tumour mutation catalogues can reveal mutational signatures but are often consistent with the mutation spectra produced by a variety of mutagens. To date, after the analysis of tens of thousands of exomes and genomes from about 40 different cancer types, tens of mutational signatures characterized by a unique probability profile across the 96 trinucleotide-based mutation types have been identified, validated and catalogued. At the same time, several concurrent methods have been developed for either the quantification of the contribution of catalogued signatures in a given cancer sequence or the identification of new signatures from a sample of cancer sequences. A review of existing computational tools has been recently published to guide researchers and practitioners through their mutational signature analyses, but other tools have been introduced since its publication and, a systematic evaluation and comparison of the performance of such tools is still lacking. In order to fill this gap, we have carried out an empirical evaluation of the main packages available to date, using both real and simulated data. Among other results, our empirical study shows that the identification of signatures is more difficult for cancers characterized by multiple signatures each having a small contribution. This work suggests that detection methods based on probabilistic models, especially EMu and bayesNMF, have in general better performance than NMF-based methods.

Identifying Putative Susceptibility Genes and Evaluating Their Associations with Somatic Mutations in Human Cancers

Genome-wide association studies (GWASs) have identified hundreds of genetic risk variants for human cancers. However, target genes for the majority of risk loci remain largely unexplored. It is also unclear whether GWAS risk-loci-associated genes contribute to mutational signatures and tumor mutational burden (TMB) in cancer tissues. We systematically conducted cis-expression quantitative trait loci (cis-eQTL) analyses for 294 GWAS-identified variants for six major types of cancer-colorectal, lung, ovary, prostate, pancreas, and melanoma-by using transcriptome data from the Genotype-Tissue Expression (GTEx) Project, the Cancer Genome Atlas (TCGA), and other public data sources. By using integrative analysis strategies, we identified 270 candidate target genes, including 99 with previously unreported associations, for six cancer types. By analyzing functional genomic data, our results indicate that 180 genes (66.7% of 270) had evidence of cis-regulation by putative functional variants via proximal promoter or distal enhancer-promoter interactions. Together with our previously reported associations for breast cancer risk, our results show that 24 genes are shared by at least two cancer types, including four genes for both breast and ovarian cancer. By integrating mutation data from TCGA, we found that expression levels of 33 and 66 putative susceptibility genes were associated with specific mutational signatures and TMB of cancer-driver genes, respectively, at a Bonferroni-corrected p < 0.05. Together, these findings provide further insight into our understanding of how genetic risk variants might contribute to carcinogenesis through the regulation of susceptibility genes that are related to the biogenesis of somatic mutations.

Integrative genomic analysis identifies associations of molecular alterations to APOBEC and BRCA1/2 mutational signatures in breast cancer

BACKGROUND

The observed mutations in cancer are the result of ~30 mutational processes, which stamp particular mutational signatures (MS). Nevertheless, it is still not clear which genomic alterations correlate to several MS. Here, a method to analyze associations of genomic data with MS is presented and applied to The Cancer Genome Atlas breast cancer data revealing promising associations.

METHODS

The MS were discretized into clusters whose extremes were statistically associated with mutations, copy number, and gene expression data.

RESULTS

Known associations for apolipoprotein B editing complex (APOBEC) and for BRCA1 and BRCA2 support the proposal. For BRCA1/2, mutations in ARAP3, three focal deletions, and one amplification were detected. Around 50 mutated genes for the two APOBEC signatures were identified including three kinesins (KIF13A, KIF1B, KIF4A), three ubiquitins (USP45, UBR4, UBR1), and two demethylases (KDM5B, KDM5C) among other genes also connected to DNA damage pathways. The results suggest novel roles for other genes currently not involved in DNA repair. The altered expression program was very high for the BRCA1/2 signature, high for APOBEC signature 13 clearly associated to immune response, and low for APOBEC signature 2. The remaining signatures show scarce associations.

CONCLUSION

Specific genetic alterations can be associated with particular MS.

CoMutPlotter: a web tool for visual summary of mutations in cancer cohorts

BACKGROUND

CoMut plot is widely used in cancer research publications as a visual summary of mutational landscapes in cancer cohorts. This summary plot can inspect gene mutation rate and sample mutation burden with their relevant clinical details, which is a common first step for analyzing the recurrence and co-occurrence of gene mutations across samples. The cBioPortal and iCoMut are two web-based tools that allow users to create intricate visualizations from pre-loaded TCGA and ICGC data. For custom data analysis, only limited command-line packages are available now, making the production of CoMut plots difficult to achieve, especially for researchers without advanced bioinformatics skills. To address the needs for custom data and TCGA/ICGC data comparison, we have created CoMutPlotter, a web-based tool for the production of publication-quality graphs in an easy-of-use and automatic manner.

RESULTS

We introduce a web-based tool named CoMutPlotter to lower the barriers between complex cancer genomic data and researchers, providing intuitive access to mutational profiles from TCGA/ICGC projects as well as custom cohort studies. A wide variety of file formats are supported by CoMutPlotter to translate cancer mutation profiles into biological insights and clinical applications, which include Mutation Annotation Format (MAF), Tab-separated values (TSV) and Variant Call Format (VCF) files.

CONCLUSIONS

In summary, CoMutPlotter is the first tool of its kind that supports VCF file, the most widely used file format, as its input material. CoMutPlotter also provides the most-wanted function for comparing mutation patterns between custom cohort and TCGA/ICGC project. Contributions of COSMIC mutational signatures in individual samples are also included in the summary plot, which is a unique feature of our tool. CoMutPlotter is freely available at http://tardis.cgu.edu.tw/comutplotter .

Somatic mutational signatures in polyposis and colorectal cancer

The somatic mutation spectrum imprinted in the genome of a tumor represents the mutational processes that have been active in that tumor. Large sequencing efforts in various cancer types have resulted in the identification of multiple mutational signatures, of which several have been linked to specific biological mechanisms. Several pan-cancer mutational signatures have been identified, while other signatures are only found in specific tissue types. Research on tumors from individuals with specific DNA repair defects has led to links between specific mutational signatures and mutational processes. Studying mutational signatures in cancers that are likely the result of a genetic predisposition may represent an interesting strategy to identify constitutional DNA repair defects, including those underlying polyposis and colorectal cancer.

Mutational Signatures in Mandibular Ameloblastoma Correlate with Smoking

Ameloblastoma is a rare tumor of odontogenic epithelium, the low incidence rate of which precludes statistical determination of its molecular characterizations. Despite recent genomic and transcriptomic profiling, the etiology of ameloblastomas remains poorly understood. Risk factors of ameloblastoma development are also largely unknown. Whole exome sequencing was performed on 11 mandibular ameloblastoma samples. We identified 2 convergent mutational signatures in ameloblastoma: 1) a signature found in multiple types of lung cancers with probable etiology of tobacco carcinogens (COSMIC signature 4) and 2) a signature present in gingivobuccal oral squamous cell carcinoma and correlated with tobacco-chewing habits (COSMIC signature 29). These mutational signatures highlight tobacco usage or related mutagens as one possible risk factor of ameloblastoma, since the association of BRAF mutations and smoking was demonstrated in multiple studies. In addition to BRAF hotspot mutations (V600E), we observed clear inter- and intratumor heterogeneities. Interestingly, prior to BRAF mutation, important genes regulating odontogenesis mutated (e.g., corepressor BCOR), possibly playing important roles in tumorigenesis. Furthermore, recurrent mutations in the CDC73 gene, the germline mutations of which predispose patients to the development of jaw tumors, were found in 2 patients, which may lead to recurrence if not targeted by therapeutic drugs. Our unbiased profiling of coding regions of ameloblastoma genomes provides insights to the possible etiology of mandibular ameloblastoma and highlights potential disease risk factors for screening and prevention, especially for Asian patients. Because of the limited sample size and incomplete habitual, dietary, and occupational data, a causal link between tobacco usage and ameloblastoma still requires further investigations.

Pan-cancer association of a centrosome amplification gene expression signature with genomic alterations and clinical outcome

Centrosome amplification (CA) is a common feature of human tumours and a promising target for cancer therapy. However, CA's pan-cancer prevalence, molecular role in tumourigenesis and therapeutic value in the clinical setting are still largely unexplored. Here, we used a transcriptomic signature (CA20) to characterise the landscape of CA-associated gene expression in 9,721 tumours from The Cancer Genome Atlas (TCGA). CA20 is upregulated in cancer and associated with distinct clinical and molecular features of breast cancer, consistently with our experimental CA quantification in patient samples. Moreover, we show that CA20 upregulation is positively associated with genomic instability, alteration of specific chromosomal arms and C>T mutations, and we propose novel molecular players associated with CA in cancer. Finally, high CA20 is associated with poor prognosis and, by integrating drug sensitivity with drug perturbation profiles in cell lines, we identify candidate compounds for selectively targeting cancer cells exhibiting transcriptomic evidence for CA.

Mutational Signatures in Cancer (MuSiCa): a web application to implement mutational signatures analysis in cancer samples

BACKGROUND

Mutational signatures have been proved as a valuable pattern in somatic genomics, mainly regarding cancer, with a potential application as a biomarker in clinical practice. Up to now, several bioinformatic packages to address this topic have been developed in different languages/platforms. MutationalPatterns has arisen as the most efficient tool for the comparison with the signatures currently reported in the Catalogue of Somatic Mutations in Cancer (COSMIC) database. However, the analysis of mutational signatures is nowadays restricted to a small community of bioinformatic experts.

RESULTS

In this work we present Mutational Signatures in Cancer (MuSiCa), a new web tool based on MutationalPatterns and built using the Shiny framework in R language. By means of a simple interface suited to non-specialized researchers, it provides a comprehensive analysis of the somatic mutational status of the supplied cancer samples. It permits characterizing the profile and burden of mutations, as well as quantifying COSMIC-reported mutational signatures. It also allows classifying samples according to the above signature contributions.

CONCLUSIONS

MuSiCa is a helpful web application to characterize mutational signatures in cancer samples. It is accessible online at http://bioinfo.ciberehd.org/GPtoCRC/en/tools.html and source code is freely available at https://github.com/marcos-diazg/musica .

The cytidine deaminase under-representation reporter (CDUR) as a tool to study evolution of sequences under deaminase mutational pressure

Background

Activation induced deaminase (AID) and apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like 3 (APOBEC3) are deaminases that mutate C to U on single-stranded DNA (ssDNA). AID is expressed primarily in germinal center B-cells, where it facilitates affinity maturation and class-switch recombination. APOBEC3 are a family of anti-viral proteins that act as part of the intrinsic immune response. In both cases, there are particular sequence motifs, also known as “mutation motifs”, to which these deaminases prefer to bind and mutate.

Results

We present a program, the cytidine deaminase under-representation reporter (CDUR) designed to statistically determine whether a given sequence has an under/over-representation of these mutation motifs. CDUR shows consitency with other studies of mutation motifs, as we show by analyzing sequences from the adeno-associated virus 2 (AAV2) and human papillomavirus (HPV).

Conclusion

Using various shuffling mechanisms to generate different null model distributions, we can tailor CDUR to correct for metrics such as GC-content, dinucleotide frequency, and codon bias.