The mutagenic forces shaping the genomic landscape of lung cancer in never smokers.

Lung cancer in never smokers (LCINS) accounts for up to 25% of all lung cancers and has been associated with exposure to secondhand tobacco smoke and air pollution in observational studies. Here, we evaluate the mutagenic exposures in LCINS by examining deep whole-genome sequencing data from a large international cohort of 871 treatment-naïve LCINS recruited from 28 geographical locations within the Sherlock-Lung study. KRAS mutations were 3.8-fold more common in adenocarcinomas of never smokers from North America and Europe, while a 1.6-fold higher prevalence of EGFR and TP53 mutations was observed in adenocarcinomas from East Asia. Signature SBS40a, with unknown cause, was found in most samples and accounted for the largest proportion of single base substitutions in adenocarcinomas, being enriched in EGFR-mutated cases. Conversely, the aristolochic acid signature SBS22a was almost exclusively observed in patients from Taipei. Even though LCINS exposed to secondhand smoke had an 8.3% higher mutational burden and 5.4% shorter telomeres, passive smoking was not associated with driver mutations in cancer driver genes or the activities of individual mutational signatures. In contrast, patients from regions with high levels of air pollution were more likely to have TP53 mutations while exhibiting shorter telomeres and an increase in most types of somatic mutations, including a 3.9-fold elevation of signature SBS4 (q-value=3.1 × 10-5), previously linked mainly to tobacco smoking, and a 76% increase of clock-like signature SBS5 (q-value=5.0 × 10-5). A positive dose-response effect was observed with air pollution levels, which correlated with both a decrease in telomere length and an elevation in somatic mutations, notably attributed to signatures SBS4 and SBS5. Our results elucidate the diversity of mutational processes shaping the genomic landscape of lung cancer in never smokers.

APOBEC shapes tumor evolution and age at onset of lung cancer in smokers.

APOBEC enzymes are part of the innate immunity and are responsible for restricting viruses and retroelements by deaminating cytosine residues1,2. Most solid tumors harbor different levels of somatic mutations attributed to the off-target activities of APOBEC3A (A3A) and/or APOBEC3B (A3B)3-6. However, how APOBEC3A/B enzymes shape the tumor evolution in the presence of exogenous mutagenic processes is largely unknown. Here, by combining deep whole-genome sequencing with multi-omics profiling of 309 lung cancers from smokers with detailed tobacco smoking information, we identify two subtypes defined by low (LAS) and high (HAS) APOBEC mutagenesis. LAS are enriched for A3B-like mutagenesis and KRAS mutations, whereas HAS for A3A-like mutagenesis and TP53 mutations. Unlike APOBEC3A, APOBEC3B expression is strongly associated with an upregulation of the base excision repair pathway. Hypermutation by unrepaired A3A and tobacco smoking mutagenesis combined with TP53-induced genomic instability can trigger senescence7, apoptosis8, and cell regeneration9, as indicated by high expression of pulmonary healing signaling pathway, stemness markers and distal cell-of-origin in HAS. The expected association of tobacco smoking variables (e.g., time to first cigarette) with genomic/epigenomic changes are not observed in HAS, a plausible consequence of frequent cell senescence or apoptosis. HAS have more neoantigens, slower clonal expansion, and older age at onset compared to LAS, particularly in heavy smokers, consistent with high proportions of newly generated, unmutated cells and frequent immuno-editing. These findings show how heterogeneity in mutational burden across co-occurring mutational processes and cell types contributes to tumor development, with important clinical implications.

mSigSDK - private, at scale, computation of mutation signatures.

In our previous work, we demonstrated that it is feasible to perform analysis on mutation signature data without the need for downloads or installations and analyze individual patient data at scale without compromising privacy. Building on this foundation, we developed an in-browser Software Development Kit (a JavaScript SDK), mSigSDK, to facilitate the orchestration of distributed data processing workflows and graphic visualization of mutational signature analysis results. We strictly adhered to modern web computing standards, particularly the modularization standards set by the ECMAScript ES6 framework (JavaScript modules). Our approach allows for the computation to be entirely performed by secure delegation to the computational resources of the user's own machine (in-browser), without any downloads or installations. The mSigSDK was developed primarily as a companion library to the mSig Portal resource of the National Cancer Institute Division of Cancer Epidemiology and Genetics (NIH/NCI/DCEG), with a focus on FAIR extensibility as components of other researchers' own data science constructs. Anticipated extensions include the programmatic operation of other mutation signature API ecosystems such as SIGNAL and COSMIC, advancing towards a data commons for mutational signature research (Grossman et al., 2016).

Pan-cancer mutational signature analysis of 111,711 targeted sequenced tumors using SATS.

Tumor mutational signatures have the potential to inform cancer diagnosis and treatment. However, their detection in targeted sequenced tumors is hampered by sparse mutations and variability in targeted gene panels. Here we present SATS, a scalable mutational signature analyzer addressing these challenges by leveraging tumor mutational burdens from targeted gene panels. Through analyzing simulated data, pseudo-targeted sequencing data generated by down-sampling whole exome and genome data, and samples with matched whole genome sequencing and targeted sequencing, we showed that SATS can accurately detect common mutational signatures and estimate signature burdens. Applying SATS to 111,711 targeted sequenced tumors from the AACR Project GENIE, we generated a pan-cancer catalogue of mutational signatures tailored to targeted sequencing, enabling estimation of signature burdens within individual tumors. Integrating signatures with clinical data, we demonstrated SATS's clinical utility, including identifying signatures enriched in early-onset hypermutated colorectal cancers and signatures associated with cancer prognosis and immunotherapy response.

Single-cell profiling of MC1R-inhibited melanocytes.

The human red hair color (RHC) trait is caused by increased pheomelanin (red-yellow) and reduced eumelanin (black-brown) pigment in skin and hair due to diminished melanocortin 1 receptor (MC1R) function. In addition, individuals harboring the RHC trait are predisposed to melanoma development. While MC1R variants have been established as causative of RHC and are a well-defined risk factor for melanoma, it remains unclear mechanistically why decreased MC1R signaling alters pigmentation and increases melanoma susceptibility. Here, we use single-cell RNA sequencing (scRNA-seq) of melanocytes isolated from RHC mouse models to define a MC1R-inhibited Gene Signature (MiGS) comprising a large set of previously unidentified genes which may be implicated in melanogenesis and oncogenic transformation. We show that one of the candidate MiGS genes, TBX3, a well-known anti-senescence transcription factor implicated in melanoma progression, binds both E-box and T-box elements to regulate genes associated with melanogenesis and senescence bypass. Our results provide key insights into further mechanisms by which melanocytes with reduced MC1R signaling may regulate pigmentation and offer new candidates of study toward understanding how individuals with the RHC phenotype are predisposed to melanoma.

Context-aware single-cell multiome approach identified cell-type specific lung cancer susceptibility genes.

Genome-wide association studies (GWAS) identified over fifty loci associated with lung cancer risk. However, the genetic mechanisms and target genes underlying these loci are largely unknown, as most risk-associated-variants might regulate gene expression in a context-specific manner. Here, we generated a barcode-shared transcriptome and chromatin accessibility map of 117,911 human lung cells from age/sex-matched ever- and never-smokers to profile context-specific gene regulation. Accessible chromatin peak detection identified cell-type-specific candidate cis-regulatory elements (cCREs) from each lung cell type. Colocalization of lung cancer candidate causal variants (CCVs) with these cCREs prioritized the variants for 68% of the GWAS loci, a subset of which was also supported by transcription factor abundance and footprinting. cCRE colocalization and single-cell based trait relevance score nominated epithelial and immune cells as the main cell groups contributing to lung cancer susceptibility. Notably, cCREs of rare proliferating epithelial cell types, such as AT2-proliferating (0.13%) and basal cells (1.8%), overlapped with CCVs, including those in TERT. A multi-level cCRE-gene linking system identified candidate susceptibility genes from 57% of lung cancer loci, including those not detected in tissue- or cell-line-based approaches. cCRE-gene linkage uncovered that adjacent genes expressed in different cell types are correlated with distinct subsets of coinherited CCVs, including JAML and MPZL3 at the 11q23.3 locus. Our data revealed the cell types and contexts where the lung cancer susceptibility genes are functional.

Genome-wide association study of lung adenocarcinoma in East Asia and comparison with a European population.

Lung adenocarcinoma is the most common type of lung cancer. Known risk variants explain only a small fraction of lung adenocarcinoma heritability. Here, we conducted a two-stage genome-wide association study of lung adenocarcinoma of East Asian ancestry (21,658 cases and 150,676 controls; 54.5% never-smokers) and identified 12 novel susceptibility variants, bringing the total number to 28 at 25 independent loci. Transcriptome-wide association analyses together with colocalization studies using a Taiwanese lung expression quantitative trait loci dataset (n = 115) identified novel candidate genes, including FADS1 at 11q12 and ELF5 at 11p13. In a multi-ancestry meta-analysis of East Asian and European studies, four loci were identified at 2p11, 4q32, 16q23, and 18q12. At the same time, most of our findings in East Asian populations showed no evidence of association in European populations. In our studies drawn from East Asian populations, a polygenic risk score based on the 25 loci had a stronger association in never-smokers vs. individuals with a history of smoking (Pinteraction = 0.0058). These findings provide new insights into the etiology of lung adenocarcinoma in individuals from East Asian populations, which could be important in developing translational applications.

Germline modifiers of the tumor immune microenvironment implicate drivers of cancer risk and immunotherapy response.

With the continued promise of immunotherapy for treating cancer, understanding how host genetics contributes to the tumor immune microenvironment (TIME) is essential to tailoring cancer screening and treatment strategies. Here, we study 1084 eQTLs affecting the TIME found through analysis of The Cancer Genome Atlas and literature curation. These TIME eQTLs are enriched in areas of active transcription, and associate with gene expression in specific immune cell subsets, such as macrophages and dendritic cells. Polygenic score models built with TIME eQTLs reproducibly stratify cancer risk, survival and immune checkpoint blockade (ICB) response across independent cohorts. To assess whether an eQTL-informed approach could reveal potential cancer immunotherapy targets, we inhibit CTSS, a gene implicated by cancer risk and ICB response-associated polygenic models; CTSS inhibition results in slowed tumor growth and extended survival in vivo. These results validate the potential of integrating germline variation and TIME characteristics for uncovering potential targets for immunotherapy.

Loss of MC1R signaling implicates TBX3 in pheomelanogenesis and melanoma predisposition.

The human Red Hair Color (RHC) trait is caused by increased pheomelanin (red-yellow) and reduced eumelanin (black-brown) pigment in skin and hair due to diminished melanocortin 1 receptor (MC1R) function. In addition, individuals harboring the RHC trait are predisposed to melanoma development. While MC1R variants have been established as causative of RHC and are a well-defined risk factor for melanoma, it remains unclear mechanistically why decreased MC1R signaling alters pigmentation and increases melanoma susceptibility. Here, we use single-cell RNA-sequencing (scRNA-seq) of melanocytes isolated from RHC mouse models to reveal a Pheomelanin Gene Signature (PGS) comprising genes implicated in melanogenesis and oncogenic transformation. We show that TBX3, a well-known anti-senescence transcription factor implicated in melanoma progression, is part of the PGS and binds both E-box and T-box elements to regulate genes associated with melanogenesis and senescence bypass. Our results provide key insights into mechanisms by which MC1R signaling regulates pigmentation and how individuals with the RHC phenotype are predisposed to melanoma.

Oncogenic CDK13 mutations impede nuclear RNA surveillance.

RNA surveillance pathways detect and degrade defective transcripts to ensure RNA fidelity. We found that disrupted nuclear RNA surveillance is oncogenic. Cyclin-dependent kinase 13 (CDK13) is mutated in melanoma, and patient-mutated CDK13 accelerates zebrafish melanoma. CDK13 mutation causes aberrant RNA stabilization. CDK13 is required for ZC3H14 phosphorylation, which is necessary and sufficient to promote nuclear RNA degradation. Mutant CDK13 fails to activate nuclear RNA surveillance, causing aberrant protein-coding transcripts to be stabilized and translated. Forced aberrant RNA expression accelerates melanoma in zebrafish. We found recurrent mutations in genes encoding nuclear RNA surveillance components in many malignancies, establishing nuclear RNA surveillance as a tumor-suppressive pathway. Activating nuclear RNA surveillance is crucial to avoid accumulation of aberrant RNAs and their ensuing consequences in development and disease.

DNA methylation age in paired tumor and adjacent normal breast tissue in Chinese women with breast cancer.

BACKGROUND: Few studies have examined epigenetic age acceleration (AA), the difference between DNA methylation (DNAm) predicted age and chronological age, in relation to somatic genomic features in paired cancer and normal tissue, with less work done in non-European populations. In this study, we aimed to examine DNAm age and its associations with breast cancer risk factors, subtypes, somatic genomic profiles including mutation and copy number alterations and other aging markers in breast tissue of Chinese breast cancer (BC) patients from Hong Kong. METHODS: We performed genome-wide DNA methylation profiling of 196 tumor and 188 paired adjacent normal tissue collected from Chinese BC patients in Hong Kong (HKBC) using Illumina MethylationEPIC array. The DNAm age was calculated using Horvath's pan-tissue clock model. Somatic genomic features were based on data from RNA sequencing (RNASeq), whole-exome sequencing (WES), and whole-genome sequencing (WGS). Pearson's correlation (r), Kruskal-Wallis test, and regression models were used to estimate associations of DNAm AA with somatic features and breast cancer risk factors. RESULTS: DNAm age showed a stronger correlation with chronological age in normal (Pearson r = 0.78, P < 2.2e-16) than in tumor tissue (Pearson r = 0.31, P = 7.8e-06). Although overall DNAm age or AA did not vary significantly by tissue within the same individual, luminal A tumors exhibited increased DNAm AA (P = 0.004) while HER2-enriched/basal-like tumors exhibited markedly lower DNAm AA (P = < .0001) compared with paired normal tissue. Consistent with the subtype association, tumor DNAm AA was positively correlated with ESR1 (Pearson r = 0.39, P = 6.3e-06) and PGR (Pearson r = 0.36, P = 2.4e-05) gene expression. In line with this, we found that increasing DNAm AA was associated with higher body mass index (P = 0.039) and earlier age at menarche (P = 0.035), factors that are related to cumulative exposure to estrogen. In contrast, variables indicating extensive genomic instability, such as TP53 somatic mutations, high tumor mutation/copy number alteration burden, and homologous repair deficiency were associated with lower DNAm AA. CONCLUSIONS: Our findings provide additional insights into the complexity of breast tissue aging that is associated with the interaction of hormonal, genomic, and epigenetic mechanisms in an East Asian population.

Gene Expression Profiling Identifies Two Chordoma Subtypes Associated with Distinct Molecular Mechanisms and Clinical Outcomes.

PURPOSE: Chordoma is a rare bone tumor with a high recurrence rate and limited treatment options. The aim of this study was to identify molecular subtypes of chordoma that may improve clinical management. EXPERIMENTAL DESIGN: We conducted RNA sequencing in 48 tumors from patients with Chinese skull-base chordoma and identified two major molecular subtypes. We then replicated the classification using a NanoString panel in 48 patients with chordoma from North America. RESULTS: Tumors in one subtype were more likely to have somatic mutations and reduced expression in chromatin remodeling genes, such as PBRM1 and SETD2, whereas the other subtype was characterized by the upregulation of genes in epithelial-mesenchymal transition and Sonic Hedgehog pathways. IHC staining of top differentially expressed genes between the two subtypes in 312 patients with Chinese chordoma with long-term follow-up data showed that the expression of some markers such as PTCH1 was significantly associated with survival outcomes. CONCLUSIONS: Our findings may improve the understanding of subtype-specific tumorigenesis of chordoma and inform clinical prognostication and targeted options.

Massively parallel reporter assays and variant scoring identified functional variants and target genes for melanoma loci and highlighted cell-type specificity.

The most recent genome-wide association study (GWAS) of cutaneous melanoma identified 54 risk-associated loci, but functional variants and their target genes for most have not been established. Here, we performed massively parallel reporter assays (MPRAs) by using malignant melanoma and normal melanocyte cells and further integrated multi-layer annotation to systematically prioritize functional variants and susceptibility genes from these GWAS loci. Of 1,992 risk-associated variants tested in MPRAs, we identified 285 from 42 loci (78% of the known loci) displaying significant allelic transcriptional activities in either cell type (FDR < 1%). We further characterized MPRA-significant variants by motif prediction, epigenomic annotation, and statistical/functional fine-mapping to create integrative variant scores, which prioritized one to six plausible candidate variants per locus for the 42 loci and nominated a single variant for 43% of these loci. Overlaying the MPRA-significant variants with genome-wide significant expression or methylation quantitative trait loci (eQTLs or meQTLs, respectively) from melanocytes or melanomas identified candidate susceptibility genes for 60% of variants (172 of 285 variants). CRISPRi of top-scoring variants validated their cis-regulatory effect on the eQTL target genes, MAFF (22q13.1) and GPRC5A (12p13.1). Finally, we identified 36 melanoma-specific and 45 melanocyte-specific MPRA-significant variants, a subset of which are linked to cell-type-specific target genes. Analyses of transcription factor availability in MPRA datasets and variant-transcription-factor interaction in eQTL datasets highlighted the roles of transcription factors in cell-type-specific variant functionality. In conclusion, MPRAs along with variant scoring effectively prioritized plausible candidates for most melanoma GWAS loci and highlighted cellular contexts where the susceptibility variants are functional.

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.

CSMD1 Shows Complex Patterns of Somatic Copy Number Alterations and Expressions of mRNAs and Target Micro RNAs in Esophageal Squamous Cell Carcinoma.

BACKGROUND: Human Cub and Sushi Multiple Domains 1 (CSMD1) is a novel candidate tumor-suppressor gene that codes for multiple domains, including complement regulatory and adhesion proteins, and has recently been shown to have alterations in multiple cancers. We investigated CSMD1 in esophageal squamous cell carcinoma (ESCC) by performing an integrated analysis on somatic copy number alterations (CNAs), including copy-number gain or loss, allelic imbalance (AI), loss of heterozygosity (LOH), and the expressions of mRNA and its target miRNAs on specimens from the same patients with ESCC. RESULTS: (i) Two-thirds of ESCC patients had all three types of alterations studied-somatic DNA alterations in 70%, and abnormal expressions of CSMD1 RNA in 69% and in target miRNAs in 66%; patterns among these alterations were complex. (ii) In total, 97% of 888 CSMD1 SNPs studied showed somatic DNA alterations, with most located near exons 4-11, 24-25, 39-40, 55-56, and 69-70. (iii) In total, 68% of SNPs with a CNA were correlated with expression of CSMD1. (iv) A total of 33 correlations between non-coding SNPs and expression of CSMD1 target miRs were found. CONCLUSIONS: Our results indicate that the CSMD1 gene may play a role in ESCC through complex patterns of DNA alterations and RNA and miRNA expressions. Alterations in some somatic SNPs in non-coding regions of CSMD1 appear to influence expression of this gene and its target miRNAs.

Germline-somatic JAK2 interactions are associated with clonal expansion in myelofibrosis.

Myelofibrosis is a rare myeloproliferative neoplasm (MPN) with high risk for progression to acute myeloid leukemia. Our integrated genomic analysis of up to 933 myelofibrosis cases identifies 6 germline susceptibility loci, 4 of which overlap with previously identified MPN loci. Virtual karyotyping identifies high frequencies of mosaic chromosomal alterations (mCAs), with enrichment at myelofibrosis GWAS susceptibility loci and recurrently somatically mutated MPN genes (e.g., JAK2). We replicate prior MPN associations showing germline variation at the 9p24.1 risk haplotype confers elevated risk of acquiring JAK2V617F mutations, demonstrating with long-read sequencing that this relationship occurs in cis. We also describe recurrent 9p24.1 large mCAs that selectively retained JAK2V617F mutations. Germline variation associated with longer telomeres is associated with increased myelofibrosis risk. Myelofibrosis cases with high-frequency JAK2 mCAs have marked reductions in measured telomere length - suggesting a relationship between telomere biology and myelofibrosis clonal expansion. Our results advance understanding of the germline-somatic interaction at JAK2 and implicate mCAs involving JAK2 as strong promoters of clonal expansion of those mutated clones.

Tumor Mutational Burden by Whole-Genome Sequencing in Resected NSCLC of Never Smokers.

BACKGROUND: Data are scarce about tumor mutational burden (TMB) as a biomarker in never smokers with non-small cell lung cancer (NSCLC). METHODS: TMB was assessed by whole-genome sequencing (WGS) and compared with in silico reduced whole-exome sequencing (WES) and targeted commercial next-generation sequencing (NGS) gene panels in 92 paired tumor-normal samples from never smokers who underwent NSCLC resection with curative intent. Analyses were performed to test for association with survival after surgery and to identify the optimal prognostic TMB cutoff. RESULTS: Tumors of never smokers with NSCLC had low TMB scores (median 1.57 mutations/Mb; range, 0.13-17.94). A TMB cutoff of 1.70 mutations/Mb was associated with a 5-year overall survival of 58% in the high-TMB (42% of cases) compared with 86% in low-TMB patients (Wald P = 0.0029). TMB scores from WGS and WES were highly correlated (Spearman ρ = 0.93, P < 2.2e-16). TMB scores from NGS panels demonstrated high intraindividual fluctuations and identified high-TMB patients with 65% concordance in average compared with WGS. CONCLUSIONS: In resected NSCLC of never smokers, high TMB was associated with worse prognosis. WES provided a good estimate of TMB while targeted NGS panels seem to lack adequate depth and resolution in the setting of low mutation burden. IMPACT: TMB is a prognostic indicator of survival in resected NSCLC from individuals who never smoked. In this setting of low mutation counts, TMB can be accurately measured by WGS or WES, but not NGS panels.

Cross-ancestry genome-wide meta-analysis of 61,047 cases and 947,237 controls identifies new susceptibility loci contributing to lung cancer.

To identify new susceptibility loci to lung cancer among diverse populations, we performed cross-ancestry genome-wide association studies in European, East Asian and African populations and discovered five loci that have not been previously reported. We replicated 26 signals and identified 10 new lead associations from previously reported loci. Rare-variant associations tended to be specific to populations, but even common-variant associations influencing smoking behavior, such as those with CHRNA5 and CYP2A6, showed population specificity. Fine-mapping and expression quantitative trait locus colocalization nominated several candidate variants and susceptibility genes such as IRF4 and FUBP1. DNA damage assays of prioritized genes in lung fibroblasts indicated that a subset of these genes, including the pleiotropic gene IRF4, potentially exert effects by promoting endogenous DNA damage.

DNA promoter hypermethylation of melanocyte lineage genes determines melanoma phenotype.

Cellular stress contributes to the capacity of melanoma cells to undergo phenotype switching into highly migratory and drug-tolerant dedifferentiated states. Such dedifferentiated melanoma cell states are marked by loss of melanocyte-specific gene expression and increase of mesenchymal markers. Two crucial transcription factors, microphthalmia-associated transcription factor (MITF) and SRY-box transcription factor 10 (SOX10), important in melanoma development and progression, have been implicated in this process. In this study we describe that loss of MITF is associated with a distinct transcriptional program, MITF promoter hypermethylation, and poor patient survival in metastatic melanoma. From a comprehensive collection of melanoma cell lines, we observed that MITF-methylated cultures were subdivided in 2 distinct subtypes. Examining mRNA levels of neural crest-associated genes, we found that 1 subtype had lost the expression of several lineage genes, including SOX10. Intriguingly, SOX10 loss was associated with SOX10 gene promoter hypermethylation and distinct phenotypic and metastatic properties. Depletion of SOX10 in MITF-methylated melanoma cells using CRISPR/Cas9 supported these findings. In conclusion, this study describes the significance of melanoma state and the underlying functional properties explaining the aggressiveness of such states.