Signatures of positive selection reveal a universal role of chromatin modifiers as cancer driver genes

Revealing cancer driver genes through integrative transcriptomic and epigenomic analyses with Moonlight

Cancer involves dynamic changes caused by (epi)genetic alterations such as mutations or abnormal DNA methylation patterns which occur in cancer driver genes. These driver genes are divided into oncogenes and tumor suppressors depending on their function and mechanism of action. Discovering driver genes in different cancer (sub)types is important not only for increasing current understanding of carcinogenesis but also from prognostic and therapeutic perspectives. We have previously developed a framework called Moonlight which uses a systems biology multi-omics approach for prediction of driver genes. Here, we present an important development in Moonlight2 by incorporating a DNA methylation layer which provides epigenetic evidence for deregulated expression profiles of driver genes. To this end, we present a novel functionality called Gene Methylation Analysis (GMA) which investigates abnormal DNA methylation patterns to predict driver genes. This is achieved by integrating the tool EpiMix which is designed to detect such aberrant DNA methylation patterns in a cohort of patients and further couples these patterns with gene expression changes. To showcase GMA, we applied it to three cancer (sub)types (basal-like breast cancer, lung adenocarcinoma, and thyroid carcinoma) where we discovered 33, 190, and 263 epigenetically driven genes, respectively. A subset of these driver genes had prognostic effects with expression levels significantly affecting survival of the patients. Moreover, a subset of the driver genes demonstrated therapeutic potential as drug targets. This study provides a framework for exploring the driving forces behind cancer and provides novel insights into the landscape of three cancer sub(types) by integrating gene expression and methylation data.

A Comparative Genomic Study of Conventional and Undifferentiated Melanoma

Undifferentiated melanoma, defined as melanoma that has lost all usual phenotypic and immunohistochemical characteristics of conventional melanoma, can pose significant diagnostic challenges. Molecular studies have advanced our understanding of undifferentiated melanoma by demonstrating that a subset of these tumors harbors known melanoma driver alterations in genes such as BRAF, NRAS, and NF1. However, there is a paucity of data describing genetic alterations that may distinguish undifferentiated melanoma from conventional melanoma. In this study, we directly compared the genomic profiles of undifferentiated melanoma to a cohort of conventional melanomas, including 14 undifferentiated melanoma cases (comprised of 2 primary cases, 2 cutaneous recurrences, and 10 metastases) and a cohort of 127 conventional melanomas including primary, recurrent, and metastatic cases. Targeted sequencing of 447 cancer-associated genes was performed, including identification of mutations and copy number alterations. NRAS was the most frequent melanoma driver in undifferentiated melanoma (8/14 cases, 57%), although notably, only 1 undifferentiated melanoma harbored an NRAS Q61R mutation. Compared with the conventional melanoma cohort, undifferentiated melanoma demonstrated statistically significant enrichment of pathogenic activating RAC1 mutations (6/14 total cases, 43%), including P29S (4/6 cases), P29L (1/6 cases), and D11E (1/6 cases). In addition to providing insight into the molecular pathogenesis of undifferentiated melanoma, these findings also suggest that RAS Q61R immunohistochemistry may have limited utility for its diagnosis. The presence of recurrent RAC1 mutations in undifferentiated melanoma is also notable as these alterations may contribute to mitogen-activated protein kinase pathway-targeted therapy resistance. Furthermore, the RAC1 alterations identified in this cohort have been shown to drive a melanocytic to mesenchymal switch in melanocytes, offering a possible explanation for the undifferentiated phenotype of these melanomas.

A Novel Affordable and Reliable Framework for Accurate Detection and Comprehensive Analysis of Somatic Mutations in Cancer

Accurate detection and analysis of somatic variants in cancer involve multiple third-party tools with complex dependencies and configurations, leading to laborious, error-prone, and time-consuming data conversions. This approach lacks accuracy, reproducibility, and portability, limiting clinical application. Musta was developed to address these issues as an end-to-end pipeline for detecting, classifying, and interpreting cancer mutations. Musta is based on a Python command-line tool designed to manage tumor-normal samples for precise somatic mutation analysis. The core is a Snakemake-based workflow that covers all key cancer genomics steps, including variant calling, mutational signature deconvolution, variant annotation, driver gene detection, pathway analysis, and tumor heterogeneity estimation. Musta is easy to install on any system via Docker, with a Makefile handling installation, configuration, and execution, allowing for full or partial pipeline runs. Musta has been validated at the CRS4-NGS Core facility and tested on large datasets from The Cancer Genome Atlas and the Beijing Institute of Genomics. Musta has proven robust and flexible for somatic variant analysis in cancer. It is user-friendly, requiring no specialized programming skills, and enables data processing with a single command line. Its reproducibility ensures consistent results across users following the same protocol.

Immune evasion impacts the landscape of driver genes during cancer evolution

BACKGROUND

Carcinogenesis is driven by interactions between genetic mutations and the local tumor microenvironment. Recent research has identified hundreds of cancer driver genes; however, these studies often include a mixture of different molecular subtypes and ecological niches and ignore the impact of the immune system.

RESULTS

In this study, we compare the landscape of driver genes in tumors that escaped the immune system (escape +) versus those that did not (escape -). We analyze 9896 primary tumors from The Cancer Genome Atlas using the ratio of non-synonymous to synonymous mutations (dN/dS) and find 85 driver genes, including 27 and 16 novel genes, in escape - and escape + tumors, respectively. The dN/dS of driver genes in immune escaped tumors is significantly lower and closer to neutrality than in non-escaped tumors, suggesting selection buffering in driver genes fueled by immune escape. Additionally, we find that immune evasion leads to more mutated sites, a diverse array of mutational signatures and is linked to tumor prognosis.

CONCLUSIONS

Our findings highlight the need for improved patient stratification to identify new therapeutic targets for cancer treatment.

Strength of selection in lung tumors correlates with clinical features better than tumor mutation burden

Single nucleotide substitutions are the most common type of somatic mutations in cancer genome. The goal of this study was to use publicly available somatic mutation data to quantify negative and positive selection in individual lung tumors and test how strength of directional and absolute selection is associated with clinical features. The analysis found a significant variation in strength of selection (both negative and positive) among tumors, with median selection tending to be negative even though tumors with strong positive selection also exist. Strength of selection estimated as the density of missense mutations relative to the density of silent mutations showed only a weak correlation with tumor mutation burden. In the "all histology together" analysis we found that absolute strength of selection was strongly correlated with all clinically relevant features analyzed. In histology-stratified analysis selection was strongest in small cell lung cancer. Selection in adenocarcinoma was somewhat higher compared to squamous cell carcinoma. The study suggests that somatic mutation- based quantifying of directional and absolute selection in individual tumors can be a useful biomarker of tumor aggressiveness.

Prediction of cancer driver genes and mutations: the potential of integrative computational frameworks

The vast amount of available sequencing data allows the scientific community to explore different genetic alterations that may drive cancer or favor cancer progression. Software developers have proposed a myriad of predictive tools, allowing researchers and clinicians to compare and prioritize driver genes and mutations and their relative pathogenicity. However, there is little consensus on the computational approach or a golden standard for comparison. Hence, benchmarking the different tools depends highly on the input data, indicating that overfitting is still a massive problem. One of the solutions is to limit the scope and usage of specific tools. However, such limitations force researchers to walk on a tightrope between creating and using high-quality tools for a specific purpose and describing the complex alterations driving cancer. While the knowledge of cancer development increases daily, many bioinformatic pipelines rely on single nucleotide variants or alterations in a vacuum without accounting for cellular compartments, mutational burden or disease progression. Even within bioinformatics and computational cancer biology, the research fields work in silos, risking overlooking potential synergies or breakthroughs. Here, we provide an overview of databases and datasets for building or testing predictive cancer driver tools. Furthermore, we introduce predictive tools for driver genes, driver mutations, and the impact of these based on structural analysis. Additionally, we suggest and recommend directions in the field to avoid silo-research, moving towards integrative frameworks.

Mismatch repair deficiency is not sufficient to elicit tumor immunogenicity

DNA mismatch repair deficiency (MMRd) is associated with a high tumor mutational burden (TMB) and sensitivity to immune checkpoint blockade (ICB) therapy. Nevertheless, most MMRd tumors do not durably respond to ICB and critical questions remain about immunosurveillance and TMB in these tumors. In the present study, we developed autochthonous mouse models of MMRd lung and colon cancer. Surprisingly, these models did not display increased T cell infiltration or ICB response, which we showed to be the result of substantial intratumor heterogeneity of mutations. Furthermore, we found that immunosurveillance shapes the clonal architecture but not the overall burden of neoantigens, and T cell responses against subclonal neoantigens are blunted. Finally, we showed that clonal, but not subclonal, neoantigen burden predicts ICB response in clinical trials of MMRd gastric and colorectal cancer. These results provide important context for understanding immune evasion in cancers with a high TMB and have major implications for therapies aimed at increasing TMB.

Integrating somatic CNV and gene expression in breast cancers from women with PTEN hamartoma tumor syndrome

Women with germline PTEN variants (PTEN hamartoma tumor syndrome, PHTS) have up to 85% lifetime risk of female breast cancer (BC). We previously showed that PHTS-derived BCs are distinct from sporadic BCs both at the clinical and genomic levels. In this study, we examined somatic copy number variations (CNV) and transcriptome data to further characterize the somatic landscape of PHTS-derived BCs. We analyzed exome sequencing data from 44 BCs from women with PHTS for CNV. The control group comprised of 558 women with sporadic BCs from The Cancer Genome Atlas (TCGA) dataset. Here, we found that PHTS-derived BCs have several distinct CNV peaks compared to TCGA. Furthermore, RNA sequencing data revealed that PHTS-derived BCs have a distinct immunologic cell type signature, which points toward cancer immune evasion. Transcriptomic data also revealed PHTS-derived BCs with pathogenic germline PTEN variants appear to have vitamin E degradation as a key pathway associated with tumorigenesis. In conclusion, our study revealed distinct CNV x transcript features in PHTS-derived BCs, which further facilitate understanding of BC biology arising in the setting of germline PTEN mutations.

Immune selection determines tumor antigenicity and influences response to checkpoint inhibitors

In cancer, evolutionary forces select for clones that evade the immune system. Here we analyzed >10,000 primary tumors and 356 immune-checkpoint-treated metastases using immune dN/dS, the ratio of nonsynonymous to synonymous mutations in the immunopeptidome, to measure immune selection in cohorts and individuals. We classified tumors as immune edited when antigenic mutations were removed by negative selection and immune escaped when antigenicity was covered up by aberrant immune modulation. Only in immune-edited tumors was immune predation linked to CD8 T cell infiltration. Immune-escaped metastases experienced the best response to immunotherapy, whereas immune-edited patients did not benefit, suggesting a preexisting resistance mechanism. Similarly, in a longitudinal cohort, nivolumab treatment removes neoantigens exclusively in the immunopeptidome of nonimmune-edited patients, the group with the best overall survival response. Our work uses dN/dS to differentiate between immune-edited and immune-escaped tumors, measuring potential antigenicity and ultimately helping predict response to treatment.

Whole-genome analysis identifies novel drivers and high-risk double-hit events in relapsed/refractory myeloma

Large-scale analyses of genomic data from patients with newly diagnosed multiple myeloma (ndMM) have been undertaken, however, large-scale analysis of relapsed/refractory MM (rrMM) has not been performed. We hypothesize that somatic variants chronicle the therapeutic exposures and clonal structure of myeloma from ndMM to rrMM stages. We generated whole-genome sequencing (WGS) data from 418 tumors (386 patients) derived from 6 rrMM clinical trials and compared them with WGS from 198 unrelated patients with ndMM in a population-based case-control fashion. We identified significantly enriched events at the rrMM stage, including drivers (DUOX2, EZH2, TP53), biallelic inactivation (TP53), noncoding mutations in bona fide drivers (TP53BP1, BLM), copy number aberrations (CNAs; 1qGain, 17pLOH), and double-hit events (Amp1q-ISS3, 1qGain-17p loss-of-heterozygosity). Mutational signature analysis identified a subclonal defective mismatch repair signature enriched in rrMM and highly active in high mutation burden tumors, a likely feature of therapy-associated expanding subclones. Further analysis focused on the association of genomic aberrations enriched at different stages of resistance to immunomodulatory agent (IMiD)-based therapy. This analysis revealed that TP53, DUOX2, 1qGain, and 17p loss-of-heterozygosity increased in prevalence from ndMM to lenalidomide resistant (LENR) to pomalidomide resistant (POMR) stages, whereas enrichment of MAML3 along with immunoglobulin lambda (IGL) and MYC translocations distinguished POM from the LEN subgroup. Genomic drivers associated with rrMM are those that confer clonal selective advantage under therapeutic pressure. Their role in therapy evasion should be further evaluated in longitudinal patient samples, to confirm these associations with the evolution of clinical resistance and to identify molecular subsets of rrMM for the development of targeted therapies.

Exome sequencing reveals a distinct somatic genomic landscape in breast cancer from women with germline PTEN variants

Germline PTEN variants (PTEN hamartoma tumor syndrome [PHTS]) confer up to 85% lifetime risk of female breast cancer (BC). BCs arising in PHTS are clinically distinct from sporadic BCs, including younger age of onset, multifocality, and an increased risk of second primary BCs. Yet, there is no previous investigation into the underlying genomic landscape of this entity. We sought to address the hypothesis that BCs arising in PHTS have a distinct genomic landscape compared to sporadic counterparts. We performed and analyzed exome sequencing data from 44 women with germline PTEN variants who developed BCs. The control cohort comprised of 497 women with sporadic BCs from The Cancer Genome Atlas (TCGA) dataset. We demonstrate that PHTS-derived BCs have a distinct somatic mutational landscape compared to the sporadic counterparts, namely second somatic hits in PTEN, distinct mutational signatures, and increased genomic instability. The PHTS group had a significantly higher frequency of somatic PTEN variants compared to TCGA (22.7% versus 5.6%; odds ratio [OR] 4.93; 95% confidence interval [CI] 2.21 to 10.98; p < 0.001) and a lower mutational frequency in PIK3CA (22.7% versus 33.4%; OR 0.59; 95% CI 0.28 to 1.22; p = 0.15). Somatic variants in PTEN and PIK3CA were mutually exclusive in PHTS (p = 0.01) but not in TCGA. Our findings have important implications for the personalized management of PTEN-related BCs, especially in the context of more accessible genetic testing.

Molecular Features in Lymphatic Metastases Reflect the Metastasis Mechanism of Lymph Nodes With Non-Small-Cell Lung Cancers

Lymphatic metastasis influences clinical treatment and prognosis of patients with non-small-cell lung cancer (NSCLC). There is an urgency to understand the molecular features and mechanisms of lymph node metastasis. We analyzed the molecular features on pairs of the primary tumor and lymphatic metastasis tissue samples from 15 NSCLC patients using targeted next-generation sequencing. The potential metastasis-related genes were screened from our cohort based on cancer cell fraction. After filtering with gene functions, candidate metastasis-related events were validated in the MSK cohort with Fisher's exact test. The molecular signature and tumor mutational burden were similar in paired samples, and the average mutational concordance was 42.0% ± 28.9%. Its metastatic mechanism is potentially a linear progression based on the metastatic seeding theory. Furthermore, mutated ataxia telangiectasia mutated and Rad3-related (ATR) and tet methylcytosine dioxygenase 2 (TET2) genes were significantly enriched in lymphatic metastases (p ≤ 0.05). Alterations in these two genes could be considered metastasis-related driving events. Mutated ATR and TET2 might play an active role in the metastasis of lymph nodes with NSCLC. More case enrollment and long-term follow-up will further verify the clinical significance of these two genes.

Preneoplastic somatic mutations including MYD88L265P in lymphoplasmacytic lymphoma

Normal cell counterparts of solid and myeloid tumors accumulate mutations years before disease onset; whether this occurs in B lymphocytes before lymphoma remains uncertain. We sequenced multiple stages of the B lineage in elderly individuals and patients with lymphoplasmacytic lymphoma, a singular disease for studying lymphomagenesis because of the high prevalence of mutated MYD88. We observed similar accumulation of random mutations in B lineages from both cohorts and unexpectedly found MYD88^L265P in normal precursor and mature B lymphocytes from patients with lymphoma. We uncovered genetic and transcriptional pathways driving malignant transformation and leveraged these to model lymphoplasmacytic lymphoma in mice, based on mutated MYD88 in B cell precursors and BCL2 overexpression. Thus, MYD88^L265P is a preneoplastic event, which challenges the current understanding of lymphomagenesis and may have implications for early detection of B cell lymphomas.

Whole-genome analysis of Nigerian patients with breast cancer reveals ethnic-driven somatic evolution and distinct genomic subtypes

Black women across the African diaspora experience more aggressive breast cancer with higher mortality rates than white women of European ancestry. Although inter-ethnic germline variation is known, differential somatic evolution has not been investigated in detail. Analysis of deep whole genomes of 97 breast cancers, with RNA-seq in a subset, from women in Nigeria in comparison with The Cancer Genome Atlas (n = 76) reveal a higher rate of genomic instability and increased intra-tumoral heterogeneity as well as a unique genomic subtype defined by early clonal GATA3 mutations with a 10.5-year younger age at diagnosis. We also find non-coding mutations in bona fide drivers (ZNF217 and SYPL1) and a previously unreported INDEL signature strongly associated with African ancestry proportion, underscoring the need to expand inclusion of diverse populations in biomedical research. Finally, we demonstrate that characterizing tumors for homologous recombination deficiency has significant clinical relevance in stratifying patients for potentially life-saving therapies.

Breast cancer heterogeneity and tumour evolutionary trajectories remain largely unknown among women of African ancestry. Here, the authors perform whole genome and transcriptome sequencing of Nigerian breast cancer patients and identify unique evolutionary phenomena.

The rate and spectrum of mosaic mutations during embryogenesis revealed by RNA sequencing of 49 tissues

BACKGROUND

Mosaic mutations acquired during early embryogenesis can lead to severe early-onset genetic disorders and cancer predisposition, but are often undetectable in blood samples. The rate and mutational spectrum of embryonic mosaic mutations (EMMs) have only been studied in few tissues, and their contribution to genetic disorders is unknown. Therefore, we investigated how frequent mosaic mutations occur during embryogenesis across all germ layers and tissues.

METHODS

Mosaic mutation detection in 49 normal tissues from 570 individuals (Genotype-Tissue Expression (GTEx) cohort) was performed using a newly developed multi-tissue, multi-individual variant calling approach for RNA-seq data. Our method allows for reliable identification of EMMs and the developmental stage during which they appeared.

RESULTS

The analysis of EMMs in 570 individuals revealed that newborns on average harbor 0.5-1 EMMs in the exome affecting multiple organs (1.3230 × 10-8 per nucleotide per individual), a similar frequency as reported for germline de novo mutations. Our multi-tissue, multi-individual study design allowed us to distinguish mosaic mutations acquired during different stages of embryogenesis and adult life, as well as to provide insights into the rate and spectrum of mosaic mutations. We observed that EMMs are dominated by a mutational signature associated with spontaneous deamination of methylated cytosines and the number of cell divisions. After birth, cells continue to accumulate somatic mutations, which can lead to the development of cancer. Investigation of the mutational spectrum of the gastrointestinal tract revealed a mutational pattern associated with the food-borne carcinogen aflatoxin, a signature that has so far only been reported in liver cancer.

CONCLUSIONS

In summary, our multi-tissue, multi-individual study reveals a surprisingly high number of embryonic mosaic mutations in coding regions, implying novel hypotheses and diagnostic procedures for investigating genetic causes of disease and cancer predisposition.

Clonal selection confers distinct evolutionary trajectories in BRAF-driven cancers

Molecular determinants governing the evolution of tumor subclones toward phylogenetic branches or fixation remain unknown. Using sequencing data, we model the propagation and selection of clones expressing distinct categories of BRAF mutations to estimate their evolutionary trajectories. We show that strongly activating BRAF mutations demonstrate hard sweep dynamics, whereas mutations with less pronounced activation of the BRAF signaling pathway confer soft sweeps or are subclonal. We use clonal reconstructions to estimate the strength of "driver" selection in individual tumors. Using tumors cells and human-derived murine xenografts, we show that tumor sweep dynamics can significantly affect responses to targeted inhibitors of BRAF/MEK or DNA damaging agents. Our study uncovers patterns of distinct BRAF clonal evolutionary dynamics and nominates therapeutic strategies based on the identity of the BRAF mutation and its clonal composition.

Maftools: efficient and comprehensive analysis of somatic variants in cancer

Numerous large-scale genomic studies of matched tumor-normal samples have established the somatic landscapes of most cancer types. However, the downstream analysis of data from somatic mutations entails a number of computational and statistical approaches, requiring usage of independent software and numerous tools. Here, we describe an R Bioconductor package, Maftools, which offers a multitude of analysis and visualization modules that are commonly used in cancer genomic studies, including driver gene identification, pathway, signature, enrichment, and association analyses. Maftools only requires somatic variants in Mutation Annotation Format (MAF) and is independent of larger alignment files. With the implementation of well-established statistical and computational methods, Maftools facilitates data-driven research and comparative analysis to discover novel results from publicly available data sets. In the present study, using three of the well-annotated cohorts from The Cancer Genome Atlas (TCGA), we describe the application of Maftools to reproduce known results. More importantly, we show that Maftools can also be used to uncover novel findings through integrative analysis.

Tissue-specific DNA methylation loss during ageing and carcinogenesis is linked to chromosome structure, replication timing and cell division rates

DNA methylation is an epigenetic mechanism known to affect gene expression and aberrant DNA methylation patterns have been described in cancer. However, only a small fraction of differential methylation events target genes with a defined role in cancer, raising the question of how aberrant DNA methylation contributes to carcinogenesis. As recently a link has been suggested between methylation patterns arising in ageing and those arising in cancer, we asked which aberrations are unique to cancer and which are the product of normal ageing processes. We therefore compared the methylation patterns between ageing and cancer in multiple tissues. We observed that hypermethylation preferentially occurs in regulatory elements, while hypomethylation is associated with structural features of the chromatin. Specifically, we observed consistent hypomethylation of late-replicating, lamina-associated domains. The extent of hypomethylation was stronger in cancer, but in both ageing and cancer it was proportional to the replication timing of the region and the cell division rate of the tissue. Moreover, cancer patients who displayed more hypomethylation in late-replicating, lamina-associated domains had higher expression of cell division genes. These findings suggest that different cell division rates contribute to tissue- and cancer type-specific DNA methylation profiles.

Negative selection in tumor genome evolution acts on essential cellular functions and the immunopeptidome

Background

Natural selection shapes cancer genomes. Previous studies used signatures of positive selection to identify genes driving malignant transformation. However, the contribution of negative selection against somatic mutations that affect essential tumor functions or specific domains remains a controversial topic.

Results

Here, we analyze 7546 individual exomes from 26 tumor types from TCGA data to explore the portion of the cancer exome under negative selection. Although we find most of the genes neutrally evolving in a pan-cancer framework, we identify essential cancer genes and immune-exposed protein regions under significant negative selection. Moreover, our simulations suggest that the amount of negative selection is underestimated. We therefore choose an empirical approach to identify genes, functions, and protein regions under negative selection. We find that expression and mutation status of negatively selected genes is indicative of patient survival. Processes that are most strongly conserved are those that play fundamental cellular roles such as protein synthesis, glucose metabolism, and molecular transport. Intriguingly, we observe strong signals of selection in the immunopeptidome and proteins controlling peptide exposition, highlighting the importance of immune surveillance evasion. Additionally, tumor type-specific immune activity correlates with the strength of negative selection on human epitopes.

Conclusions

In summary, our results show that negative selection is a hallmark of cell essentiality and immune response in cancer. The functional domains identified could be exploited therapeutically, ultimately allowing for the development of novel cancer treatments.

Electronic supplementary material

The online version of this article (10.1186/s13059-018-1434-0) contains supplementary material, which is available to authorized users.