The effects of mutational processes and selection on driver mutations across cancer types

Coevolution of Atypical BRAF and KRAS Mutations in Colorectal Tumorigenesis

BRAF mutations in colorectal cancer comprise three functional classes: class 1 (V600E) with strong constitutive activation, class 2 with pathogenic kinase activity lower than that of class 1, and class 3 which paradoxically lacks kinase activity. Non-class 1 mutations associate with better prognosis, microsatellite stability, distal tumor location, and better anti-EGFR response. An analysis of 13 colorectal cancer cohorts (n = 6,605 tumors) compared class 1 (n = 709, 10.7% of colorectal cancers), class 2 (n = 31, 0.47%), and class 3 (n = 81, 1.22%) mutations. Class 2-mutant and class 3-mutant colorectal cancers frequently co-occurred with additional Ras pathway mutations (29.0% and 45.7%, respectively, vs. 2.40% in class 1; P < 0.001), often at atypical sites (KRAS noncodon 12/13/61, NRAS, or NF1). Ras pathway activation was highest in class 1 and lowest in class 3, with a greater distal expression of EGFR ligands (amphiregulin/epiregulin) supporting weaker BRAF driver mutations. Unlike class 1 mutants, class 3 tumors resembled chromosomally unstable colorectal cancers in mutation burdens, signatures, driver mutations, and transcriptional subtypes, whereas class 2 mutants displayed intermediate characteristics. Atypical BRAF mutations were associated with longer overall survival than class 1 mutations (HR = 0.25; P = 0.011) but lost this advantage in cancers with additional Ras mutations (HR = 0.94; P = 0.86). This study supports the suggestion that class 3 BRAF mutations amplify existing Ras signaling in a two-mutation model and that the enhancement of weak/atypical Ras mutations may suffice for tumorigenesis, with potentially clinically important heterogeneity in the class 2/3 subgroup. Implications: The heterogeneous nature of BRAF-mutant colorectal cancers, particularly among class 2/3 mutations which frequently harbor additional Ras mutations, highlights the necessity of comprehensive molecular profiling.

KRAS Mutations in Cancer: Understanding Signaling Pathways to Immune Regulation and the Potential of Immunotherapy

The Kirsten rat sarcoma viral oncogene homologue (KRAS) mutation is one of the most prevailing mutations in various tumors and is difficult to cure. Long-term proliferation in carcinogenesis is primarily initiated by oncogenic KRAS-downstream signaling. Recent research suggests that it also activates the autocrine effect and interplays the tumor microenvironment (TME). Here, we discuss the emerging research, including KRAS mutations to immune evasion in TME, which induce immunological modulation that promotes tumor development. This review gives an overview of the existing knowledge of the underlying connection between KRAS mutations and tumor immune modulation. It also addresses the mechanisms to reduce the effect of oncogenes on the immune system and recent advances in clinical trials for immunotherapy in KRAS-mutated cancers.

Addressing the rising colorectal cancer burden in the older adult: examining modifiable risk and protective factors for comprehensive prevention strategies

Background

Colorectal cancer is one of the most prevalent and deadly cancer types worldwide. Emerging evidence suggests that high body mass index (BMI) is a significant risk factor for colorectal cancer, particularly among the older adult population. This comprehensive analysis aims to explore the complex epidemiological patterns of colorectal cancer, with a focus on the association between high BMI and disease burden in the older adult.

Methods

The study leveraged data from the Global Burden of Disease (GBD) 2021 study to examine the temporal trends, regional disparities, and the interplay of age, period, and cohort factors in shaping the global colorectal cancer landscape. Epidemiological techniques, including age-period-cohort modeling and joinpoint regression analysis, were employed to provide insights into the potential drivers of the evolving disease burden while controlling for relevant confounding factors.

Results

The analysis revealed significant geographical disparities in the burden of colorectal cancer among the older adult population. Countries like Uruguay, Monaco, Croatia, Hungary, and Poland exhibited higher mortality and disability-adjusted life-year (DALY) rates, while regions like Bangladesh, Nepal, and much of Africa had relatively lower disease burden. These regional differences are likely attributable to variations in healthcare systems, access to screening and early detection programs, as well as differences in lifestyle behaviors and risk factor prevalence.

Conclusion

The strong association between high BMI and colorectal cancer risk, particularly in the older adult population and among men, emphasizes the importance of comprehensive obesity management strategies as part of comprehensive cancer control efforts. Targeted interventions, such as community-based weight management programs and enhanced screening initiatives in high-risk regions, could help mitigate the disproportionate burden of colorectal cancer observed in countries like Monaco, Croatia, and Hungary. Ongoing research and multifaceted public health interventions are crucial to address the growing global burden of colorectal cancer and mitigate the disproportionate impact on vulnerable populations. Strengthening healthcare systems, improving access to quality cancer care, and promoting lifestyle modifications to reduce obesity and other modifiable risk factors should be prioritized to effectively combat this pressing public health challenge.

Combination of farnesyl-transferase inhibition with KRAS G12D targeting breaks down therapeutic resistance in pancreatic cancer

Pancreatic adenocarcinoma is one of the deadliest forms of cancer with no effective therapeutic options. A KRAS mutation can be found in up to 90% of all pancreatic tumors, making it a promising therapeutic target. The introduction of new KRAS inhibitors has been a milestone in the history of KRAS mutant tumors; however, therapeutic resistance limits their efficacy. Thus, new therapeutic options, including combination therapies, are urgently needed. Recently, we have shown that KRAS G12C inhibitors in combination with farnesyl-transferase inhibitors exert synergistic antitumor effects. Here, we provide evidence for the feasibility of this combinational approach to break down resistance in KRAS G12D mutant pancreatic cancer. Although we have shown that the 3D environment dramatically sensitizes cells to MRTX1133 treatment, the synergistic effect of this drug combination is present in both 2D and 3D in the PANC1 pancreatic adenocarcinoma model, which showed high resistance to MRTX1133 in 2D. The effects of the combination treatment show an association with the inhibition of farnesylated regulatory proteins, including HRAS and RHEB, along with the expression level of KRAS. Our study warrants further investigation for the potential applicability of KRAS G12D inhibitors in combination with farnesyl-transferase inhibitors for the treatment of KRAS mutant pancreatic adenocarcinoma.

Recapitulating the adenoma-carcinoma sequence by selection of four spontaneous oncogenic mutations in mismatch-repair-deficient human colon organoids

Carcinogenesis results from the sequential acquisition of oncogenic mutations that convert normal cells into invasive, metastasizing cancer cells. Colorectal cancer exemplifies this process through its well-described adenoma-carcinoma sequence, modeled previously using clustered regularly interspaced short palindromic repeats (CRISPR) to induce four consecutive mutations in wild-type human gut organoids. Here, we demonstrate that long-term culture of mismatch-repair-deficient organoids allows the selection of spontaneous oncogenic mutations through the sequential withdrawal of Wnt agonists, epidermal growth factor (EGF) agonists and the bone morphogenetic protein (BMP) antagonist Noggin, while TP53 mutations were selected through the addition of Nutlin-3. Thus, organoids sequentially acquired mutations in AXIN1 and AXIN2 (Wnt pathway), TP53, ACVR2A and BMPR2 (BMP pathway) and NRAS (EGF pathway), gaining complete independence from stem cell niche factors. Quadruple-pathway (Wnt, EGF receptor, p53 and BMP) mutant organoids formed solid tumors upon xenotransplantation. This demonstrates that carcinogenesis can be recapitulated in a DNA repair-mutant background through in vitro selection that targets four consecutive cancer pathways.

Pan-cancer analysis of the interplay between mutational signatures and cellular signaling

Cancer is a multi-faceted disease with intricate relationships between mutagenic processes, alterations in cellular signaling, and the tissue microenvironment. To date, these processes have been largely studied in isolation. A systematic understanding of how they interact and influence each other is lacking. Here, we present a framework for systematically characterizing the interaction between pairs of mutational signatures and between signatures and signaling pathway alterations. We applied this framework to large-scale data from TCGA and PCAWG and identified multiple positive and negative interactions, both cross֊tissue and tissue֊specific, that provide new insights into the molecular routes observed in tumorigenesis and their respective drivers. This framework allows for a more fine-grained dissection of common and distinct etiology of mutational signatures. We further identified several interactions with both positive and negative impacts on patient survival, demonstrating their clinical relevance and potential for improving personalized cancer care.

Cancer mutational signatures identification in clinical assays using neural embedding-based representations

While mutational signatures provide a plethora of prognostic and therapeutic insights, their application in clinical-setting, targeted gene panels is extremely limited. We develop a mutational representation model (which learns and embeds specific mutation signature connections) that enables prediction of dominant signatures with only a few mutations. We predict the dominant signatures across more than 60,000 tumors with gene panels, delineating their landscape across different cancers. Dominant signature predictions in gene panels are of clinical importance. These included UV, tobacco, and apolipoprotein B mRNA editing enzyme, catalytic polypeptide (APOBEC) signatures that are associated with better survival, independently from mutational burden. Further analyses reveal gene and mutation associations with signatures, such as SBS5 with TP53 and APOBEC with FGFR3S249C. In a clinical use case, APOBEC signature is a robust and specific predictor for resistance to epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs). Our model provides an easy-to-use way to detect signatures in clinical setting assays with many possible clinical implications for an unprecedented number of cancer patients.

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.

Targeting RAF dimers in RAS mutant tumors: From biology to clinic

RAS mutations occur in approximately 30% of tumors worldwide and have a poor prognosis due to limited therapies. Covalent targeting of KRAS G12C has achieved significant success in recent years, but there is still a lack of efficient therapeutic approaches for tumors with non-G12C KRAS mutations. A highly promising approach is to target the MAPK pathway downstream of RAS, with a particular focus on RAF kinases. First-generation RAF inhibitors have been authorized to treat BRAF mutant tumors for over a decade. However, their use in RAS-mutated tumors is not recommended due to the paradoxical ERK activation mainly caused by RAF dimerization. To address the issue of RAF dimerization, type II RAF inhibitors have emerged as leading candidates. Recent clinical studies have shown the initial effectiveness of these agents against RAS mutant tumors. Promisingly, type II RAF inhibitors in combination with MEK or ERK inhibitors have demonstrated impressive efficacy in RAS mutant tumors. This review aims to clarify the importance of RAF dimerization in cellular signaling and resistance to treatment in tumors with RAS mutations, as well as recent progress in therapeutic approaches to address the problem of RAF dimerization in RAS mutant tumors.

KRAS: Biology, Inhibition, and Mechanisms of Inhibitor Resistance

KRAS is a small GTPase that is among the most commonly mutated oncogenes in cancer. Here, we discuss KRAS biology, therapeutic avenues to target it, and mechanisms of resistance that tumors employ in response to KRAS inhibition. Several strategies are under investigation for inhibiting oncogenic KRAS, including small molecule compounds targeting specific KRAS mutations, pan-KRAS inhibitors, PROTACs, siRNAs, PNAs, and mutant KRAS-specific immunostimulatory strategies. A central challenge to therapeutic effectiveness is the frequent development of resistance to these treatments. Direct resistance mechanisms can involve KRAS mutations that reduce drug efficacy or copy number alterations that increase the expression of mutant KRAS. Indirect resistance mechanisms arise from mutations that can rescue mutant KRAS-dependent cells either by reactivating the same signaling or via alternative pathways. Further, non-mutational forms of resistance can take the form of epigenetic marks, transcriptional reprogramming, or alterations within the tumor microenvironment. As the possible strategies to inhibit KRAS expand, understanding the nuances of resistance mechanisms is paramount to the development of both enhanced therapeutics and innovative drug combinations.

KRASG12C mutant lung adenocarcinoma: unique biology, novel therapies and new challenges

KRAS mutant lung cancer is the most prevalent molecular subclass of adenocarcinoma (LUAD), which is a heterogenous group depending on the mutation-type which affects not only the function of the oncogene but affects the biological behavior of the cancer as well. Furthermore, KRAS mutation affects radiation sensitivity but leads also to bevacizumab and bisphosphonate resistance as well. It was highly significant that allele specific irreversible inhibitors have been developed for the smoking associated G12C mutant KRAS (sotorasib and adagrasib). Based on trial data both sotorasib and adagrasib obtained conditional approval by FDA for the treatment of previously treated advanced LUAD. Similar to other target therapies, clinical administration of KRASG12C inhibitors (sotorasib and adagrasib) resulted in acquired resistance due to various genetic changes not only in KRAS but in other oncogenes as well. Recent clinical studies are aiming to increase the efficacy of G12C inhibitors by novel combination strategies.

Mutational processes of tobacco smoking and APOBEC activity generate protein-truncating mutations in cancer genomes

Mutational signatures represent a genomic footprint of endogenous and exogenous mutational processes through tumor evolution. However, their functional impact on the proteome remains incompletely understood. We analyzed the protein-coding impact of single-base substitution (SBS) signatures in 12,341 cancer genomes from 18 cancer types. Stop-gain mutations (SGMs) (i.e., nonsense mutations) were strongly enriched in SBS signatures of tobacco smoking, APOBEC cytidine deaminases, and reactive oxygen species. These mutational processes alter specific trinucleotide contexts and thereby substitute serines and glutamic acids with stop codons. SGMs frequently affect cancer hallmark pathways and tumor suppressors such as TP53, FAT1, and APC. Tobacco-driven SGMs in lung cancer correlate with smoking history and highlight a preventable determinant of these harmful mutations. APOBEC-driven SGMs are enriched in YTCA motifs and associate with APOBEC3A expression. Our study exposes SGM expansion as a genetic mechanism by which endogenous and carcinogenic mutational processes directly contribute to protein loss of function, oncogenesis, and tumor heterogeneity.

Mutation bias and the predictability of evolution

Predicting evolutionary outcomes is an important research goal in a diversity of contexts. The focus of evolutionary forecasting is usually on adaptive processes, and efforts to improve prediction typically focus on selection. However, adaptive processes often rely on new mutations, which can be strongly influenced by predictable biases in mutation. Here, we provide an overview of existing theory and evidence for such mutation-biased adaptation and consider the implications of these results for the problem of prediction, in regard to topics such as the evolution of infectious diseases, resistance to biochemical agents, as well as cancer and other kinds of somatic evolution. We argue that empirical knowledge of mutational biases is likely to improve in the near future, and that this knowledge is readily applicable to the challenges of short-term prediction. This article is part of the theme issue 'Interdisciplinary approaches to predicting evolutionary biology'.

Genomic mutation landscape of skin cancers from DNA repair-deficient xeroderma pigmentosum patients

Xeroderma pigmentosum (XP) is a genetic disorder caused by mutations in genes of the Nucleotide Excision Repair (NER) pathway (groups A-G) or in Translesion Synthesis DNA polymerase η (V). XP is associated with an increased skin cancer risk, reaching, for some groups, several thousand-fold compared to the general population. Here, we analyze 38 skin cancer genomes from five XP groups. We find that the activity of NER determines heterogeneity of the mutation rates across skin cancer genomes and that transcription-coupled NER extends beyond the gene boundaries reducing the intergenic mutation rate. Mutational profile in XP-V tumors and experiments with POLH knockout cell line reveal the role of polymerase η in the error-free bypass of (i) rare TpG and TpA DNA lesions, (ii) 3' nucleotides in pyrimidine dimers, and (iii) TpT photodimers. Our study unravels the genetic basis of skin cancer risk in XP and provides insights into the mechanisms reducing UV-induced mutagenesis in the general population.

Cancer driver mutations: predictions and reality

Cancer cells accumulate many genetic alterations throughout their lifetime, but only a few of them drive cancer progression, termed driver mutations. Driver mutations may vary between cancer types and patients, can remain latent for a long time and become drivers at particular cancer stages, or may drive oncogenesis only in conjunction with other mutations. The high mutational, biochemical, and histological tumor heterogeneity makes driver mutation identification very challenging. In this review we summarize recent efforts to identify driver mutations in cancer and annotate their effects. We underline the success of computational methods to predict driver mutations in finding novel cancer biomarkers, including in circulating tumor DNA (ctDNA). We also report on the boundaries of their applicability in clinical research.

Influence network model uncovers relations between biological processes and mutational signatures

BACKGROUND

There has been a growing appreciation recently that mutagenic processes can be studied through the lenses of mutational signatures, which represent characteristic mutation patterns attributed to individual mutagens. However, the causal links between mutagens and observed mutation patterns as well as other types of interactions between mutagenic processes and molecular pathways are not fully understood, limiting the utility of mutational signatures.

METHODS

To gain insights into these relationships, we developed a network-based method, named GENESIGNET that constructs an influence network among genes and mutational signatures. The approach leverages sparse partial correlation among other statistical techniques to uncover dominant influence relations between the activities of network nodes.

RESULTS

Applying GENESIGNET to cancer data sets, we uncovered important relations between mutational signatures and several cellular processes that can shed light on cancer-related processes. Our results are consistent with previous findings, such as the impact of homologous recombination deficiency on clustered APOBEC mutations in breast cancer. The network identified by GENESIGNET also suggest an interaction between APOBEC hypermutation and activation of regulatory T Cells (Tregs), as well as a relation between APOBEC mutations and changes in DNA conformation. GENESIGNET also exposed a possible link between the SBS8 signature of unknown etiology and the Nucleotide Excision Repair (NER) pathway.

CONCLUSIONS

GENESIGNET provides a new and powerful method to reveal the relation between mutational signatures and gene expression. The GENESIGNET method was implemented in python, and installable package, source codes and the data sets used for and generated during this study are available at the Github site https://github.com/ncbi/GeneSigNet.

Non-Association of Driver Alterations in PTEN with Differential Gene Expression and Gene Methylation in IDH1 Wildtype Glioblastomas

During oncogenesis, alterations in driver genes called driver alterations (DAs) modulate the transcriptome, methylome and proteome through oncogenic signaling pathways. These modulatory effects of any DA may be analyzed by examining differentially expressed mRNAs (DEMs), differentially methylated genes (DMGs) and differentially expressed proteins (DEPs) between tumor samples with and without that DA. We aimed to analyze these modulations with 12 common driver genes in Isocitrate Dehydrogenase 1 wildtype glioblastomas (IDH1-W-GBs). Using Cbioportal, groups of tumor samples with and without DAs in these 12 genes were generated from the IDH1-W-GBs available from "The Cancer Genomics Atlas Firehose Legacy Study Group" (TCGA-FL-SG) on Glioblastomas (GBs). For all 12 genes, samples with and without DAs were compared for DEMs, DMGs and DEPs. We found that DAs in PTEN were unassociated with any DEM or DMG in contrast to DAs in all other drivers, which were associated with several DEMs and DMGs. This contrasting PTEN-related property of being unassociated with differential gene expression or methylation in IDH1-W-GBs was unaffected by concurrent DAs in other common drivers or by the types of DAs affecting PTEN. From the lists of DEMs and DMGs associated with some common drivers other than PTEN, enriched gene ontology terms and insights into the co-regulatory effects of these drivers on the transcriptome were obtained. The findings from this study can improve our understanding of the molecular mechanisms underlying gliomagenesis with potential therapeutic benefits.

Prognosis and Characterization of Microenvironment in Cervical Cancer Influenced by Fatty Acid Metabolism-Related Genes

Increasing evidence suggests that diverse activation patterns of metabolic signalling pathways may lead to molecular diversity of cervical cancer (CC). But rare research focuses on the alternation of fatty acid metabolism (FAM) in CC. Therefore, we constructed and compared models based on the expression of FAM-related genes from the Cancer Genome Atlas by different machine learning algorithms. The most reliable model was built with 14 significant genes by LASSO-Cox regression, and the CC cohort was divided into low-/high-risk groups by the median of risk score. Then, a feasible nomogram was established and validated by C-index, calibration curve, net benefit, and decision curve analysis. Furthermore, the hub genes among differential expression genes were identified and the post-transcriptional and translational regulation networks were characterized. Moreover, the somatic mutation and copy number variation landscapes were depicted. Importantly, the specific mutation drivers and signatures of the FAM phenotypes were excavated. As a result, the high-risk samples were featured by activated de novo fatty acid synthesis, epithelial to mesenchymal transition, angiogenesis, and chronic inflammation response, which might be caused by mutations of oncogenic driver genes in RTK/RAS, PI3K, and NOTCH signalling pathways. Besides the hyperactivity of cytidine deaminase and deficiency of mismatch repair, the mutations of POLE might be partially responsible for the mutations in the high-risk group. Next, the antigenome including the neoantigen and cancer germline antigens was estimated. The decreasing expression of a series of cancer germline antigens was identified to be related to reduction of CD8 T cell infiltration in the high-risk group. Then, the comprehensive evaluation of connotations between the tumour microenvironment and FAM phenotypes demonstrated that the increasing risk score was related to the suppressive immune microenvironment. Finally, the prediction of therapy targets revealed that the patients with high risk might be sensitive to the RAF inhibitor AZ628. Our findings provide a novel insight for personalized treatment in CC.

Evolutionary Analysis of TCGA Data Using Over- and Under- Mutated Genes Identify Key Molecular Pathways and Cellular Functions in Lung Cancer Subtypes

We identify critical conserved and mutated genes through a theoretical model linking a gene’s fitness contribution to its observed mutational frequency in a clinical cohort. “Passenger” gene mutations do not alter fitness and have mutational frequencies determined by gene size and the mutation rate. Driver mutations, which increase fitness (and proliferation), are observed more frequently than expected. Non-synonymous mutations in essential genes reduce fitness and are eliminated by natural selection resulting in lower prevalence than expected. We apply this “evolutionary triage” principle to TCGA data from EGFR-mutant, KRAS-mutant, and NEK (non-EGFR/KRAS) lung adenocarcinomas. We find frequent overlap of evolutionarily selected non-synonymous gene mutations among the subtypes suggesting enrichment for adaptations to common local tissue selection forces. Overlap of conserved genes in the LUAD subtypes is rare suggesting negative evolutionary selection is strongly dependent on initiating mutational events during carcinogenesis. Highly expressed genes are more likely to be conserved and significant changes in expression (>20% increased/decreased) are common in genes with evolutionarily selected mutations but not in conserved genes. EGFR-mut cancers have fewer average mutations (89) than KRAS-mut (228) and NEK (313). Subtype-specific variation in conserved and mutated genes identify critical molecular components in cell signaling, extracellular matrix remodeling, and membrane transporters. These findings demonstrate subtype-specific patterns of co-adaptations between the defining driver mutation and somatically conserved genes as well as novel insights into epigenetic versus genetic contributions to cancer evolution.

Genomic Landscapes and Hallmarks of Mutant RAS in Human Cancers

The RAS family of small GTPases represents the most commonly activated oncogenes in human cancers. To better understand the prevalence of somatic RAS mutations and the compendium of genes that are coaltered in RAS-mutant tumors, we analyzed targeted next-generation sequencing data of 607,863 mutations from 66,372 tumors in 51 cancer types in the AACR Project GENIE Registry. Bayesian hierarchical models were implemented to estimate the cancer-specific prevalence of RAS and non-RAS somatic mutations, to evaluate co-occurrence and mutual exclusivity, and to model the effects of tumor mutation burden and mutational signatures on comutation patterns. These analyses revealed differential RAS prevalence and comutations with non-RAS genes in a cancer lineage-dependent and context-dependent manner, with differences across age, sex, and ethnic groups. Allele-specific RAS co-mutational patterns included an enrichment in NTRK3 and chromatin-regulating gene mutations in KRAS G12C-mutant non-small cell lung cancer. Integrated multiomic analyses of 10,217 tumors from The Cancer Genome Atlas (TCGA) revealed distinct genotype-driven gene expression programs pointing to differential recruitment of cancer hallmarks as well as phenotypic differences and immune surveillance states in the tumor microenvironment of RAS-mutant tumors. The distinct genomic tracks discovered in RAS-mutant tumors reflected differential clinical outcomes in TCGA cohort and in an independent cohort of patients with KRAS G12C-mutant non-small cell lung cancer that received immunotherapy-containing regimens. The RAS genetic architecture points to cancer lineage-specific therapeutic vulnerabilities that can be leveraged for rationally combining RAS-mutant allele-directed therapies with targeted therapies and immunotherapy.

SIGNIFICANCE

The complex genomic landscape of RAS-mutant tumors is reflective of selection processes in a cancer lineage-specific and context-dependent manner, highlighting differential therapeutic vulnerabilities that can be clinically translated.

Single cell metabolism: current and future trends

Single cell metabolomics is an emerging and rapidly developing field that complements developments in single cell analysis by genomics and proteomics. Major goals include mapping and quantifying the metabolome in sufficient detail to provide useful information about cellular function in highly heterogeneous systems such as tissue, ultimately with spatial resolution at the individual cell level. The chemical diversity and dynamic range of metabolites poses particular challenges for detection, identification and quantification. In this review we discuss both significant technical issues of measurement and interpretation, and progress toward addressing them, with recent examples from diverse biological systems. We provide a framework for further directions aimed at improving workflow and robustness so that such analyses may become commonly applied, especially in combination with metabolic imaging and single cell transcriptomics and proteomics.

Unboxing the molecular modalities of mutagens in cancer

The etiology of the majority of human cancers is associated with a myriad of environmental causes, including physical, chemical, and biological factors. DNA damage induced by such mutagens is the initial step in the process of carcinogenesis resulting in the accumulation of mutations. Mutational events are considered the major triggers for introducing genetic and epigenetic insults such as DNA crosslinks, single- and double-strand DNA breaks, formation of DNA adducts, mismatched bases, modification in histones, DNA methylation, and microRNA alterations. However, DNA repair mechanisms are devoted to protect the DNA to ensure genetic stability, any aberrations in these calibrated mechanisms provoke cancer occurrence. Comprehensive knowledge of the type of mutagens and carcinogens and the influence of these agents in DNA damage and cancer induction is crucial to develop rational anticancer strategies. This review delineated the molecular mechanism of DNA damage and the repair pathways to provide a deep understanding of the molecular basis of mutagenicity and carcinogenicity. A relationship between DNA adduct formation and cancer incidence has also been summarized. The mechanistic basis of inflammatory response and oxidative damage triggered by mutagens in tumorigenesis has also been highlighted. We elucidated the interesting interplay between DNA damage response and immune system mechanisms. We addressed the current understanding of DNA repair targeted therapies and DNA damaging chemotherapeutic agents for cancer treatment and discussed how antiviral agents, anti-inflammatory drugs, and immunotherapeutic agents combined with traditional approaches lay the foundations for future cancer therapies.

Pan-Cancer Analysis for Immune Cell Infiltration and Mutational Signatures Using Non-Negative Canonical Correlation Analysis

Mutational signatures indicate the mutational processes and substitution patterns in cancer cell genomes. However, the functional consequences of mutational signatures remain unclear, and there have been no comprehensive systematic studies to examine the relationships between the mutational signatures and the immune cell infiltration. Here, the relationship between mutational signatures and immune cell infiltration using non-negative canonical correlation analysis based on 8927 patients across 25 tumor types was investigated. By inspecting mutational signatures with the maximal coefficients determined by the non-negative canonical correlation analysis, the study identified mutational signatures related to immune cell infiltration composed of tumor microenvironments. The analysis was validated by showing that the genes associated with the identified mutational signatures were linked to overall survival by a Kaplan–Meier curve and a log-rank test and were mainly related to immunity by gene set enrichment analysis. These results will help expand our knowledge of tumor biology and recognize the functional roles and associations of immune systems with mutational signatures.

Mutational signatures and processes in hepatobiliary cancers

The evolutionary history of hepatobiliary cancers is embedded in their genomes. By analysing their catalogue of somatic mutations and the DNA sequence context in which they occur, it is possible to infer the mechanisms underpinning tumorigenesis. These mutational signatures reflect the exogenous and endogenous origins of genetic damage as well as the capacity of hepatobiliary cells to repair and replicate DNA. Genomic analysis of thousands of patients with hepatobiliary cancers has highlighted the diversity of mutagenic processes active in these malignancies, highlighting a prominent source of the inter-cancer-type, inter-patient, intertumour and intratumoural heterogeneity that is observed clinically. However, a substantial proportion of mutational signatures detected in hepatocellular carcinoma and biliary tract cancer remain of unknown cause, emphasizing the important contribution of processes yet to be identified. Exploiting mutational signatures to retrospectively understand hepatobiliary carcinogenesis could advance preventative management of these aggressive tumours as well as potentially predict treatment response and guide the development of therapies targeting tumour evolution.

The translational challenges of precision oncology

The translational challenges in the field of precision oncology are in part related to the biological complexity and diversity of this disease. Technological advances in genomics have facilitated large sequencing efforts and discoveries that have further supported this notion. In this review, we reflect on the impact of these discoveries on our understanding of several concepts: cancer initiation, cancer prevention, early detection, adjuvant therapy and minimal residual disease monitoring, cancer drug resistance, and cancer evolution in metastasis. We discuss key areas of focus for improving cancer outcomes, from biological insights to clinical application, and suggest where the development of these technologies will lead us. Finally, we discuss practical challenges to the wider adoption of molecular profiling in the clinic and the need for robust translational infrastructure.

Attribution of Cancer Origins to Endogenous, Exogenous, and Preventable Mutational Processes

Mutational processes in tumors create distinctive patterns of mutations, composed of neutral "passenger" mutations and oncogenic drivers that have quantifiable effects on the proliferation and survival of cancer cell lineages. Increases in proliferation and survival are mediated by natural selection, which can be quantified by comparing the frequency at which we detect substitutions to the frequency at which we expect to detect substitutions assuming neutrality. Most of the variants detectable with whole-exome sequencing in tumors are neutral or nearly neutral in effect, and thus the processes generating the majority of mutations may not be the primary sources of the tumorigenic mutations. Across 24 cancer types, we identify the contributions of mutational processes to each oncogenic variant and quantify the degree to which each process contributes to tumorigenesis. We demonstrate that the origination of variants driving melanomas and lung cancers is predominantly attributable to the preventable, exogenous mutational processes associated with ultraviolet light and tobacco exposure, respectively, whereas the origination of selected variants in gliomas and prostate adenocarcinomas is largely attributable to endogenous processes associated with aging. Preventable mutations associated with pathogen exposure and apolipoprotein B mRNA-editing enzyme activity account for a large proportion of the cancer effect within head-and-neck, bladder, cervical, and breast cancers. These attributions complement epidemiological approaches-revealing the burden of cancer driven by single-nucleotide variants caused by either endogenous or exogenous, nonpreventable, or preventable processes, and crucially inform public health strategies.

Non-canonical genomic driver mutations of urethane carcinogenesis

The carcinogen urethane induces pulmonary tumors in mice initiated by an incredibly specific Q61L/R oncogenic mutation in the proto-oncogene Kras. Previous Whole-Exome Sequencing of urethane-induced tumors revealed a bias towards A➙T/G and G➙A substitutions. Subsequent ultra-sensitive Maximum-Depth Sequencing of Kras shortly after urethane exposure suggest a further refinement to CA➙CT/G substitutions. As C182AA➙C182T/GA substitutions in Kras result in Q61L/R mutations, the extreme bias of urethane towards these genomic driver mutations can be ascribed to the specificity of the carcinogen for CA➙CT/G substitutions. However, we previously found that changing rare codons to common in the Kras gene to increase protein expression shifted mutations in urethane-induced tumors away from Kras, or when detected in Kras, to G12D mutations that are usually rarely detected in such tumors. Moreover, the loss of p53 partially reversed this effect, generating tumors with either Q61L/R or G12D oncogenic Kras mutations, or no Kras mutations, presumably due to other genomic driver mutations. Determining the origin of these G12D and other unknown non-canonical genomic driver mutations would provide critical insight into the extreme bias of carcinogens for specific genomic driver mutations. We thus compared the types of Single Nucleotide Variations detected by previously performed Maximum-Depth Sequencing immediately after urethane exposure to the mutation signatures derived from Whole Exome Sequencing of urethane-induced tumors. This identified two types of non-canonical mutations. First, a V637E oncogenic mutation in the proto-oncogene Braf that conforms to the mutation signature of urethane, suggesting that the mutational bias of the carcinogen may account for this non-canonical mutation, similar to that for canonical Q61L/R mutations in Kras. Second, G12D and Q61H mutations in Kras that did not fit this mutation signature, and instead shared similarity with Single Nucleotide Variations detected by Maximum-Depth Sequencing from normal cells, suggesting that perhaps these mutations were pre-existing. We thus posit that when canonical Kras mutations are selected against that the carcinogen may instead promote the expansion of pre-existing genomic driver mutations, although admittedly we cannot rule out other mechanisms. Interrogating the mutation signatures of human lung cancers similarly identified KRAS genomic driver mutations that failed to match the mutation signature of the tumor. Thus, we also speculate that the selection for non-canonical genomic driver mutations during urethane carcinogenesis may reflect the process by which discordance between genomic driver mutations and mutational signatures arises in human cancers.

USP28 enables oncogenic transformation of respiratory cells and its inhibition potentiates molecular therapy targeting mutant EGFR, BRAF and PI3K

Oncogenic transformation of lung epithelial cells is a multistep process, frequently starting with the inactivation of tumour suppressors and subsequent development of activating mutations in proto‐oncogenes, such as members of the PI3K or MAPK families. Cells undergoing transformation have to adjust to changes, including altered metabolic requirements. This is achieved, in part, by modulating the protein abundance of transcription factors. Here, we report that the ubiquitin carboxyl‐terminal hydrolase 28 (USP28) enables oncogenic reprogramming by regulating the protein abundance of proto‐oncogenes such as c‐JUN, c‐MYC, NOTCH and ∆NP63 at early stages of malignant transformation. USP28 levels are increased in cancer compared with in normal cells due to a feed‐forward loop, driven by increased amounts of oncogenic transcription factors such as c‐MYC and c‐JUN. Irrespective of oncogenic driver, interference with USP28 abundance or activity suppresses growth and survival of transformed lung cells. Furthermore, inhibition of USP28 via a small‐molecule inhibitor resets the proteome of transformed cells towards a ‘premalignant’ state, and its inhibition synergizes with clinically established compounds used to target EGFR^L858R‐, BRAF^V600E‐ or PI3K^H1047R‐driven tumour cells. Targeting USP28 protein abundance at an early stage via inhibition of its activity is therefore a feasible strategy for the treatment of early‐stage lung tumours, and the observed synergism with current standard‐of‐care inhibitors holds the potential for improved targeting of established tumours.

APOBEC SBS13 Mutational Signature-A Novel Predictor of Radioactive Iodine Refractory Papillary Thyroid Carcinoma

Standard surgery followed by radioactive iodine (131I, RAI) therapy are not curative for 5−20% of papillary thyroid carcinoma (PTC) patients with RAI refractory disease. Early predictors indicating therapeutic response to RAI therapy in PTC are yet to be elucidated. Whole-exome sequencing was performed (at median depth 198x) on 66 RAI-refractory and 92 RAI-avid PTCs with patient-matched germline. RAI-refractory tumors were significantly associated with distinct aggressive clinicopathological features, including positive surgical margins (p = 0.016) and the presence of lymph node metastases at primary diagnosis (p = 0.012); higher nonsilent tumor mutation burden (p = 0.011); TERT promoter (TERTp) mutation (p < 0.0001); and the enrichment of the APOBEC-related single-base substitution (SBS) COSMIC mutational signatures 2 (p = 0.030) and 13 (p < 0.001). Notably, SBS13 (odds ratio [OR] 30.4, 95% confidence intervals [CI] 1.43−647.22) and TERTp mutation (OR 41.3, 95% CI 4.35−391.60) were revealed to be independent predictors of RAI refractoriness in PTC (p = 0.029 and 0.001, respectively). Although SBS13 and TERTp mutations alone highly predicted RAI refractoriness, when combined, they significantly increased the likelihood of predicting RAI refractoriness in PTC. This study highlights the APOBEC SBS13 mutational signature as a novel independent predictor of RAI refractoriness in a distinct subgroup of PTC.

Mutation bias shapes the spectrum of adaptive substitutions

How do mutational biases influence the process of adaptation? A common assumption is that selection alone determines the course of adaptation from abundant preexisting variation. Yet, theoretical work shows broad conditions under which the mutation rate to a given type of variant strongly influences its probability of contributing to adaptation. Here we introduce a statistical approach to analyzing how mutation shapes protein sequence adaptation. Using large datasets from three different species, we show that the mutation spectrum has a proportional influence on the types of changes fixed in adaptation. We also show via computer simulations that a variety of factors can influence how closely the spectrum of adaptive substitutions reflects the spectrum of variants introduced by mutation.

Evolutionary adaptation often occurs by the fixation of beneficial mutations. This mode of adaptation can be characterized quantitatively by a spectrum of adaptive substitutions, i.e., a distribution for types of changes fixed in adaptation. Recent work establishes that the changes involved in adaptation reflect common types of mutations, raising the question of how strongly the mutation spectrum shapes the spectrum of adaptive substitutions. We address this question with a codon-based model for the spectrum of adaptive amino acid substitutions, applied to three large datasets covering thousands of amino acid changes identified in natural and experimental adaptation in Saccharomyces cerevisiae, Escherichia coli, and Mycobacterium tuberculosis. Using species-specific mutation spectra based on prior knowledge, we find that the mutation spectrum has a proportional influence on the spectrum of adaptive substitutions in all three species. Indeed, we find that by inferring the mutation rates that best explain the spectrum of adaptive substitutions, we can accurately recover the species-specific mutation spectra. However, we also find that the predictive power of the model differs substantially between the three species. To better understand these differences, we use population simulations to explore the factors that influence how closely the spectrum of adaptive substitutions mirrors the mutation spectrum. The results show that the influence of the mutation spectrum decreases with increasing mutational supply (Nμ) and that predictive power is strongly affected by the number and diversity of beneficial mutations.

Analysis of Mutations and Dysregulated Pathways Unravels Carcinogenic Effect and Clinical Actionability of Mutational Processes

Somatic mutations accumulate over time in cancer cells as a consequence of mutational processes. However, the role of mutational processes in carcinogenesis remains poorly understood. Here, we infer the causal relationship between mutational processes and somatic mutations in 5,828 samples spanning 34 cancer subtypes. We found most mutational processes cause abundant recurrent mutations in cancer genes, while exceptionally ultraviolet exposure and altered activity of the error-prone polymerase bring a large number of recurrent non-driver mutations. Furthermore, some mutations are specifically induced by a certain mutational process, such as IDH1 p.R132H which is mainly caused by spontaneous deamination of 5-methylcytosine. At the pathway level, clock-like mutational processes extensively trigger mutations to dysregulate cancer signal transduction pathways. In addition, APOBEC mutational process destroys DNA double-strand break repair pathway, and bladder cancer patients with high APOBEC activity, though with homologous recombination proficient, show a significantly longer overall survival with platinum regimens. These findings help to understand how mutational processes act on the genome to promote carcinogenesis, and further, presents novel insights for cancer prevention and treatment, as our results showing, APOBEC mutagenesis and HRD synergistically contributed to the clinical benefits of platinum-based treatment.

The Mutagenic Impact of Environmental Exposures in Human Cells and Cancer: Imprints Through Time

During life, the DNA of our cells is continuously exposed to external damaging processes. Despite the activity of various repair mechanisms, DNA damage eventually results in the accumulation of mutations in the genomes of our cells. Oncogenic mutations are at the root of carcinogenesis, and carcinogenic agents are often highly mutagenic. Over the past decade, whole genome sequencing data of healthy and tumor tissues have revealed how cells in our body gradually accumulate mutations because of exposure to various mutagenic processes. Dissection of mutation profiles based on the type and context specificities of the altered bases has revealed a variety of signatures that reflect past exposure to environmental mutagens, ranging from chemotherapeutic drugs to genotoxic gut bacteria. In this review, we discuss the latest knowledge on somatic mutation accumulation in human cells, and how environmental mutagenic factors further shape the mutation landscapes of tissues. In addition, not all carcinogenic agents induce mutations, which may point to alternative tumor-promoting mechanisms, such as altered clonal selection dynamics. In short, we provide an overview of how environmental factors induce mutations in the DNA of our healthy cells and how this contributes to carcinogenesis. A better understanding of how environmental mutagens shape the genomes of our cells can help to identify potential preventable causes of cancer.

WNT as a Driver and Dependency in Cancer

The WNT signaling pathway is a critical regulator of development and adult tissue homeostasis and becomes dysregulated in many cancer types. Although hyperactivation of WNT signaling is common, the type and frequency of genetic WNT pathway alterations can vary dramatically between different cancers, highlighting possible cancer-specific mechanisms for WNT-driven disease. In this review, we discuss how WNT pathway disruption contributes to tumorigenesis in different organs and how WNT affects the tumor cell and immune microenvironment. Finally, we describe recent and ongoing efforts to target oncogenic WNT signaling as a therapeutic strategy. SIGNIFICANCE: WNT signaling is a fundamental regulator of tissue homeostasis and oncogenic driver in many cancer types. In this review, we highlight recent advances in our understanding of WNT signaling in cancer, particularly the complexities of WNT activation in distinct cancer types, its role in immune evasion, and the challenge of targeting the WNT pathway as a therapeutic strategy.

Genetic Determinants of Somatic Selection of Mutational Processes in 3,566 Human Cancers

The somatic landscape of the cancer genome results from different mutational processes represented by distinct "mutational signatures." Although several mutagenic mechanisms are known to cause specific mutational signatures in cell lines, the variation of somatic mutational activities in patients, which is mostly attributed to somatic selection, is still poorly explained. Here, we introduce a quantitative trait, mutational propensity (MP), and describe an integrated method to infer genetic determinants of variations in the mutational processes in 3,566 cancers with specific underlying mechanisms. As a result, we report 2,314 candidate determinants with both significant germline and somatic effects on somatic selection of mutational processes, of which, 485 act via cancer gene expression and 1,427 act through the tumor-immune microenvironment. These data demonstrate that the genetic determinants of MPs provide complementary information to known cancer driver genes, clonal evolution, and clinical biomarkers. SIGNIFICANCE: The genetic determinants of the somatic mutational processes in cancer elucidate the biology underlying somatic selection and evolution of cancers and demonstrate complementary predictive power across cancer types.

Pan-Cancer Survey of Tumor Mass Dormancy and Underlying Mutational Processes

Tumor mass dormancy is the key intermediate step between immune surveillance and cancer progression, yet due to its transitory nature it has been difficult to capture and characterize. Little is understood of its prevalence across cancer types and of the mutational background that may favor such a state. While this balance is finely tuned internally by the equilibrium between cell proliferation and cell death, the main external factors contributing to tumor mass dormancy are immunological and angiogenic. To understand the genomic and cellular context in which tumor mass dormancy may develop, we comprehensively profiled signals of immune and angiogenic dormancy in 9,631 cancers from the Cancer Genome Atlas and linked them to tumor mutagenesis. We find evidence for immunological and angiogenic dormancy-like signals in 16.5% of bulk sequenced tumors, with a frequency of up to 33% in certain tissues. Mutations in the CASP8 and HRAS oncogenes were positively selected in dormant tumors, suggesting an evolutionary pressure for controlling cell growth/apoptosis signals. By surveying the mutational damage patterns left in the genome by known cancer risk factors, we found that aging-induced mutations were relatively depleted in these tumors, while patterns of smoking and defective base excision repair were linked with increased tumor mass dormancy. Furthermore, we identified a link between APOBEC mutagenesis and dormancy, which comes in conjunction with immune exhaustion and may partly depend on the expression of the angiogenesis regulator PLG as well as interferon and chemokine signals. Tumor mass dormancy also appeared to be impaired in hypoxic conditions in the majority of cancers. The microenvironment of dormant cancers was enriched in cytotoxic and regulatory T cells, as expected, but also in macrophages and showed a reduction in inflammatory Th17 signals. Finally, tumor mass dormancy was linked with improved patient survival outcomes. Our analysis sheds light onto the complex interplay between dormancy, exhaustion, APOBEC activity and hypoxia, and sets directions for future mechanistic explorations.

Mutational signatures impact the evolution of anti-EGFR antibody resistance in colorectal cancer

Anti-EGFR antibodies such as cetuximab are active against KRAS/NRAS wild-type colorectal cancers (CRC) but acquired resistance invariably evolves. Which mutational mechanisms enable resistance evolution and whether adaptive mutagenesis, a transient cetuximab-induced increase in mutation generation, contributes in patients is unknown. Here, we investigate this in exome sequencing data of 42 baseline and progression biopsies from cetuximab treated CRCs. Mutation loads did not increase from baseline to progression and evidence for a contribution of adaptive mutagenesis was limited. However, the chemotherapy-induced mutational signature SBS17b was the main contributor of specific KRAS/NRAS and EGFR driver mutations that are enriched at acquired resistance. Detectable SBS17b activity before treatment predicted for shorter progression free survival and for the evolution of these specific mutations during subsequent cetuximab treatment. This suggests that chemotherapy mutagenesis can accelerate resistance evolution. Mutational signatures may be a new class of cancer evolution predictor.

Signaling levels mold the RAS mutation tropism of urethane

RAS genes are commonly mutated in human cancer. Despite many possible mutations, individual cancer types often have a 'tropism' towards a specific subset of RAS mutations. As driver mutations, these patterns ostensibly originate from normal cells. High oncogenic RAS activity causes oncogenic stress and different oncogenic mutations can impart different levels of activity, suggesting a relationship between oncoprotein activity and RAS mutation tropism. Here, we show that changing rare codons to common in the murine Kras gene to increase protein expression shifts tumors induced by the carcinogen urethane from arising from canonical Q₆₁ to biochemically less active G₁₂ Kras driver mutations, despite the carcinogen still being biased towards generating Q₆₁ mutations. Conversely, inactivating the tumor suppressor p53 to blunt oncogenic stress partially reversed this effect, restoring Q₆₁ mutations. One interpretation of these findings is that the RAS mutation tropism of urethane arises from selection in normal cells for specific mutations that impart a narrow window of signaling that promotes proliferation without causing oncogenic stress.

Germline APOBEC3B deletion increases somatic hypermutation in Asian breast cancer that is associated with Her2 subtype, PIK3CA mutations and immune activation

A 30-kb deletion that eliminates the coding region of APOBEC3B (A3B) is >5 times more common in women of Asian descent compared to European descent. This polymorphism creates a chimera with the APOBEC3A (A3A) coding region and A3B 3'UTR, and it is associated with an increased risk for breast cancer in Asian women. Here, we explored the relationship between the A3B deletion polymorphism with tumour characteristics in Asian women. Using whole exome and whole transcriptome sequencing data of 527 breast tumours, we report that germline A3B deletion polymorphism leads to expression of the A3A-B hybrid isoform and increased APOBEC-associated somatic hypermutation. Hypermutated tumours, regardless of A3B germline status, were associated with the Her2 molecular subtype and PIK3CA mutations. Compared to nonhypermutated tumours, hypermutated tumours also had higher neoantigen burden, tumour heterogeneity and immune activation. Taken together, our results suggest that the germline A3B deletion polymorphism, via the A3A-B hybrid isoform, contributes to APOBEC mutagenesis in a significant proportion of Asian breast cancers. In addition, APOBEC somatic hypermutation, regardless of A3B background, may be an important clinical biomarker for Asian breast cancers.

Spectrum of mutational signatures in T-cell lymphoma reveals a key role for UV radiation in cutaneous T-cell lymphoma

T-cell non-Hodgkin's lymphomas develop following transformation of tissue resident T-cells. We performed a meta-analysis of whole exome sequencing data from 403 patients with eight subtypes of T-cell non-Hodgkin's lymphoma to identify mutational signatures and associated recurrent gene mutations. Signature 1, indicative of age-related deamination, was prevalent across all T-cell lymphomas, reflecting the derivation of these malignancies from memory T-cells. Adult T-cell leukemia-lymphoma was specifically associated with signature 17, which was found to correlate with the IRF4 K59R mutation that is exclusive to Adult T-cell leukemia-lymphoma. Signature 7, implicating UV exposure was uniquely identified in cutaneous T-cell lymphoma (CTCL), contributing 52% of the mutational burden in mycosis fungoides and 23% in Sezary syndrome. Importantly this UV signature was observed in CD4 + T-cells isolated from the blood of Sezary syndrome patients suggesting extensive re-circulation of these T-cells through skin and blood. Analysis of non-Hodgkin's T-cell lymphoma cases submitted to the national 100,000 WGS project confirmed that signature 7 was only identified in CTCL strongly implicating UV radiation in the pathogenesis of cutaneous T-cell lymphoma.

Whole-Exome Profiling of NSCLC Among African Americans

INTRODUCTION

Lung cancer incidence is higher among African Americans (AAs) compared with European Americans (EAs) in the United States, especially among men. Although significant progress has been made profiling the genomic makeup of lung cancer in EAs, AAs continue to be underrepresented. Our objective was to chart the genome-wide landscape of somatic mutations in lung cancer tumors from AAs.

METHODS

In this study, we used the whole-exome sequencing of 82 tumor and noninvolved tissue pairs from AAs. Patients were selected from an ongoing case-control study conducted by the National Cancer Institute and the University of Maryland.

RESULTS

Among all samples, we identified 178 significantly mutated genes (p < 0.05), five of which passed the threshold for false discovery rate (p < 0.1). In lung adenocarcinoma (LUAD) tumors, mutation rates in STK11 (p = 0.05) and RB1 (p = 0.008) were significantly higher in AA LUAD tumors (25% and 13%, respectively) compared with The Cancer Genome Atlas EA samples (14% and 4%, respectively). In squamous cell carcinomas, mutation rates in STK11 (p = 0.002) were significantly higher among AA (8%) than EA tumors from The Cancer Genome Atlas (1%). Integrated somatic mutation data with CIBERSORT (Cell-type Identification By Estimating Relative Subsets Of RNA Transcripts) data analysis revealed LUAD tumors from AAs carrying STK11 mutations have decreased interferon signaling.

CONCLUSIONS

Although a considerable degree of the somatic mutation landscape is shared between EAs and AAs, discrete differences in mutation frequency in potentially important oncogenes and tumor suppressors exist. A better understanding of the molecular basis of lung cancer in AA patients and leveraging this information to guide clinical interventions may help reduce disparities.

Molecular epidemiology and diagnostics of KRAS mutations in human cancer

RAS mutation is the most frequent oncogenic alteration in human cancers. KRAS is the most frequently mutated followed by NRAS. The emblematic KRAS mutant cancers are pancreatic, colorectal, lung adenocarcinomas and urogenital cancers. KRAS mutation frequencies are relatively stable worldwide in various cancer types with the one exception of lung adenocarcinoma. The frequencies of KRAS variant alleles appears cancer type specific, reflecting the various carcinogenic processes. In addition to point mutation KRAS, allelic imbalances are also frequent in human cancers leading to the predominance of a mutant allele. KRAS mutant cancers are characterized by typical, cancer-type-specific co-occurring mutations and distinct gene expression signatures. The heterogeneity of KRAS mutant primary cancers is significant, affecting the variant allele frequency, which could lead to unpredictable branching development in metastases. Selection of minute mutant subclones in the primary tumors or metastases during target therapies can also occur frequently in lung or colorectal cancers leading to acquired resistance. Ultrahigh sensitivity techniques are now routinely available for diagnostic purposes, but the proper determination of mutant allele frequency of KRAS in the primary or metastatic tissues may have larger clinical significance.

Next-generation sequencing reveals heterogeneous genetic alterations in key signaling pathways of mismatch repair deficient colorectal carcinomas

Colorectal carcinoma (CRC) with deficient mismatch repair (dMMR) is an etiologically heterogeneous molecular entity. We investigated the genetic profile, focusing on key signaling pathways and molecular diversity of dMMR CRCs. In this study, next-generation sequencing was applied to 156 consecutive dMMR CRCs and 225 randomly selected proficient MMR (pMMR) CRCs diagnosed between July 2015 and December 2019 at Peking Union Medical College Hospital. Genetic alterations and MLH1 promoter hypermethylation (MLH1^me+) were analyzed. Among the most frequently mutated genes, RNF43, ARID1A, PIK3CA, ATM, and BRCA2 mutants were enriched in dMMR CRCs, whereas APC and TP53 mutations were enriched in pMMR CRCs. In dMMR group, RNF43, APC, ARID1A, and BRCA2 mutations were largely microsatellite instability events. WNT pathway was commonly altered regardless of MMR status. Compared to pMMR CRCs, dMMR CRCs had remarkably more prevalent PI3K, RTK-RAS, TGFβ, and DNA damage repair pathway alterations and more multiple mutations in WNT and PI3K pathways. Within dMMR tumors, mutual exclusivity occurred between CTNNB1 mutation and APC or RNF43 mutation, while coexistence existed between BRAF and RNF43 mutation, as well as RAS and APC mutation. MLH1^me+ dMMR CRCs had significantly more frequent RNF43 mutations but less frequent KRAS, APC, and CTNNB1 mutations comparing to MLH1-unmethylated dMMR CRCs. RNF43/BRAF comutations were detected in MLH1^me+ dMMR CRCs, whereas RAS/APC comutations were largely detected in Lynch syndrome-associated cases. RNF43 mutation was independently associated with MLH1^me+ rather than BRAF mutations. dMMR CRCs bearing receptor tyrosine kinase fusion demonstrated no additional RTK-RAS mutations, significantly fewer PI3K alterations and more TGFBR2 mutations than other dMMR tumors. Our study revealed that dMMR CRCs had distinctive gene mutation spectra and signaling pathway interaction patterns compared to proficient mismatch repair (pMMR) CRCs, and molecular heterogeneity was evident for these divergent oncogenic pathways. These findings justify the use of individualized therapy targeted to dMMR CRC subgroups.

Why Tumor Genetic Heterogeneity May Require Rethinking Cancer Genesis and Treatment

Tumor genetic heterogeneity, in which individual tumors contain both multiple variant cancer-associated and normal genes, has been widely reported, although its significance has yet to be fully understood. We propose a genetic heterogeneity-based selection-centric hypothesis in which genetic heterogeneity, caused by the temporary reduction of DNA repair efficiency, occurs very early in human development, resulting in a small minority of cells in normal tissues acquiring cancer-associated genes that remain dormant. Cancer develops when precancer cells are selected for by altered tissue microenvironments; similar scenarios occur with development of metastases and therapeutic resistance in established cancer. This suggests that a normal cell selection treatment approach based on preferentially selecting normal cells within tumors may be effective in treating cancer.

[Mutation signatures in head and neck squamous cell carcinoma : Pathogenesis and therapeutic potential]

BACKGROUND

The pathogenesis of head and neck squamous cell carcinoma (HNSCC) is a complex and multistage process which results from the interaction of exogenous and endogenous cellular processes. Each of these processes leaves a characteristic pattern of mutations on the tumor genome, a so-called mutational signature.

STATE OF THE ART

The subject of current studies is to decipher specific signatures of mutational processes operating during HNSCC pathogenesis and to address their prognostic value. Computational analysis of genomic sequencing data by The Cancer Genome Atlas (TCGA) revealed mutational signatures 1, 2, 4, 5, 7, and 13 as the main players in HNSCC pathogenesis. Signature 16 was first discovered in human papillomavirus (HPV)-negative oral and oropharyngeal tumors. In many studies, an association of signature 16 with alcohol and tobacco consumption as well as with an unfavorable prognosis was described.

Copper Complexes as Anticancer Agents Targeting Topoisomerases I and II

Organometallics, such as copper compounds, are cancer chemotherapeutics used alone or in combination with other drugs. One small group of copper complexes exerts an effective inhibitory action on topoisomerases, which participate in the regulation of DNA topology. Copper complexes inhibitors of topoisomerases 1 and 2 work by different molecular mechanisms, analyzed herein. They allow genesis of DNA breaks after the formation of a ternary complex, or act in a catalytic mode, often display DNA intercalative properties and ROS production, and sometimes display dual effects. These amplified actions have repercussions on the cell cycle checkpoints and death effectors. Copper complexes of topoisomerase inhibitors are analyzed in a broader synthetic view and in the context of cancer cell mutations. Finally, new emerging treatment aspects are depicted to encourage the expansion of this family of highly active anticancer drugs and to expend their use in clinical trials and future cancer therapy.

Evolutionary dynamics of neoantigens in growing tumors

Cancers accumulate mutations that lead to neoantigens, novel peptides that elicit an immune response, and consequently undergo evolutionary selection. Here we establish how negative selection shapes the clonality of neoantigens in a growing cancer by constructing a mathematical model of neoantigen evolution. The model predicts that, without immune escape, tumor neoantigens are either clonal or at low frequency; hypermutated tumors can only establish after the evolution of immune escape. Moreover, the site frequency spectrum of somatic variants under negative selection appears more neutral as the strength of negative selection increases, which is consistent with classical neutral theory. These predictions are corroborated by the analysis of neoantigen frequencies and immune escape in exome and RNA sequencing data from 879 colon, stomach and endometrial cancers.

Identification of new driver and passenger mutations within APOBEC-induced hotspot mutations in bladder cancer

BACKGROUND

APOBEC-driven mutagenesis and functional positive selection of mutated genes may synergistically drive the higher frequency of some hotspot driver mutations compared to other mutations within the same gene, as we reported for FGFR3 S249C. Only a few APOBEC-associated driver hotspot mutations have been identified in bladder cancer (BCa). Here, we systematically looked for and characterised APOBEC-associated hotspots in BCa.

METHODS

We analysed 602 published exome-sequenced BCas, for part of which gene expression data were also available. APOBEC-associated hotspots were identified by motif-mapping, mutation signature fitting and APOBEC-mediated mutagenesis comparison. Joint analysis of DNA hairpin stability and gene expression was performed to predict driver or passenger hotspots. Aryl hydrocarbon receptor (AhR) activity was calculated based on its target genes expression. Effects of AhR knockout/inhibition on BCa cell viability were analysed.

RESULTS

We established a panel of 44 APOBEC-associated hotspot mutations in BCa, which accounted for about half of the hotspot mutations. Fourteen of them overlapped with the hotspots found in other cancer types with high APOBEC activity. They mostly occurred in the DNA lagging-strand templates and the loop of DNA hairpins. APOBEC-associated hotspots presented systematically a higher prevalence than the other mutations within each APOBEC-target gene, independently of their functional impact. A combined analysis of DNA loop stability and gene expression allowed to distinguish known passenger from known driver hotspot mutations in BCa, including loss-of-function mutations affecting tumour suppressor genes, and to predict new candidate drivers, such as AHR Q383H. We further characterised AHR Q383H as an activating driver mutation associated with high AhR activity in luminal tumours. High AhR activity was also found in tumours presenting amplifications of AHR and its co-receptor ARNT. We finally showed that BCa cells presenting those different genetic alterations were sensitive to AhR inhibition.

CONCLUSIONS

Our study identified novel potential drivers within APOBEC-associated hotspot mutations in BCa reinforcing the importance of APOBEC mutagenesis in BCa. It could allow a better understanding of BCa biology and aetiology and have clinical implications such as AhR as a potential therapeutic target. Our results also challenge the dogma that all hotspot mutations are drivers and mostly gain-of-function mutations affecting oncogenes.

Characteristics of mutational signatures of unknown etiology

Although not all somatic mutations are cancer drivers, their mutational signatures, i.e. the patterns of genomic alterations at a genome-wide scale, provide insights into past exposure to mutagens, DNA damage and repair processes. Computational deconvolution of somatic mutation patterns and expert curation pan-cancer studies have identified a number of mutational signatures associated with point mutations, dinucleotide substitutions, insertions and deletions, and rearrangements, and have established etiologies for a subset of these signatures. However, the mechanisms underlying nearly one-third of all mutational signatures are not yet understood. The signatures with established etiology and those with hitherto unknown origin appear to have some differences in strand bias, GC content and nucleotide context diversity. It is possible that some of the hitherto ‘unknown’ signatures predominantly occur outside gene regions. While nucleotide contexts might be adequate to establish etiologies of some mutational signatures, in other cases additional features, such as broader (epi)genomic contexts, including chromatin, replication timing, processivity and local mutational patterns, may help fully understand the underlying DNA damage and repair processes. Nonetheless, remarkable progress in characterization of mutational signatures has provided fundamental insights into the biology of cancer, informed disease etiology and opened up new opportunities for cancer prevention, risk management, and therapeutic decision making.

Somatic selection distinguishes oncogenes and tumor suppressor genes

Motivation

Functions of cancer driver genes vary substantially across tissues and organs. Distinguishing passenger genes, oncogenes (OGs) and tumor-suppressor genes (TSGs) for each cancer type is critical for understanding tumor biology and identifying clinically actionable targets. Although many computational tools are available to predict putative cancer driver genes, resources for context-aware classifications of OGs and TSGs are limited.

Results

We show that the direction and magnitude of somatic selection of protein-coding mutations are significantly different for passenger genes, OGs and TSGs. Based on these patterns, we develop a new method (genes under selection in tumors) to discover OGs and TSGs in a cancer-type specific manner. Genes under selection in tumors shows a high accuracy (92%) when evaluated via strict cross-validations. Its application to 10 172 tumor exomes found known and novel cancer drivers with high tissue-specificities. In 11 out of 13 OGs shared among multiple cancer types, we found functional domains selectively engaged in different cancers, suggesting differences in disease mechanisms.

Availability and implementation

An R implementation of the GUST algorithm is available at https://github.com/liliulab/gust. A database with pre-computed results is available at https://liliulab.shinyapps.io/gust.

Supplementary information

Supplementary data are available at Bioinformatics online.

Can smoking duration alone replace pack-years to predict the risk of smoking-related oncogenic mutations in non-small cell lung cancer? A cross-sectional study in Japan

OBJECTIVE

To investigate whether smoking duration alone can replace pack-years to predict the risk of oncogenic mutations in non-small cell lung cancer (NSCLC).

DESIGN

A cross-sectional study using the baseline dataset from the Japan Molecular Epidemiology for Lung Cancer Study.

SETTING

Forty-three medical institutions nationwide in Japan.

PARTICIPANTS

From July 2012 to December 2013, 957 patients with newly diagnosed stage I-IIIB NSCLC who underwent surgery were enrolled, and molecular analyses were performed on 876 samples (from 441 ever-smokers and 435 never-smokers).

MAIN OUTCOMES MEASURED

We calculated the area under the receiver operating characteristic curve (AUC) values using logistic regression to compare between the predictive values of smoking duration and pack-years for mutational frequencies in the v-Ki-ras2 Kirsten rat sarcoma (KRAS), tumour suppressor p53 (TP53), and epidermal growth factor receptor (EGFR) genes and for cytosine-to-adenine base substitution (C>A).

RESULTS

For predicting KRAS mutations, the AUC values for smoking duration and pack-years were 0.746 (95% CI 0.682 to 0.800) and 0.759 (95% CI 0.700 to 0.810), respectively (p=0.058). For predicting KRAS mutations in smokers, the AUC values for smoking duration and pack-years were 0.772 (95% CI 0.697 to 0.833) and 0.787 (95% CI 0.714 to 0.845), respectively (p=0.036). There were no significant differences between the AUC values for smoking duration and pack-years in terms of predicting TP53 and EGFR mutations and C>A. Pack-years was a significantly better predictor of KRAS mutations than smoking duration.

CONCLUSION

Smoking duration was not significantly different from pack-years in predicting the likelihood of smoking-related gene mutations. Given the recall bias in obtaining smoking information, smoking duration alone should be considered for further investigation as a simpler alternative to pack-years.