Mutational signatures: the patterns of somatic mutations hidden in cancer genomes

Multi-regional sequencing reveals the genetic and immune heterogeneity of non-cancerous tissues in gastric cancer

Gastric cancer (GC) is one of the most heterogeneous tumors. However, research on normal tissue adjacent to the tumor (NAT) is very limited. We performed multi-regional omics sequencing on 150 samples to assess the genetic basis and immune microenvironment in NAT and matched primary tumor or lymph node metastases. NATs demonstrated different mutated genes compared with GC, and NAT genomes underwent independent evolution with low variant allele frequency. Mutation profiles were predominated by aging and smoking-associated signatures in NAT instead of signatures associated with genetic instability. Although the immune microenvironment within NATs shows substantial intra-patient heterogeneity, the proportion of shared TCR clones among NATs is five times higher than that of tumor regions. These findings support the notion that subclonal expansion is not pronounced in NATs. We also demonstrated remarkable intra-patient heterogeneity of GCs and revealed heterogeneity of focal amplification of CD274 (encoding PD-L1) that leads to differential expression. Finally, we identified that monoclonal seeding is predominant in GC, which is followed by metastasis-to-metastasis dissemination in individual lymph nodes. These results provide novel insights into GC carcinogenesis. © 2024 The Pathological Society of Great Britain and Ireland.

Topography of mutational signatures in non-small cell lung cancer: emerging concepts, clinical applications, and limitations

The genome of a cell is continuously battered by a plethora of exogenous and endogenous processes that can lead to damaged DNA. Repair mechanisms correct this damage most of the time, but failure to do so leaves mutations. Mutations do not occur in random manner, but rather typically follow a more or less specific pattern due to known or imputed mutational processes. Mutational signature analysis is the process by which the predominant mutational process can be inferred for a cancer and can be used in several contexts to study both the genesis of cancer and its response to therapy. Recent pan-cancer genomic efforts such as "The Cancer Genome Atlas" have identified numerous mutational signatures that can be categorized into single base substitutions, doublet base substitutions, or small insertions/deletions. Understanding these mutational signatures as they occur in non-small lung cancer could improve efforts at prevention, predict treatment response to personalized treatments, and guide the development of therapies targeting tumor evolution. For non-small cell lung cancer, several mutational signatures have been identified that correlate with exposures such as tobacco smoking and radon and can also reflect endogenous processes such as aging, APOBEC activity, and loss of mismatch repair. Herein, we provide an overview of the current knowledge of mutational signatures in non-small lung cancer.

Genomic Mosaicism of the Brain: Origin, Impact, and Utility

Genomic mosaicism describes the phenomenon where some but not all cells within a tissue harbor unique genetic mutations. Traditionally, research focused on the impact of genomic mosaicism on clinical phenotype-motivated by its involvement in cancers and overgrowth syndromes. More recently, we increasingly shifted towards the plethora of neutral mosaic variants that can act as recorders of cellular lineage and environmental exposures. Here, we summarize the current state of the field of genomic mosaicism research with a special emphasis on our current understanding of this phenomenon in brain development and homeostasis. Although the field of genomic mosaicism has a rich history, technological advances in the last decade have changed our approaches and greatly improved our knowledge. We will provide current definitions and an overview of contemporary detection approaches for genomic mosaicism. Finally, we will discuss the impact and utility of genomic mosaicism.

Mutations in cancer-relevant genes are ubiquitous in histologically normal endometrial tissue

OBJECTIVE

Endometrial cancer (EndoCA) is the most common gynecologic cancer and incidence and mortality rate continue to increase. Despite well-characterized knowledge of EndoCA-defining mutations, no effective diagnostic or screening tests exist. To lay the foundation for testing development, our study focused on defining the prevalence of somatic mutations present in non-cancerous uterine tissue.

METHODS

We obtained ≥8 uterine samplings, including separate endometrial and myometrial layers, from each of 22 women undergoing hysterectomy for non-cancer conditions. We ultra-deep sequenced (>2000× coverage) samples using a 125 cancer-relevant gene panel.

RESULTS

All women harbored complex mutation patterns. In total, 308 somatic mutations were identified with mutant allele frequencies ranging up to 96.0%. These encompassed 56 unique mutations from 24 genes. The majority of samples possessed predicted functional cancer mutations but curiously no growth advantage over non-functional mutations was detected. Functional mutations were enriched with increasing patient age (p = 0.045) and BMI (p = 0.0007) and in endometrial versus myometrial layers (68% vs 39%, p = 0.0002). Finally, while the somatic mutation landscape shared similar mutation prevalence in key TCGA-defined EndoCA genes, notably PIK3CA, significant differences were identified, including NOTCH1 (77% vs 10%), PTEN (9% vs 61%), TP53 (0% vs 37%) and CTNNB1 (0% vs 26%).

CONCLUSIONS

An important caveat for future liquid biopsy/DNA-based cancer diagnostics is the repertoire of shared and distinct mutation profiles between histologically unremarkable and EndoCA tissues. The lack of selection pressure between functional and non-functional mutations in histologically unremarkable uterine tissue may offer a glimpse into an unrecognized EndoCA protective mechanism.

Mutational signatures of colorectal cancers according to distinct computational workflows

Tumor mutational signatures have gained prominence in cancer research, yet the lack of standardized methods hinders reproducibility and robustness. Leveraging colorectal cancer (CRC) as a model, we explored the influence of computational parameters on mutational signature analyses across 230 CRC cell lines and 152 CRC patients. Results were validated in three independent datasets: 483 endometrial cancer patients stratified by mismatch repair (MMR) status, 35 lung cancer patients by smoking status and 12 patient-derived organoids (PDOs) annotated for colibactin exposure. Assessing various bioinformatic tools, reference datasets and input data sizes including whole genome sequencing, whole exome sequencing and a pan-cancer gene panel, we demonstrated significant variability in the results. We report that the use of distinct algorithms and references led to statistically different results, highlighting how arbitrary choices may induce variability in the mutational signature contributions. Furthermore, we found a differential contribution of mutational signatures between coding and intergenic regions and defined the minimum number of somatic variants required for reliable mutational signature assignment. To facilitate the identification of the most suitable workflows, we developed Comparative Mutational Signature analysis on Coding and Extragenic Regions (CoMSCER), a bioinformatic tool which allows researchers to easily perform comparative mutational signature analysis by coupling the results from several tools and public reference datasets and to assess mutational signature contributions in coding and non-coding genomic regions. In conclusion, our study provides a comparative framework to elucidate the impact of distinct computational workflows on mutational signatures.

CDK4/6 Inhibition - Therapy Sequences and the Quest to Find the Best Biomarkers - an Overview of Current Programs

In recent years, new targeted therapies have been developed to treat patients with hormone receptor-positive (HR+)/human epidermal growth factor receptor 2-negative (HER2-) breast cancer. Some of these therapies have not just become the new therapy standard but also led to significantly longer overall survival rates. The cyclin-dependent kinase 4 and 6 inhibitors (CDK4/6i) have become the therapeutic standard for first-line therapy. Around 70 - 80% of patients are treated with a CDK4/6i. In recent years, a number of biomarkers associated with progression, clonal selection or evolution have been reported for CDK4/6i and their endocrine combination partners. Understanding the mechanisms behind treatment efficacy and resistance is important. A better understanding could contribute to planning the most effective therapeutic sequences and utilizing basic molecular information to overcome endocrine resistance. One study with large numbers of patients which aims to elucidate these mechanisms is the Comprehensive Analysis of sPatial, TempORal and molecular patterns of ribociclib efficacy and resistance in advanced Breast Cancer patients (CAPTOR BC) trial. This overview summarizes the latest clinical research on resistance to endocrine therapies, focusing on CDK4/6 inhibitors and discussing current study concepts.

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

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

Epidemiologic Factors in Relation to Colorectal Cancer Risk and Survival by Genotoxic Colibactin Mutational Signature

BACKGROUND

The genotoxin colibactin causes a tumor single-base substitution (SBS) mutational signature, SBS88. It is unknown whether epidemiologic factors' association with colorectal cancer risk and survival differs by SBS88.

METHODS

Within the Genetic Epidemiology of Colorectal Cancer Consortium and Colon Cancer Family Registry, we measured SBS88 in 4,308 microsatellite stable/microsatellite instability low tumors. Associations of epidemiologic factors with colorectal cancer risk by SBS88 were assessed using multinomial regression (N = 4,308 cases, 14,192 controls; cohort-only cases N = 1,911), and with colorectal cancer-specific survival using Cox proportional hazards regression (N = 3,465 cases).

RESULTS

392 (9%) tumors were SBS88 positive. Among all cases, the highest quartile of fruit intake was associated with lower risk of SBS88-positive colorectal cancer than SBS88-negative colorectal cancer [odds ratio (OR) = 0.53, 95% confidence interval (CI) 0.37-0.76; OR = 0.75, 95% CI 0.66-0.85, respectively, Pheterogeneity = 0.047]. Among cohort studies, associations of body mass index (BMI), alcohol, and fruit intake with colorectal cancer risk differed by SBS88. BMI ≥30 kg/m2 was associated with worse colorectal cancer-specific survival among those SBS88-positive [hazard ratio (HR) = 3.40, 95% CI 1.47-7.84], but not among those SBS88-negative (HR = 0.97, 95% CI 0.78-1.21, Pheterogeneity = 0.066).

CONCLUSIONS

Most epidemiologic factors did not differ by SBS88 for colorectal cancer risk or survival. Higher BMI may be associated with worse colorectal cancer-specific survival among those SBS88-positive; however, validation is needed in samples with whole-genome or whole-exome sequencing available.

IMPACT

This study highlights the importance of identification of tumor phenotypes related to colorectal cancer and understanding potential heterogeneity for risk and survival.

The spectrum of TP53 mutations in Rwandan patients with gastric cancer

BACKGROUND

Gastric cancer is the sixth most frequently diagnosed cancer and third in causing cancer-related death globally. The most frequently mutated gene in human cancers is TP53, which plays a pivotal role in cancer initiation and progression. In Africa, particularly in Rwanda, data on TP53 mutations are lacking. Therefore, this study intended to obtain TP53 mutation status in Rwandan patients with gastric cancer.

RESULTS

Formalin-fixed paraffin-embedded tissue blocks of 95 Rwandan patients with histopathologically proven gastric carcinoma were obtained from the University Teaching Hospital of Kigali. After DNA extraction, all coding regions of the TP53 gene and the exon-intron boundary region of TP53 were sequenced using the Sanger sequencing. Mutated TP53 were observed in 24 (25.3%) of the 95 cases, and a total of 29 mutations were identified. These TP53 mutations were distributed between exon 4 and 8 and most of them were missense mutations (19/29; 65.5%). Immunohistochemical analysis for TP53 revealed that most of the TP53 missense mutations were associated with TP53 protein accumulation. Among the 29 mutations, one was novel (c.459_477delCGGCACCCGCGTCCGCGCC). This 19-bp deletion mutation in exon 5 caused the production of truncated TP53 protein (p.G154Wfs*10). Regarding the spectrum of TP53 mutations, G:C > A:T at CpG sites was the most prevalent (10/29; 34.5%) and G:C > T:A was the second most prevalent (7/29; 24.1%). Interestingly, when the mutation spectrum of TP53 was compared to three previous TP53 mutational studies on non-Rwandan patients with gastric cancer, G:C > T:A mutations were significantly more frequent in this study than in our previous study (p = 0.013), the TCGA database (p = 0.017), and a previous study on patients from Hong Kong (p = 0.006). Even after correcting for false discovery, statistical significance was observed.

CONCLUSIONS

Our results suggested that TP53 G:C > T:A transversion mutation in Rwandan patients with gastric cancer is more frequent than in non-Rwandan patients with gastric cancer, indicating at an alternative etiological and carcinogenic progression of gastric cancer in Rwanda.

Latent evolutionary signatures: a general framework for analysing music and cultural evolution

Cultural processes of change bear many resemblances to biological evolution. The underlying units of non-biological evolution have, however, remained elusive, especially in the domain of music. Here, we introduce a general framework to jointly identify underlying units and their associated evolutionary processes. We model musical styles and principles of organization in dimensions such as harmony and form as following an evolutionary process. Furthermore, we propose that such processes can be identified by extracting latent evolutionary signatures from musical corpora, analogously to identifying mutational signatures in genomics. These signatures provide a latent embedding for each song or musical piece. We develop a deep generative architecture for our model, which can be viewed as a type of variational autoencoder with an evolutionary prior constraining the latent space; specifically, the embeddings for each song are tied together via an energy-based prior, which encourages songs close in evolutionary space to share similar representations. As illustration, we analyse songs from the McGill Billboard dataset. We find frequent chord transitions and formal repetition schemes and identify latent evolutionary signatures related to these features. Finally, we show that the latent evolutionary representations learned by our model outperform non-evolutionary representations in such tasks as period and genre prediction.

Evaluating topography of mutational signatures with SigProfilerTopography

The mutations found in a cancer genome are shaped by diverse processes, each displaying a characteristic mutational signature that may be influenced by the genome's architecture. While prior analyses have evaluated the effect of topographical genomic features on mutational signatures, there has been no computational tool that can comprehensively examine this interplay. Here, we present SigProfilerTopography, a Python package that allows evaluating the effect of chromatin organization, histone modifications, transcription factor binding, DNA replication, and DNA transcription on the activities of different mutational processes. SigProfilerTopography elucidates the unique topographical characteristics of mutational signatures, unveiling their underlying biological and molecular mechanisms.

Distinct patterns of proteostasis network gene expression are associated with different prognoses in melanoma patients

The proteostasis network (PN) is a collection of protein folding and degradation pathways that spans cellular compartments and acts to preserve the integrity of the proteome. The differential expression of PN genes is a hallmark of many cancers, and the inhibition of protein quality control factors is an effective way to slow cancer cell growth. However, little is known about how the expression of PN genes differs between patients and how this impacts survival outcomes. To address this, we applied unbiased hierarchical clustering to gene expression data obtained from primary and metastatic cutaneous melanoma (CM) samples and found that two distinct groups of individuals emerge across each sample type. These patient groups are distinguished by the differential expression of genes encoding ATP-dependent and ATP-independent chaperones, and proteasomal subunits. Differences in PN gene expression were associated with increased levels of the transcription factors, MEF2A, SP4, ZFX, CREB1 and ATF2, as well as markedly different survival outcomes. However, surprisingly, similar PN alterations in primary and metastatic samples were associated with discordant survival outcomes in patients. Our findings reveal that the expression of PN genes demarcates CM patients and highlights several new proteostasis sub-networks that could be targeted for more effective suppression of CM within specific individuals.

Exploring the basis of heterogeneity of cancer aggressiveness among the mutated POLE variants

Germline pathogenic variants in the exonuclease domain of the replicative DNA polymerase Pol ε encoded by the POLE gene, predispose essentially to colorectal and endometrial tumors by inducing an ultramutator phenotype. It is still unclear whether all the POLE alterations influence similar strength tumorigenesis, immune microenvironment, and treatment response. In this review, we summarize the current understanding of the mechanisms and consequences of POLE mutations in human malignancies; we highlight the heterogeneity of mutation rate and cancer aggressiveness among POLE variants, propose some mechanistic basis underlining such heterogeneity, and discuss novel considerations for the choice and efficacy of therapies of POLE tumors.

Mutational signature dynamics indicate SARS-CoV-2's evolutionary capacity is driven by host antiviral molecules

The COVID-19 pandemic has been characterised by sequential variant-specific waves shaped by viral, individual human and population factors. SARS-CoV-2 variants are defined by their unique combinations of mutations and there has been a clear adaptation to more efficient human infection since the emergence of this new human coronavirus in late 2019. Here, we use machine learning models to identify shared signatures, i.e., common underlying mutational processes and link these to the subset of mutations that define the variants of concern (VOCs). First, we examined the global SARS-CoV-2 genomes and associated metadata to determine how viral properties and public health measures have influenced the magnitude of waves, as measured by the number of infection cases, in different geographic locations using regression models. This analysis showed that, as expected, both public health measures and virus properties were associated with the waves of regional SARS-CoV-2 reported infection numbers and this impact varies geographically. We attribute this to intrinsic differences such as vaccine coverage, testing and sequencing capacity and the effectiveness of government stringency. To assess underlying evolutionary change, we used non-negative matrix factorisation and observed three distinct mutational signatures, unique in their substitution patterns and exposures from the SARS-CoV-2 genomes. Signatures 1, 2 and 3 were biased to C→T, T→C/A→G and G→T point mutations. We hypothesise assignments of these mutational signatures to the host antiviral molecules APOBEC, ADAR and ROS respectively. We observe a shift amidst the pandemic in relative mutational signature activity from predominantly Signature 1 changes to an increasingly high proportion of changes consistent with Signature 2. This could represent changes in how the virus and the host immune response interact and indicates how SARS-CoV-2 may continue to generate variation in the future. Linkage of the detected mutational signatures to the VOC-defining amino acids substitutions indicates the majority of SARS-CoV-2's evolutionary capacity is likely to be associated with the action of host antiviral molecules rather than virus replication errors.

Mutational signatures and their association with survival and gene expression in urological carcinomas

Different sources of mutagenesis cause consistently identifiable patterns of mutations and mutational signatures that mirror the various carcinogenetic processes. We used publicly available data from the Cancer Genome Atlas to evaluate the associations between the activity of the mutational signatures and various survival endpoints in six types of urological cancers after adjusting for established prognostic factors. The predictive power of the signatures was evaluated with dynamic area under curve models. In addition, links between mutational signature activities and differences in gene expression patterns were analysed. APOBEC-related signature SBS2 was associated with improved overall survival (OS) and disease-specific survival (DSS) in bladder carcinomas in the multivariate analysis, while clock-like signature SBS1 predicted shortened DSS and progression-free interval (PFI) in clear cell renal cell carcinomas (ccRCC). In papillary renal cell carcinomas (pRCC), SBS45 was a predictor of improved outcomes, and APOBEC-related SBS13 was a predictor of worse outcomes. Gene expression analyses revealed various enriched pathways between the low- and high-signature groups. Interestingly, in both the ccRCC and pRCC cohorts, the genes of several members of the melanoma antigen (MAGE) family were highly upregulated in the signatures, which predicted poor outcomes, and downregulated in signatures, which were associated with improved survival. To summarize, SBS signatures provide substantial prognostic value compared with just the traditional prognostic factors in certain cancer types. APOBEC-related SBS2 and SBS13 seem to provide robust prognostic information for particular urological cancers, maybe driven by the expression of specific groups of genes, including the MAGE gene family.

A systematic pan-cancer analysis identifies TRIM28 as an immunological and prognostic predictor and involved in immunotherapy resistance

Tripartite motif-containing protein 28 (TRIM28), as a transcriptional cofactor, has pleiotropic biological effects, such as silencing genes, promoting cellular proliferation and differentiation, and facilitating DNA repair. It is reported that TRIM28 is also correlated with immune infiltration in liver cancer that highlights an unnoticed function of TRIM28 in immune system. However, the prognostic and immunotherapeutic role of TRIM28 in human cancer has not been elucidated. In this study, we conducted a systematic pan-cancer analysis and partial experimental validation of TRIM28 as an immunological and prognostic predictor and its involvement in immunotherapy resistance. We found that TRIM28 expression was higher in various tumor tissues than in normal tissues. Higher TRIM28 expression was associated with poorer prognosis in multiple cancers. The expression of TRIM28 was positively correlated with the presence of T cells, macrophages and neutrophils, and TRIM28 also promoted the infiltration of a series of immune cell. Moreover, TRIM28 affected a wide range of cancer-related scores, and the abnormal expression of TRIM28 was also involved in tumor mutational burden, drug sensitivity, and microsatellite instability in cancer. The results suggest that TRIM28 is a potentially valuable immune response indicator and a molecular biomarker for predicting the prognosis of cancer patients.

Multiomics and machine-learning identify novel transcriptional and mutational signatures in amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis is a fatal and incurable neurodegenerative disease that mainly affects the neurons of the motor system. Despite the increasing understanding of its genetic components, their biological meanings are still poorly understood. Indeed, it is still not clear to which extent the pathological features associated with amyotrophic lateral sclerosis are commonly shared by the different genes causally linked to this disorder. To address this point, we combined multiomics analysis covering the transcriptional, epigenetic and mutational aspects of heterogenous human induced pluripotent stem cell-derived C9orf72-, TARDBP-, SOD1- and FUS-mutant motor neurons as well as datasets from patients' biopsies. We identified a common signature, converging towards increased stress and synaptic abnormalities, which reflects a unifying transcriptional program in amyotrophic lateral sclerosis despite the specific profiles due to the underlying pathogenic gene. In addition, whole genome bisulphite sequencing linked the altered gene expression observed in mutant cells to their methylation profile, highlighting deep epigenetic alterations as part of the abnormal transcriptional signatures linked to amyotrophic lateral sclerosis. We then applied multi-layer deep machine-learning to integrate publicly available blood and spinal cord transcriptomes and found a statistically significant correlation between their top predictor gene sets, which were significantly enriched in toll-like receptor signalling. Notably, the overrepresentation of this biological term also correlated with the transcriptional signature identified in mutant human induced pluripotent stem cell-derived motor neurons, highlighting novel insights into amyotrophic lateral sclerosis marker genes in a tissue-independent manner. Finally, using whole genome sequencing in combination with deep learning, we generated the first mutational signature for amyotrophic lateral sclerosis and defined a specific genomic profile for this disease, which is significantly correlated to ageing signatures, hinting at age as a major player in amyotrophic lateral sclerosis. This work describes innovative methodological approaches for the identification of disease signatures through the combination of multiomics analysis and provides novel knowledge on the pathological convergencies defining amyotrophic lateral sclerosis.

Cancer-inspired genomics mapper model for the generation of synthetic DNA sequences with desired genomics signatures

Genome data are crucial in modern medicine, offering significant potential for diagnosis and treatment. Thanks to technological advancements, many millions of healthy and diseased genomes have already been sequenced; however, obtaining the most suitable data for a specific study, and specifically for validation studies, remains challenging with respect to scale and access. Therefore, in silico genomics sequence generators have been proposed as a possible solution. However, the current generators produce inferior data using mostly shallow (stochastic) connections, detected with limited computational complexity in the training data. This means they do not take the appropriate biological relations and constraints, that originally caused the observed connections, into consideration. To address this issue, we propose cancer-inspired genomics mapper model (CGMM), that combines genetic algorithm (GA) and deep learning (DL) methods to tackle this challenge. CGMM mimics processes that generate genetic variations and mutations to transform readily available control genomes into genomes with the desired phenotypes. We demonstrate that CGMM can generate synthetic genomes of selected phenotypes such as ancestry and cancer that are indistinguishable from real genomes of such phenotypes, based on unsupervised clustering. Our results show that CGMM outperforms four current state-of-the-art genomics generators on two different tasks, suggesting that CGMM will be suitable for a wide range of purposes in genomic medicine, especially for much-needed validation studies.

New insights into the biology and development of lung cancer in never smokers-implications for early detection and treatment

Lung cancer is the leading cause of cancer deaths worldwide. Despite never smokers comprising between 10 and 25% of all cases, lung cancer in never smokers (LCNS) is relatively under characterized from an etiological and biological perspective. The application of multi-omics techniques on large patient cohorts has significantly advanced the current understanding of LCNS tumor biology. By synthesizing the findings of multi-omics studies on LCNS from a clinical perspective, we can directly translate knowledge regarding tumor biology into implications for patient care. Primarily focused on never smokers with lung adenocarcinoma, this review details the predominance of driver mutations, particularly in East Asian patients, as well as the frequency and importance of germline variants in LCNS. The mutational patterns present in LCNS tumors are thoroughly explored, highlighting the high abundance of the APOBEC signature. Moreover, this review recognizes the spectrum of immune profiles present in LCNS tumors and posits how it can be translated to treatment selection. The recurring and novel insights from multi-omics studies on LCNS tumor biology have a wide range of clinical implications. Risk factors such as exposure to outdoor air pollution, second hand smoke, and potentially diet have a genomic imprint in LCNS at varying degrees, and although they do not encompass all LCNS cases, they can be leveraged to stratify risk. Germline variants similarly contribute to a notable proportion of LCNS, which warrants detailed documentation of family history of lung cancer among never smokers and demonstrates value in developing testing for pathogenic variants in never smokers for early detection in the future. Molecular driver subtypes and specific co-mutations and mutational signatures have prognostic value in LCNS and can guide treatment selection. LCNS tumors with no known driver alterations tend to be stem-like and genes contributing to this state may serve as potential therapeutic targets. Overall, the comprehensive findings of multi-omics studies exert a wide influence on clinical management and future research directions in the realm of LCNS.

Advantages of the Combinatorial Molecular Targeted Therapy of Head and Neck Cancer-A Step before Anakoinosis-Based Personalized Treatment

The molecular initiators of Head and Heck Squamous Cell Carcinoma (HNSCC) are complex. Human Papillomavirus (HPV) infection is linked to an increasing number of HNSCC cases, but HPV-positive tumors generally have a good prognosis. External factors that promote the development of HPV-negative HNSCC include tobacco use, excessive alcohol consumption, and proinflammatory poor oral hygiene. On a molecular level, several events, including the well-known overexpression of epidermal growth factor receptors (EGFR) and related downstream signaling pathways, contribute to the development of HNSCC. Conventional chemotherapy is insufficient for many patients. Thus, molecular-based therapy for HNSCC offers patients a better chance at a cure. The first molecular target for therapy of HNSCC was EGFR, inhibited by monoclonal antibody cetuximab, but its use in monotherapy is insufficient and induces resistance. This article describes attempts at combinatorial molecular targeted therapy of HNSCC based on several molecular targets and exemplary drugs/drug candidates. The new concept of anakoinosis-based therapy, which means treatment that targets the intercellular and intracellular communication of cancer cells, is thought to be the way to improve the clinical outcome for HNSCC patients. The identification of a link between molecular targeted therapy and anakoinosis raises the potential for further progress in HPV-negative HNSCC therapy.

Copy number alteration is an independent prognostic biomarker in triple-negative breast cancer patients

BACKGROUND

Next-generation sequencing (NGS) has enabled comprehensive genomic profiling to identify gene alterations that play important roles in cancer biology. However, the clinical significance of these genomic alterations in triple-negative breast cancer (TNBC) patients has not yet been fully elucidated. The aim of this study was to clarify the clinical significance of genomic profiling data, including copy number alterations (CNA) and tumor mutation burden (TMB), in TNBC patients.

METHODS

A total of 47 patients with Stage I-III TNBC with genomic profiling of 435 known cancer genes by NGS were enrolled in this study. Disease-free survival (DFS) and overall survival (OS) were evaluated for their association to gene profiling data.

RESULTS

CNA-high patients showed significantly worse DFS and OS than CNA-low patients (p = 0.0009, p = 0.0041, respectively). TMB was not associated with DFS or OS in TNBC patients. Patients with TP53 alterations showed a tendency of worse DFS (p = 0.0953) and significantly worse OS (p = 0.0338) compared with patients without TP53 alterations. Multivariable analysis including CNA and other clinicopathological parameters revealed that CNA was an independent prognostic factor for DFS (p = 0.0104) and OS (p = 0.0306). Finally, multivariable analysis also revealed the combination of CNA-high and TP53 alterations is an independent prognostic factor for DFS (p = 0.0005) and OS (p = 0.0023).

CONCLUSIONS

We revealed that CNA, but not TMB, is significantly associated with DFS and OS in TNBC patients. The combination of CNA-high and TP53 alterations may be a promising biomarker that can inform beyond standard clinicopathologic factors to identify a subgroup of TNBC patients with significantly worse prognosis.

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'.

The French Cohort of DNA Repair-Deficient Xeroderma Pigmentosum Patients: Risk of Hematological Malignancies

BACKGROUND

Xeroderma pigmentosum (XP) is a rare genetic disorder characterized by a high incidence of skin cancers. These patients are deficient in nucleotide excision repair caused by mutations in one of the 7 XP genes.

METHODS

We diagnosed 181 XP patients using UV-induced DNA repair measurements and/or DNA sequencing from 1982 to 2022 in France.

RESULTS

As all XP patients, the French ones are very sensitive to UV exposure but since they are usually very well protected, they develop relatively few skin cancers. A majority of French XP patients originate from North Africa and bear a founder mutation on the XPC gene. The striking discovery is that these patients are at a very high risk to develop aggressive and lethal internal tumors such as hematological malignancies (more than a 100-fold risk compared to the general population for myelodysplasia/leukemia) with a median age of death of 25 years, and brain, gynecological, and thyroid tumors with even lower median ages of death. The high mutation rates found in XP-C internal tumors allow us to think that these XP patients could be successfully treated by immunotherapies. A full analysis of the molecular origins of these DNA repair-deficient tumors is discussed. Several explanations for this high predisposition risk are proposed.

CONCLUSIONS

As the age of the XP population is increasing due to better photo-protection, the risk of lethal internal tumors is a new Damocles sword that hangs over XP-C patients. This review of the French cohort is of particular importance for alerting physicians and families to the prevention and early detection of aggressive internal tumors in XP patients.

Distinct genomic features in a retrospective cohort of mucosal, acral, and vulvovaginal melanomas

BACKGROUND

Compared with sun-exposed melanomas, less is known regarding the pathogenesis of sun-protected melanomas. Sun-protected melanomas share many epidemiologic factors, but their genetic heterogeneity is not well studied.

OBJECTIVE

We investigated the genomic profile of acral, mucosal, and vulvovaginal melanomas. We hypothesize that mucosal melanomas, recognized for their uniquely aggressive clinical behavior, have distinct genomic features.

METHODS

We performed whole transcriptome messenger RNA and DNA (1711 genes) sequencing, messenger RNA expression profiling, tumor mutational burden, ultraviolet signature, and copy number variants analysis on 29 volar/digital acral, 7 mucosal, and 6 vulvovaginal melanomas.

RESULTS

There was significant genetic heterogeneity, particularly in acral melanomas, with 36% having BRAF alterations, whereas other melanomas had none (P = .0159). Nonzero ultraviolet signatures were more frequent in acral melanomas, suggesting greater ultraviolet involvement. Mucosal melanomas formed a distinct group with increased expression of cell cycle and proliferation genes. Various targetable aberrations were identified, such as AURKA and ERBB2, in mucosal and acral melanomas, respectively.

LIMITATIONS

The sample size was a small.

CONCLUSION

There is significant genetic heterogeneity among sun-protected melanomas. Mucosal melanomas have upregulation in cell cycle and proliferation genes, which may explain their aggressive behavior. Ultraviolet radiation plays some role in a subset of acral but not other melanomas.

Familial CCM Genes Might Not Be Main Drivers for Pathogenesis of Sporadic CCMs-Genetic Similarity between Cancers and Vascular Malformations

Cerebral cavernous malformations (CCMs) are abnormally dilated intracranial capillaries that form cerebrovascular lesions with a high risk of hemorrhagic stroke. Recently, several somatic "activating" gain-of-function (GOF) point mutations in PIK3CA (phosphatidylinositol-4, 5-bisphosphate 3-kinase catalytic subunit p110α) were discovered as a dominant mutation in the lesions of sporadic forms of cerebral cavernous malformation (sCCM), raising the possibility that CCMs, like other types of vascular malformations, fall in the PIK3CA-related overgrowth spectrum (PROS). However, this possibility has been challenged with different interpretations. In this review, we will continue our efforts to expound the phenomenon of the coexistence of gain-of-function (GOF) point mutations in the PIK3CA gene and loss-of-function (LOF) mutations in CCM genes in the CCM lesions of sCCM and try to delineate the relationship between mutagenic events with CCM lesions in a temporospatial manner. Since GOF PIK3CA point mutations have been well studied in reproductive cancers, especially breast cancer as a driver oncogene, we will perform a comparative meta-analysis for GOF PIK3CA point mutations in an attempt to demonstrate the genetic similarities shared by both cancers and vascular anomalies.

Deciphering gene contributions and etiologies of somatic mutational signatures of cancer

Somatic mutational signatures (MSs) identified by genome sequencing play important roles in exploring the cause and development of cancer. Thus far, many such signatures have been identified, and some of them do imply causes of cancer. However, a major bottleneck is that we do not know the potential meanings (i.e. carcinogenesis or biological functions) and contributing genes for most of them. Here, we presented a computational framework, Gene Somatic Genome Pattern (GSGP), which can decipher the molecular mechanisms of the MSs. More importantly, it is the first time that the GSGP is able to process MSs from ribonucleic acid (RNA) sequencing, which greatly extended the applications of both MS analysis and RNA sequencing (RNAseq). As a result, GSGP analyses match consistently with previous reports and identify the etiologies for a number of novel signatures. Notably, we applied GSGP to RNAseq data and revealed an RNA-derived MS involved in deficient deoxyribonucleic acid mismatch repair and microsatellite instability in colorectal cancer. Researchers can perform customized GSGP analysis using the web tools or scripts we provide.

Predicting Cancer Risk from Germline Whole-exome Sequencing Data Using a Novel Context-based Variant Aggregation Approach

Many studies have shown that the distributions of the genomic, nucleotide, and epigenetic contexts of somatic variants in tumors are informative of cancer etiology. Recently, a new direction of research has focused on extracting signals from the contexts of germline variants and evidence has emerged that patterns defined by these factors are associated with oncogenic pathways, histologic subtypes, and prognosis. It remains an open question whether aggregating germline variants using meta-features capturing their genomic, nucleotide, and epigenetic contexts can improve cancer risk prediction. This aggregation approach can potentially increase statistical power for detecting signals from rare variants, which have been hypothesized to be a major source of the missing heritability of cancer. Using germline whole-exome sequencing data from the UK Biobank, we developed risk models for 10 cancer types using known risk variants (cancer-associated SNPs and pathogenic variants in known cancer predisposition genes) as well as models that additionally include the meta-features. The meta-features did not improve the prediction accuracy of models based on known risk variants. It is possible that expanding the approach to whole-genome sequencing can lead to gains in prediction accuracy.

Significance

There is evidence that cancer is partly caused by rare genetic variants that have not yet been identified. We investigate this issue using novel statistical methods and data from the UK Biobank.

Update Breast Cancer 2022 Part 6 - Advanced-Stage Breast Cancer

Large-scale study programs on CDK4/6 inhibitors, targeted therapies, and antibody-drug conjugates launched in recent years have yielded results from current studies which are now being published in journals and presented at international conferences. In this context, new results are available from the major CDK4/6 inhibitor studies. Also, an increasing amount of data is being published from large-scale genomic studies on efficacy and resistance mechanisms in patients treated with CDK4/6 inhibitors. These results now form the basis for further research plans to investigate combination therapies and treatment sequencing. Based on the latest published results, sacituzumab govitecan is now available as a second antibody-drug conjugate; this brings an advantage in terms of overall survival for patients with hormone receptor-positive (HRpos)/HER2-negative (HER2neg) breast cancer. In this review article, we summarize the latest developments and place them in context according to the current status of research.

Concepts of association between cancer and ionising radiation: accounting for specific biological mechanisms

The probability that an observed cancer was caused by radiation exposure is usually estimated using cancer rates and risk models from radioepidemiological cohorts and is called assigned share (AS). This definition implicitly assumes that an ongoing carcinogenic process is unaffected by the studied radiation exposure. However, there is strong evidence that radiation can also accelerate an existing clonal development towards cancer. In this work, we define different association measures that an observed cancer was newly induced, accelerated, or retarded. The measures were quantified exemplarily by Monte Carlo simulations that track the development of individual cells. Three biologically based two-stage clonal expansion (TSCE) models were applied. In the first model, radiation initiates cancer development, while in the other two, radiation has a promoting effect, i.e. radiation accelerates the clonal expansion of pre-cancerous cells. The parameters of the TSCE models were derived from breast cancer data from the atomic bomb survivors of Hiroshima and Nagasaki. For exposure at age 30, all three models resulted in similar estimates of AS at age 60. For the initiation model, estimates of association were nearly identical to AS. However, for the promotion models, the cancerous clonal development was frequently accelerated towards younger ages, resulting in associations substantially higher than AS. This work shows that the association between a given cancer and exposure in an affected person depends on the underlying biological mechanism and can be substantially larger than the AS derived from classic radioepidemiology.

Analysis of KRAS Mutations in Gastrointestinal Tract Adenocarcinomas Reveals Site-Specific Mutational Signatures

Adenocarcinomas of the luminal gastrointestinal tract and pancreatobiliary system often show histologic and immunohistochemical overlap, making delineation of the primary site in a metastatic setting difficult. Previous studies have shown that site-specific missense mutations in the oncogene KRAS could be used in conjunction with immunohistochemistry to differentiate metastatic pancreatic adenocarcinoma from primary lung adenocarcinoma. In this study, we assessed the patterning of KRAS mutations across sites in the gastrointestinal and pancreatobiliary system. By integrating sequencing data from 44 separate studies, we assessed 2523 KRAS mutations in 7382 distinct cases of adenocarcinoma, including those from the esophagus, stomach, ampulla, biliary system, pancreas, and colon. We found that gastrointestinal adenocarcinomas demonstrate a marked regional variation in the frequency of KRAS mutations, with the most frequent KRAS mutation observed in pancreatic adenocarcinoma (up to 94.9%), whereas the frequency is much lower in adenocarcinomas from the esophagus and stomach (5.4% and 8.7%, respectively). Intriguingly, the pattern of missense mutations showed site specificity as well, with c.35G>T (p.G12V) and c.34G>C (p.G12R) mutations enriched in pancreatic primaries and codon 13 and non-codon 12/13 alterations enriched in gastric primaries (specificity of 98.9% and 93.2%, respectively, with a negative predictive value of 93.6% and 92.93% against pancreatic adenocarcinoma). Furthermore, we found that esophageal and gastric adenocarcinomas show an enrichment in transitional mutations, whereas other sites showed an equal distribution. Importantly, the examination of a validation cohort from our own institution revealed similar trends. These findings indicate that, in addition to providing therapeutic and diagnostic information, KRAS mutational analysis may also prove useful in delineating the site of origin in gastrointestinal adenocarcinomas that share morphologic and immunohistochemical overlap. Moreover, transitional mutations are more frequent in esophageal and gastric adenocarcinomas, reiterating the role of chronic inflammation in the pathogenesis of foregut adenocarcinomas.

Whole genome sequencing analysis reveals post-zygotic mutation variability in monozygotic twins discordant for amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis is a heterogeneous, fatal neurodegenerative disease, characterized by motor neuron loss and in 50% of cases also by cognitive and/or behavioral changes. Mendelian forms of ALS comprise approximately 10-15% of cases. The majority is however considered sporadic, but also with a high contribution of genetic risk factors. To explore the contribution of somatic mutations and/or epigenetic changes to disease risk, we performed whole genome sequencing and methylation analyses using samples from multiple tissues on a cohort of 26 monozygotic twins discordant for ALS, followed by in-depth validation and replication experiments. The results of these analyses implicate several mechanisms in ALS pathophysiology, which include a role for de novo mutations, defects in DNA damage repair and accelerated aging.

DNA damage and somatic mutations in mammalian cells after irradiation with a nail polish dryer

Ultraviolet A light is commonly emitted by UV-nail polish dryers with recent reports suggesting that long-term use may increase the risk for developing skin cancer. However, no experimental evaluation has been conducted to reveal the effect of radiation emitted by UV-nail polish dryers on mammalian cells. Here, we show that irradiation by a UV-nail polish dryer causes high levels of reactive oxygen species, consistent with 8-oxo-7,8-dihydroguanine damage and mitochondrial dysfunction. Analysis of somatic mutations reveals a dose-dependent increase of C:G>A:T substitutions in irradiated samples with mutagenic patterns similar to mutational signatures previously attributed to reactive oxygen species. In summary, this study demonstrates that radiation emitted by UV-nail polish dryers can both damage DNA and permanently engrave mutations on the genomes of primary mouse embryonic fibroblasts, human foreskin fibroblasts, and human epidermal keratinocytes.

Fast, accurate, and racially unbiased pan-cancer tumor-only variant calling with tabular machine learning

Accurately identifying somatic mutations is essential for precision oncology and crucial for calculating tumor-mutational burden (TMB), an important predictor of response to immunotherapy. For tumor-only variant calling (i.e., when the cancer biopsy but not the patient's normal tissue sample is sequenced), accurately distinguishing somatic mutations from germline variants is a challenging problem that, when unaddressed, results in unreliable, biased, and inflated TMB estimates. Here, we apply machine learning to the task of somatic vs germline classification in tumor-only solid tumor samples using TabNet, XGBoost, and LightGBM, three machine-learning models for tabular data. We constructed a training set for supervised classification using features derived exclusively from tumor-only variant calling and drawing somatic and germline truth labels from an independent pipeline using the patient-matched normal samples. All three trained models achieved state-of-the-art performance on two holdout test datasets: a TCGA dataset including sarcoma, breast adenocarcinoma, and endometrial carcinoma samples (AUC > 94%), and a metastatic melanoma dataset (AUC > 85%). Concordance between matched-normal and tumor-only TMB improves from R2 = 0.006 to 0.71-0.76 with the addition of a machine-learning classifier, with LightGBM performing best. Notably, these machine-learning models generalize across cancer subtypes and capture kits with a call rate of 100%. We reproduce the recent finding that tumor-only TMB estimates for Black patients are extremely inflated relative to that of white patients due to the racial biases of germline databases. We show that our approach with XGBoost and LightGBM eliminates this significant racial bias in tumor-only variant calling.

Arginine limitation drives a directed codon-dependent DNA sequence evolution response in colorectal cancer cells

Utilization of specific codons varies between organisms. Cancer represents a model for understanding DNA sequence evolution and could reveal causal factors underlying codon evolution. We found that across human cancer, arginine codons are frequently mutated to other codons. Moreover, arginine limitation-a feature of tumor microenvironments-is sufficient to induce arginine codon-switching mutations in human colon cancer cells. Such DNA codon switching events encode mutant proteins with arginine residue substitutions. Mechanistically, arginine limitation caused rapid reduction of arginine transfer RNAs and the stalling of ribosomes over arginine codons. Such selective pressure against arginine codon translation induced an adaptive proteomic shift toward low-arginine codon-containing genes, including specific amino acid transporters, and caused mutational evolution away from arginine codons-reducing translational bottlenecks that occurred during arginine starvation. Thus, environmental availability of a specific amino acid can influence DNA sequence evolution away from its cognate codons and generate altered proteins.

Mutational Landscape of Bladder Cancer in Mexican Patients: KMT2D Mutations and chr11q15.5 Amplifications Are Associated with Muscle Invasion

Bladder cancer (BC) is the most common neoplasm of the urinary tract, which originates in the epithelium that covers the inner surface of the bladder. The molecular BC profile has led to the development of different classifications of non-muscle invasive bladder cancer (NMIBC) and muscle-invasive bladder cancer (MIBC). However, the genomic BC landscape profile of the Mexican population, including NMIBC and MIBC, is unknown. In this study, we aimed to identify somatic single nucleotide variants (SNVs) and copy number variations (CNVs) in Mexican patients with BC and their associations with clinical and pathological characteristics. We retrospectively evaluated 37 patients treated between 2012 and 2021 at the National Cancer Institute-Mexico (INCan). DNA samples were obtained from paraffin-embedded tumor tissues and exome sequenced. Strelka2 and Lancet packages were used to identify SNVs and insertions or deletions. FACETS was used to determine CNVs. We found a high frequency of mutations in TP53 and KMT2D, gains in 11q15.5 and 19p13.11-q12, and losses in 7q11.23. STAG2 mutations and 1q11.23 deletions were also associated with NMIBC and low histologic grade.

Non-CpG sites preference in G:C > A:T transition of TP53 in gastric cancer of Eastern Europe (Poland, Romania and Hungary) compared to East Asian countries (China and Japan)

AIM

Mutation spectrum of TP53 in gastric cancer (GC) has been investigated world-widely, but a comparison of mutation spectrum among GCs from various regions in the world are still sparsely documented. In order to identify the difference of TP53 mutation spectrum in GCs in Eastern Europe and in East Asia, we sequenced TP53 in GCs from Eastern Europe, Lujiang (China), and Yokohama, Kanagawa (Japan) and identified the feature of TP53 mutations of GC in these regions.

SUBJECTS AND METHOD

In total, 689 tissue samples of GC were analyzed: 288 samples from East European populations (25 from Hungary, 71 from Poland and 192 from Romania), 268 from Yokohama, Kanagawa, Japan and 133 from Lujiang, Anhui province, China. DNA was extracted from FFPE tissue of Chinese, East European cases; and from frozen tissue of Japanese GCs. PCR products were direct-sequenced by Sanger method, and in ambiguous cases, PCR product was cloned and up to 8 clones were sequenced. We used No. NC_000017.11(hg38) as the reference sequence of TP53. Mutation patterns were categorized into nine groups: six base substitutions, insertion, deletion and deletion-insertion. Within G:C > A:T mutations the mutations in CpG and non-CpG sites were divided. The Cancer Genome Atlas data (TCGA, ver.R20, July, 2019) having somatic mutation list of GCs from Whites, Asians, and other ethnicities were used as a reference for our data.

RESULTS

The most frequent base substitutions were G:C > A:T transition in all the areas investigated. The G:C > A:T transition in non-CpG sites were prominent in East European GCs, compared with Asian ones. Mutation pattern from TCGA data revealed the same trend between GCs from White (TCGA category) vs Asian countries. Chinese and Japanese GCs showed higher ratio of G:C > A:T transition in CpG sites and A:T > G:C mutation was more prevalent in Asian countries.

CONCLUSION

The divergence in mutation spectrum of GC in different areas in the world may reflect various pathogeneses and etiologies of GC, region to region. Diversified mutation spectrum in GC in Eastern Europe may suggest GC in Europe has different carcinogenic pathway of those from Asia.

Arginine limitation causes a directed DNA sequence evolution response in colorectal cancer cells

Utilization of specific codons varies significantly across organisms. Cancer represents a model for understanding DNA sequence evolution and could reveal causal factors underlying codon evolution. We found that across human cancer, arginine codons are frequently mutated to other codons. Moreover, arginine restriction-a feature of tumor microenvironments-is sufficient to induce arginine codon-switching mutations in human colon cancer cells. Such DNA codon switching events encode mutant proteins with arginine residue substitutions. Mechanistically, arginine limitation caused rapid reduction of arginine transfer RNAs and the stalling of ribosomes over arginine codons. Such selective pressure against arginine codon translation induced a proteomic shift towards low arginine codon containing genes, including specific amino acid transporters, and caused mutational evolution away from arginine codons-reducing translational bottlenecks that occurred during arginine starvation. Thus, environmental availability of a specific amino acid can influence DNA sequence evolution away from its cognate codons and generate altered proteins.

Leveraging the replication stress response to optimize cancer therapy

High-fidelity DNA replication is critical for the faithful transmission of genetic information to daughter cells. Following genotoxic stress, specialized DNA damage tolerance pathways are activated to ensure replication fork progression. These pathways include translesion DNA synthesis, template switching and repriming. In this Review, we describe how DNA damage tolerance pathways impact genome stability, their connection with tumorigenesis and their effects on cancer therapy response. We discuss recent findings that single-strand DNA gap accumulation impacts chemoresponse and explore a growing body of evidence that suggests that different DNA damage tolerance factors, including translesion synthesis polymerases, template switching proteins and enzymes affecting single-stranded DNA gaps, represent useful cancer targets. We further outline how the consequences of DNA damage tolerance mechanisms could inform the discovery of new biomarkers to refine cancer therapies.

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.

Integrated analysis of racial disparities in genomic architecture identifies a trans-ancestry prognostic subtype in bladder cancer

The incidence of bladder cancer and patient survival vary greatly among different populations, but the influence of the associated molecular features and evolutionary processes on its clinical treatment and prognostication remains unknown. Here, we analyze the genomic architectures of 505 bladder cancer patients from Asian/Black/White populations. We identify a previously unknown association between AHNAK mutations and activity of the APOBEC-a mutational signature, the activity of which varied substantially across populations. All significantly mutated genes but only half of arm-level somatic copy number alterations (SCNAs) are enriched with clonal events, indicating large-scale SCNAs as rich sources of bladder cancer clonal diversities. The prevalence of TP53 and ATM clonal mutations as well as the associated burden of SCNAs is significantly higher in Whites/Blacks than in Asians. We identify a trans-ancestry prognostic subtype of bladder cancer characterized by enrichment of non-muscle-invasive patients and muscle-invasive patients with good prognosis, increased CREBBP/FGFR3/HRAS/NFE2L2 mutations, decreased intra-tumor heterogeneity and genome instability, and an activated tumor microenvironment.

Proteogenomic characterization of MiT family translocation renal cell carcinoma

Microphthalmia transcription factor (MiT) family translocation renal cell carcinoma (tRCC) is a rare type of kidney cancer, which is not well characterized. Here we show the comprehensive proteogenomic analysis of tRCC tumors and normal adjacent tissues to elucidate the molecular landscape of this disease. Our study reveals that defective DNA repair plays an important role in tRCC carcinogenesis and progression. Metabolic processes are markedly dysregulated at both the mRNA and protein levels. Proteomic and phosphoproteome data identify mTOR signaling pathway as a potential therapeutic target. Moreover, molecular subtyping and immune infiltration analysis characterize the inter-tumoral heterogeneity of tRCC. Multi-omic integration reveals the dysregulation of cellular processes affected by genomic alterations, including oxidative phosphorylation, autophagy, transcription factor activity, and proteasome function. This study represents a comprehensive proteogenomic analysis of tRCC, providing valuable insights into its biological mechanisms, disease diagnosis, and prognostication.

Contribution of mechanical homeostasis to epithelial-mesenchymal transition

BACKGROUND

Metastasis refers to the spread of cancer cells from a primary tumor to other parts of the body via the lymphatic system and bloodstream. With tremendous effort over the past decades, remarkable progress has been made in understanding the molecular and cellular basis of metastatic processes. Metastasis occurs through five steps, including infiltration and migration, intravasation, survival, extravasation, and colonization. Various molecular and cellular factors involved in the metastatic process have been identified, such as epigenetic factors of the extracellular matrix (ECM), cell-cell interactions, soluble signaling, adhesion molecules, and mechanical stimuli. However, the underlying cause of cancer metastasis has not been elucidated.

CONCLUSION

In this review, we have focused on changes in the mechanical properties of cancer cells and their surrounding environment to understand the causes of cancer metastasis. Cancer cells have unique mechanical properties that distinguish them from healthy cells. ECM stiffness is involved in cancer cell growth, particularly in promoting the epithelial-mesenchymal transition (EMT). During tumorigenesis, the mechanical properties of cancer cells change in the direction opposite to their environment, resulting in a mechanical stress imbalance between the intracellular and extracellular domains. Disruption of mechanical homeostasis may be one of the causes of EMT that triggers the metastasis of cancer cells.

RB1-deficient squamous cell carcinoma: the proposed source of combined Merkel cell carcinoma

Merkel cell carcinoma (MCC) is an aggressive cutaneous neuroendocrine (NE) carcinoma arising from integration of Merkel cell polyomavirus (MCPyV) DNA into a host cell or from ultraviolet light-induced genetic damage (proportions vary geographically). Tumors in the latter group include those with "pure" NE phenotype and those "combined" with other elements, most often squamous cell carcinoma (SCC). We performed comprehensive genomic profiling (CGP) of MCPyV+ and MCPyV- (pure and combined) tumors, to better understand their mutational profiles and shed light on their pathogenesis. Supplemental immunohistochemistry for Rb expression was also undertaken. After eliminating low quality samples, 37 tumors were successfully analyzed (14 MCPyV+, 8 pure MCPyV- and 15 combined MCPyV-). The SCC and NE components were sequenced separately in 5 combined tumors. Tumor mutational burden was lower in MCPyV+ tumors (mean 1.66 vs. 29.9/Mb, P < 0.0001). MCPyV- tumors featured frequent mutations in TP53 (95.6%), RB1 (87%), and NOTCH family genes (95.6%). No recurrently mutated genes were identified in MCPyV+ tumors. Mutational overlap in the NE and SCC components of combined tumors was substantial ('similarity index' >24% in 4/5 cases). Loss of Rb expression correlated with RB1 mutational (P < 0.0001) and MCPyV- status (P < 0.0001) in MCCs and it was observed more frequently in the SCC component of combined MCC than in a control group of conventional cutaneous SCC (P = 0.0002). Our results (i) support existing evidence that MCPyV+ and MCPyV- MCCs are pathogenetically distinct entities (ii) concur with earlier studies linking the NE and SCC components of combined MCCs via shared genetic profiles and (iii) lend credence to the proposal that an Rb-deficient subset of SCC's is the source of phenotypically divergent combined MCCs.

Competition for DNA binding between the genome protector replication protein A and the genome modifying APOBEC3 single-stranded DNA deaminases

The human APOBEC family of eleven cytosine deaminases use RNA and single-stranded DNA (ssDNA) as substrates to deaminate cytosine to uracil. This deamination event has roles in lipid metabolism by altering mRNA coding, adaptive immunity by causing evolution of antibody genes, and innate immunity through inactivation of viral genomes. These benefits come at a cost where some family members, primarily from the APOBEC3 subfamily (APOBEC3A-H, excluding E), can cause off-target deaminations of cytosine to form uracil on transiently single-stranded genomic DNA, which induces mutations that are associated with cancer evolution. Since uracil is only promutagenic, the mutations observed in cancer genomes originate only when uracil is not removed by uracil DNA glycosylase (UNG) or when the UNG-induced abasic site is erroneously repaired. However, when ssDNA is present, replication protein A (RPA) binds and protects the DNA from nucleases or recruits DNA repair proteins, such as UNG. Thus, APOBEC enzymes must compete with RPA to access their substrate. Certain APOBEC enzymes can displace RPA, bind and scan ssDNA efficiently to search for cytosines, and can become highly overexpressed in tumor cells. Depending on the DNA replication conditions and DNA structure, RPA can either be in excess or deficient. Here we discuss the interplay between these factors and how despite RPA, multiple cancer genomes have a mutation bias at cytosines indicative of APOBEC activity.

Establishing Linkages Among DNA Damage, Mutagenesis, and Genetic Diseases

DNA damage by chemicals, radiation, or oxidative stress leads to a mutational spectrum, which is complex because it is determined in part by lesion structure, the DNA sequence context of the lesion, lesion repair kinetics, and the type of cells in which the lesion is replicated. Accumulation of mutations may give rise to genetic diseases such as cancer and therefore understanding the process underlying mutagenesis is of immense importance to preserve human health. Chemical or physical agents that cause cancer often leave their mutational fingerprints, which can be used to back-calculate the molecular events that led to disease. To make a clear link between DNA lesion structure and the mutations a given lesion induces, the field of single-lesion mutagenesis was developed. In the last three decades this area of research has seen much growth in several directions, which we attempt to describe in this Perspective.

PARP Inhibitors in Advanced Prostate Cancer in Tumors with DNA Damage Signatures

Simple Summary

This review paper seeks to summarize the current literature on the role of PARP Inhibitors in Advanced Prostate Cancer in tumors with defects in genes associated with DNA damage repair. It will give particular attention to the role of PARPi in tumors with non-BRCA DNA damage repair genes. The aim of this review is to summarize the literature on PARPi and their activity treating BRCA and non BRCA tumors with DNA damage signatures.

Abstract

Since 2010, significant progress has been made in the treatment of metastatic castrate resistant prostate cancer (mCRPC). While these advancements have improved survival, mCRPC remains a lethal disease, with a precision medicine framework that is lagging behind compared to other cancers. Poly (ADP-ribose) polymerase (PARP) inhibitor (PARPi) studies in prostate cancer (PCa) have focused primarily on the homologous recombination repair (HRR) genes, specifically BRCA1 and BRCA2. While homologous recombination deficiency (HRD) can be prompted by germline or somatic BRCA1/2 genetic mutations, it can also exist in tumors with intact BRCA1/BRCA2 genes. While the sensitivity of PARPi in tumors with non-BRCA DNA damage signatures is not as well established, it has been suggested that genomic alterations in DNA damage repair (DDR) genes other than BRCA may confer synthetic lethality with PARPI in mCRPC. The aim of this review is to summarize the literature on PARPi and their activity treating BRCA and non BRCA tumors with DNA damage signatures.

UVA Radiation, DNA Damage, and Melanoma

Melanoma is a lethal type of skin tumor that has been linked with sunlight exposure chiefly in fair-skinned human populations. Wavelengths from the sun that can reach the earth's surface include UVA radiation (320-400 nm) and UVB radiation (280-320 nm). UVB effectively induces the formation of dimeric DNA photoproducts, preferentially the cyclobutane pyrimidine dimers (CPDs). The characteristic UVB signature mutations in the form of C to T mutations at dipyrimidine sequences are prevalent in melanoma tumor genomes and have been ascribed to deamination of cytosines within CPDs before DNA polymerase bypass. However, evidence from epidemiological, animal, and other experimental studies also suggest that UVA radiation may participate in melanoma formation. The DNA damage relevant for UVA includes specific types of CPDs at TT sequences and perhaps oxidative DNA damage to guanine, both induced by direct or indirect, photosensitization-mediated chemical and biophysical processes. We summarize the evidence for a potential role of UVA in melanoma and discuss some of the mechanistic pathways of how UVA may induce mutagenesis in melanocytes.

Most cancers carry a substantial deleterious load due to Hill-Robertson interference

Cancer genomes exhibit surprisingly weak signatures of negative selection^1,2. This may be because selective pressures are relaxed or because genome-wide linkage prevents deleterious mutations from being removed (Hill-Robertson interference)³. By stratifying tumors by their genome-wide mutational burden, we observe negative selection (dN/dS ~ 0.56) in low mutational burden tumors, while remaining cancers exhibit dN/dS ratios ~1. This suggests that most tumors do not remove deleterious passengers. To buffer against deleterious passengers, tumors upregulate heat shock pathways as their mutational burden increases. Finally, evolutionary modeling finds that Hill-Robertson interference alone can reproduce patterns of attenuated selection and estimates the total fitness cost of passengers to be 46% per cell on average. Collectively, our findings suggest that the lack of observed negative selection in most tumors is not due to relaxed selective pressures, but rather the inability of selection to remove deleterious mutations in the presence of genome-wide linkage.

Mycotoxin Exposure and Renal Cell Carcinoma Risk: An Association Study in the EPIC European Cohort

BACKGROUND

Mycotoxins have been suggested to contribute to a spectrum of adverse health effects in humans, including at low concentrations. The recognition of these food contaminants being carcinogenic, as co-occurring rather than as singularly present, has emerged from recent research. The aim of this study was to assess the potential associations of single and multiple mycotoxin exposures with renal cell carcinoma risk in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort.

METHODS

Food questionnaire data from the EPIC cohort were matched to mycotoxin food occurrence data compiled by the European Food Safety Authority (EFSA) from European Member States to assess long-term dietary mycotoxin exposures, and to associate these with the risk of renal cell carcinoma (RCC, n = 911 cases) in 450,112 EPIC participants. Potential confounding factors were taken into account. Analyses were conducted using Cox's proportional hazards regression models to compute hazard ratios (HRs) and 95% confidence intervals (95% CIs) with mycotoxin exposures expressed as µg/kg body weight/day.

RESULTS

Demographic characteristics differed between the RCC cases and non-cases for body mass index, age, alcohol intake at recruitment, and other dietary factors. In addition, the mycotoxin exposure distributions showed that a large proportion of the EPIC population was exposed to some of the main mycotoxins present in European foods such as deoxynivalenol (DON) and derivatives, fumonisins, Fusarium toxins, Alternaria toxins, and total mycotoxins. Nevertheless, no statistically significant associations were observed between the studied mycotoxins and mycotoxin groups, and the risk of RCC development.

CONCLUSIONS

These results show an absence of statistically significant associations between long-term dietary mycotoxin exposures and RCC risk. However, these results need to be validated in other cohorts and preferably using repeated dietary exposure measurements. In addition, more occurrence data of, e.g., citrinin and fumonisins in different food commodities and countries in the EFSA database are a prerequisite to establish a greater degree of certainty.

Bioinformatics: From NGS Data to Biological Complexity in Variant Detection and Oncological Clinical Practice

The use of next-generation sequencing (NGS) techniques for variant detection has become increasingly important in clinical research and in clinical practice in oncology. Many cancer patients are currently being treated in clinical practice or in clinical trials with drugs directed against specific genomic alterations. In this scenario, the development of reliable and reproducible bioinformatics tools is essential to derive information on the molecular characteristics of each patient’s tumor from the NGS data. The development of bioinformatics pipelines based on the use of machine learning and statistical methods is even more relevant for the determination of complex biomarkers. In this review, we describe some important technologies, computational algorithms and models that can be applied to NGS data from Whole Genome to Targeted Sequencing, to address the problem of finding complex cancer-associated biomarkers. In addition, we explore the future perspectives and challenges faced by bioinformatics for precision medicine both at a molecular and clinical level, with a focus on an emerging complex biomarker such as homologous recombination deficiency (HRD).