Examining clustered somatic mutations with SigProfilerClusters

Exploring the Role of Clustered Mutations in Carcinogenesis and Their Potential Clinical Implications in Cancer

Abnormal cell proliferation and growth leading to cancer primarily result from cumulative genome mutations. Single gene mutations alone do not fully explain cancer onset and progression; instead, clustered mutations-simultaneous occurrences of multiple mutations-are considered to be pivotal in cancer development and advancement. These mutations can affect different genes and pathways, resulting in cells undergoing malignant transformation with multiple functional abnormalities. Clustered mutations influence cancer growth rates, metastatic potential, and drug treatment sensitivity. This summary highlights the various types and characteristics of clustered mutations to understand their associations with carcinogenesis and discusses their potential clinical significance in cancer. As a unique mutation type, clustered mutations may involve genomic instability, DNA repair mechanism defects, and environmental exposures, potentially correlating with responsiveness to immunotherapy. Understanding the characteristics and underlying processes of clustered mutations enhances our comprehension of carcinogenesis and cancer progression, providing new diagnostic and therapeutic approaches for cancer.

Mutational impact of APOBEC3A and APOBEC3B in a human cell line and comparisons to breast cancer

A prominent source of mutation in cancer is single-stranded DNA cytosine deamination by cellular APOBEC3 enzymes, which results in signature C-to-T and C-to-G mutations in TCA and TCT motifs. Although multiple enzymes have been implicated, reports conflict and it is unclear which protein(s) are responsible. Here we report the development of a selectable system to quantify genome mutation and demonstrate its utility by comparing the mutagenic activities of three leading candidates-APOBEC3A, APOBEC3B, and APOBEC3H. The human cell line, HAP1, is engineered to express the thymidine kinase (TK) gene of HSV-1, which confers sensitivity to ganciclovir. Expression of APOBEC3A and APOBEC3B, but not catalytic mutant controls or APOBEC3H, triggers increased frequencies of TK mutation and similar TC-biased cytosine mutation profiles in the selectable TK reporter gene. Whole genome sequences from independent clones enabled an analysis of thousands of single base substitution mutations and extraction of local sequence preferences with APOBEC3A preferring YTCW motifs 70% of the time and APOBEC3B 50% of the time (Y = C/T; W = A/T). Signature comparisons with breast tumor whole genome sequences indicate that most malignancies manifest intermediate percentages of APOBEC3 signature mutations in YTCW motifs, mostly between 50 and 70%, suggesting that both enzymes contribute in a combinatorial manner to the overall mutation landscape. Although the vast majority of APOBEC3A- and APOBEC3B-induced single base substitution mutations occur outside of predicted chromosomal DNA hairpin structures, whole genome sequence analyses and supporting biochemical studies also indicate that both enzymes are capable of deaminating the single-stranded loop regions of DNA hairpins at elevated rates. These studies combine to help resolve a long-standing etiologic debate on the source of APOBEC3 signature mutations in cancer and indicate that future diagnostic and therapeutic efforts should focus on both APOBEC3A and APOBEC3B.

APOBEC3B regulates R-loops and promotes transcription-associated mutagenesis in cancer

The single-stranded DNA cytosine-to-uracil deaminase APOBEC3B is an antiviral protein implicated in cancer. However, its substrates in cells are not fully delineated. Here APOBEC3B proteomics reveal interactions with a surprising number of R-loop factors. Biochemical experiments show APOBEC3B binding to R-loops in cells and in vitro. Genetic experiments demonstrate R-loop increases in cells lacking APOBEC3B and decreases in cells overexpressing APOBEC3B. Genome-wide analyses show major changes in the overall landscape of physiological and stimulus-induced R-loops with thousands of differentially altered regions, as well as binding of APOBEC3B to many of these sites. APOBEC3 mutagenesis impacts genes overexpressed in tumors and splice factor mutant tumors preferentially, and APOBEC3-attributed kataegis are enriched in RTCW motifs consistent with APOBEC3B deamination. Taken together with the fact that APOBEC3B binds single-stranded DNA and RNA and preferentially deaminates DNA, these results support a mechanism in which APOBEC3B regulates R-loops and contributes to R-loop mutagenesis in cancer.

Topography of mutational signatures in human cancer

The somatic mutations found in a cancer genome are imprinted by different mutational processes. Each process exhibits a characteristic mutational signature, which can be affected by the genome architecture. However, the interplay between mutational signatures and topographical genomic features has not been extensively explored. Here, we integrate mutations from 5,120 whole-genome-sequenced tumors from 40 cancer types with 516 topographical features from ENCODE to evaluate the effect of nucleosome occupancy, histone modifications, CTCF binding, replication timing, and transcription/replication strand asymmetries on the cancer-specific accumulation of mutations from distinct mutagenic processes. Most mutational signatures are affected by topographical features, with signatures of related etiologies being similarly affected. Certain signatures exhibit periodic behaviors or cancer-type-specific enrichments/depletions near topographical features, revealing further information about the processes that imprinted them. Our findings, disseminated via the COSMIC (Catalog of Somatic Mutations in Cancer) signatures database, provide a comprehensive online resource for exploring the interactions between mutational signatures and topographical features across human cancer.

Assigning mutational signatures to individual samples and individual somatic mutations with SigProfilerAssignment

Analysis of mutational signatures is a powerful approach for understanding the mutagenic processes that have shaped the evolution of a cancer genome. Here we present SigProfilerAssignment, a desktop and an online computational framework for assigning all types of mutational signatures to individual samples. SigProfilerAssignment is the first tool that allows both analysis of copy-number signatures and probabilistic assignment of signatures to individual somatic mutations. As its computational engine, the tool uses a custom implementation of the forward stagewise algorithm for sparse regression and nonnegative least squares for numerical optimization. Analysis of 2,700 synthetic cancer genomes with and without noise demonstrates that SigProfilerAssignment outperforms four commonly used approaches for assigning mutational signatures. SigProfilerAssignment is freely available at https://github.com/AlexandrovLab/SigProfilerAssignment with a web implementation at https://cancer.sanger.ac.uk/signatures/assignment/.

Oncogenic structural aberration landscape in gastric cancer genomes

Structural variants (SVs) are responsible for driver events in gastric cancer (GC); however, their patterns and processes remain poorly understood. Here, we examine 170 GC whole genomes to unravel the oncogenic structural aberration landscape in GC genomes and identify six rearrangement signatures (RSs). Non-random combinations of RSs elucidate distinctive GC subtypes comprising one or a few dominant RS that are associated with specific driver events (BRCA1/2 defects, mismatch repair deficiency, and TP53 mutation) and epidemiological backgrounds. Twenty-seven SV hotspots are identified as GC driver candidates. SV hotspots frequently constitute complexly clustered SVs involved in driver gene amplification, such as ERBB2, CCNE1, and FGFR2. Further deconstruction of the locally clustered SVs uncovers amplicon-generating profiles characterized by super-large SVs and intensive segmental amplifications, contributing to the extensive amplification of GC oncogenes. Comprehensive analyses using adjusted SV allele frequencies indicate the significant involvement of extra-chromosomal DNA in processes linked to specific RSs.

Distinguishing Curable from Progressive Dementias for Defining Cancer Care Options

The likelihood of a diagnosis of dementia increases with a person's age, as is also the case for many cancers, including melanoma and multiple myeloma, where the median age of diagnosis is above 60 years. However, patients diagnosed with dementia are less likely to be offered invasive curative therapies for cancer. Together with analysis of diet and medication history, advanced imaging methods and genetic profiling can now indicate more about syndromes causing the neurological symptoms. Cachexia, malnutrition, dehydration, alcohol consumption, and even loneliness can all accentuate or cause the "3Ds" of dementia, delirium and depression. Many common drugs, especially in the context of polypharmacy, can cause cognitive difficulties resembling neurodegenerative disease. These syndromes may be reversed by diet, social and caregiver changes, and stopping potentially inappropriate medications (PIMs). More insidious are immune reactions to many different autoantigens, some of which are related to cancers and tumors. These can induce movement and cognitive difficulties that mimic Alzheimer's and Parkinson's diseases and other ataxias associated with aging. Paraneoplastic neurological syndromes may be reversed by directed immunotherapies if detected in their early stages but are best treated by removal of the causative tumor. A full genetic workup should be done for all individuals as soon as possible after diagnosis, to guide less invasive treatments suitable for frail individuals. While surgical interventions may be contraindicated, genetic profile guided immunotherapies, oral treatments, and radiation may be equally curative in a significant number of cancers.

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.

Katdetectr: an R/bioconductor package utilizing unsupervised changepoint analysis for robust kataegis detection

BACKGROUND

Kataegis refers to the occurrence of regional genomic hypermutation in cancer and is a phenomenon that has been observed in a wide range of malignancies. A kataegis locus constitutes a genomic region with a high mutation rate (i.e., a higher frequency of closely interspersed somatic variants than the overall mutational background). It has been shown that kataegis is of biological significance and possibly clinically relevant. Therefore, an accurate and robust workflow for kataegis detection is paramount.

FINDINGS

Here we present Katdetectr, an open-source R/Bioconductor-based package for the robust yet flexible and fast detection of kataegis loci in genomic data. In addition, Katdetectr houses functionalities to characterize and visualize kataegis and provides results in a standardized format useful for subsequent analysis. In brief, Katdetectr imports industry-standard formats (MAF, VCF, and VRanges), determines the intermutation distance of the genomic variants, and performs unsupervised changepoint analysis utilizing the Pruned Exact Linear Time search algorithm followed by kataegis calling according to user-defined parameters.We used synthetic data and an a priori labeled pan-cancer dataset of whole-genome sequenced malignancies for the performance evaluation of Katdetectr and 5 publicly available kataegis detection packages. Our performance evaluation shows that Katdetectr is robust regarding tumor mutational burden and shows the fastest mean computation time. Additionally, Katdetectr reveals the highest accuracy (0.99, 0.99) and normalized Matthews correlation coefficient (0.98, 0.92) of all evaluated tools for both datasets.

CONCLUSIONS

Katdetectr is a robust workflow for the detection, characterization, and visualization of kataegis and is available on Bioconductor: https://doi.org/doi:10.18129/B9.bioc.katdetectr.

Whole-exome sequencing identified mutational profiles of urothelial carcinoma post kidney transplantation

Kidney transplantation is a lifesaving option for patients with end-stage kidney disease. In Taiwan, urothelial carcinoma (UC) is the most common de novo cancer after kidney transplantation (KT). UC has a greater degree of molecular heterogeneity than do other solid tumors. Few studies have explored genomic alterations in UC after KT. We performed whole-exome sequencing to compare the genetic alterations in UC developed after kidney transplantation (UCKT) and in UC in patients on hemodialysis (UCHD). After mapping and variant calling, 18,733 and 11,093 variants were identified in patients with UCKT and UCHD, respectively. We excluded known single-nucleotide polymorphisms (SNPs) and retained genes that were annotated in the Catalogue of Somatic Mutations in Cancer (COSMIC), in the Integrative Onco Genomic cancer mutations browser (IntOGen), and in the Cancer Genome Atlas (TCGA) database of genes associated with bladder cancer. A total of 14 UCKT-specific genes with SNPs identified in more than two patients were included in further analyses. The single-base substitution (SBS) profile and signatures showed a relative high T > A pattern compared to COMSIC UC mutations. Ingenuity pathway analysis was used to explore the connections among these genes. GNAQ, IKZF1, and NTRK3 were identified as potentially involved in the signaling network of UCKT. The genetic analysis of posttransplant malignancies may elucidate a fundamental aspect of the molecular pathogenesis of UCKT.