scholarly journals Mutational signatures associated with tobacco smoking in human cancer

2016 ◽  
Author(s):  
Ludmil B. Alexandrov ◽  
Young Seok Ju ◽  
Kerstin Haase ◽  
Peter Van Loo ◽  
Iñigo Martincorena ◽  
...  
Keyword(s):  
Tobacco Smoke ◽  
Tobacco Smoking ◽  
Human Cancer ◽  
Mutational Signatures ◽  
Cytidine Deaminases ◽  
Endogenous Clock ◽  
Cancer Types ◽  
Tobacco Carcinogens ◽  
Mutational Processes ◽  
Mutational Process

ABSTRACTTobacco smoking increases the risk of at least 15 classes of cancer. We analyzed somatic mutations and DNA methylation in 5,243 cancers of types for which tobacco smoking confers an elevated risk. Smoking is associated with increased mutation burdens of multiple distinct mutational signatures, which contribute to different extents in different cancers. One of these signatures, mainly found in cancers derived from tissues directly exposed to tobacco smoke, is attributable to misreplication of DNA damage caused by tobacco carcinogens. Others likely reflect indirect activation of DNA editing by APOBEC cytidine deaminases and of an endogenous clock-like mutational process. The results are consistent with the proposition that smoking increases cancer risk by increasing the somatic mutation load, although direct evidence for this mechanism is lacking in some smoking-related cancer types.ONE SENTENCE SUMMARYMultiple distinct mutational processes associate with tobacco smoking in cancer reflecting direct and indirect effects of tobacco smoke.

scholarly journals Mutational signatures associated with tobacco smoking in human cancer

Science ◽  
2016 ◽  
Vol 354 (6312) ◽  
pp. 618-622 ◽  
Author(s):  
L. B. Alexandrov ◽  
Y. S. Ju ◽  
K. Haase ◽  
P. Van Loo ◽  
I. Martincorena ◽  
...  
Keyword(s):  
Tobacco Smoking ◽  
Human Cancer ◽  
Mutational Signatures

scholarly journals Comprehensive analysis of clustered mutations in cancer reveals recurrent APOBEC3 mutagenesis of ecDNA

2021 ◽  
Author(s):  
Erik N Bergstrom ◽  
Jens-Christian Luebeck ◽  
Mia Petljak ◽  
Vineet Bafna ◽  
Paul S. Mischel ◽  
...  
Keyword(s):  
Somatic Mutations ◽  
Human Cancer ◽  
Cancer Genes ◽  
Base Substitutions ◽  
Cancer Genomes ◽  
Cancer Types ◽  
Mutational Processes ◽  
Comprehensive Characterization

Clustered somatic mutations are common in cancer genomes with prior analyses revealing several types of clustered single-base substitutions, including doublet- and multi-base substitutions, diffuse hypermutation termed omikli, and longer strand-coordinated events termed kataegis. Here, we provide a comprehensive characterization of clustered substitutions and clustered small insertions and deletions (indels) across 2,583 whole-genome sequenced cancers from 30 cancer types. While only 3.7% of substitutions and 0.9% of indels were found to be clustered, they contributed 8.4% and 6.9% of substitution and indel drivers, respectively. Multiple distinct mutational processes gave rise to clustered indels including signatures enriched in tobacco smokers and homologous-recombination deficient cancers. Doublet-base substitutions were caused by at least 12 mutational processes, while the majority of multi-base substitutions were generated by either tobacco smoking or exposure to ultraviolet light. Omikli events, previously attributed to the activity of APOBEC3 deaminases, accounted for a large proportion of clustered substitutions. However, only 16.2% of omikli matched APOBEC3 patterns with experimental validation confirming additional mutational processes giving rise to omikli. Kataegis was generated by multiple mutational processes with 76.1% of all kataegic events exhibiting AID/APOBEC3-associated mutational patterns. Co-occurrence of APOBEC3 kataegis and extrachromosomal-DNA (ecDNA) was observed in 31% of samples with ecDNA. Multiple distinct APOBEC3 kataegic events were observed on most mutated ecDNA. ecDNA containing known cancer genes exhibited both positive selection and kataegic hypermutation. Our results reveal the diversity of clustered mutational processes in human cancer and the role of APOBEC3 in recurrently mutating and fueling the evolution of ecDNA.

scholarly journals Mutation signatures reveal biological processes in human cancer

2016 ◽  
Author(s):  
Kyle Covington ◽  
Eve Shinbrot ◽  
David A Wheeler
Keyword(s):  
Sparse Matrix ◽  
Human Cancer ◽  
Replication Errors ◽  
Repair Processes ◽  
Relative Contribution ◽  
History Of ◽  
Mutational Processes ◽  
Insight Into ◽  
Mutational Process ◽  
Non Negative Matrix Factorization

Replication errors in the genome accumulate from a variety of mutational processes, which leave a history of mutations on the affected genome. The relative contribution of each mutational process has been characterized by non-negative matrix factorization and has lead to deeper insight into both mutational and repair processes contributing to cancer. However current implementations of NMF have left unresolved some specific patterns that should be present in the mutation data and have not generated signatures designed for classification. Here, we use a variant of NMF, termed non-smooth NMF, to generate sparse matrix factorizations of somatic mutation profiles present in 7129 tumors. nsNMF factorization revealed 21 mutational signatures. We found three APOBEC mutational processes clearly segregating with the published APOBEC enzymology and trans-lesion repair processes. We discovered several signatures differed between geographic locations even between closely related tissues.

scholarly journals The APOBEC3A deaminase drives episodic mutagenesis in cancer cells

2021 ◽  
Author(s):  
Mia Petljak ◽  
Kevan Chu ◽  
Alexandra Dananberg ◽  
Erik N. Bergstrom ◽  
Patrick von Morgen ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Cells ◽  
Cell Lines ◽  
Human Cancer ◽  
B Cell Lymphoma ◽  
Lymphoma Cell ◽  
Mutational Signatures ◽  
Cytidine Deaminases ◽  
Human Cancer Cells ◽  
Cancer Genomes

ABSTRACTThe APOBEC3 family of cytidine deaminases is widely speculated to be a major source of somatic mutations in cancer1–3. However, causal links between APOBEC3 enzymes and mutations in human cancer cells have not been established. The identity of the APOBEC3 paralog(s) that may act as prime drivers of mutagenesis and the mechanisms underlying different APOBEC3-associated mutational signatures are unknown. To directly investigate the roles of APOBEC3 enzymes in cancer mutagenesis, candidate APOBEC3 genes were deleted from cancer cell lines recently found to naturally generate APOBEC3-associated mutations in episodic bursts4. Deletion of the APOBEC3A paralog severely diminished the acquisition of mutations of speculative APOBEC3 origins in breast cancer and lymphoma cell lines. APOBEC3 mutational burdens were undiminished in APOBEC3B knockout cell lines. APOBEC3A deletion reduced the appearance of the clustered mutation types kataegis and omikli, which are frequently found in cancer genomes. The uracil glycosylase UNG and the translesion polymerase REV1 were found to play critical roles in the generation of mutations induced by APOBEC3A. These data represent the first evidence for a long-postulated hypothesis that APOBEC3 deaminases generate prevalent clustered and non-clustered mutational signatures in human cancer cells, identify APOBEC3A as a driver of episodic mutational bursts, and dissect the roles of the relevant enzymes in generating the associated mutations in breast cancer and B cell lymphoma cell lines.

scholarly journals The APOBEC3A deaminase drives episodic mutagenesis in cancer cells

2021 ◽  
Author(s):  
John Maciejowski ◽  
Mia Petljak ◽  
Kevan Chu ◽  
Alexandra Dananberg ◽  
Erik Bergstrom ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Cells ◽  
Cell Lines ◽  
Human Cancer ◽  
B Cell Lymphoma ◽  
Lymphoma Cell ◽  
Mutational Signatures ◽  
Cytidine Deaminases ◽  
Human Cancer Cells ◽  
Cancer Genomes

Abstract The APOBEC3 family of cytidine deaminases is widely speculated to be a major source of somatic mutations in cancer1–3. However, causal links between APOBEC3 enzymes and mutations in human cancer cells have not been established. The identity of the APOBEC3 paralog(s) that may act as prime drivers of mutagenesis and the mechanisms underlying different APOBEC3-associated mutational signatures are unknown. To directly investigate the roles of APOBEC3 enzymes in cancer mutagenesis, candidate APOBEC3 genes were deleted from cancer cell lines recently found to naturally generate APOBEC3-associated mutations in episodic bursts4. Deletion of the APOBEC3A paralog severely diminished the acquisition of mutations of speculative APOBEC3 origins in breast cancer and lymphoma cell lines. APOBEC3 mutational burdens were undiminished in APOBEC3B knockout cell lines. APOBEC3A deletion reduced the appearance of the clustered mutation types kataegis and omikli, which are frequently found in cancer genomes. The uracil glycosylase UNG and the translesion polymerase REV1 were found to play critical roles in the generation of mutations induced by APOBEC3A. These data represent the first evidence for a long-postulated hypothesis that APOBEC3 deaminases generate prevalent clustered and non-clustered mutational signatures in human cancer cells, identify APOBEC3A as a driver of episodic mutational bursts, and dissect the roles of the relevant enzymes in generating the associated mutations in breast cancer and B cell lymphoma cell lines.

scholarly journals Process-specific somatic mutation distributions vary with three-dimensional genome structure

2018 ◽  
Author(s):  
Kadir C. Akdemir ◽  
Victoria T. Le ◽  
Sarah Killcoyne ◽  
Devin A. King ◽  
Ya-Ping Li ◽  
...  
Keyword(s):  
Somatic Mutation ◽  
X Chromosome ◽  
Genome Organization ◽  
Somatic Mutations ◽  
Light Exposure ◽  
Human Cancer ◽  
Three Dimensional ◽  
Cancer Evolution ◽  
Cancer Types ◽  
Mutational Processes

AbstractSomatic mutations arise during the life history of a cell. Mutations occurring in cancer driver genes may ultimately lead to the development of clinically detectable disease. Nascent cancer lineages continue to acquire somatic mutations throughout the neoplastic process and during cancer evolution (Martincorena and Campbell, 2015). Extrinsic and endogenous mutagenic factors contribute to the accumulation of these somatic mutations (Zhang and Pellman, 2015). Understanding the underlying factors generating somatic mutations is crucial for developing potential preventive, therapeutic and clinical decisions. Earlier studies have revealed that DNA replication timing (Stamatoyannopoulos et al., 2009) and chromatin modifications (Schuster-Böckler and Lehner, 2012) are associated with variations in mutational density. What is unclear from these early studies, however, is whether all extrinsic and exogenous factors that drive somatic mutational processes share a similar relationship with chromatin state and structure. In order to understand the interplay between spatial genome organization and specific individual mutational processes, we report here a study of 3000 tumor-normal pair whole genome datasets from more than 40 different human cancer types. Our analyses revealed that different mutational processes lead to distinct somatic mutation distributions between chromatin folding domains. APOBEC- or MSI-related mutations are enriched in transcriptionally-active domains while mutations occurring due to tobacco-smoke, ultraviolet (UV) light exposure or a signature of unknown aetiology (signature 17) enrich predominantly in transcriptionally-inactive domains. Active mutational processes dictate the mutation distributions in cancer genomes, and we show that mutational distributions shift during cancer evolution upon mutational processes switch. Moreover, a dramatic instance of extreme chromatin structure in humans, that of the unique folding pattern of the inactive X-chromosome leads to distinct somatic mutation distribution on X chromosome in females compared to males in various cancer types. Overall, the interplay between three-dimensional genome organization and active mutational processes has a substantial influence on the large-scale mutation rate variations observed in human cancer.

scholarly journals The Repertoire of Mutational Signatures in Human Cancer

2018 ◽  
Author(s):  
Ludmil B Alexandrov ◽  
Jaegil Kim ◽  
Nicholas J Haradhvala ◽  
Mi Ni Huang ◽  
Alvin WT Ng ◽  
...  
Keyword(s):  
Somatic Mutations ◽  
Human Cancer ◽  
Base Substitution ◽  
Mutational Signatures ◽  
Insertion And Deletion ◽  
Damage Repair ◽  
Cancer Genomes ◽  
Dataset Size ◽  
Dna Maintenance ◽  
Mutational Processes

ABSTRACTSomatic mutations in cancer genomes are caused by multiple mutational processes each of which generates a characteristic mutational signature. Using 84,729,690 somatic mutations from 4,645 whole cancer genome and 19,184 exome sequences encompassing most cancer types we characterised 49 single base substitution, 11 doublet base substitution, four clustered base substitution, and 17 small insertion and deletion mutational signatures. The substantial dataset size compared to previous analyses enabled discovery of new signatures, separation of overlapping signatures and decomposition of signatures into components that may represent associated, but distinct, DNA damage, repair and/or replication mechanisms. Estimation of the contribution of each signature to the mutational catalogues of individual cancer genomes revealed associations with exogenous and endogenous exposures and defective DNA maintenance processes. However, many signatures are of unknown cause. This analysis provides a systematic perspective on the repertoire of mutational processes contributing to the development of human cancer including a comprehensive reference set of mutational signatures in human cancer.

scholarly journals Learning mutational signatures and their multidimensional genomic properties with TensorSignatures

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Harald Vöhringer ◽  
Arne Van Hoeck ◽  
Edwin Cuppen ◽  
Moritz Gerstung
Keyword(s):  
Somatic Hypermutation ◽  
Excision Repair ◽  
Metastatic Cancer ◽  
Strand Break ◽  
Lymphoid Leukaemia ◽  
Mutational Signatures ◽  
Transcription Start Sites ◽  
Nucleotide Excision ◽  
Cancer Types ◽  
Underlying Processes

AbstractWe present TensorSignatures, an algorithm to learn mutational signatures jointly across different variant categories and their genomic localisation and properties. The analysis of 2778 primary and 3824 metastatic cancer genomes of the PCAWG consortium and the HMF cohort shows that all signatures operate dynamically in response to genomic states. The analysis pins differential spectra of UV mutagenesis found in active and inactive chromatin to global genome nucleotide excision repair. TensorSignatures accurately characterises transcription-associated mutagenesis in 7 different cancer types. The algorithm also extracts distinct signatures of replication- and double strand break repair-driven mutagenesis by APOBEC3A and 3B with differential numbers and length of mutation clusters. Finally, TensorSignatures reproduces a signature of somatic hypermutation generating highly clustered variants at transcription start sites of active genes in lymphoid leukaemia, distinct from a general and less clustered signature of Polη-driven translesion synthesis found in a broad range of cancer types. In summary, TensorSignatures elucidates complex mutational footprints by characterising their underlying processes with respect to a multitude of genomic variables.

scholarly journals Cellular Fitness Phenotypes of Cancer Target Genes from Oncobiology to Cancer Therapeutics

Cells ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 433
Author(s):  
Bijesh George ◽  
P. Mukundan Pillai ◽  
Aswathy Mary Paul ◽  
Revikumar Amjesh ◽  
Kim Leitzel ◽  
...  
Keyword(s):  
Drug Targets ◽  
Target Genes ◽  
Human Cancer ◽  
Cancer Therapeutics ◽  
Survival Duration ◽  
Cancer Drug ◽  
Targeted Therapeutics ◽  
Cellular Targets ◽  
Human Cancer Cells ◽  
Cancer Types

To define the growing significance of cellular targets and/or effectors of cancer drugs, we examined the fitness dependency of cellular targets and effectors of cancer drug targets across human cancer cells from 19 cancer types. We observed that the deletion of 35 out of 47 cellular effectors and/or targets of oncology drugs did not result in the expected loss of cell fitness in appropriate cancer types for which drugs targeting or utilizing these molecules for their actions were approved. Additionally, our analysis recognized 43 cellular molecules as fitness genes in several cancer types in which these drugs were not approved, and thus, providing clues for repurposing certain approved oncology drugs in such cancer types. For example, we found a widespread upregulation and fitness dependency of several components of the mevalonate and purine biosynthesis pathways (currently targeted by bisphosphonates, statins, and pemetrexed in certain cancers) and an association between the overexpression of these molecules and reduction in the overall survival duration of patients with breast and other hard-to-treat cancers, for which such drugs are not approved. In brief, the present analysis raised cautions about off-target and undesirable effects of certain oncology drugs in a subset of cancers where the intended cellular effectors of drug might not be good fitness genes and that this study offers a potential rationale for repurposing certain approved oncology drugs for targeted therapeutics in additional cancer types.

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