The effect of age on the acquisition and selection of cancer driver mutations in sun-exposed normal skin

AbstractRecent studies have reported that genome editing by CRISPR–Cas9 induces a DNA damage response mediated by p53 in primary cells hampering their growth. This could lead to a selection of cells with pre-existing p53 mutations. In this study, employing an integrated computational and experimental framework, we systematically investigated the possibility of selection of additional cancer driver mutations during CRISPR-Cas9 gene editing. We first confirm the previous findings of the selection for pre-existing p53 mutations by CRISPR-Cas9. We next demonstrate that similar to p53, wildtype KRAS may also hamper the growth of Cas9-edited cells, potentially conferring a selective advantage to pre-existing KRAS-mutant cells. These selective effects are widespread, extending across cell-types and methods of CRISPR-Cas9 delivery and the strength of selection depends on the sgRNA sequence and the gene being edited. The selection for pre-existing p53 or KRAS mutations may confound CRISPR-Cas9 screens in cancer cells and more importantly, calls for monitoring patients undergoing CRISPR-Cas9-based editing for clinical therapeutics for pre-existing p53 and KRAS mutations.

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A systematic genome-wide mapping of oncogenic mutation selection during CRISPR-Cas9 genome editing

10.21203/rs.3.rs-199044/v1 ◽

2021 ◽

Author(s):

Sanju Sinha ◽

Karina Guerra ◽

Kuoyuan Cheng ◽

Mark Leiserson ◽

Prashant Jain ◽

...

Keyword(s):

Genome Editing ◽

Cell Types ◽

Selective Advantage ◽

Driver Mutations ◽

Cancer Driver ◽

Oncogenic Mutation ◽

Genome Wide ◽

Selection For ◽

Mutant Cells ◽

Selection Of

Abstract Recent studies have reported that genome editing by CRISPR–Cas9 induces a DNA damage response mediated by p53 in primary cells hampering their growth. This could lead to a selection of cells with pre-existing p53 mutations. In this study, employing an integrated computational and experimental framework, we systematically investigated the possibility of selection of additional cancer driver mutations during CRISPR-Cas9 gene editing. We first confirm the previous findings of the selection for pre-existing p53 mutations by CRISPR-Cas9. We next demonstrate that similar to p53, wildtype KRAS may also hamper the growth of Cas9-edited cells, potentially conferring a selective advantage to pre-existing KRAS-mutant cells. These selective effects are widespread, extending across cell-types and methods of CRISPR-Cas9 delivery and the strength of selection depends on the sgRNA sequence and the gene being edited. The selection for pre-existing p53 or KRAS mutations may confound CRISPR-Cas9 screens in cancer cells and more importantly, calls for monitoring patients undergoing CRISPR-Cas9-based editing for clinical therapeutics for pre-existing p53 and KRAS mutations.

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Precancer: Mutant clones in normal epithelium outcompete and eliminate esophageal micro-tumors

10.1101/2021.06.25.449880 ◽

2021 ◽

Author(s):

Bartomeu Colom ◽

Albert Herms ◽

Stefan Dentro ◽

Charlotte King ◽

Roshan Sood ◽

...

Keyword(s):

Genetic Selection ◽

Tumor Formation ◽

Driver Mutations ◽

Tumor Cell Death ◽

Cell Competition ◽

Normal Epithelium ◽

Cancer Driver ◽

Tissue Integrity ◽

Esophageal Carcinogenesis ◽

Selection Of

Human epithelial tissues accumulate cancer-driver mutations with age1-7, yet tumor formation remains rare. The positive selection of these mutations argues they alter the behavior and fitness of proliferating cells8-10. Hence, normal adult tissues become a patchwork of mutant clones competing for space and survival, with the fittest clones expanding by eliminating their less-competitive neighbors9-12. However, little is known about how such dynamic competition in normal epithelia impacts early tumorigenesis. Here we show that the majority of newly formed esophageal tumors are eliminated through competition with mutant clones in the surrounding normal epithelium. We followed the fate of microscopic tumors in a mouse model of esophageal carcinogenesis. Most neoplasms are rapidly lost despite no indication of tumor cell death, decreased proliferation, or an anti-tumor immune response. Deep-sequencing of 10-day and 1-year-old tumors shows evidence of genetic selection on the surviving neoplasms. Induction of highly competitive clones in transgenic mice increased tumor removal, while pharmacologically inhibiting clonal competition reduced tumor loss. The results are consistent with a model where survival of early neoplasms depends on their competitive fitness relative to that of mutant clones in the adjacent normal tissue. We have identified an unexpected anti-tumorigenic role for mutant clones in normal epithelium by purging early neoplasms through cell competition, thereby preserving tissue integrity.

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Nucleotide excision repair is impaired by binding of transcription factors to DNA

10.1101/028886 ◽

2015 ◽

Author(s):

Radhakrishnan Sabarinathan ◽

Loris Mularoni ◽

Jordi Deu-Pons ◽

Abel Gonzalez-Perez ◽

Nuria Lopez-Bigas

Keyword(s):

Nucleotide Excision Repair ◽

Mutation Rate ◽

Binding Sites ◽

Somatic Mutations ◽

Excision Repair ◽

Replication Timing ◽

Driver Mutations ◽

Cancer Driver ◽

Nucleotide Excision ◽

Active Transcription

Somatic mutations are the driving force of cancer genome evolution. The rate of somatic mutations appears in great variability across the genome due to chromatin organization, DNA accessibility and replication timing. However, other variables that may influence the mutation rate locally, such as DNA-binding proteins, are unknown. Here we demonstrate that the rate of somatic mutations in melanoma tumors is highly increased at active Transcription Factor binding sites (TFBS) and nucleosome embedded DNA, compared to their flanking regions. Using recently available excision-repair sequencing (XR-seq) data, we show that the higher mutation rate at these sites is caused by a decrease of the levels of nucleotide excision repair (NER) activity. Therefore, our work demonstrates that DNA-bound proteins interfere with the NER machinery, which results in an increased rate of mutations at their binding sites. This finding has important implications in our understanding of mutational and DNA repair processes and in the identification of cancer driver mutations.

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OncoVar: an integrated database and analysis platform for oncogenic driver variants in cancers

Nucleic Acids Research ◽

10.1093/nar/gkaa1033 ◽

2020 ◽

Vol 49 (D1) ◽

pp. D1289-D1301 ◽

Cited By ~ 2

Author(s):

Tao Wang ◽

Shasha Ruan ◽

Xiaolu Zhao ◽

Xiaohui Shi ◽

Huajing Teng ◽

...

Keyword(s):

Cancer Genome ◽

The Cancer Genome Atlas ◽

Driver Mutations ◽

Cancer Genes ◽

Driver Genes ◽

Cancer Driver ◽

Cancer Cell Population ◽

Cancer Types ◽

Neutral Mutations ◽

Analysis Platform

Abstract The prevalence of neutral mutations in cancer cell population impedes the distinguishing of cancer-causing driver mutations from passenger mutations. To systematically prioritize the oncogenic ability of somatic mutations and cancer genes, we constructed a useful platform, OncoVar (https://oncovar.org/), which employed published bioinformatics algorithms and incorporated known driver events to identify driver mutations and driver genes. We identified 20 162 cancer driver mutations, 814 driver genes and 2360 pathogenic pathways with high-confidence by reanalyzing 10 769 exomes from 33 cancer types in The Cancer Genome Atlas (TCGA) and 1942 genomes from 18 cancer types in International Cancer Genome Consortium (ICGC). OncoVar provides four points of view, ‘Mutation’, ‘Gene’, ‘Pathway’ and ‘Cancer’, to help researchers to visualize the relationships between cancers and driver variants. Importantly, identification of actionable driver alterations provides promising druggable targets and repurposing opportunities of combinational therapies. OncoVar provides a user-friendly interface for browsing, searching and downloading somatic driver mutations, driver genes and pathogenic pathways in various cancer types. This platform will facilitate the identification of cancer drivers across individual cancer cohorts and helps to rank mutations or genes for better decision-making among clinical oncologists, cancer researchers and the broad scientific community interested in cancer precision medicine.

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Finding cancer driver mutations in the era of big data research

Biophysical Reviews ◽

10.1007/s12551-018-0415-6 ◽

2018 ◽

Vol 11 (1) ◽

pp. 21-29 ◽

Cited By ~ 9

Author(s):

Rebecca C. Poulos ◽

Jason W. H. Wong

Keyword(s):

Big Data ◽

Driver Mutations ◽

Cancer Driver

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Diversity spectrum analysis identifies mutation-specific effects of cancer driver genes

Communications Biology ◽

10.1038/s42003-019-0736-4 ◽

2020 ◽

Vol 3 (1) ◽

Cited By ~ 2

Author(s):

Xiaobao Dong ◽

Dandan Huang ◽

Xianfu Yi ◽

Shijie Zhang ◽

Zhao Wang ◽

...

Keyword(s):

Clinical Trials ◽

Spectrum Analysis ◽

Driver Mutations ◽

Driver Gene ◽

Cancer Type ◽

Driver Genes ◽

Drug Responses ◽

Cancer Driver ◽

Specific Effects ◽

Cancer Driver Genes

AbstractMutation-specific effects of cancer driver genes influence drug responses and the success of clinical trials. We reasoned that these effects could unbalance the distribution of each mutation across different cancer types, as a result, the cancer preference can be used to distinguish the effects of the causal mutation. Here, we developed a network-based framework to systematically measure cancer diversity for each driver mutation. We found that half of the driver genes harbor cancer type-specific and pancancer mutations simultaneously, suggesting that the pervasive functional heterogeneity of the mutations from even the same driver gene. We further demonstrated that the specificity of the mutations could influence patient drug responses. Moreover, we observed that diversity was generally increased in advanced tumors. Finally, we scanned potentially novel cancer driver genes based on the diversity spectrum. Diversity spectrum analysis provides a new approach to define driver mutations and optimize off-label clinical trials.

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