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      Generating New FANCA-Deficient HNSCC Cell Lines by Genomic Editing Recapitulates the Cellular Phenotypes of Fanconi Anemia

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          Abstract

          Fanconi anemia (FA) patients have an exacerbated risk of head and neck squamous cell carcinoma (HNSCC). Treatment is challenging as FA patients display enhanced toxicity to standard treatments, including radio/chemotherapy. Therefore, better therapies as well as new disease models are urgently needed. We have used CRISPR/Cas9 editing tools in order to interrupt the human FANCA gene by the generation of insertions/deletions (indels) in exon 4 in two cancer cell lines from sporadic HNSCC having no mutation in FA-genes: CAL27 and CAL33 cells. Our approach allowed efficient editing, subsequent purification of single-cell clones, and Sanger sequencing validation at the edited locus. Clones having frameshift indels in homozygosis did not express FANCA protein and were selected for further analysis. When compared with parental CAL27 and CAL33, FANCA-mutant cell clones displayed a FA-phenotype as they (i) are highly sensitive to DNA interstrand crosslink (ICL) agents such as mitomycin C (MMC) or cisplatin, (ii) do not monoubiquitinate FANCD2 upon MMC treatment and therefore (iii) do not form FANCD2 nuclear foci, and (iv) they display increased chromosome fragility and G2 arrest after diepoxybutane (DEB) treatment. These FANCA-mutant clones display similar growth rates as their parental cells. Interestingly, mutant cells acquire phenotypes associated with more aggressive disease, such as increased migration in wound healing assays. Therefore, CAL27 and CAL33 cells with FANCA mutations are phenocopies of FA-HNSCC cells.

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          The Cancer Cell Line Encyclopedia enables predictive modeling of anticancer drug sensitivity

          The systematic translation of cancer genomic data into knowledge of tumor biology and therapeutic avenues remains challenging. Such efforts should be greatly aided by robust preclinical model systems that reflect the genomic diversity of human cancers and for which detailed genetic and pharmacologic annotation is available 1 . Here we describe the Cancer Cell Line Encyclopedia (CCLE): a compilation of gene expression, chromosomal copy number, and massively parallel sequencing data from 947 human cancer cell lines. When coupled with pharmacologic profiles for 24 anticancer drugs across 479 of the lines, this collection allowed identification of genetic, lineage, and gene expression-based predictors of drug sensitivity. In addition to known predictors, we found that plasma cell lineage correlated with sensitivity to IGF1 receptor inhibitors; AHR expression was associated with MEK inhibitor efficacy in NRAS-mutant lines; and SLFN11 expression predicted sensitivity to topoisomerase inhibitors. Altogether, our results suggest that large, annotated cell line collections may help to enable preclinical stratification schemata for anticancer agents. The generation of genetic predictions of drug response in the preclinical setting and their incorporation into cancer clinical trial design could speed the emergence of “personalized” therapeutic regimens 2 .
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            Next-generation characterization of the Cancer Cell Line Encyclopedia

            Large panels of comprehensively characterized human cancer models, including the Cancer Cell Line Encyclopedia (CCLE), have provided a rigorous backbone upon which to study genetic variants, candidate targets, small molecule and biological therapeutics and to identify new marker-driven cancer dependencies. To improve our understanding of the molecular features that contribute to cancer phenotypes including drug responses, here we have expanded the characterizations of cancer cell lines to include genetic, RNA splicing, DNA methylation, histone H3 modification, microRNA expression and reverse-phase protein array data for 1,072 cell lines from various lineages and ethnicities. Integrating these data with functional characterizations such as drug-sensitivity data, short hairpin RNA knockdown and CRISPR–Cas9 knockout data reveals potential targets for cancer drugs and associated biomarkers. Together, this dataset and an accompanying public data portal provide a resource to accelerate cancer research using model cancer cell lines.
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              Chromosomal instability drives metastasis through a cytosolic DNA response

              Chromosomal instability (CIN) is a hallmark of cancer and it results from ongoing errors in chromosome segregation during mitosis. While CIN is a major driver of tumor evolution, its role in metastasis has not been established. Here we show that CIN promotes metastasis by sustaining a tumor-cell autonomous response to cytosolic DNA. Errors in chromosome segregation create a preponderance of micronuclei whose rupture spills genomic DNA into the cytosol. This leads to the activation of the cGAS-STING cytosolic DNA-sensing pathway and downstream noncanonical NF-κB signaling. Genetic suppression of CIN significantly delays metastasis even in highly aneuploid tumor models, whereas inducing continuous chromosome segregation errors promotes cellular invasion and metastasis in a STING-dependent manner. By subverting lethal epithelial responses to cytosolic DNA, chromosomally unstable tumor cells co-opt chronic activation of innate immune pathways to spread to distant organs.
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                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                Genes (Basel)
                Genes (Basel)
                genes
                Genes
                MDPI
                2073-4425
                09 April 2021
                April 2021
                : 12
                : 4
                : 548
                Affiliations
                [1 ]Biomedical Research Institute I+12, University Hospital 12 de Octubre, 28041 Madrid, Spain; Ricardo.ErrazquinCiudad@ 123456externos.ciemat.es (R.E.); clorz@ 123456ciemat.es (C.L.); carmen.segrelles@ 123456ciemat.es (C.S.)
                [2 ]Molecular Oncology Unit, CIEMAT, 28040 Madrid, Spain; esiba96@ 123456gmail.com (E.S.); pilar.msanc@ 123456gmail.com (P.M.); Jorge.Peral@ 123456ciemat.es (J.P.); jessica.ortiz@ 123456ciemat.es (J.O.)
                [3 ]Join Research Unit on Genomic Medicine UAB-Sant Pau Biomedical Research Institute, Hospital de la Santa Creu i Sant Pau, 08041 Barcelona, Spain; mariajose.ramirez@ 123456uab.cat (M.J.R.); jordi.surralles@ 123456uab.cat (J.S.)
                [4 ]Centro de Investigación Biomédica en Enfermedades Raras (CIBERER), 28029 Madrid, Spain; jose.casado@ 123456ciemat.es (J.A.C.); franjrr_@ 123456hotmail.com (F.J.R.-R.); paula.rio@ 123456ciemat.es (P.R.)
                [5 ]Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), 28029 Madrid, Spain
                [6 ]Hematopoietic Innovative Therapies Division, CIEMAT, 28040 Madrid, Spain
                [7 ]Instituto de Investigaciones Sanitarias de la Fundación Jiménez Díaz, 28040 Madrid, Spain
                [8 ]University Children’s Hospital Essen, University of Duisburg-Essen, 47057 Essen, Germany; helmut.hanenberg@ 123456uk-essen.de
                [9 ]Department of Otorhinolaryngology & Head/Neck Surgery, Heinrich Heine University, 40225 Düsseldorf, Germany
                Author notes
                Author information
                https://orcid.org/0000-0002-1479-8039
                https://orcid.org/0000-0003-1417-7731
                https://orcid.org/0000-0001-8214-9076
                https://orcid.org/0000-0002-4041-7519
                https://orcid.org/0000-0001-5640-6542
                Article
                genes-12-00548
                10.3390/genes12040548
                8069753
                4bbf41bf-78dd-4b71-802c-fff2a793c6a0
                © 2021 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( https://creativecommons.org/licenses/by/4.0/).

                History
                : 28 November 2020
                : 07 April 2021
                Categories
                Article

                fanconi anemia,crispr/cas9,gene editing,fanca,head and neck cancer

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