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      Evaluating cell lines as tumour models by comparison of genomic profiles

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          Abstract

          Cancer cell lines are frequently used as in vitro tumour models. Recent molecular profiles of hundreds of cell lines from The Cancer Cell Line Encyclopedia and thousands of tumour samples from the Cancer Genome Atlas now allow a systematic genomic comparison of cell lines and tumours. Here we analyse a panel of 47 ovarian cancer cell lines and identify those that have the highest genetic similarity to ovarian tumours. Our comparison of copy-number changes, mutations and mRNA expression profiles reveals pronounced differences in molecular profiles between commonly used ovarian cancer cell lines and high-grade serous ovarian cancer tumour samples. We identify several rarely used cell lines that more closely resemble cognate tumour profiles than commonly used cell lines, and we propose these lines as the most suitable models of ovarian cancer. Our results indicate that the gap between cell lines and tumours can be bridged by genomically informed choices of cell line models for all tumour types.

          Abstract

          Cell lines are widely used in cancer research to study tumour biology. Here Domcke et al. compare genomic data from ovarian cancer cell lines with those from clinical ovarian tumour samples and identify cell lines that most closely resemble the genomic features of high-grade serous ovarian cancer.

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          Most cited references 38

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          Cancer Statistics, 2017

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            Mutation of the PIK3CA gene in ovarian and breast cancer.

            Phosphatidylinositol 3'-kinases are lipid kinases with important roles in neoplasia. Recently, a very high frequency of somatic mutations in PIK3CA has been reported among a large series of colorectal cancers. However, the relevance of PIK3CA mutation in other cancer types remains unclear because of the limited number of tumors investigated. We have screened a total of 284 primary human tumors for mutations in all coding exons of PIK3CA using a combination of single stranded conformational polymorphism and denaturing high-performance liquid chromatography analysis. Among 70 primary breast cancers, 40% (28 of 70) harbored mutations in PIK3CA, making it the most common mutation described to date in this cancer type. Mutations were not associated with histologic subtype, estrogen receptor status, grade or presence of tumor in lymph nodes. Among the primary epithelial ovarian cancers only 11 of 167 (6.6%) contain somatic mutations, but there was a clear histologic subtype bias in their distribution. Only 2 of 88 (2.3%) of serous carcinomas had PIK3CA mutations compared with 8 of 40 (20.0%) endometrioid and clear cell cancers, which was highly significant (P = 0.001). In contrast, PIK3CA gene amplification (>7-fold) was common among all histologic subtypes (24.5%) and was inversely associated with the presence of mutations. Overall, PIK3CA mutation or gene amplification was detected in 30.5% of all ovarian cancers and 45% of the endometrioid and clear cell subtypes. Our study is the first direct evidence that PIK3CA is an oncogene in ovarian cancer and greatly extends recent findings in breast cancer.
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              Ovarian cancer side population defines cells with stem cell-like characteristics and Mullerian Inhibiting Substance responsiveness.

              The recent identification of "side population" (SP) cells in a number of unrelated human cancers and their normal tissue sources has renewed interest in the hypothesis that cancers may arise from somatic stem/progenitor cells. The high incidence of recurrence attributable to multidrug resistance and the multiple histologic phenotypes indicative of multipotency suggests a stem cell-like etiology of ovarian cancer. Here we identify and characterize SP cells from two distinct genetically engineered mouse ovarian cancer cell lines. Differential efflux of the DNA-binding dye Hoechst 33342 from these cell lines defined a human breast cancer-resistance protein 1-expressing, verapamil-sensitive SP of candidate cancer stem cells. In vivo, mouse SP cells formed measurable tumors sooner than non-SP (NSP) cells when equal numbers were injected into the dorsal fat pad of nude mice. The presence of Mullerian Inhibiting Substance (MIS) signaling pathway transduction molecules in both SP and NSP mouse cells led us to investigate the efficacy of MIS against these populations in comparison with traditional chemotherapies. MIS inhibited the proliferation of both SP and NSP cells, whereas the lipophilic chemotherapeutic agent doxorubicin more significantly inhibited the NSP cells. Finally, we identified breast cancer-resistance protein 1-expressing verapamil-sensitive SPs in three of four human ovarian cancer cell lines and four of six patient primary ascites cells. In the future, individualized therapy must incorporate analysis of the stem cell-like subpopulation of ovarian cancer cells when designing therapeutic strategies for ovarian cancer patients.
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                Author and article information

                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Pub. Group
                2041-1723
                09 July 2013
                : 4
                Affiliations
                [1 ]Computational Biology Center, Memorial Sloan-Kettering Cancer Center , 1275 York Avenue, Box 460, New York, New York 10065, USA
                [2 ]Department of Chemistry, Technische Universität München , Lichtenbergstraße 4, 85747 Garching bei München, Germany
                [3 ]Department of Surgery, Memorial Sloan-Kettering Cancer Center , 1275 York Avenue, New York, New York 10065, USA
                [4 ]These authors contributed equally to this work
                Author notes
                Article
                ncomms3126
                10.1038/ncomms3126
                3715866
                23839242
                Copyright © 2013, Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved.

                This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. To view a copy of this licence visit http://creativecommons.org/licenses/by/3.0/.

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