Evaluating cell lines as tumour models by comparison of genomic profiles

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].
Nature Communications (Impact Factor: 11.47). 07/2013; 4:2126. DOI: 10.1038/ncomms3126
Source: PubMed


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.

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    • "To the aim of the study, we selected 4 different ovarian cancer cell lines among those indicated as really representative of HGSOC lesions[18,19]and evaluated the expression of hormone receptors by RT-PCR and WB analyses (Figure 1). MCF-7 cells were used as positive control. "
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    ABSTRACT: The notion that menopausal estrogen replacement therapy increases ovarian cancer risk, but only for the two more common types (i.e. serous and endometrioid), while possibly decreasing risk for clear cell tumors, is strongly suggestive of causality. However, whether estradiol (E2) is tumorigenic or promotes development of occult preexisting disease is unknown. The present study investigated molecular and cellular mechanisms by which E2 modulates the growth of high grade serous ovarian cancer (HGSOC). Results showed that ERα expression was necessary and sufficient to induce the growth of HGSOC cells in in vitro models. Conversely, in vivo experimental studies demonstrated that increasing the levels of circulating estrogens resulted in a significant growth acceleration of ERα-negative HGSOC xenografts, as well. Tumors from E2-treated mice had significantly higher proliferation rate, angiogenesis, and density of tumor-associated macrophage (TAM) compared to ovariectomized females. Accordingly, immunohistochemical analysis of ERα-negative tissue specimens from HGSOC patients showed a significantly greater TAM infiltration in premenopausal compared to postmenopausal women. This study describes novel insights into the impact of E2 on tumor microenvironment, independently of its direct effect on tumor cell growth, thus supporting the idea that multiple direct and indirect mechanisms drive estrogen-induced tumor growth in HGSOC.
    Preview · Article · Jan 2016 · Oncotarget
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    • "Differential gene expression analyses have identified differences , but not core similarities, between cell lines and tumors for particular cancers. Comparisons of cell lines and tumors on this basis are uninformative, as they simply separate in vivo and in vitro samples (Domcke et al., 2013). Supervised gene lists can be used to identify suitable tumor models from cancer cell lines (Dancik et al., 2011; Gillet et al., 2011; Uva et al., 2010), or similarities between cancer cell lines and their tumors of origin can be scored with a tissue similarity index (TSI). "
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    ABSTRACT: Molecular signatures specific to particular tumor types are required to design treatments for resistant tumors. However, it remains unclear whether tumors and corresponding cell lines used for drug development share such signatures. We developed similarity core analysis (SCA), a universal and unsupervised computational framework for extracting core molecular features common to tumors and cell lines. We applied SCA to mRNA/miRNA expression data from various sources, comparing melanoma cell lines and metastases. The signature obtained was associated with phenotypic characteristics in vitro, and the core genes CAPN3 and TRIM63 were implicated in melanoma cell migration/invasion. About 90% of the melanoma signature genes belong to an intrinsic network of transcription factors governing neural development (TFAP2A, DLX2, ALX1, MITF, PAX3, SOX10, LEF1, and GAS7) and miRNAs (211-5p, 221-3p, and 10a-5p). The SCA signature effectively discriminated between two subpopulations of melanoma patients differing in overall survival, and classified MEKi/BRAFi-resistant and -sensitive melanoma cell lines.
    Full-text · Article · Oct 2015 · Cell Reports
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    • "See also Figure S1. Cell 162, 974–986, August 27, 2015 ª2015 Elsevier Inc. 975 Domcke et al., 2013). Aza induced partial IRF7 demethylation and increased expression in this cell line at days 7 and 10 while carboplatin did not (Figures 1B, 1C, and S3A), and IRF7 knockdown significantly reduced the Aza interferon response (Figures S3B and S3C). "
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    ABSTRACT: We show that DNA methyltransferase inhibitors (DNMTis) upregulate immune signaling in cancer through the viral defense pathway. In ovarian cancer (OC), DNMTis trigger cytosolic sensing of double-stranded RNA (dsRNA) causing a type I interferon response and apoptosis. Knocking down dsRNA sensors TLR3 and MAVS reduces this response 2-fold and blocking interferon beta or its receptor abrogates it. Upregulation of hypermethylated endogenous retrovirus (ERV) genes accompanies the response and ERV overexpression activates the response. Basal levels of ERV and viral defense gene expression significantly correlate in primary OC and the latter signature separates primary samples for multiple tumor types from The Cancer Genome Atlas into low versus high expression groups. In melanoma patients treated with an immune checkpoint therapy, high viral defense signature expression in tumors significantly associates with durable clinical response and DNMTi treatment sensitizes to anti-CTLA4 therapy in a pre-clinical melanoma model. Copyright © 2015 Elsevier Inc. All rights reserved.
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