Type-specific cell line models for type-specific ovarian cancer research - PubMed (original) (raw)

. 2013 Sep 4;8(9):e72162.

doi: 10.1371/journal.pone.0072162. eCollection 2013.

Kimberly C Wiegand, Nataliya Melnyk, Christine Chow, Clara Salamanca, Leah M Prentice, Janine Senz, Winnie Yang, Monique A Spillman, Dawn R Cochrane, Karey Shumansky, Sohrab P Shah, Steve E Kalloger, David G Huntsman

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Type-specific cell line models for type-specific ovarian cancer research

Michael S Anglesio et al. PLoS One. 2013.

Erratum in

Abstract

Background: OVARIAN CARCINOMAS CONSIST OF AT LEAST FIVE DISTINCT DISEASES: high-grade serous, low-grade serous, clear cell, endometrioid, and mucinous. Biomarker and molecular characterization may represent a more biologically relevant basis for grouping and treating this family of tumors, rather than site of origin. Molecular characteristics have become the new standard for clinical pathology, however development of tailored type-specific therapies is hampered by a failure of basic research to recognize that model systems used to study these diseases must also be stratified. Unrelated model systems do offer value for study of biochemical processes but specific cellular context needs to be applied to assess relevant therapeutic strategies.

Methods: We have focused on the identification of clear cell carcinoma cell line models. A panel of 32 "ovarian cancer" cell lines has been classified into histotypes using a combination of mutation profiles, IHC mutation-surrogates, and a validated immunohistochemical model. All cell lines were identity verified using STR analysis.

Results: Many described ovarian clear cell lines have characteristic mutations (including ARID1A and PIK3CA) and an overall molecular/immuno-profile typical of primary tumors. Mutations in TP53 were present in the majority of high-grade serous cell lines. Advanced genomic analysis of bona-fide clear cell carcinoma cell lines also support copy number changes in typical biomarkers such at MET and HNF1B and a lack of any recurrent expressed re-arrangements.

Conclusions: As with primary ovarian tumors, mutation status of cancer genes like ARID1A and TP53 and a general immuno-profile serve well for establishing histotype of ovarian cancer cell We describe specific biomarkers and molecular features to re-classify generic "ovarian carcinoma" cell lines into type specific categories. Our data supports the use of prototype clear cell lines, such as TOV21G and JHOC-5, and questions the use of SKOV3 and A2780 as models of high-grade serous carcinoma.

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Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Figure 1

Figure 1. Prediction of histotype was in part based on the COSP algorithm using 9 IHC markers .

(A–B) representative IHC from a typical high-grade serous ovarian carcinoma cell line, Kuramochi, and a clear cell carcinoma cell line, TOV21G. In addition to the 9-marker COSP panel, IHC for ARID1A (BAF250a) is also shown as a mutation surrogate. (C) TFF3 mRNA expression from 60 ovarian cancer samples (12 of each histotype). As noted previously high expression is most prevalent in MUC, followed by ENOCa and LGSC , . Expression in our pilot cohort suggests the highest levels of TFF3 in MUC, which was significantly higher than all other groups (Tukey's adjusted p<0.01); no other pairwise comparisons had p<0.05. (D) TFF3 mRNA detected in ovarian cancer cell lines was used in place of an IHC score as the secreted TFF3 was considered a poor biomarker for cell culture conditions. Any cell line with measurable TFF3 mRNA above the NanoString detection threshold (see methods) was considered positive (score of 1 for use in the COSP algorithm).

Figure 2

Figure 2. Genome-wide copy number profiles of bona-fide ovarian CCC cell lines.

A large range of copy number changes are seen including typical Chr8 gains and Chr17 gains surrounding the CCC biomarker HNF1B gene, see also Table 3.

Figure 3

Figure 3. Genomic structure of CCC cell line JHOC-9. (A) 24 color FISH analysis suggested the presence of two dominant clones; one near-diploid and one near-tetraploid in the JHOC-9 CCC cell line.

A number of translocations and rearrangements can be seen in each representative clone. The complex karyotype of each dominant clone is noted below the corresponding 24-colour FISH results. Not all derivative chromosomes were identifiable resulting in a large number of ambiguous translocations and fragments (denoted by question marks in the karyotype notations). (B) Circos plot of RNAseq data and deFuse analysis depicting expressed genomic rearrangements in the JHOC-9 cell line. Translocations seen in the 24-color FISH profile are also visible as expressed transcripts including t(8;19) observed in both 2N and 4N dominant clones. No recurrent translocations were seen across our series (see also Table S3).

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Support for this project was provided to the Ovarian Cancer Research Team of BC (OVCARE; http://www.ovcare.ca) through the BC Cancer Foundation, The VGH and UBC Hospitals Foundation and the Canadian Institutes for Health Research (CIHR) Emerging Team Grant: Personalized siRNA-Based Nanomedicines (FRN: 111627). Funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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