Abstract 33: Patient-specific cancer cell line derivation methodology results in genetic stability across 150 population doublings
Authors: Naghmeh Salimi, Jeffrey D. Kent, Alex Chao, Bryan E. Roberts, Agoston Agoston, Elin S. Agoston
Journal: Clinical Cancer Research (2016)

Abstract Cancer cell lines have been, and will continue to be, important tools in oncology research, but there are major limitations in the fidelity of existing cell lines as a model of human cancers. Therefore, the aim of our study was to generate and characterize patient-specific cell lines from solid tumors that more faithfully recapitulate the primary tumor genetic and morphologic characteristics. We performed cell line derivation on a primary human breast adenocarcinoma (ER+/PR+/HER2-), a lung adenocarcinoma, a high-grade serous ovarian carcinoma, and an endometrioid ovarian carcinoma procured from a commercial tissue bank. Portions were snap-frozen for molecular analysis, and the remainder was minced and processed for cell culture. Cells were cultured and the resulting monolayer was stained by immunocytochemistry with a pan-keratin antibody for the presence of epithelial cells. Any contaminating fibroblasts were removed. We extracted DNA from the resulting breast and lung cancer cell lines at low, medium, and high passage numbers (approximately 20, 40, and 150 population doublings), as well as the corresponding primary tumor specimen, and a 250K SNP array was performed. These data were combined with that of nine breast cancer and 13 lung cancer cell lines from the GEO database, and subjected to genotyping analysis using the BLRMM algorithm in the Affymetrix Genotyping Console. The percent identity between the primary tumor tissue and the cell line was calculated from the number of identical SNP calls divided by the total number of SNP calls. Probesets resulting in “no call” genotyping results due to poor quality reads for either sample were not included in the analysis. For comparison, unrelated cancer cell line data of the same tumor type was included in the analysis. The cell lines reported here have grown for a minimum of 25 population doublings without evidence of cell culture crisis. The lung cancer, serous ovarian, and endometrioid ovarian cancer cell lines were positive for pan-keratin staining by immunocytochemistry. Both ovarian cancer subtypes exhibited tumorsphere formation under non-adherent culture conditions, whereas the lung cancer cell line formed loose aggregates. The percent identity between the primary carcinoma and cell line at 20, 40, and 150 population doublings was determined using a SNP call quality threshold of 0.1, resulting in an average 100K and 56K highest quality reads for breast and lung. The percent identity for the breast cancer cell line resulted in 98.7%, 97.4%, and 98.3% (mean +/- SD = 98.2% +/- 0.7%). The percent identity for the lung adenocarcinoma cell line at 20, 40, and 150 population doublings was 89.5%, 84.4%, and 87.2% (mean +/- SD = 87.0% +/- 2.5%). In comparison, the average % identity between unrelated existing breast cancer cell lines was 61.0% (+/- 3.1%) and between unrelated lung cancer cell lines was 58.7% (+/- 3.7%). These patient-specific breast and lung cancer cell lines exhibit genetically stable, extended growth from a primary tissue specimen for a minimum of 150 population doublings. We continue to measure extended growth in the ovarian cancer cell lines as well as a colon adenocarcinoma. Novel cell lines may be derived using this technology to represent specific patient groups and to serve the needs of researchers in precision medicine performing drug screening, target discovery, and the development of companion diagnostics. Citation Format: Naghmeh Salimi, Jeffrey D. Kent, Alex Chao, Bryan E. Roberts, Agoston Agoston, Elin S. Agoston. Patient-specific cancer cell line derivation methodology results in genetic stability across 150 population doublings. [abstract]. In: Proceedings of the AACR Precision Medicine Series: Integrating Clinical Genomics and Cancer Therapy; Jun 13-16, 2015; Salt Lake City, UT. Philadelphia (PA): AACR; Clin Cancer Res 2016;22(1_Suppl):Abstract nr 33.