Genetically-defined novel oral squamous cell carcinoma cell lines for the development of molecular therapies

用于开发分子疗法的基因定义的新型口腔鳞状细胞癌细胞系

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作者:Muhammad Zaki Hidayatullah Fadlullah, Ivy Kim-Ni Chiang, Kalen R Dionne, Pei San Yee, Chai Phei Gan, Kin Kit Sam, Kai Hung Tiong, Adrian Kwok Wen Ng, Daniel Martin, Kue Peng Lim, Thomas George Kallarakkal, Wan Mahadzir Wan Mustafa, Shin Hin Lau, Mannil Thomas Abraham, Rosnah Binti Zain, Zainal Ariff

Abstract

Emerging biological and translational insights from large sequencing efforts underscore the need for genetically-relevant cell lines to study the relationships between genomic alterations of tumors, and therapeutic dependencies. Here, we report a detailed characterization of a novel panel of clinically annotated oral squamous cell carcinoma (OSCC) cell lines, derived from patients with diverse ethnicity and risk habits. Molecular analysis by RNAseq and copy number alterations (CNA) identified that the cell lines harbour CNA that have been previously reported in OSCC, for example focal amplications in 3q, 7p, 8q, 11q, 20q and deletions in 3p, 5q, 8p, 18q. Similarly, our analysis identified the same cohort of frequently mutated genes previously reported in OSCC including TP53, CDKN2A, EPHA2, FAT1, NOTCH1, CASP8 and PIK3CA. Notably, we identified mutations (MLL4, USP9X, ARID2) in cell lines derived from betel quid users that may be associated with this specific risk factor. Gene expression profiles of the ORL lines also aligned with those reported for OSCC. By focusing on those gene expression signatures that are predictive of chemotherapeutic response, we observed that the ORL lines broadly clustered into three groups (cell cycle, xenobiotic metabolism, others). The ORL lines noted to be enriched in cell cycle genes responded preferentially to the CDK1 inhibitor RO3306, by MTT cell viability assay. Overall, our in-depth characterization of clinically annotated ORL lines provides new insight into the molecular alterations synonymous with OSCC, which can facilitate in the identification of biomarkers that can be used to guide diagnosis, prognosis, and treatment of OSCC.

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