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Landa, Iñigo; Pozdeyev, Nikita; Korch, Christopher; Marlow, Laura A; Smallridge, Robert C; Copland, John A; Henderson, Ying C; Lai, Stephen Y; Clayman, Gary L; Onoda, Naoyoshi; Tan, Aik Choon; Garcia-Rendueles, Maria E R; Knauf, Jeffrey A; Haugen, Bryan R; Fagin, James A; Schweppe, Rebecca E
Clinical cancer research, 05/2019, Letnik: 25, Številka: 10Journal Article
Thyroid cancer cell lines are valuable models but have been neglected in pancancer genomic studies. Moreover, their misidentification has been a significant problem. We aim to provide a validated dataset for thyroid cancer researchers. We performed next-generation sequencing (NGS) and analyzed the transcriptome of 60 authenticated thyroid cell lines and compared our findings with the known genomic defects in human thyroid cancers. Unsupervised transcriptomic analysis showed that 94% of thyroid cell lines clustered distinctly from other lineages. Thyroid cancer cell line mutations recapitulate those found in primary tumors (e.g., , , or gene fusions). Mutations in the promoter (83%) and (71%) were highly prevalent. There were frequent alterations in , , and of members of the SWI/SNF chromatin remodeling complex, mismatch repair, cell-cycle checkpoint, and histone methyl- and acetyltransferase functional groups. Copy number alterations (CNA) were more prevalent in cell lines derived from advanced versus differentiated cancers, as reported in primary tumors, although the precise CNAs were only partially recapitulated. Transcriptomic analysis showed that all cell lines were profoundly dedifferentiated, regardless of their derivation, making them good models for advanced disease. However, they maintained the BRAF versus RAS-dependent consequences on MAPK transcriptional output, which correlated with differential sensitivity to MEK inhibitors. Paired primary tumor-cell line samples showed high concordance of mutations. Complete loss of p53 function in heterozygous tumors was the most prominent event selected during immortalization. This cell line resource will help inform future preclinical studies exploring tumor-specific dependencies.
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JCR | SNIP | JCR | SNIP | JCR | SNIP | JCR | SNIP |
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in: SICRIS
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