Adrenocortical cancer cell line mutational profile reveals aggressive genetic background

in Journal of Molecular Endocrinology
Correspondence should be addressed to T Carling: tobias.carling@yale.edu

Preliminary data originally presented at the 13th Academic Surgical Congress, Jacksonville, Florida, January 30 through February 1, 2018

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Adrenocortical carcinomas are rare tumors with poor prognosis and limited treatment options. Although widely used as in vitro models to test novel therapeutic strategies, the adrenocortical carcinoma-derived cell lines NCI-H295R and SW-13 have only partially been described genetically. Our aim was to characterize the mutational landscape of these cells to improve their experimental utility and map them to clinical subtypes of adrenocortical carcinoma. Genomic DNA from NCI-H295R and SW-13 cells was subjected to whole-exome sequencing. Variants were filtered for non-synonymous mutations and curated for validated adrenocortical and pan-cancer driver gene mutations. Genes mutated in the cell lines were mapped using gene ontology and protein pathway tools to determine signaling effects and compared to mutational and clinical characteristics of 92 adrenocortical carcinoma cases from The Cancer Genome Atlas. NCI-H295R and SW-13 cells carried 1325 and 1836 non-synonymous variants, respectively. Of these, 61 and 76 were known cancer driver genes, of which 32 were shared between cell lines. Variant interaction analyses demonstrated dominant TP53 dysregulation in both cell lines complemented by distinct WNT (NCI-H295R) and chromatin remodeling (SW-13) pathway perturbations. Both cell lines genetically resemble more aggressive adrenocortical carcinomas with worse prognosis, for which development of targeted therapies is most critical. Careful incorporation of the genetic landscapes outlined in this study will further the in vitro utility of these cell lines in testing for novel therapeutic approaches for adrenocortical malignancy.

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    ACC, pan-cancer and ACC cell line driver mutations. Driver mutations are noted in each cell line, compared to ACC driver mutations identified in the three largest whole-exome sequencing studies of ACC tumors. Of note, TERT mutations identified in prior studies have been in the promoter region, not sequenced for our study. Genes annotated in COSMIC or IntOGen are also noted. Blue color indicates mutated genes. *The NCI-H295R mutation in TP53 is a previously shown homozygous deletion of two exons, not detectable using whole-exome sequencing. A full colour version of this figure is available at https://doi.org/10.1530/JME-18-0262.

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    Survival analysis of SW-13 type and NCI-H295R type TCGA cases. (A) SW-13 type cases demonstrate markedly worse overall survival when compared to the remainder of the cohort (log-rank P = 0.0005). (B) NCI-H295R type cases demonstrate a trend toward worse survival, but this was not statistically significant (log-rank P = 0.19).

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    NCI-H295R and SW-13 shared driver mutations. Driver genes carrying non-synonymous mutations in both cell lines, with protein–protein connections, mapped using the STRING database (Szklarczyk et al. 2017). TP53 and related genes are the nexus in this network, common to both cell lines. Genes with no connections identified are not displayed. A full colour version of this figure is available at https://doi.org/10.1530/JME-18-0262.

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    SW-13 private driver mutations. Driver genes carrying non-synonymous mutations in the SW-13 cell line, with protein–protein connections, mapped using the STRING database (Szklarczyk et al. 2017). SMARCA4, EP300 and related genes are involved in gene expression regulation via chromatin remodeling. Genes with no connections identified are not displayed. A full colour version of this figure is available at https://doi.org/10.1530/JME-18-0262.

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    NCI-H295R private driver mutations. Driver genes carrying non-synonymous mutations in the NCI-H295R cell line, with protein–protein connections, mapped using the STRING database (Szklarczyk et al. 2017). The WNT/β-catenin pathway (of which CTNNB1 is the key effector) is the most common pathway affected in ACC. Genes with no connections identified are not displayed. A full colour version of this figure is available at https://doi.org/10.1530/JME-18-0262.

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