Figure 6 from A Database Tool Integrating Genomic and Pharmacologic Data from Adrenocortical Carcinoma Cell Lines, PDX, and Patient Samples

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posted on 2024-10-30, 15:00 authored by Yasuhiro Arakawa, Fathi Elloumi, Sudhir Varma, Prashant Khandagale, Ukhyun Jo, Suresh Kumar, Nitin Roper, William C. Reinhold, Robert W. Robey, Naoko Takebe, Michael M. Gottesman, Craig J. Thomas, Valentina Boeva, Alfredo Berruti, Andrea Abate, Mariangela Tamburello, Sandra Sigala, Constanze Hantel, Isabel Weigand, Margaret E. Wierman, Katja Kiseljak-Vassiliades, Jaydira Del Rivero, Yves Pommier

Examples of gene copy number variations and mutations in the ACC cell lines. A, CU-ACC1 is defective in CDKN2A. Univariate scatterplot of CDKN2A transcriptional expression levels vs. CDKN2A gene copy number in the ACC NCI cell line data set. B, Gene mutations in the ACC cell lines; mutation scores were collected from the Colorado, Zurich, and Wurzburg datasets and plotted; CU-ACC2, MUC-1 and JIL-2266 are homozygous TP53 mutants, CU-ACC1 and H595R exhibit heterozygous β-catenin (CTNNB1) mutations. C, CU-ACC2 harbor homozygous NF1 gene mutation and heterozygous NF2 gene mutation in the ACC NCI cell line data set.

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ARTICLE ABSTRACT

Adrenocortical carcinoma (ACC) is a rare and highly heterogeneous disease with a notably poor prognosis due to significant challenges in diagnosis and treatment. Emphasizing on the importance of precision medicine, there is an increasing need for comprehensive genomic resources alongside well-developed experimental models to devise personalized therapeutic strategies. We present ACC_CellMinerCDB, a substantive genomic and drug sensitivity database (available at https://discover.nci.nih.gov/acc_cellminercdb) comprising ACC cell lines, patient-derived xenografts, surgical samples, and responses to more than 2,400 drugs examined by the NCI and National Center for Advancing Translational Sciences. This database exposes shared genomic pathways among ACC cell lines and surgical samples, thus authenticating the cell lines as research models. It also allows exploration of pertinent treatment markers such as MDR-1, SOAT1, MGMT, MMR, and SLFN11 and introduces the potential to repurpose agents like temozolomide for ACC therapy. ACC_CellMinerCDB provides the foundation for exploring larger preclinical ACC models. ACC_CellMinerCDB, a comprehensive database of cell lines, patient-derived xenografts, surgical samples, and drug responses, reveals shared genomic pathways and treatment-relevant markers in ACC. This resource offers insights into potential therapeutic targets and the opportunity to repurpose existing drugs for ACC therapy.