Activity of APOBEC3A, APOBEC3B, REV1, UNG, and FHIT is Associated with Drug Sensitivity in Specific Cancer Subtypes

Authors

• S Vural
• R Simon
• J Krushkal

Abstract

We used gene expression information and mutational signature analysis of cell lines from a diverse range of cancerous tissues to examine the activity of two members of the APOBEC family of cytidine deaminases, APOBEC3A and APOBEC3B, and three additional genes. APOBEC3B is known to increase the mutation load in many cancers, generating kataegis clusters of closely spaced, single strand-specific DNA substitutions with a characteristic hypermutation signature. Some studies also suggested that APOBEC3A, REV1, UNG, and FHIT may also participate in hypermutation processes associated with APOBEC activity. We investigated how the activities of these five genes may affect the abundance of APOBEC-like signatures and whether they may be associated with sensitivity of cancer cells to treatment in different cancer categories. We analyzed several data sources for 1,408 cell lines from 26 cancer types available from the Cancer Cell Line Encyclopedia (CCLE) and the Genomics of Drug Sensitivity in Cancer (GDSC) resources. These data included whole exome sequencing (WES) data, microarray gene expression information, and drug sensitivity information. We examined correlations of the abundance of APOBEC-associated motifs and WES-wide mutation loads with APOBEC3A, APOBEC3B, REV1, UNG, and FHIT gene expression, as well as their association with cell line chemosensitivity to 255 antitumor drugs in multiple cancer subtypes. We were able to confirm several previously reported expression and chemosensitivity associations and found additional correlations, which may be clinically important. Sensitivity to JQ1, JNK inhibitors AS601245 and VIII, BMS-509744, bicalutamide, and several other agents was correlated with candidate gene expression levels or with abundance of APOBEC-like motif clusters in specific cancer categories such as pancreatic, breast and non-small cell lung cancer cell lines. For example, we observed a strong negative correlation between APOBEC3A expression in pancreatic cell lines and sensitivity to JQ1, a BET inhibitor, which had been reported to inhibit pancreatic cancer cells in vitro and in vivo. In glioma cell lines, APOBEC3B expression was significantly negatively correlated with sensitivity to a CDK9 inhibitor THZ-2-49 and HSP90 inhibitors AUY922 and 17-AAG (tanespimycin). We observed a strong correlation between the combined length of kataegis clusters and chemoresistance to bicalutamide, a nonsteroidal antiandrogen drug, in breast cancer cell lines. Our findings suggest that associations of sensitivity to drug treatment with activities of APOBEC3A/B, REV1, UNG, and FHIT and with the rates of APOBEC-associated mutagenic processes may vary among different cancer categories.

Scientific Focus Area: Computational Biology

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