Abstract 2408: Targeted bioinformatics analysis identifies high ABAT transcript expression as a multi-cancer marker of favorable patient prognosis

Abstract

Abstract Unsupervised analysis of γ-aminobutyric acid (GABA) system genes has identified some genes as correlated with indicators of severity in several cancers. Central to GABA system function is the GABA shunt, a series of reactions bypassing two steps of the tricarboxylic acid (TCA) cycle, which encompasses the synthesis and metabolism of the non-proteinaceous amino acid GABA. Here, we have undertaken a targeted bioinformatics study utilizing publicly available databases - including cBioPortal, UALCAN, the Human Protein Atlas, and the Human Cancer Metastasis Database - to evaluate the expression of transcripts encoding GABA shunt enzymes, and their correlation with clinical outcomes, across nearly three dozen cancers from The Cancer Genome Atlas (TCGA) Pan-Cancer Atlas initiative dataset. Of the three genes encoding enzymes of the GABA shunt, we have focused on ABAT, which encodes the GABA-catabolizing enzyme γ-aminobutyrate aminotransferase (ABAT; aka GABA-transaminase or GABA-T). ABAT is widely expressed across all 32 TCGA studies, ranging from moderate to high expression in skin cutaneous melanoma and low-grade glioma (average ± SEM = 6.5 ± 0.08; 13.3 ± 0.03 log2 RSEM), respectively. For the majority of these tissues, the expression of ABAT in tumor is lower than its expression in adjacent normal tissue. Importantly, ABAT expression is prognostic in 11 cancers: upregulation is favorably prognostic for ACC, BLCA, BRCA, and PAAD, while downregulation is unfavorably prognostic for KIRC, KIRP, LGG, LIHC, LUAD, MESO, and SKCM (Kaplan-Meier survival estimates, z-score = 0.5, p < 0.05). A subset of these cancers, as well as 4 other TCGA cancers, show a decrease in ABAT transcript expression with increasing tumor stage (p < 0.05). Furthermore, 7 cancers express lower levels of ABAT transcripts in the primary tumors of patients with metastases vs the primary tumors of patients without metastases. Additionally, metastases of 4 cancers express elevated levels of ABAT transcripts vs their respective primary tumors. These results imply a dynamic regulation of ABAT expression throughout cancer progression. As very few studies have directly addressed the role of ABAT in cancer progression, the identification of ABAT transcript expression as a broadly applicable multi-cancer prognostic marker may ultimately benefit a wide variety of patients. We would like to thank the Feist-Weiller Cancer Center and LSU Health, Shreveport for supporting this work. Citation Format: Erika L. Knott, Nancy J. Leidenheimer. Targeted bioinformatics analysis identifies high ABAT transcript expression as a multi-cancer marker of favorable patient prognosis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2408.