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A Targeted Bioinformatics Assessment of Adrenocortical Carcinoma Reveals Prognostic Implications of GABA System Gene Expression.

ABSTRACT: Adrenocortical carcinoma (ACC) is a rare but deadly cancer for which few treatments exist. Here, we have undertaken a targeted bioinformatics study of The Cancer Genome Atlas (TCGA) ACC dataset focusing on the 30 genes encoding the ?-aminobutyric acid (GABA) system-an under-studied, evolutionarily-conserved system that is an emerging potential player in cancer progression. Our analysis identified a subset of ACC patients whose tumors expressed a distinct GABA system transcriptome. Transcript levels of ABAT (encoding a key GABA shunt enzyme), were upregulated in over 40% of tumors, and this correlated with several favorable clinical outcomes including patient survival; while enrichment and ontology analysis implicated two cancer-related biological pathways involved in metastasis and immune response. The phenotype associated with ABAT upregulation revealed a potential metabolic heterogeneity among ACC tumors associated with enhanced mitochondrial metabolism. Furthermore, many GABA_A receptor subunit-encoding transcripts were expressed, including two (GABRB2 and GABRD) prognostic for patient survival. Transcripts encoding GABA_B receptor subunits and GABA transporters were also ubiquitously expressed. The GABA system transcriptome of ACC tumors is largely mirrored in the ACC NCI-H295R cell line, suggesting that this cell line may be appropriate for future functional studies investigating the role of the GABA system in ACC cell growth phenotypes and metabolism.

SUBMITTER: Knott EL

PROVIDER: S-EPMC7697095 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

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A Targeted Bioinformatics Assessment of Adrenocortical Carcinoma Reveals Prognostic Implications of GABA System Gene Expression.

Knott Erika L EL Leidenheimer Nancy J NJ

International journal of molecular sciences 20201111 22

Adrenocortical carcinoma (ACC) is a rare but deadly cancer for which few treatments exist. Here, we have undertaken a targeted bioinformatics study of The Cancer Genome Atlas (TCGA) ACC dataset focusing on the 30 genes encoding the γ-aminobutyric acid (GABA) system-an under-studied, evolutionarily-conserved system that is an emerging potential player in cancer progression. Our analysis identified a subset of ACC patients whose tumors expressed a distinct GABA system transcriptome. Transcript lev ...[more]

PMID: 33187258

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Project description:ImportanceThe risk stratification of adrenocortical carcinoma (ACC) based on tumor proliferation index and stage is limited. Adjuvant therapy after surgery is recommended for most patients. Pan-genomic studies have identified distinct molecular groups closely associated with outcome.ObjectiveTo compare the molecular classification for prognostic assessment of ACC with other known prognostic factors.Design, setting, and participantsIn this retrospective biomarker analysis, ACC tumor samples from 368 patients who had undergone surgical tumor removal were collected from March 1, 2005, to September 30, 2015 (144 in the training cohort and 224 in the validation cohort) at 21 referral centers with a median follow-up of 35 months (interquartile range, 18-74 months). Data were analyzed from March 2016 to March 2018.ExposuresMeta-analysis of pan-genomic studies (transcriptome, methylome, chromosome alteration, and mutational profiles) was performed on the training cohort. Targeted biomarker analysis, including targeted gene expression (BUB1B and PINK1), targeted methylation (PAX5, GSTP1, PYCARD, and PAX6), and targeted next-generation sequencing, was performed on the training and validation cohorts.Main outcomes and measuresDisease-free survival. Cox proportional hazards regression and C indexes were used to assess the prognostic value of each model.ResultsOf the 368 patients (mean [SD] age, 49 [16] years), 144 were in the training cohort (100 [69.4%] female) and 224 were in the validation cohort (142 [63.4%] female). In the training cohort, pan-genomic measures classified ACC into 3 molecular groups (A1, A2, and A3-B), with 5-year survival of 9% for group A1, 45% for group A2, and 82% for group A3-B (log-rank P < .001). Molecular class was an independent prognostic factor of recurrence in stage I to III ACC after complete surgery (hazard ratio, 55.91; 95% CI, 8.55-365.40; P < .001). The combination of European Network for the Study of Adrenal Tumors (ENSAT) stage, tumor proliferation index, and molecular class provided the most discriminant prognostic model (C index, 0.88). In the validation cohort, the molecular classification, determined by targeted biomarker measures, was confirmed as an independent prognostic factor of recurrence (hazard ratio, 5.96 [95% CI, 1.81-19.58], P = .003 for the targeted classifier combining expression, methylation, and chromosome alterations; and 2.61 [95% CI, 1.31-5.19], P = .006 for the targeted classifier combining methylation, chromosome alterations, and mutational profile). The prognostic value of the molecular markers was limited for patients with stage IV ACC.Conclusions and relevanceThe findings suggest that in localized ACC, targeted classifiers may be used as independent markers of recurrence. The determination of molecular class may improve individual prognostic assessment and thus may spare unnecessary adjuvant treatment.

Project description:BACKGROUND:The 7th AJCC T-stage system for adrenocortical carcinoma (ACC), based on size and extra-adrenal invasion, does not adequately stratify patients by survival. Lymphovascular invasion (LVI) is a known poor prognostic factor. We propose a novel T-stage system that incorporates LVI to better risk-stratify patients undergoing resection for ACC. METHOD:Patients undergoing curative-intent resections for ACC from 1993 to 2014 at 13 institutions comprising the US ACC Group were included. Primary outcome was disease-specific survival (DSS). RESULTS:Of the 265 patients with ACC, 149 were included for analysis. The current T-stage system failed to differentiate patients with T2 versus T3 disease (p = 0.10). Presence of LVI was associated with worse DSS versus no LVI (36 mo vs. 168 mo; p = 0.001). After accounting for the individual components of the current T-stage system (size, extra-adrenal invasion), LVI remained a poor prognostic factor on multivariable analysis (hazard ratio 2.14, 95% confidence interval 1.05-4.38, p = 0.04). LVI positivity further stratified patients with T2 and T3 disease (T2: 37 mo vs. median not reached; T3: 36 mo vs. 96 mo; p = 0.03) but did not influence survival in patients with T1 or T4 disease. By incorporating LVI, a new T-stage classification system was created: [T1: ≤ 5 cm, (-)local invasion, (+/-)LVI; T2: > 5 cm, (-)local invasion, (-)LVI OR any size, (+)local invasion, (-)LVI; T3: > 5 cm, (-)local invasion, (+)LVI OR any size, (+)local invasion, (+)LVI; T4: any size, (+)adjacent organ invasion, (+/-)LVI]. Each progressive new T-stage group was associated with worse median DSS (T1: 167 mo; T2: 96 mo; T3: 37 mo; T4: 15 mo; p < 0.001). CONCLUSIONS:Compared with the current T-stage system, the proposed T-stage system, which incorporates LVI, better differentiates T2 and T3 disease and accurately stratifies patients by disease-specific survival. If externally validated, this T-stage classification should be considered for future AJCC staging systems.

Dataset Information

A Targeted Bioinformatics Assessment of Adrenocortical Carcinoma Reveals Prognostic Implications of GABA System Gene Expression.

Publications

A Targeted Bioinformatics Assessment of Adrenocortical Carcinoma Reveals Prognostic Implications of GABA System Gene Expression.

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