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Molecular classification and prognostication of adrenocortical tumors by transcriptome profiling.

ABSTRACT: Our understanding of adrenocortical carcinoma (ACC) has improved considerably, yet many unanswered questions remain. For instance, can molecular subtypes of ACC be identified? If so, what is their underlying pathogenetic basis and do they possess clinical significance?We did a whole genome gene expression study of a large cohort of adrenocortical tissues annotated with clinicopathologic data. Using Affymetrix Human Genome U133 Plus 2.0 oligonucleotide arrays, transcriptional profiles were generated for 10 normal adrenal cortices (NC), 22 adrenocortical adenomas (ACA), and 33 ACCs.The overall classification of adrenocortical tumors was recapitulated using principal component analysis of the entire data set. The NC and ACA cohorts showed little intragroup variation, whereas the ACC cohort revealed much greater variation in gene expression. A robust list of 2,875 differentially expressed genes in ACC compared with both NC and ACA was generated and used in functional enrichment analysis to find pathways and attributes of biological significance. Cluster analysis of the ACCs revealed two subtypes that reflected tumor proliferation, as measured by mitotic counts and cell cycle genes. Kaplan-Meier analysis of these ACC clusters showed a significant difference in survival (P < 0.020). Multivariate Cox modeling using stage, mitotic rate, and gene expression data as measured by the first principal component for ACC samples showed that gene expression data contains significant independent prognostic information (P < 0.017).This study lays the foundation for the molecular classification and prognostication of adrenocortical tumors and also provides a rich source of potential diagnostic and prognostic markers.

SUBMITTER: Giordano TJ

PROVIDER: S-EPMC2629378 | biostudies-literature | 2009 Jan

REPOSITORIES: biostudies-literature

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Molecular classification and prognostication of adrenocortical tumors by transcriptome profiling.

Giordano Thomas J TJ Kuick Rork R Else Tobias T Gauger Paul G PG Vinco Michelle M Bauersfeld Juliane J Sanders Donita D Thomas Dafydd G DG Doherty Gerard G Hammer Gary G

Clinical cancer research : an official journal of the American Association for Cancer Research 20090101 2

<h4>Purpose</h4>Our understanding of adrenocortical carcinoma (ACC) has improved considerably, yet many unanswered questions remain. For instance, can molecular subtypes of ACC be identified? If so, what is their underlying pathogenetic basis and do they possess clinical significance?<h4>Experimental design</h4>We did a whole genome gene expression study of a large cohort of adrenocortical tissues annotated with clinicopathologic data. Using Affymetrix Human Genome U133 Plus 2.0 oligonucleotide ...[more]

PMID: 19147773

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Project description:Prognosis and therapeutic management of dogs with cutaneous mast cell tumors (MCTs) depend on clinical stage and histological grade. However, the prognostic value of this latter is still questionable. In the present study, MCT transcriptome was analyzed to identify a set of candidate genes potentially useful for predicting the biological behavior of MCTs. Fifty-one canine MCT biopsies were analyzed. Isolated and purified total RNAs were individually hybridized to the Agilent Canine V2 4x44k DNA microarray. The comparison of reference differentiated and undifferentiated MCT transcriptome revealed a total of 597 differentially expressed genes (147 down-regulated and 450 up-regulated). The functional analysis of this set of genes provided evidence that they were mainly involved in cell cycle, DNA replication, p53 signaling pathway, nucleotide excision repair and pyrimidine metabolism. Class prediction analysis identified 13 transcripts providing the greatest accuracy of class prediction and divided samples into two categories (differentiated and undifferentiated), harboring a different prognosis. The Principal Component Analysis of all samples, made by using the selected 13 markers, confirmed MCT classification. The first three components accounted for 99.924% of the total variance. This molecular classification significantly correlated with survival time (p = 0.0026). Furthermore, among all marker genes, a significant association was found between mRNA expression and MCT-related mortality for FOXM1, GSN, FEN1 and KPNA2 (p<0.05). Finally, marker genes mRNA expression was evaluated in a cohort of 22 independent samples. Data obtained enabled to identify MCT cases with different prognosis. Overall, the molecular characterization of canine MCT transcriptome allowed the identification of a set of 13 transcripts that clearly separated differentiated from undifferentiated MCTs, thus predicting outcome regardless of the histological grade. These results may have clinical relevance and warrant future validation in a prospective study.

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:Pediatric adrenocortical carcinomas (ACCs) are aggressive; the overall survival of patients with ACCs is 40%-50%. Appropriate staging and histologic classification are crucial because children with incomplete resections, metastases, or relapsed disease have a dismal prognosis. The clinical course of pediatric adrenocortical tumors (ACTs) is difficult to predict using the current classification schemas, which rely on subjective microscopic and gross macroscopic variables. Recent advances in adult ACT studies have revealed distinct DNA methylation patterns with prognostic significance that have not been systematically interrogated in the pediatric population. We performed DNA methylation analyses on 48 newly diagnosed ACTs from the International Pediatric Adrenocortical Tumor Registry and 12 pediatric adrenal controls to evaluate for distinct methylation groups. Pediatric methylation data were also compared systematically with the adult ACC cohort from The Cancer Genome Atlas (TCGA). Two pediatric ACT methylation groups were identified and showed differences in selected clinicopathologic and outcome characteristics. The A1 group was enriched for CTNNB1 variants and unfavorable outcome. The A2 group was enriched for TP53 germline variants, younger age at onset, and favorable outcome. Pediatric ACT methylation groups were maintained when International Pediatric Adrenocortical Tumor Registry cohort data were combined with TCGA cohort data. The CpG-island hypermethylator phenotype characterizing the TCGA cohort was not identified in the pediatric patients. When methylome findings were combined with independent histopathologic review using the Wieneke criteria, a high-risk population was identified with uniform fatal outcome. Our results indicate DNA methylation analysis can enhance current diagnostic algorithms. A combination of methylation and histologic classification produced the strongest prediction model and may prove useful in future risk-adapted therapeutic trials.

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Molecular classification and prognostication of adrenocortical tumors by transcriptome profiling.

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Molecular classification and prognostication of adrenocortical tumors by transcriptome profiling.

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