Genome-scale methylome profiling of adrenocortical carcinomas (ACC) and adenomas (ACA)
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
SUBMITTER: 
Olivia Barreau Windy Luscap Eric Letouzé Aurélien de Reyniès Nabila Elarouci Jérome Bertherat Guillaume Assié
PROVIDER: E-GEOD-49277 | ArrayExpress | 2014-04-29
SECONDARY ACCESSION(S): GSE49277PRJNA213473
REPOSITORIES: GEO, ArrayExpress
Dataset's files
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| E-GEOD-49277.additional.1.zip | Other | |||
| E-GEOD-49277.idf.txt | Idf | |||
| E-GEOD-49277.processed.1.zip | Processed | |||
| E-GEOD-49277.sdrf.txt | Txt |
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Project description:Adrenocortical carcinoma (ACC) is an aggressive malignancy with high rates of recurrence following surgical resection. Long noncoding RNAs (lncRNAs) play an important role in cancer development. Pathogenesis of adrenal tumours has been characterised by mRNA, microRNA and methylation expression signatures but it is unknown if this extends to lncRNAs. We sought to describe lncRNA expression signatures in adrenocortical carcinoma (ACC), adrenal cortical adenoma (ACA) and normal adrenal cortex (NAC). RNA was extracted from freshly frozen tissue with confirmation of diagnosis by histopathology. Focused lncRNA and mRNA transcriptome analysis was performed using the ArrayStar Human LncRNA V3.0 microarray. Differentially expressed lncRNAs were validated using qRT-PCR. Overall design: 21 samples were used in total, 15 cases were included (10 ACCs and 5 ACAs) and compared to 6 controls (NAC). Differentially expressed lncRNAs were selected if they had a minimum fold change of 2.0 up or down regulated and a P-value corrected by the false discovery rate of equal to or less than 0.05.
2015-01-01 | GSE61359 | GEO
Project description:PURPOSE:We have reported previously nonsense inactivating mutations of the phosphodiesterase 11A (PDE11A) gene in patients with micronodular adrenocortical hyperplasia and Cushing syndrome. The aim of this study is to investigate the presence of somatic or germ-line PDE11A mutations in various types of adrenocortical tumors: ACTH-independent macronodular adrenocortical hyperplasia (AIMAH), adrenocortical adenoma (ACA), and adrenocortical cancer (ACC). EXPERIMENTAL DESIGN:PDE11A was sequenced in 117 adrenocortical tumors and 192 controls subjects; immunohistochemistry for PDE11A and tumor cyclic AMP levels were studied in a subgroup of adrenocortical tumors. RESULTS:One PDE11A inactivating mutation (R307X) was found in one ACA, 22 germ-line missense variants (18.8%) were found in adrenocortical tumors, and only 11 missense variants (5.7%) were found in controls. By comparing the common mutations, a higher frequency of mutations in adrenocortical tumors than in age/sex-matched controls were observed [16% versus 10% in ACC, 19% versus 10% in ACA, and 24% versus 9% in AIMAH; odds ratio (OR), 3.53; P = 0.05]. Somatic DNA from adrenocortical tumors with missense variants showed a wild-type allelic loss. A significant difference between ACC and controls was observed for a polymorphism in exon 6 (E421E; OR, 2.1; P = 0.03) and three associated polymorphisms located in intron 10-exon 11-intron 11 (OR, 0.5; P = 0.01). In AIMAH/ACA, cyclic AMP levels were higher than in normal adrenals and decreased PDE11A immunostaining was present in adrenocortical tumors with PDE11A variants. CONCLUSIONS:The present investigation of a large cohort of adrenocortical tumors suggests that PDE11A sequence defects predispose to a variety of lesions (beyond micronodular adrenocortical hyperplasia) and may contribute to the development of these tumors in the general population.
2008-01-01 | S-EPMC3134879 | BioStudies
Project description:Background: Adrenal myelolipoma (AML) is a relatively common and invariably benign tumor composed of adipose tissue and hematopoietic elements. Due to the variable proportion of fat and hematopoietic elements, it is sometimes challenging to differentiate AML from adrenocortical carcinoma (ACC). MicroRNAs have been identified as promising biomarkers in many tumors, including adrenocortical neoplasms, but the microRNA expression of adrenal myelolipoma has not been investigated, yet. Aims: To perform a large scale microRNA expression profiling in adrenal myelolipoma, benign and malignant adrenocortical tumors to identify potential microRNA biomarkers. Methods: Next-generation sequencing (NGS) on 30 formalin-fixed paraffin-embedded archived tissue samples (discovery cohort: 10 adrenocortical adenoma (ACA), 10 ACC and 10 myelolipoma) was performed by Illumina MiSeq. Significantly differentially expressed microRNAs were validated by real-time RT-qPCR in an independent validation cohort comprised of 10 ACA, 10 myelolipoma and 9 ACC samples. Results: We have found relative overexpression of miR- 451a, miR-486-5p, miR-363-3p and miR-150-5p in myelolipoma compared to the other two tumor groups by NGS. For ACC, we have found up-regulation of miR-184, miR-483-5p, miR-431-5p and miR-183-5p compared to myelolipoma and ACA. Validation by RT-qPCR, confirmed significant overexpression of miR-451a, miR-486-5p and miR-150-5p in myelolipomas relative to ACA and ACC, whereas significant overexpression of miR-184 and miR-183-5p was confirmed in ACC relative to the other 2 groups. The overexpression of miR-483-5p has not turned out to be significant in ACC relative to myelolipomas in the validation cohort. Conclusions: Overexpressed miR-451a, miR-486-5p and miR-150-5p might be potential tissue markers of adrenal myelolipoma. The lack of significance in the expression of miR-483-5p between ACC and myelolipoma is remarkable, as miR-483-5p has been considered to be the best marker of adrenal malignancy to date. Overall design: Altogether 30 samples were investigated by high-throughput microRNA expression profiling
2018-04-07 | GSE112804 | GEO
Project description: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.
2009-01-01 | S-EPMC2629378 | BioStudies
Project description:Adrenocortical carcinomas (ACC) are a rare tumor type with a poor five-year survival rate and limited treatment options.Understanding of the molecular pathogenesis of this disease has been aided by genomic analyses highlighting alterations in TP53, WNT, and IGF signaling pathways. Further elucidation is needed to reveal therapeutically actionable targets in ACC.In this study, global DNA methylation levels were assessed by the Infinium HumanMethylation450 BeadChip Array on 18 ACC tumors and 6 normal adrenal tissues. A new, non-linear correlation approach, the discretization method, assessed the relationship between DNA methylation/gene expression across ACC tumors.This correlation analysis revealed epigenetic regulation of genes known to modulate TP53, WNT, and IGF signaling, as well as silencing of the tumor suppressor MARCKS, previously unreported in ACC.DNA methylation may regulate genes known to play a role in ACC pathogenesis as well as known tumor suppressors.
2016-01-01 | S-EPMC4786116 | BioStudies
Project description:BACKGROUND:Adrenocortical adenomas (ACAs) can lead to the autonomous secretion of aldosterone responsible for primary aldosteronism (PA), which is the most common form of secondary arterial hypertension. However, the authentic fundamental mechanisms underlying ACAs remain unclear. OBJECTIVE:Isobaric tags for relative and absolute quantitation (iTRAQ)-based proteomics and bioinformatics analyses from etiological studies of ACAs were performed to screen the differentially expressed proteins (DEPs) and investigate the relevant mechanisms of their occurrence and development. Results could help determine therapeutic targets of clinical significance. METHODS:In the present study, iTRAQ-based proteomics was applied to analyze ACA tissue samples from normal adrenal cortex tissues adjacent to the tumor. Using proteins extracted from a panel of four pairs of ACA samples, we identified some upregulated proteins and other downregulated proteins in all four pairs of ACA samples compared with adjacent normal tissue. Subsequently, we predicted protein-protein interaction networks of three DEPs to determine the authentic functional factors in ACA. RESULTS:A total of 753 DEPs were identified, including 347 upregulated and 406 downregulated proteins. The expression of three upregulated proteins (E2F3, KRT6A, and ALDH1A2) was validated by Western blot in 24 ACA samples. Our data suggested that some DEPs might be important hallmarks during the development of ACA. CONCLUSIONS:This study is the first proteomic research to investigate alterations in protein levels and affected pathways in ACA using the iTRAQ technique. Thus, this study not only provides a comprehensive dataset on overall protein changes but also sheds light on its potential molecular mechanism in human ACAs.
2019-01-01 | S-EPMC6697928 | BioStudies
Project description:Angiogenesis is essential for tumor growth and metastasis. Endocrine gland-derived vascular endothelial growth factor (EG-VEGF) is an angiogenic factor predominantly expressed in steroidogenic organs like the adrenal gland, ovary, testes, and placenta. EG-VEGF has antiapoptotic, mitogenic, and chemoattractive properties mediated via the two G protein-coupled receptors prokineticin receptor 1 (PKR1) and prokineticin receptor 2 (PKR2). We investigated the expression of EG-VEGF and its receptors in a large number of normal adrenal glands (NAG), adrenocortical adenomas (ACA), and carcinomas (ACC) using real-time PCR (NAG, n = 12; ACA, n = 24; and ACC, n = 30) and immunohistochemistry (NAG, n = 9; ACA, n = 23; and ACC, n = 163) and evaluated its impact on patients' survival. EG-VEGF, PKR1, and PKR2 mRNA and protein are expressed in NAG and the vast majority of ACA and ACC samples. The mean EG-VEGF mRNA expression was significantly lower in ACC (606.5 ± 77.1 copies) compared to NAG (4,043 ± 1,111) and cortisol-producing adenomas (CPA) (4,433 ± 2,378) (p < 0.01 and p < 0.05, respectively). However, cytoplasmic and nuclear EG-VEGF protein expression was either significantly higher or similar in ACC (H score 2.4 ± 0.05, p < 0.05 and 1.7 ± 0.08, n.s., respectively) compared to NAG (1.8 ± 0.14 and 1.7 ± 0.2). Nuclear protein expression of either EG-VEGF or PKR1 or both is predictive for a higher mortality compared to patients without nuclear expression (hazard ratio (HR)?= 5.15; 95% confidence interval (CI)?= 1.24-21.36, n = 100, p = 0.02 independent of age, sex, and tumor stage). These findings suggest that EG-VEGF and its receptor PKR1 might play a role in the pathogenesis of adrenocortical tumors and could serve as prognostic markers for this rare malignant disease.
2015-01-01 | S-EPMC4630243 | BioStudies
Project description:Adrenocortical carcinoma (ACC) is an aggressive malignancy with a low but variable overall survival rate. Even after complete tumor resection, over half of patients develop recurrent disease. Long noncoding RNAs (lncRNAs) have been found to be involved in cancer initiation/progression and as markers of cancer prognosis. The role of lncRNAs in ACC is poorly understood. Thus, in this study we performed lncRNA expression profiling in ACC, adrenocortical adenoma (ACA) and normal adrenal cortex (NAC). Total RNA was extracted from fresh frozen tissue samples (11 ACA, nine ACC and five NAC samples) with histopathological confirmed diagnosis. ArrayStar Human LncRNA/mRNA Expression Microarray V3.0 was used for transcriptome analysis. Differentially expressed lncRNAs were validated using TaqMan real-time quantitative PCR in a validation cohort including an additional 10 ACCs. The ACC dataset from the Cancer Genome Atlas (TCGA) project was used to evaluate the prognostic utility of lncRNAs found to be differentially expressed in ACC. Survival curves were plotted by Kaplan-Meier analysis, and differences in survival rates were assessed using a log-rank test. P < 0.05 was considered significant. Gene Set Enrichment Analysis (GSEA) was performed to identify lncRNA-associated biological signaling pathways. Unsupervised hierarchical and heat map clustering showed distinct clustering of ACC samples compared with NAC and ACA samples by lncRNA expression profiles. A total of 874 lncRNAs were differentially expressed between ACC and NAC, including known carcinogenesis-related lncRNAs such as HOTTIP, HOXA11-AS1, CRNDE, LINC00271 and TBXAS1. One thousand seventy-six lncRNAs were differentially expressed between ACC and ACA. LINC00271 was a prognostic marker, with patients with low LINC00271 expression surviving significantly shorter than patients with a high LINC00271 expression. Median survival time (MST) for the low-expression group was 1788 days, whereas the MST was not reached for the high-expression group (P < 0.019). Importantly, low LINC00271 expression was positively associated with WNT signaling, cell cycle, chromosome segregation and tissue morphogenesis pathways. ACC has a distinct lncRNA expression profile. LINC00271 is a prognostic marker in ACC and is involved in biological pathways commonly dysregulated in ACC. Overall design: 11 ACA, nine ACC and five NAC samples
2019-07-01 | GSE124531 | GEO
Project description:We describe a comprehensive genomic characterization of adrenocortical carcinoma (ACC). Using this dataset, we expand the catalogue of known ACC driver genes to include PRKAR1A, RPL22, TERF2, CCNE1, and NF1. Genome wide DNA copy-number analysis revealed frequent occurrence of massive DNA loss followed by whole-genome doubling (WGD), which was associated with aggressive clinical course, suggesting WGD is a hallmark of disease progression. Corroborating this hypothesis were increased TERT expression, decreased telomere length, and activation of cell-cycle programs. Integrated subtype analysis identified three ACC subtypes with distinct clinical outcome and molecular alterations which could be captured by a 68-CpG probe DNA-methylation signature, proposing a strategy for clinical stratification of patients based on molecular markers.
2016-01-01 | S-EPMC4864952 | BioStudies
Project description:BACKGROUND: Adrenocortical carcinoma (ACC) is a relatively rare, but aggressive type of cancer, which affects both children and adults. OBJECTIVE: Small non-coding RNAs (sncRNAs) play important roles and may serve as biomarkers for disease diagnosis, prognosis and treatment. METHODS: In our study, we sought to identify sncRNAs associated with malignant adrenal tumors. We obtained publicly available, small RNA sequencing data derived from 45 ACC and 30 benign tumors arising from the cortex of the adrenal gland, adrenocortical adenomas (ACA), and compared their sncRNA expression profiles. RESULTS: First, we remapped small RNA-seq to miRBase version 21 to check expression of miRNAs and found 147 miRNAs were aberrantly expressed (p<0.05) in ACC samples compared to ACA samples. Pathway analysis of differentially expressed miRNAs revealed p53 signaling pathways to be profoundly affected in ACC samples. Further examination for other types of small RNAs revealed 16 piRNAs, 48 lncRNAs and 19 sn/snoRNAs identified in ACC samples. Conclusions: Our data analysis suggests that publically available resources can be mined for biomarker development and improvements in-patient care; however, further research must be performed to correlate tumor grade with gene expression.
2017-01-01 | S-EPMC5607708 | BioStudies