Pathogenesis Of Adrenocortical Carcinoma Research Articles

Identification of key genes and pathways in adrenocortical carcinoma: evidence from bioinformatic analysis.

Adrenocortical carcinoma (ACC) is a rare endocrine malignancy with poor prognosis. The disease originates from the cortex of adrenal gland and lacks effective treatment. Efforts have been made to elucidate the pathogenesis of ACC, but the molecular mechanisms remain elusive. To identify key genes and pathways in ACC, the expression profiles of GSE12368, GSE90713 and GSE143383 were downloaded from the Gene Expression Omnibus (GEO) database. After screening differentially expressed genes (DEGs) in each microarray dataset on the basis of cut-off, we identified 206 DEGs, consisting of 72 up-regulated and 134 down-regulated genes in three datasets. Function enrichment analyses of DEGs were performed by DAVID online database and the results revealed that the DEGs were mainly enriched in cell cycle, cell cycle process, mitotic cell cycle, response to oxygen-containing compound, progesterone-mediated oocyte maturation, p53 signaling pathway. The STRING database was used to construct the protein-protein interaction (PPI) network, and modules analysis was performed using Cytoscape. Finally, we filtered out eight hub genes, including CDK1, CCNA2, CCNB1, TOP2A, MAD2L1, BIRC5, BUB1 and AURKA. Biological process analysis showed that these hub genes were significantly enriched in nuclear division, mitosis, M phase of mitotic cell cycle and cell cycle process. Violin plot, Kaplan-Meier curve and stage plot of these hub genes confirmed the reliability of the results. In conclusion, the results in this study provided reliable key genes and pathways for ACC, which will be useful for ACC mechanisms, diagnosis and candidate targeted treatment.

Machine learning combining multi-omics data and network algorithms identifies adrenocortical carcinoma prognostic biomarkers.

Background: Rare endocrine cancers such as Adrenocortical Carcinoma (ACC) present a serious diagnostic and prognostication challenge. The knowledge about ACC pathogenesis is incomplete, and patients have limited therapeutic options. Identification of molecular drivers and effective biomarkers is required for timely diagnosis of the disease and stratify patients to offer the most beneficial treatments. In this study we demonstrate how machine learning methods integrating multi-omics data, in combination with system biology tools, can contribute to the identification of new prognostic biomarkers for ACC. Methods: ACC gene expression and DNA methylation datasets were downloaded from the Xena Browser (GDC TCGA Adrenocortical Carcinoma cohort). A highly correlated multi-omics signature discriminating groups of samples was identified with the data integration analysis for biomarker discovery using latent components (DIABLO) method. Additional regulators of the identified signature were discovered using Clarivate CBDD (Computational Biology for Drug Discovery) network propagation and hidden nodes algorithms on a curated network of molecular interactions (MetaBase™). The discriminative power of the multi-omics signature and their regulators was delineated by training a random forest classifier using 55 samples, by employing a 10-fold cross validation with five iterations. The prognostic value of the identified biomarkers was further assessed on an external ACC dataset obtained from GEO (GSE49280) using the Kaplan-Meier estimator method. An optimal prognostic signature was finally derived using the stepwise Akaike Information Criterion (AIC) that allowed categorization of samples into high and low-risk groups. Results: A multi-omics signature including genes, micro RNA's and methylation sites was generated. Systems biology tools identified additional genes regulating the features included in the multi-omics signature. RNA-seq, miRNA-seq and DNA methylation sets of features revealed a high power to classify patients from stages I-II and stages III-IV, outperforming previously identified prognostic biomarkers. Using an independent dataset, associations of the genes included in the signature with Overall Survival (OS) data demonstrated that patients with differential expression levels of 8 genes and 4 micro RNA's showed a statistically significant decrease in OS. We also found an independent prognostic signature for ACC with potential use in clinical practice, combining 9-gene/micro RNA features, that successfully predicted high-risk ACC cancer patients. Conclusion: Machine learning and integrative analysis of multi-omics data, in combination with Clarivate CBDD systems biology tools, identified a set of biomarkers with high prognostic value for ACC disease. Multi-omics data is a promising resource for the identification of drivers and new prognostic biomarkers in rare diseases that could be used in clinical practice.

THU616 Analysis Of Germline Mutations In Patients With Sporadic Adrenocortical Carcinoma

Abstract Disclosure: M. Terzolo: None. S. Grisanti: None. M. Scatolini: None. P. Tomaiuolo: None. E. Grosso: None. V. Basile: None. D. Cosentini: None. S. Puglisi: None. M. Laganà: None. P. Perotti: None. L. Saba: None. E. Rossini: None. S. Sigala: None. M. Volante: None. A. Berruti: None. Background: Adrenocortical carcinoma (ACC) is a rare cancer associated with hereditary syndromes in 10% of cases. Germline variants (GVs) in patients with ACC have been identified mainly in pediatric patients and in family cases, while data on GVs in adult patients with sporadic ACC are limited. Methods: We analyzed germline DNA from 150 adult patients with sporadic ACC sequentially referred to our centers between 1998 and 2019. We designed a custom panel of 17 genes potentially involved in the pathogenesis of ACC: AIP, APC, ARMC5, ARNT, BRCA1, BRCA2, CTNNB1, IGF2, MEN1, MSH2, MSH6, PDE8B, PDE11A, PRKACA, PRKACB, PRKAR1A, and TP53. NGS data were analyzed by a semi-automated bioinformatic pipeline. All GVs were studied using effect predictor tools (PolyPhen and SIFT). Specific databases (ClinVar, Varsome, gnomAD, IARC TP53, HGMD) were used for variant classification according to ACMG criteria. Variants interpreted as pathogenic (P) or likely pathogenic (LP) were considered as positive. Clinical, pathological and genomic data were analyzed in different Cox models to study prognostic impact of covariates for disease-free survival (DFS), progression-free survival (PFS) and overall survival (OS). Results: We identified 21 unique GVs in 24/150 patients (16%). GVs were found in 9 genes including APC (n=3), ARMC5 (n=3), MSH2 (n=3), PDE11A (n=3), TP53 (n=3), MSH6 (n=2), PDE8B (n=2), AIP (n=1) and CTNNB1 (n=1). Eleven positive GVs including 3 GVs with deleterious potential were found in 14/150 patients (9.3%). Some variants were particularly enriched, with a frequency of 0.02% compared to an overall frequency of 0.001-0.004% in the gnomAD database. We found a new GV in TP53 (G105D) in a patient who was later found to have a sister with ACC and, for the first time, 3 GVs in ARMC5 (P731R). Patients with ARMC5 GVs had large cortisol-secreting tumors and one case displayed pathologic features of ACC and combined macronodular cortical disease. Positive GVs were associated with a shorter OS (50 vs 142 months, HR 1.81; 95%CI, 0.86-3.82, p=0.118) and PFS (8 vs 30 months, HR 3.11; 95%CI, 1.57-6.16, p=0.001) but not DFS (27 vs 32 months, HR 1.07; 95%CI, 0.52-2.22, p=0.845). At multivariate analysis, known clinical factors (age, surgery of primary ACC, ENSAT stage, hypercortisolism) were found to have prognostic impact on OS. However, GVs remained independent predictors of PFS and OS in metastatic patients. Conclusions: In a series of 150 patients with ACC, we found that 9.3% of them had positive GVs, thus confirming findings from the TCGA analysis. We describe for the first time the presence of ARMC5 GVs in patients with ACC and we found a novel pathogenic variant of TP53. Pathologic features of one ARMC5 case suggest a possible progression from macronodular hyperplasia to ACC. Finally, the present findings suggest that GVs can affect ACC progression and survival of affected patients. Presentation: Thursday, June 15, 2023

Adrenocortical carcinoma: Diagnosis, prognostic classification and treatment of localized and advanced disease

Adrenocortical carcinoma (ACC) is a rare cancer with an estimated incidence of 0.7 to 2.0 cases per 1 million population per year in the United States. It is an aggressive cancer originating in the cortex of the adrenal gland with a poor prognosis. The 5-year survival rate is less than 15% among patients with metastatic disease. In this article, we review the epidemiology and pathogenesis of ACC, the diagnostic procedures, the prognostic classification of ACC, and the treatment options from localized and resectable forms to advanced disease detailing recent therapeutic developments such as immunotherapy and molecularly targeted therapy.

Identification of a ferroptosis-related long noncoding RNA signature with a prognostic value in adrenocortical carcinoma.

Background: Adrenocortical carcinoma (ACC) is an uncommon endocrine malignancy associated with poor clinical outcome. As a novel form of cell death, ferroptosis is reliant on the accumulation of iron and reactive oxygen species and is involved in the pathogenesis of various tumors, including ACC. Our study aimed to identify and characterize the prognostic ferroptosis-related lncRNA signature (FerRLSig) in ACC. Methods: A regulatory network of ferroptosis-related lncRNAs (FerRLs) and mRNAs was constructed based on The Cancer Genome Atlas (TCGA). Univariate and multivariate Cox regression assays were performed to construct the FerRLSig. Results: Twenty-four FerRLs were identified in the prognostic model, and the high-risk FerRLSig was related to the worse overall survival (OS) in ACC [hazard ratio (HR): 1.936 (1.484-2.526), p < 0.001]. The area under the curve (AUC) value of the FerRLSig was 0.936 according to the receiver operating characteristic (ROC) analyses, superior to other traditional clinicopathological features, further supported the utility in prognosis prediction of ACC. We further established a prognostic nomogram combining clinical factors with the FerRLSig, which showed favorable efficacy for survival prediction. Next, gene set enrichment analysis (GSEA) revealed that gene sets were involved in many immune regulatory biological processes related to malignancies. T-cell function of type II INF response and the immune checkpoints, including CD40, CD276, IDO2, NRP1, and CD80, were expressed with a significant difference between the low- and high-risk groups. Conclusion: This study offered new insights into the pathogenesis of ACC. The novel FerRLSig could be useful in predicting survival and may provide information of immunological research and treatment for ACC patients.

Altered expression of the IGF2‑H19 locus and mitochondrial respiratory complexes in adrenocortical carcinoma.

Abnormalities of the insulin-like growth factor 2 (IGF2)-H19 locus with the overexpression of IGF2 are frequent findings in adrenocortical carcinoma (ACC). The present study assessed the expression of RNAs and microRNAs (miRNAs/miRs) from the IGF2-H19 locus using PCR-based methods in ACC and adrenocortical adenoma (ACA). The results were associated with proteomics data. IGF2 was overexpressed in ACC, and its expression correlated with that of miR-483-3p and miR-483-5p hosted by IGF2. The downregulated expression of H19 in ACC compared to ACA correlated with miR-675 expression hosted by H19. Several proteins exhibited an inverse correlation in expression and were predicted as targets of miR-483-3p, miR-483-5p or miR-675. Subsets of these proteins were differentially expressed between ACC and ACA. These included several proteins involved in mitochondrial metabolism. Among the mitochondrial respiratory complexes, complex I and IV were significantly decreased in ACC compared to ACA. The protein expression of NADH:ubiquinone oxidoreductase subunit C1 (NDUFC1), a subunit of mitochondrial respiratory complex I, was further validated as being lower in ACC compared to ACA and normal adrenals. The silencing of miR-483-5p increased NDUFC1 protein expression and reduced both oxygen consumption and glycolysis rates. On the whole, the findings of the present study reveal the dysregulation of the IGF2-H19 locus and mitochondrial respiration in ACC. These findings may provide a basis for the further understanding of the pathogenesis of ACC and may have potential values for diagnostics and treatment.

Synergistic effects of telomerase reverse transcriptase and regulator of telomere elongation helicase 1 on aggressiveness and outcomes in adrenocortical carcinoma

Adrenocortical carcinoma (ACC) is one of the deadliest endocrine malignancies and telomere maintenance by activated telomerase is critically required for ACC development and progression. Because telomerase reverse transcriptase (TERT) and regulator of telomere elongation helicase 1 (RTEL1) play key roles in telomere homeostasis, we determined their effect on ACC pathogenesis and outcomes. Analyses of TCGA and GEO datasets showed significantly higher expression of RTEL1 but not TERT in ACC tumors, compared to their benign or normal counterparts. Furthermore, gains/amplifications of both TERT and RTEL1 genes were widespread in ACC tumors and their expression correlated with their gene copy numbers. Higher expression of either TERT or RTEL1 was associated with shorter overall and progression-free survival (OS and PFS) in the TCGA ACC patient cohort, and higher levels of both TERT and RTEL1 mRNA predicted the shortest patient OS and PFS. However, multivariate analyses showed that only RTEL1 independently predicted patient OS and PFS. Gene set enrichment analysis further showed enrichments of wnt/β-catenin, MYC, glycolysis, MTOR, and DNA repair signaling pathways in ACC tumors expressing high TERT and RTEL1 mRNA levels. Taken together, TERT and RTEL1 promote ACC aggressiveness synergistically and may serve as prognostic factors and therapeutic targets for ACC.

Pharmacological profile and effects of mitotane in adrenocortical carcinoma.

Mitotane is the only adrenolytic drug approved by the Food and Drug Administration for treating adrenocortical carcinoma (ACC). This drug has cytotoxic effects on tumour tissues; it induces cell death and antisecretory effects on adrenal cells by inhibiting the synthesis of adrenocortical steroids, which are involved in the pathogenesis of ACC. However, high doses of mitotane are usually necessary to reach the therapeutic plasma concentration, which may result in several adverse effects. This suggests that important pharmacological processes, such as first pass metabolism, tissue accumulation and extensive time for drug elimination, are associated with mitotane administration. Few studies have reported the pharmacological aspects and therapeutic effects of mitotane. Therefore, the aim of this review was to summarize the chemistry, pharmacokinetics and pharmacodynamics, and therapeutic and toxic effects of mitotane. This review also discusses new perspectives of mitotane formulation that are currently under investigation. Understanding the pharmacological profile of mitotane can improve the monitoring and efficacy of this drug in ACC treatment and can provide useful information for the development of new drugs with specific action against ACC with fewer adverse effects.

Adrenocortical carcinoma: current state of the art, ongoing controversies, and future directions in diagnosis and treatment.

Adrenocortical carcinoma (ACC) is a rare, aggressive malignancy with an annual incidence of ~1 case per million population. Differentiating between ACC and benign adrenocortical tumors can be challenging in patients who present with an incidentally discovered adrenal mass, due to the limited specificity of standard diagnostic imaging. Recently, urine steroid metabolite profiling has been prospectively validated as a novel diagnostic tool for the detection of malignancy with improved accuracy over current modalities. Surgery represents the only curative treatment for ACC, although local recurrence and metastases are common, even after a margin-negative resection is performed. Unlike other intra-abdominal cancers, the role of minimally invasive surgery and lymphadenectomy in ACC is controversial. Adjuvant therapy with the adrenolytic drug mitotane is used to reduce the risk of recurrence after surgery, although evidence supporting its efficacy is limited; it is also currently unclear whether all patients or a subset with the highest risk of recurrence should receive this treatment. Large-scale pan-genomic studies have yielded insights into the pathogenesis of ACC and have defined distinct molecular signatures associated with clinical outcomes that may be used to improve prognostication. For patients with advanced ACC, palliative combination chemotherapy with mitotane is the current standard of care; however, this is associated with poor response rates (RR). Knowledge from molecular profiling studies has been used to guide the development of novel targeted therapies; however, these have shown limited efficacy in early phase trials. As a result, there is an urgent unmet need for more effective therapies for patients with this devastating disease.

Bioinformatic analysis of long non-coding RNA-associated competing endogenous RNA network in adrenocortical carcinoma

Background: Adrenocortical carcinoma (ACC) is a malignant tumor with poor prognosis and unclear pathogenesis. This study aimed to explore the role of long non-coding RNAs (lncRNAs) in ACC. Methods: We obtained the lncRNA expression profiles of 10 ACC samples and 6 normal control samples from the GEO database and identified differentially expressed RNAs using the limma package in R. Results: We obtained a total of 391 differentially expressed lncRNAs (DElncRNAs) and 1,313 differentially expressed mRNAs (DEmRNAs) between ACC samples and normal control samples. Using Cytoscape v3.7.0, we then constructed a lncRNA-miRNA-mRNA (competing endogenous RNA, or ceRNA) network consisting of 87 lncRNAs, 31 miRNAs, and 78 mRNAs. Applying GO and KEGG enrichment analysis for 78 mRNAs in the ceRNA network, we identified 9 GO terms and 21 significantly enriched pathways. A PPI network was constructed using STRING online tools and Cytoscape v3.7.0, identifying 10 key genes. Finally, through Kaplan-Meier survival analysis, we identified five lncRNAs (LINC00887, MEIS1-AS2, MIR29B2CHG, MIR503HG, and SREBF2-AS1) associated with prognosis in patients with ACC. Conclusions: In summary, we constructed a ceRNA network and propose a new method for lncRNA research in ACC. Our results provide new clues for further exploration of lncRNAs in the pathogenesis of ACC.

Screening and identification of key biomarkers in adrenocortical carcinoma based on bioinformatics analysis

Adrenocortical carcinoma (ACC) is a rare malignancy with a poor prognosis. The presently available understanding of the pathogenesis of ACC is incomplete and the treatment options for patients with ACC are limited. Gene marker identification is required for accurate and timely diagnosis of the disease. In order to identify novel candidate genes associated with the occurrence and progression of ACC, the microarray datasets, GSE12368 and GSE19750, were obtained from Gene Expression Omnibus. Differentially expressed genes (DEGs) were identified, and functional enrichment analysis was performed. A protein-protein interaction network (PPI) was constructed to identify significantly altered modules, and module analysis was performed using Search Tool for the Retrieval of Interacting Genes and Cytoscape. A total of 228 DEGs were screened, consisting of 29 up and 199 downregulated genes. The enriched functions and pathways of the DEGs primarily included ‘cell division’, ‘regulation of transcription involved in G1/S transition of mitotic cell cycle’, ‘G1/S transition of mitotic cell cycle’, ‘p53 signaling pathway’ and ‘oocyte meiosis’. A total of 14 hub genes were identified, and biological process analysis revealed that these genes were significantly enriched in cell division and mitotic cell cycle. Furthermore, survival analysis revealed that AURKA, TYMS, GINS1, RACGAP1, RRM2, EZH2, ZWINT, CDK1, CCNB1, NCAPG and TPX2 may be involved in the tumorigenesis, progression or prognosis of ACC. In conclusion, the 14 hub genes identified in the present study may aid researchers in elucidating the molecular mechanisms associated with the tumorigenesis and progression of ACC, and may be powerful and promising candidate biomarkers for the diagnosis and treatment of ACC.

Bioinformatic analysis of long non-coding RNA-associated competing endogenous RNA network in adrenocortical carcinoma.

BackgroundAdrenocortical carcinoma (ACC) is a malignant tumor with poor prognosis and unclear pathogenesis. This study aimed to explore the role of long non-coding RNAs (lncRNAs) in ACC.MethodsWe obtained the lncRNA expression profiles of 10 ACC samples and 6 normal control samples from the GEO database and identified differentially expressed RNAs using the limma package in R.ResultsWe obtained a total of 391 differentially expressed lncRNAs (DElncRNAs) and 1,313 differentially expressed mRNAs (DEmRNAs) between ACC samples and normal control samples. Using Cytoscape v3.7.0, we then constructed a lncRNA-miRNA-mRNA (competing endogenous RNA, or ceRNA) network consisting of 87 lncRNAs, 31 miRNAs, and 78 mRNAs. Applying GO and KEGG enrichment analysis for 78 mRNAs in the ceRNA network, we identified 9 GO terms and 21 significantly enriched pathways. A PPI network was constructed using STRING online tools and Cytoscape v3.7.0, identifying 10 key genes. Finally, through Kaplan-Meier survival analysis, we identified five lncRNAs (LINC00887, MEIS1-AS2, MIR29B2CHG, MIR503HG, and SREBF2-AS1) associated with prognosis in patients with ACC.ConclusionsIn summary, we constructed a ceRNA network and propose a new method for lncRNA research in ACC. Our results provide new clues for further exploration of lncRNAs in the pathogenesis of ACC.

DLK1/PREF1 marks a novel cell population in the human adrenal cortex

The adrenal cortex governs fundamental metabolic processes though synthesis of glucocorticoid, mineralocorticoids and androgens. Studies in rodents have demonstrated that the cortex undergoes a self-renewal process and that capsular/subcapsular stem/progenitor cell pools differentiate towards functional steroidogenic cells supporting the dynamic centripetal streaming of adrenocortical cells throughout life. We previously demonstrated that the Notch atypical ligand Delta-like homologue 1 (DLK1)/preadipocyte factor 1 (PREF1) is expressed in subcapsular Sf1 and Shh-positive, CYP11B1-negative and CYP11B2-partially positive cortical progenitor cells in rat adrenals, and that secreted DLK1 can modulate GLI1 expression in H295R cells. Here we show that the human adrenal cortex remodels with age to generate clusters of relatively undifferentiated cells expressing DLK1. These clusters (named DLK1-expressing cell clusters or DCCs) increased with age in size and were found to be different entities to aldosterone-producing cell clusters, another well-characterized and age-dependent cluster structure. DLK1 was markedly overexpressed in adrenocortical carcinomas but not in aldosterone-producing adenomas. Thus, this data identifies a novel cell population in the human adrenal cortex and might suggest a yet-to be identified role of DLK1 in the pathogenesis of adrenocortical carcinoma in humans.

Molecular Drivers of Potential Immunotherapy Failure in Adrenocortical Carcinoma.

Adrenocortical carcinoma (ACC) is a rare, highly aggressive cancer, often insensitive to conventional chemotherapeutics agents. Early diagnosis, followed by radical surgical resection plus/minus adjuvant mitotane therapy, is nowadays the only valuable option. Unfortunately, one out of four patients has metastatic disease at diagnosis and most of radically resected ACC patients are destined to recur with local or metastatic disease. Numerous efforts aimed at identifying molecular alterations crucial for ACC pathogenesis have been extensively conducted, with the hope to develop new treatments. Indeed, multiple genes and pathways have been identified as potentially targetable in ACC patients; however, despite the strong preclinical rationale, translational findings to clinical trials led to date to disappointing results. The immunotherapeutic intervention targeting T-cell checkpoint molecules has been proposed as well, but results obtained in early studies indicate that ACC patients would be unlikely to benefit from immunotherapy. Genetic alterations of different pathways involved in ACC carcinogenesis are also known substrates of resistance to immunotherapy. Among them, β-catenin gene CTNNB1 and TP53 gene are frequently mutated in ACC samples. Overactivation of the β-catenin pathway and loss of p53 protein function are potential tumor-intrinsic factors that, impacting on the ability of ACC cells to recruit dendritic cells, leading to T-cell exclusion, put this tumor among those that are potentially resistant to immunotherapy. Moreover, the steroid phenotype, which implies glucocorticoids hypersecretion in a subset of ACC, contributes to generating an immunosuppressive microenvironment. Here, we review clinical results of immunotherapy in ACC and we highlight molecular mechanisms driving immunotherapy failure in ACC, suggesting possible approaches to overcome resistance.

Pathobiology and genetics of adrenocortical carcinoma.

Adrenocortical carcinoma (ACC) is a rare malignancy with an incidence worldwide of 0.7-2.0 cases/million/year. Initial staging is the most important factor in determining prognosis. If diagnosed early, complete surgical resection +/- adjuvant treatment can lead to 5-year survival of up to 80%. However, often it is diagnosed late and in advanced disease, 5-year survival is <15% with a high recurrence rate even after radical surgery. The mainstay of adjuvant treatment is with the drug mitotane. Mitotane has a specific cytotoxic effect on steroidogenic cells of the adrenal cortex, but despite this, progression through treatment is common. Developments in genetic analysis in the form of next-generation sequencing, aided by bioinformatics, have enabled high-throughput molecular characterisation of these tumours. This, in addition to a better appreciation of the processes of physiological, homeostatic self-renewal of the adrenal cortex, has furthered our understanding of the pathogenesis of this malignancy. In this review, we have detailed the pathobiology and genetic alterations in adrenocortical carcinoma by integrating current understanding of homeostasis and self-renewal in the normal adrenal cortex with molecular profiling of tumours from recent genetic analyses. Improved understanding of the mechanisms involved in self-renewal and stem cell hierarchy in normal human adrenal cortices, together with the identification of cell populations likely to be co-opted by oncogenic mutations, will enable further progress in the definition of the molecular pathways involved in the pathogenesis of ACC. The combination of these advances eventually will lead to the development of novel, effective and personalised strategies to eradicate molecularly annotated ACCs.

LncRNA HOTAIR participates in the development and progression of adrenocortical carcinoma via regulating cell cycle.

To explore the role of HOTAIR in the pathogenesis of adrenocortical carcinoma (ACC) and its underlying mechanism. Differentially expressed lncRNA (HOTAIR) in ACC was screened out from the GEO database. The survival analysis and ROC curve were performed according to HOTAIR expressions in ACC patients. The correlation between HOTAIR expression and clinical information of ACC patients was analyzed by chi-square test. The univariate and multivariate COX regression analysis was carried out to analyze the relationship between HOTAIR expression, disease-free survival (DFS) and overall survival (OS) of ACC patients. We then detected HOTAIR expression in 77 ACC tissues and 30 normal tissues by qRT-PCR (quantitative Real-time polymerase chain reaction). ACC cell lines were further screened out for the following in vitro experiments. After altering HOTAIR expression in ACC cells by plasmid transfection, proliferation and cell cycle were detected by Cell Counting Kit-8 (CCK-8) and colony formation assay, respectively. Finally, Western blot was utilized to detect expressions of cell cycle-related genes in ACC cells. HOTAIR was overexpressed in ACC tissues than that of normal tissues. HOTAIR expression was remarkably increased in ACC with T3 and T4 stage than that of T1 and T2 stage. Moreover, HOTAIR expression was remarkably increased in ACC with stage III and IV than that of stage I and II. HOTAIR was an independent prognostic factor for DFS and OS of ACC patients. For in vitro experiments, inhibited proliferation and arrested cell cycle were observed in H295R cells transfected with si-HOTAIR. Opposite results were obtained after SW-13 cells were transfected with HOTAIR overexpression plasmid. Furthermore, expressions of cell cycle-related genes, including Cyclin D1, p-Rb and p-GSK3β were remarkably decreased after HOTAIR knockdown. We demonstrated for the first time that HOTAIR is overexpressed in ACC and is a prognostic risk factor in ACC patients. HOTAIR participates in the development and progression of ACC via shortening cell cycle and promoting proliferation of ACC cells.

MiR-483-5p and miR-139-5p promote aggressiveness by targeting N-myc downstream-regulated gene family members in adrenocortical cancer.

Adrenocortical carcinoma (ACC) is a tumor with poor prognosis in which overexpression of a panel of microRNAs has been associated with malignancy but a very limited number of investigations on their role in ACC pathogenesis have been conducted. We examined the involvement of miR-483-5p and miR-139-5p in adrenocortical cancer aggressiveness. Using bioinformatics predictions and mRNA/miRNA expression profiles, we performed an integrated analysis to identify inversely correlated miRNA-mRNA pairs in ACC. We identified N-myc downstream-regulated gene family members 2 and 4 (NDRG2 and NDRG4) as targets of miR-483-5p and miR-139-5p, respectively. NDRG2 and NDRG4 expressions were inversely correlated respectively with miR-483-5p and miR-139-5p levels in aggressive ACC samples from two independent cohorts of 20 and 44 ACC. Moreover, upregulation of miR-139-5p and downregulation of NDRG4 demonstrated a striking prognostic value. A direct interaction between miR-483-5p or miR-139-5p and their targets was demonstrated in reporter assays. Downregulation of miR-483-5p or miR-139-5p in the ACC cell lines NCI-H295R and SW13 increased NDRG2 or NDRG4 mRNA and protein expression, compromised adrenocortical cancer cell invasiveness and anchorage-independent growth. MiR-483-5p or miR-139-5p overexpression and NDRG2 or NDRG4 inhibition produce similar changes, which are rescued by NDRG2 or NDRG4 ectopic expression. We established that key factors mediating epithelial-to-mesenchymal transition are downstream effectors of miR-483-5p/NDRG2 and miR-139-5p/NDRG4 pathways. Collectively, our data show for the first time that miR-483-5p/NDRG2 and miR-139-5p/NDRG4 axes promote ACC aggressiveness, with potential implications for prognosis and therapeutic interventions in adrenocortical malignancies.

P53/Rb inhibition induces metastatic adrenocortical carcinomas in a preclinical transgenic model.

Adrenocortical carcinoma (ACC) is a rare cancer with poor prognosis. Pan-genomic analyses identified p53/Rb and WNT/β-catenin signaling pathways as main contributors to the disease. However, isolated β-catenin constitutive activation failed to induce malignant progression in mouse adrenocortical tumors. Therefore, there still was a need for a relevant animal model to study ACC pathogenesis and to test new therapeutic approaches. Here, we have developed a transgenic mice model with adrenocortical specific expression of SV40 large T-antigen (AdTAg mice), to test the oncogenic potential of p53/Rb inhibition in the adrenal gland. All AdTAg mice develop large adrenal carcinomas that eventually metastasize to the liver and lungs, resulting in decreased overall survival. Consistent with ACC in patients, adrenal tumors in AdTAg mice autonomously produce large amounts of glucocorticoids and spontaneously activate WNT/β-catenin signaling pathway during malignant progression. We show that this activation is associated with downregulation of secreted frizzled related proteins (Sfrp) and Znrf3 that act as inhibitors of the WNT signaling. We also show that mTORC1 pathway activation is an early event during neoplasia expansion and further demonstrate that mTORC1 pathway is activated in ACC patients. Preclinical inhibition of mTORC1 activity induces a marked reduction in tumor size, associated with induction of apoptosis and inhibition of proliferation that results in normalization of corticosterone plasma levels in AdTAg mice. Altogether, these data establish AdTAg mice as the first preclinical model for metastatic ACC.

Adrenocortical Carcinoma: in the Search for a Pre-Operative Biomarker

Adrenocortical tumors (ACT) are common malignancies of the cortex adrenal gland frequently non-functioning and benign. Differently, adrenocortical carcinoma (ACC) is a very rare neoplasia with an incidence of 0.7-2.0 cases per million people and an aggressive behaviour. Moreover ACC shows a poor prognosis with an estimated survival of 16-38%. Only surgery and the use of mitotane (sometime associated to standard chemotherapy) can represent a useful tool to fight against this malignancy, nonetheless ACC often metastasizes and recurs, decreasing considerably patient survival prospect. In the search of new potential tools to combat cancer, in the latest years omics works extended our knowledge on the ACC pathogenesis and made possible the investigation of novel ACC biomarkers. In this field of research, epigenetic studies identified a common signature in ACC, where the most altered miRNA found in ACC (miR-483-5p) seems now to represent a concrete biomarker to be used in the pre-operative diagnosis of ACC. A larger patient cohort is necessary to confirm this pivotal data: collaboration between scientific communities will be the key to determine the success of this fundamental discovery.

MicroRNAs as Potential Biomarkers in Adrenocortical Cancer: Progress and Challenges

Adrenocortical carcinoma (ACC) is a rare malignancy with poor prognosis and limited therapeutic options. Over the last decade, pan-genomic analyses of genetic and epigenetic alterations and genome-wide expression profile studies allowed major advances in the understanding of the molecular genetics of ACC. Besides the well-known dysfunctional molecular pathways in adrenocortical tumors, such as the IGF2 pathway, the Wnt pathway, and TP53, high-throughput technologies enabled a more comprehensive genomic characterization of adrenocortical cancer. Integration of expression profile data with exome sequencing, SNP array analysis, methylation, and microRNA (miRNA) profiling led to the identification of subgroups of malignant tumors with distinct molecular alterations and clinical outcomes. miRNAs post-transcriptionally silence their target gene expression either by degrading mRNA or by inhibiting translation. Although our knowledge of the contribution of deregulated miRNAs to the pathogenesis of ACC is still in its infancy, recent studies support their relevance in gene expression alterations in these tumors. Some miRNAs have been shown to carry potential diagnostic and prognostic values, while others may be good candidates for therapeutic interventions. With the emergence of disease-specific blood-borne miRNAs signatures, analyses of small cohorts of patients with ACC suggest that circulating miRNAs represent promising non-invasive biomarkers of malignancy or recurrence. However, some technical challenges still remain, and most of the miRNAs reported in the literature have not yet been validated in sufficiently powered and longitudinal studies. In this review, we discuss the current knowledge regarding the deregulation of tumor-associated and circulating miRNAs in ACC patients, while emphasizing their potential significance in pathogenic pathways in light of recent insights into the role of miRNAs in shaping the tumor microenvironment.