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Livin/BIRC7 is a member of the inhibitors of apoptosis proteins family, which are involved in tumor development through the inhibition of caspases. Aim was to investigate the expression of livin and other members of its pathway in adrenocortical tumors and in the adrenocortical carcinoma (ACC) cell line NCI-H295R.
The mRNA expression of livin, its isoforms α and β, XIAP, CASP3 and DIABLO was evaluated by qRT-PCR in 82 fresh-frozen adrenal tissues (34 ACC, 25 adenomas = ACA, 23 normal adrenal glands = NAG). Livin protein expression was assessed by immunohistochemistry in 270 paraffin-embedded tissues (192 ACC, 58 ACA, 20 NAG). Livin, CASP3 and cleaved caspase-3 were evaluated in NCI-H295R after induction of livin overexpression.
Relative livin mRNA expression was significantly higher in ACC than in ACA and NAG (0.060 ± 0.116 vs 0.004 ± 0.014 and 0.002 ± 0.009, respectively, p < 0.01), being consistently higher in tumors than in adjacent NAG and isoform β more expressed than α. No significant differences in CASP3, XIAP and DIABLO levels were found among these groups. In immunohistochemistry, livin was localized in both cytoplasm and nuclei. The ratio between cytoplasmic and nuclear staining was significantly higher in ACC (1.51 ± 0.66) than in ACA (0.80 ± 0.35) and NAG (0.88 ± 0.27; p < 0.0001). No significant correlations were observed between livin expression and histopathological parameters or clinical outcome. In NCI-H295R cells, the livin overexpression slightly reduced the activation of CASP3, but did not correlate with cell viability.
In conclusion, livin is specifically over-expressed in ACC, suggesting that it might be involved in adrenocortical tumorigenesis and represent a new molecular marker of malignancy.
The genetic mechanisms underlying adrenocortical tumor development are still largely unknown. We used high-resolution single nucleotide polymorphism microarrays (Affymetrix SNP 6.0) to detect copy number alterations (CNAs) and copy-neutral losses of heterozygosity (cnLOH) in 15 cortisol-secreting adrenocortical adenomas with matched blood samples. We focused on microalterations aiming to discover new candidate genes involved in early tumorigenesis and/or autonomous cortisol secretion. We identified 962 CNAs with a median of 18 CNAs per sample. Half of them involved noncoding regions, 89% were less than 100 kb, and 28% were found in at least two samples. The most frequently gained regions were 5p15.33, 6q16.1, 7p22.3-22.2, 8q24.3, 9q34.2-34.3, 11p15.5, 11q11, 12q12, 16q24.3, 20p11.1-20q21.11, and Xq28 (>= 20% of cases), most of them being identified in the same three adenomas. These regions contained among others genes like NOTCH1, CYP11B2, HRAS, and IGF2. Recurrent losses were less common and smaller than gains, being mostly localized at 1p, 6q, and 11q. Pathway analysis revealed that Notch signaling was the most frequently altered. We identified 46 recurrent CNAs that each affected a single gene (31 gains and 15 losses), including genes involved in steroidogenesis (CYP11B1) or tumorigenesis (CTNNB1, EPHA7, SGK1, STIL, FHIT). Finally, 20 small cnLOH in four cases affecting 15 known genes were found. Our findings provide the first high-resolution genome-wide view of chromosomal changes in cortisol-secreting adenomas and identify novel candidate genes, such as HRAS, EPHA7, and SGK1. Furthermore, they implicate that the Notch1 signaling pathway might be involved in the molecular pathogenesis of adrenocortical tumors.
Background
Adrenocortical tumors comprise frequent adenomas (ACA) and rare carcinomas (ACC). Human cytochrome P450 2W1 (CYP2W1) is highly expressed in some cancers holding the potential to activate certain drugs into tumor cytotoxins.
Objective
To investigate the CYP2W1 expression in adrenal samples and its relationship with clinical outcome in ACC.
Material and Methods
CYP2W1 expression was investigated by qRT-PCR in 13 normal adrenal glands, 32 ACA, 25 ACC, and 9 different non-adrenal normal tissue samples and by immunohistochemistry in 352 specimens (23 normal adrenal glands, 33 ACA, 239 ACC, 67 non-adrenal normal or neoplastic samples).
Results
CYP2W1 mRNA expression was absent/low in normal non-adrenal tissues, but high in normal and neoplastic adrenal glands (all P<0.01 vs non-adrenal normal tissues). Accordingly, CYP2W1 immunoreactivity was absent/low (H-score 0–1) in 72% of non-adrenal normal tissues, but high (H-score 2–3) in 44% of non-adrenal cancers, in 65% of normal adrenal glands, in 62% of ACAs and in 50% of ACCs (all P<0.001 vs non-adrenal normal tissues), being significantly increased in steroid-secreting compared to non-secreting tumors. In ACC patients treated with mitotane only, high CYP2W1 immunoreactivity adjusted for ENSAT stage was associated with longer overall survival and time to progression (P<0.05 and P<0.01, respectively), and with a better response to therapy both as palliative (response/stable disease in 42% vs 6%, P<0.01) or adjuvant option (absence of disease recurrence in 69% vs 45%, P<0.01).
Conclusion
CYP2W1 is highly expressed in both normal and neoplastic adrenal glands making it a promising tool for targeted therapy in ACC. Furthermore, CYP2W1 may represent a new predictive marker for the response to mitotane treatment.
Adrenocortical tumors consist of benign adenomas and highly malignant carcinomas with a still incompletely understood pathogenesis. A total of 46 adrenocortical tumors (24 adenomas and 22 carcinomas) were investigated aiming to identify novel genes involved in adrenocortical tumorigenesis. High-resolution single nucleotide polymorphism arrays (Affymetrix) were used to detect copy number alterations (CNAs) and copy neutral losses of heterozygosity (cnLOH). Genomic clustering showed good separation between adenomas and carcinomas, with best partition including only chromosome 5, which was highly amplified in 17/22 malignant tumors. The malignant tumors had more relevant genomic aberrations than benign tumors, such as a higher median number of recurrent CNA (2631 vs 94), CNAs >100 Kb (62.5 vs 7) and CN losses (72.5 vs 5.5), and a higher percentage of samples with cnLOH (91% vs 29%). Within the carcinoma cohort, a precise genetic pattern (i.e. large gains at chr 5, 7, 12, and 19, and losses at chr 1, 2, 13, 17, and 22) was associated with a better prognosis (overall survival: 72.2 vs 35.4 months, P=0.063). Interestingly, >70% of gains frequent in beningn were also present in malignant tumors. Notch signaling was the most frequently involved pathway in both tumor entities. Finally, a CN gain at imprinted “IGF2” locus chr 11p15.5 appeared to be an early alteration in a multi-step tumor progression, followed by the loss of one or two alleles, associated with increased IGF2 expression, only in carcinomas. Our study serves as database for the identification of genes and pathways, such as Notch signaling, which could be involved in the pathogenesis of adrenocortical tumors. Using these data, we postulate an adenoma-carcinoma sequence for these tumors.
Mutations in the PRKACA gene are the most frequent cause of cortisol-producing adrenocortical adenomas leading to Cushing’s syndrome. PRKACA encodes for the catalytic subunit α of protein kinase A (PKA). We already showed that PRKACA mutations lead to impairment of regulatory (R) subunit binding. Furthermore, PRKACA mutations are associated with reduced RIIβ protein levels; however, the mechanisms leading to reduced RIIβ levels are presently unknown. Here, we investigate the effects of the most frequent PRKACA mutation, L206R, on regulatory subunit stability. We find that Ser\(^{114}\) phosphorylation of RIIβ is required for its degradation, mediated by caspase 16. Last, we show that the resulting reduction in RIIβ protein levels leads to increased cortisol secretion in adrenocortical cells. These findings reveal the molecular mechanisms and pathophysiological relevance of the R subunit degradation caused by PRKACA mutations, adding another dimension to the deregulation of PKA signaling caused by PRKACA mutations in adrenal Cushing’s syndrome.
Non-coding RNAs (ncRNAs) are a type of genetic material that do not encode proteins but regulate the gene expression at an epigenetic level, such as microRNAs (miRNAs) and long non-coding RNAs (lncRNAs). The role played by ncRNAs in many physiological and pathological processes has gained attention during the last few decades, as they might be useful in the diagnosis, treatment and management of several human disorders, including endocrine and oncological diseases. Adrenocortical carcinoma (ACC) is a rare and aggressive endocrine cancer, still characterized by high mortality and morbidity due to both endocrine and oncological complications. Despite the rarity of this disease, recently, the role of ncRNA has been quite extensively evaluated in ACC. In order to better explore the role of the ncRNA in human ACC, this review summarizes the current knowledge on ncRNA dysregulation in ACC and its potential role in the diagnosis, treatment, and management of this tumor.
Mitotane is the only approved drug for advanced adrenocortical carcinoma (ACC) and no biomarkers are available to predict attainment of therapeutic plasma concentrations and clinical response. Aim of the study was to evaluate the suitability of cytochrome P450(CYP)2W1 and CYP2B6 single nucleotide polymorphisms (SNPs) as biomarkers. A multicenter cohort study including 182 ACC patients (F/M = 121/61) treated with mitotane monotherapy after radical resection (group A, n = 103) or in not completely resectable, recurrent or advanced disease (group B, n = 79) was performed. CYP2W1*2, CYP2W1*6, CYP2B6*6 and CYP2B6 rs4803419 were genotyped in germline DNA. Mitotane blood levels were measured regularly. Response to therapy was evaluated as time to progression (TTP) and disease control rate (DCR). Among investigated SNPs, CYP2W1*6 and CYP2B6*6 correlated with mitotane treatment only in group B. Patients with CYP2W1*6 (n = 21) achieved less frequently therapeutic mitotane levels (>14 mg/L) than those with wild type (WT) allele (76.2% vs 51.7%, p = 0.051) and experienced shorter TTP (HR = 2.10, p = 0.019) and lower DCR (chi-square = 6.948, p = 0.008). By contrast, 55% of patients with CYP2B6*6 vs. 28.2% WT (p = 0.016) achieved therapeutic range. Combined, a higher rate of patients with CYP2W1*6WT+CYP2B6*6 (60.6%) achieved mitotane therapeutic range (p = 0.034). In not completely resectable, recurrent or advanced ACC, CYP2W1*6 SNP was associated with a reduced probability to reach mitotane therapeutic range and lower response rates, whereas CYP2B6*6 correlated with higher mitotane levels. The association of these SNPs may predict individual response to mitotane.
Somatic mutations in protein kinase A catalytic α subunit (PRKACA) were found to be causative for 30-40% of cortisol-producing adenomas (CPA) of the adrenal gland, rendering PKA signalling constitutively active. In its resting state, PKA is a stable and inactive heterotetramer, consisting of two catalytic and two regulatory subunits with the latter inhibiting PKA activity. The human genome encodes three different PKA catalytic subunits and four different regulatory subunits that are preferentially expressed in different organs. In normal adrenal glands all regulatory subunits are expressed, while CPA exhibit reduced protein levels of the regulatory subunit IIβ. In this study, we linked for the first time the loss of RIIβ protein levels to the PRKACA mutation status and found the down-regulation of RIIβ to arise post-transcriptionally. We further found the PKA subunit expression pattern of different tumours is also present in the zones of the normal adrenal cortex and demonstrate that the different PKA subunits have a differential expression pattern in each zone of the normal adrenal gland, indicating potential specific roles of these subunits in the regulation of different hormones secretion.
Simple Summary
Using a visual-based clustering method on the TCGA RNA sequencing data of a large adrenocortical carcinoma (ACC) cohort, we were able to classify these tumors in two distinct clusters largely overlapping with previously identified ones. As previously shown, the identified clusters also correlated with patient survival. Applying the visual clustering method to a second dataset also including benign adrenocortical samples additionally revealed that one of the ACC clusters is more closely located to the benign samples, providing a possible explanation for the better survival of this ACC cluster. Furthermore, the subsequent use of machine learning identified new possible biomarker genes with prognostic potential for this rare disease, that are significantly differentially expressed in the different survival clusters and should be further evaluated.
Abstract
Adrenocortical carcinoma (ACC) is a rare disease, associated with poor survival. Several “multiple-omics” studies characterizing ACC on a molecular level identified two different clusters correlating with patient survival (C1A and C1B). We here used the publicly available transcriptome data from the TCGA-ACC dataset (n = 79), applying machine learning (ML) methods to classify the ACC based on expression pattern in an unbiased manner. UMAP (uniform manifold approximation and projection)-based clustering resulted in two distinct groups, ACC-UMAP1 and ACC-UMAP2, that largely overlap with clusters C1B and C1A, respectively. However, subsequent use of random-forest-based learning revealed a set of new possible marker genes showing significant differential expression in the described clusters (e.g., SOAT1, EIF2A1). For validation purposes, we used a secondary dataset based on a previous study from our group, consisting of 4 normal adrenal glands and 52 benign and 7 malignant tumor samples. The results largely confirmed those obtained for the TCGA-ACC cohort. In addition, the ENSAT dataset showed a correlation between benign adrenocortical tumors and the good prognosis ACC cluster ACC-UMAP1/C1B. In conclusion, the use of ML approaches re-identified and redefined known prognostic ACC subgroups. On the other hand, the subsequent use of random-forest-based learning identified new possible prognostic marker genes for ACC.