Prognostic Factors for Adrenocortical Carcinoma Outcomes.
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ABSTRACT:
SUBMITTER: Scollo C
PROVIDER: S-EPMC4958635 | biostudies-literature | 2016
REPOSITORIES: biostudies-literature
Publications
Prognostic Factors for Adrenocortical Carcinoma Outcomes.
Scollo Claudia C Russo Marco M Trovato Maria Antonietta MA Sambataro Daniela D Giuffrida Dario D Manusia Mario M Sapuppo Giulia G Malandrino Pasqualino P Vigneri Riccardo R Pellegriti Gabriella G
Frontiers in endocrinology 20160725
<h4>Purpose</h4>Adrenocortical carcinoma (ACC) is an aggressive tumor characterized by a high recurrence rate and poor response to treatment. This study analyzes a consecutive series of ACC patients to evaluate the prognostic value of various clinical and pathological characteristics.<h4>Methods</h4>We retrospectively evaluated 32 ACC patients followed at our Medical Center from 1997 to 2015 and evaluated the prognostic value of age at diagnosis, gender, tumor functional status, stage, and type ...[more]
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Project description:Alternative splicing is involved in the pathogenesis of human diseases, including cancer. Here, we investigated the potential application of alternative splicing events (ASEs) and splicing factors (SFs) in the prognosis of adrenocortical carcinoma (ACC). Transcriptome data from 79 ACC cases were downloaded from The Cancer Genome Atlas database, and percent spliced-in values of seven splicing types were downloaded from The Cancer Genome Atlas SpliceSeq database. By the univariate Cox regression analysis, 1,839 survival-related ASEs were identified. Prognostic indices based on seven types of survival-related ASEs were calculated by multivariate Cox regression analysis. Survival curves and receiver operating characteristic curves were used to assess the diagnostic value of the prognostic model. Independent prognosis analysis identified several ASEs (e.g., THNSL2| 54469| ME) that could be used as biomarkers to predict the prognosis of patients with ACC accurately. By analyzing the co-expression correlation between SFs and ASEs, 188 highly correlated interactions were established. From the protein interaction network, we finally screened six hub SFs, including YBX1, SART1, PRCC, SNRPG, SNRPE, and SF3B4, whose expression levels were significantly related to the overall survival and prognosis of ACC. Our findings provide a reliable model for predicting the prognosis of ACC patients based on aberrant alternative splicing patterns.
| S-EPMC7494975 | biostudies-literature
Project description:BackgroundThis paper aims to identify alternative RNA splicing landscape and its prognostic value in adrenocortical carcinoma.MethodsThe alternative splicing events data with corresponding clinical information data of 79 ACC patients were obtained from the Cancer Genome Atlas and SpliceSeq package. Prognosis-associated AS events by using univariate Cox regression analysis were selected. Gene functional enrichment analysis demonstrated the potential pathways enriched by survival-associated AS. Prognosis-related splicing events were submitted to develop moderate predictors using Lasso regression model.ResultsOne thousand five survival-associated alternative splicing events were identified. The prognostic genes included ATXN2L, MEIS1, IKBKB, COX4I1. Functional enrichment analysis suggested that prognostic splicing events are associated with Wnt signaling pathway. A prediction model including 12 alternative splicing events was constructed by Lasso regression using train set. ROC analysis showed good performance of the prediction model in test set. Then, a nomogram integrating the clinical-pathological factors and riskscore was constructed for predicting 1- and 3-year survival rate.ConclusionOur data provide a comprehensive bioinformatics analysis of AS events in ACC, providing biomarkers for disease progression and a potentially rich source of novel therapeutic targets.
| S-EPMC7994755 | biostudies-literature
Project description:Importance:The 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. Objective:To compare the molecular classification for prognostic assessment of ACC with other known prognostic factors. Design, Setting, and Participants:In 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. Exposures:Meta-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 Measures:Disease-free survival. Cox proportional hazards regression and C indexes were used to assess the prognostic value of each model. Results:Of 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 Relevance:The 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.
| S-EPMC6624825 | biostudies-literature
Project description:Objective: Adrenocortical carcinoma (ACC) is a rare but aggressive malignant cancer that has been attracting growing attention over recent decades. This study aims to integrate protein interaction networks with gene expression profiles to identify potential biomarkers with prognostic value in silico. Methods: Three microarray data sets were downloaded from the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs) according to the normalization annotation information. Enrichment analyses were utilized to describe biological functions. A protein-protein interaction network (PPI) of the DEGs was developed, and the modules were analyzed using STRING and Cytoscape. LASSO Cox regression was used to identify independent prognostic factors. The Kaplan-Meier method for the integrated expression score was applied to analyze survival outcomes. A receiver operating characteristic (ROC) curve was constructed with area under curve (AUC) analysis to determine the diagnostic ability of the candidate biomarkers. Results: A total of 150 DEGs and 24 significant hub genes with functional enrichment were identified as candidate prognostic biomarkers. LASSO Cox regression suggested that ZWINT, PRC1, CDKN3, CDK1 and CCNA2 were independent prognostic factors in ACC. In multivariate Cox analysis, the integrated expression scores of the modules showed statistical significance in predicting disease-free survival (DFS, P = 0.019) and overall survival (OS, P < 0.001). Meanwhile, ROC curves were generated to validate the ability of the Cox model to predict prognosis. The AUC index for the integrated genes scores was 0.861 (P < 0.0001). Conclusion: In conclusion, the present study identifies DEGs and hub genes that may be involved in poor prognosis and early recurrence of ACC. The expression levels of ZWINT, PRC1, CDKN3, CDK1 and CCNA2 are of high prognostic value, and may help us understand better the underlying carcinogenesis or progression of ACC. Further studies are required to elucidate molecular pathogenesis and alteration in signaling pathways for these genes in ACC.
| S-EPMC6749084 | biostudies-literature
Project description:Current treatment guidelines recommend adjuvant mitotane after resection of adrenocortical carcinoma with high-risk features (eg, tumor rupture, positive margins, positive lymph nodes, high grade, elevated mitotic index, and advanced stage). Limited data exist on the outcomes associated with these practice guidelines.Patients who underwent resection of adrenocortical carcinoma from 1993 to 2014 at the 13 academic institutions of the US Adrenocortical Carcinoma Group were included. Factors associated with mitotane administration were determined. Primary end points were recurrence-free survival (RFS) and overall survival (OS).Of 207 patients, 88 (43%) received adjuvant mitotane. Receipt of mitotane was associated with hormonal secretion (58% vs 32%; p = 0.001), advanced TNM stage (stage IV: 42% vs 23%; p = 0.021), adjuvant chemotherapy (37% vs 5%; p < 0.001), and adjuvant radiation (17% vs 5%; p = 0.01), but was not associated with tumor rupture, margin status, or N-stage. Median follow-up was 44 months. Adjuvant mitotane was associated with decreased RFS (10.0 vs 27.9 months; p = 0.007) and OS (31.7 vs 58.9 months; p = 0.006). On multivariable analysis, mitotane was not independently associated with RFS or OS, and margin status, advanced TNM stage, and receipt of chemotherapy were associated with survival. After excluding all patients who received chemotherapy, adjuvant mitotane remained associated with decreased RFS and similar OS; multivariable analyses again showed no association with recurrence or survival. Stage-specific analyses in both cohorts revealed no association between adjuvant mitotane and improved RFS or OS.When accounting for stage and adverse tumor and treatment-related factors, adjuvant mitotane after resection of adrenocortical carcinoma is not associated with improved RFS or OS. Current guidelines should be revisited and prospective trials are needed.
| S-EPMC4957938 | biostudies-other
Project description:BackgroundRecurrent adrenocortical carcinoma (ACC) has a poor prognosis with minimal clinical and biochemical factors to guide management. The aim of this study was to evaluate the prognostic significance of systemic inflammatory response in patients with recurrent ACC.MethodsPatients who underwent resection for recurrent ACC were retrospectively analyzed. Preoperative neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, lymphocyte-to-monocyte ratio (LMR), and mean platelet volume were calculated.ResultsTwenty-five patients (age at operation 52.2 ± 9.5 years) were identified. We observed a statistically significant shorter disease-specific survival (DSS) in patients with LMR less than 4 (41 ± 7.4 months vs 71 ± 12.3, P = .023) and male sex (26.6 ± 4.2 months vs 57.6 ± 9.5 months, P = .079), while time-to-recurrence (TTR) less than 12 months (40 ± 7.7 months vs 70.3 ± 13.1 months, P = .059) had a trend on univariate analysis for worse DSS. On multivariable analysis, LMR < 4 (hazard ratio [HR] 4.18; 95% confidence interval [CI]: 1.18-14.76; P = .027) and TTR less than 12 months (HR 2.77 95% CI: 1-7.62; P = .049) were found to be significantly associated with worse DSS.ConclusionPreoperative LMR greater than 4 and TTR greater than 12 months are associated with longer DSS. Patients with LMR greater than 4 and TTR greater than 12 months may benefit from a more aggressive therapeutic approach and may require less frequent surveillance.
| S-EPMC8192065 | biostudies-literature
Project description:BackgroundThe prognosis of adrenocortical carcinoma (ACC) is heterogeneous. Genomic studies have identified ACC subgroups characterized by specific molecular alterations, including features measured at DNA level (somatic mutations, chromosome alterations, DNA methylation), which are closely associated with outcome. The aim of this study was to evaluate intratumor heterogeneity of prognostic molecular markers at the DNA level.MethodsTwo different tissue samples (primary tumor, local recurrence or metastasis) were analyzed in 26 patients who underwent surgery for primary or recurrent ACC. DNA-related biomarkers with prognostic role were investigated in frozen and paraffin-embedded samples. Somatic mutations of p53/Rb and Wnt/β-catenin pathways were assessed using next-generation sequencing (n = 26), chromosome alteration profiles were determined using SNP arrays (n = 14) and methylation profiles were determined using four-gene bisulfite pyrosequencing (n = 12).ResultsSomatic mutations for ZNRF3, TP53, CTNN1B and CDKN2A were found in 7, 6, 6 and 4 patients, respectively, with intratumor heterogeneity in 8/26 patients (31%). Chromosome alteration profiles were 'Noisy' (numerous and anarchic alterations) in 8/14 and 'Chromosomal' (extended patterns of loss of heterozygosity) in 5/14 of the study samples. For these profiles, no intratumor heterogeneity was observed. Methylation profiles were hypermethylated in 5/12 and non-hypermethylated in 7/12 of the study samples. Intratumor heterogeneity of methylation profiles was observed in 2/12 patients (17%).ConclusionsIntratumor heterogeneity impacts DNA-related molecular markers. While somatic mutation can differ, prognostic DNA methylation and chromosome alteration profile seem rather stable and might be more robust for the prognostic assessment.
| S-EPMC7424337 | biostudies-literature
Project description:ContextRetinoic acid receptor responder protein 2 (RARRES2) is a small secreted protein involved in multiple cancers, including adrenocortical carcinoma (ACC). However, discordant tumor and serum RARRES2 levels have been reported in various cancers. The etiology of this discordance is unknown and has not been studied in pair-matched tumor and serum samples.ObjectiveTo determine tissue and serum RARRES2 levels in patients with adrenocortical neoplasm and to elucidate the prognostic implications of RARRES2 levels.Design, settings, and patientsTissue and serum RARRES2 levels were analyzed. A pair-matched analysis was performed to examine tissue and serum RARRES2 from 51 patients with benign adrenocortical tumors and 18 patients with ACC. Overall survival was analyzed based on RARRES2 expression. A mouse xenograft model was used to determine the source of serum RARRES2.ResultsPatients with ACC had decreased tumor RARRES2 gene expression (P < .0001) and increased serum RARRES2 levels (P < .005) as compared with patients with benign adrenocortical tumors. Higher serum RARRES2 levels were associated with improved overall survival (P = .0227). A mouse xenograft model demonstrated that higher tissue RARRES2 expression was associated with higher RARRES2 secretion in the serum and that there was an intrinsic mechanism in maintaining serum RARRES2 homeostasis.ConclusionsSerum and tissue RARRES2 expression levels are paradoxical in patients with ACC. The elevated RARRES2 in patient serum is unlikely to be secreted from tumor cells. Serum RARRES2 may be used as a novel prognostic marker for ACC.
| S-EPMC5010575 | biostudies-literature
Project description:BackgroundTo identify prognostic genes which were associated with adrenocortical carcinoma (ACC) tumor microenvironment (TME).Methods and materialsTranscriptome profiles and clinical data of ACC samples were collected from The Cancer Genome Atlas (TCGA) database. We use ESTIMATE (estimation of stromal and Immune cells in malignant tumor tissues using expression data) algorithm to calculate immune scores, stromal scores and estimate scores. Heatmap and volcano plots were applied for differential analysis. Venn plots were used for intersect genes selection. We used protein-protein interaction (PPI) networks and functional analysis to explore underlying pathways. After performing stepwise regression method and multivariate Cox analysis, we finally screened hub genes associated with ACC TME. We calculated risk scores (RS) for ACC cases based on multivariate Cox results and evaluated the prognostic value of RS shown by receiver operating characteristic curve (ROC). We investigated the association between hub genes with immune infiltrates supported by algorithm from online TIMER database.ResultsGene expression profiles and clinical data were downloaded from TCGA. Lower immune scores were observed in disease with distant metastasis (DM) and locoregional recurrence (LR) than other cases (P = .0204). Kaplan-Meier analysis revealed that lower immune scores were significantly associated with poor overall survival (OS) (P = .0495). We screened 1649 differentially expressed genes (DEGs) and 1521 DEGs based on immune scores and stromal scores, respectively. Venn plots helped us find 1122 intersect genes. After analysing by cytoHubba from Cytoscape software, 18 hub genes were found. We calculated RS and ROC showed significantly predictive accuracy (area under curve (AUC) = 0.887). ACC patients with higher RS had worse survival outcomes (P < .0001). Results from TIMER (tumor immune estimation resource) database revealed that HLA-DOA was significantly related with immune cells infiltration.ConclusionWe screened a list of TME-related genes which predict poor survival outcomes in ACC patients from TCGA database.
| S-EPMC6997077 | biostudies-literature
Project description:Adrenocortical carcinoma (ACC) is a rare endocrine malignancy with an unfavorable prognosis. Despite the poor prognosis in the majority of patients, no improvements in treatment strategies have been achieved. Therefore, the discovery of new prognostic biomarkers is of enormous interest. Sterol-O-acyl transferase 1 (SOAT1) is involved in cholesterol esterification and lipid droplet formation. Recently, it was demonstrated that SOAT1 inhibition leads to impaired steroidogenesis and cell viability in ACC. To date, no studies have addressed the impact of SOAT1 expression on ACC prognosis and clinical outcomes. We evaluated SOAT1 expression by quantitative real-time polymerase chain reaction and immunohistochemistry in a tissue microarray of 112 ACCs (Weiss score ≥ 3) from adults treated in a single tertiary center in Brazil. Two independent pathologists evaluated the immunohistochemistry results through a semiquantitative approach (0-4). We aimed to evaluate the correlation between SOAT1 expression and clinical, biochemical and anatomopathological parameters, recurrence-free survival (RFS), progression-free survival (PFS), and overall survival (OS). SOAT1 protein expression was heterogeneous in this cohort, 37.5% of the ACCs demonstrated a strong SOAT1 protein expression (score > 2), while 62.5% demonstrated a weak or absent protein expression (score ≤ 2). Strong SOAT1 protein expression correlated with features of high aggressiveness in ACC, such as excessive tumor cortisol secretion (p = 0.01), an advanced disease stage [European Network for the Study of Adrenal Tumors (ENSAT) staging system 3 and 4 (p = 0.011)] and a high Ki67 index (p = 0.002). In multivariate analysis, strong SOAT1 protein expression was an independent predictor of a reduced OS (hazard ratio (HR) 2.15, confidence interval (CI) 95% 1.26-3.66; p = 0.005) in all patients (n = 112), and a reduced RFS (HR 2.1, CI 95% 1.09-4.06; p = 0.027) in patients with localized disease at diagnosis (n = 83). Our findings demonstrated that SOAT1 protein expression has prognostic value in ACC and reinforced the importance of investigating SOAT1 as a possible therapeutic target for patients with ACC.
| S-EPMC7016635 | biostudies-literature