Dataset Information

WIPI1, BAG1, and PEX3 Autophagy-Related Genes Are Relevant Melanoma Markers.

ABSTRACT: ROS and oxidative stress may promote autophagy; on the other hand, autophagy may help reduce oxidative damages. According to the known interplay of ROS, autophagy, and melanoma onset, we hypothesized that autophagy-related genes (ARGs) may represent useful melanoma biomarkers. We therefore analyzed the gene and protein expression of 222 ARGs in human melanoma samples, from 5 independent expression databases (overall 572 patients). Gene expression was first evaluated in the GEO database. Forty-two genes showed extremely high ability to discriminate melanoma from nevi (63 samples) according to ROC (AUC ? 0.85) and Mann-Whitney (p < 0.0001) analyses. The 9 genes never related to melanoma before were then in silico validated in the IST online database. BAG1, CHMP2B, PEX3, and WIPI1 confirmed a strong differential gene expression, in 355 samples. A second-round validation performed on the Human Protein Atlas database showed strong differential protein expression for BAG1, PEX3, and WIPI1 in melanoma vs control samples, according to the image analysis of 80 human histological sections. WIPI1 gene expression also showed a significant prognostic value (p < 0.0001) according to 102 melanoma patients' survival data. We finally addressed in Oncomine database whether WIPI1 overexpression is melanoma-specific. Within more than 20 cancer types, the most relevant WIPI1 expression change (p = 0.00002; fold change = 3.1) was observed in melanoma. Molecular/functional relationships of the investigated molecules with melanoma and their molecular/functional network were analyzed via Chilibot software, STRING analysis, and gene ontology enrichment analysis. We conclude that WIPI1 (AUC = 0.99), BAG1 (AUC = 1), and PEX3 (AUC = 0.93) are relevant novel melanoma markers at both gene and protein levels.

SUBMITTER: D'Arcangelo D

PROVIDER: S-EPMC6304818 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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WIPI1, BAG1, and PEX3 Autophagy-Related Genes Are Relevant Melanoma Markers.

D'Arcangelo Daniela D Giampietri Claudia C Muscio Mario M Scatozza Francesca F Facchiano Francesco F Facchiano Antonio A

Oxidative medicine and cellular longevity 20181202

ROS and oxidative stress may promote autophagy; on the other hand, autophagy may help reduce oxidative damages. According to the known interplay of ROS, autophagy, and melanoma onset, we hypothesized that autophagy-related genes (ARGs) may represent useful melanoma biomarkers. We therefore analyzed the gene and protein expression of 222 ARGs in human melanoma samples, from 5 independent expression databases (overall 572 patients). Gene expression was first evaluated in the GEO database. Forty-tw ...[more]

PMID: 30622661

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Project description:BackgroundAutophagy, a highly conserved lysosomal degradation pathway, is associated with the prognosis of melanoma. However, prognostic prediction models based on autophagy related genes (ARGs) have never been recognized in melanoma. In the present study, we aimed to establish a novel nomogram to predict the prognosis of melanoma based on ARGs signature and clinical parameters.MethodsData from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) databases were extracted to identify the differentially expressed ARGs. Univariate, least absolute shrinkage and selection operator (LASSO) and multivariate analysis were used to select the prognostic ARGs. ARGs signature, age and stage were then enrolled to establish a nomogram to predict the survival probabilities of melanoma. The nomogram was evaluated by concordance index (C-index), receiver operating characteristic (ROC) curve and calibration curve. Decision curve analysis (DCA) was performed to assess the clinical benefits of the nomogram and TNM stage model. The nomogram was validated in GEO cohorts.ResultsFive prognostic ARGs were selected to construct ARGs signature model and validated in the GEO cohort. Kaplan-Meier survival analysis suggested that patients in high-risk group had significantly worse overall survival than those in low-risk group in TCGA cohort (P = 5.859 × 10-9) and GEO cohort (P = 3.075 × 10-9). We then established and validated a novel promising prognostic nomogram through combining ARGs signature and clinical parameters. The C-index of the nomogram was 0.717 in TCGA training cohort and 0.738 in GEO validation cohort. TCGA/GEO-based ROC curve and decision curve analysis (DCA) demonstrated that the nomogram was better than traditional TNM staging system for melanoma prognosis.ConclusionWe firstly developed and validated an ARGs signature based-nomogram for individualized prognosis prediction in melanoma patients, which could assist with decision making for clinicians.

Project description:BackgroundColorectal cancer (CRC) is a common malignant solid tumor with an extremely low survival rate after relapse. Previous investigations have shown that autophagy possesses a crucial function in tumors. However, there is no consensus on the value of autophagy-associated genes in predicting the prognosis of CRC patients. This work screens autophagy-related markers and signaling pathways that may participate in the development of CRC, and establishes a prognostic model of CRC based on autophagy-associated genes.MethodsGene transcripts from the TCGA database and autophagy-associated gene data from the GeneCards database were used to obtain expression levels of autophagy-associated genes, followed by Wilcox tests to screen for autophagy-related differentially expressed genes. Then, 11 key autophagy-associated genes were identified through univariate and multivariate Cox proportional hazard regression analysis and used to establish prognostic models. Additionally, immunohistochemical and CRC cell line data were used to evaluate the results of our three autophagy-associated genes EPHB2, NOL3, and SNAI1 in TCGA. Based on the multivariate Cox analysis, risk scores were calculated and used to classify samples into high-risk and low-risk groups. Kaplan-Meier survival analysis, risk profiling, and independent prognosis analysis were carried out. Receiver operating characteristic analysis was performed to estimate the specificity and sensitivity of the prognostic model. Finally, GSEA, GO, and KEGG analysis were performed to identify the relevant signaling pathways.ResultsA total of 301 autophagy-related genes were differentially expressed in CRC. The areas under the 1-year, 3-year, and 5-year receiver operating characteristic curves of the autophagy-based prognostic model for CRC were 0.764, 0.751, and 0.729, respectively. GSEA analysis of the model showed significant enrichment in several tumor-relevant pathways and cellular protective biological processes. The expression of EPHB2, IL-13, MAP2, RPN2, and TRAF5 was correlated with microsatellite instability (MSI), while the expression of IL-13, RPN2, and TRAF5 was related to tumor mutation burden (TMB). GO analysis showed that the 11 target autophagy genes were chiefly enriched in mRNA processing, RNA splicing, and regulation of the mRNA metabolic process. KEGG analysis showed enrichment mainly in spliceosomes. We constructed a prognostic risk assessment model based on 11 autophagy-related genes in CRC.ConclusionA prognostic risk assessment model based on 11 autophagy-associated genes was constructed in CRC. The new model suggests directions and ideas for evaluating prognosis and provides guidance to choose better treatment strategies for CRC.

Dataset Information

WIPI1, BAG1, and PEX3 Autophagy-Related Genes Are Relevant Melanoma Markers.

Publications

WIPI1, BAG1, and PEX3 Autophagy-Related Genes Are Relevant Melanoma Markers.

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