Dataset Information

Stage-specific prognostic biomarkers in melanoma.

ABSTRACT: The melanoma staging system proposed by the American Joint Committee on Cancer (AJCC) (which classifies melanoma patients into four clinical stages) is currently the most widely used tool for melanoma prognostication, and clinical management decision making by clinicians. However, multiple studies have shown that melanomas within specific AJCC Stages can exhibit varying progression and clinical outcomes. Thus, additional information, such as that provided by biomarkers is needed to assist in identifying the patients at risk of disease progression. Having previously found six independent prognostic biomarkers in melanoma, including BRAF, MMP2, p27, Dicer, Fbw7 and Tip60, our group has gone on to investigate if these markers are useful in risk stratification of melanoma patients in individual AJCC stages. First, we performed Kaplan-Meier survival and Cox proportional multivariate analyses comparing prognostication power of these markers in 254 melanoma patients for whom the expression levels were known, identifying the best performing markers as candidates for stage-specific melanoma markers. We then verified the results by incorporating an additional independent cohort (87 patients) and in a combined cohort (341 patients). Our data indicate that BRAF and MMP2 are optimal prognostic biomarkers for AJCC Stages I and II, respectively (P = 0.010, 0.000, Log-rank test); whereas p27 emerged as a good marker for AJCC Stages III/IV (0.018, 0.046, respectively, log-rank test). Thus, our study has identified stage-specific biomarkers in melanoma, a finding which may assist clinicians in designing improved personalized therapeutic modalities.

SUBMITTER: Cheng Y

PROVIDER: S-EPMC4414181 | biostudies-literature | 2015 Feb

REPOSITORIES: biostudies-literature

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Stage-specific prognostic biomarkers in melanoma.

Cheng Yabin Y Lu Jing J Chen Guangdi G Ardekani Gholamreza Safaee GS Rotte Anand A Martinka Magdalena M Xu Xuezhu X McElwee Kevin J KJ Zhang Guohong G Zhou Youwen Y

Oncotarget 20150201 6

The melanoma staging system proposed by the American Joint Committee on Cancer (AJCC) (which classifies melanoma patients into four clinical stages) is currently the most widely used tool for melanoma prognostication, and clinical management decision making by clinicians. However, multiple studies have shown that melanomas within specific AJCC Stages can exhibit varying progression and clinical outcomes. Thus, additional information, such as that provided by biomarkers is needed to assist in ide ...[more]

PMID: 25784655

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Project description:Squamous cell lung cancer (LUSC) is a frequently diagnosed histological subtype of lung malignancy associated with high mortality due to limited number of treatment options. Identification of potential targets suitable for drug development using high-throughput methods is still lacking. Therefore, the purpose of this research is to analyze expression profiles of mRNA and miRNA in LUSC, aiming to identify the key molecules associated with tumorigenesis and prognosis (overall survival; OS). We performed differential gene expression analysis, pathway enrichment analysis and gene ontology analysis on RNA-seq data obtained from 23 FFPE tumor samples and 3 FFPE healthy individuals. TCGA LUSC and GTEx healthy donors’ cohorts were used for validation. We identified 1133 up-regulated and 644 down-regulated genes, common for both cohorts. The most significant up-regulated genes were involved in cell-cycle regulation pathways, while down-regulated genes predominately belonged to immune-related pathways. Survival analysis performed on selected genes, commonly dysregulated in both cohorts and performed only on non-metastatic patients, identified novel prognostic biomarkers associated with OS in early-stage LUSC patients (HOXC4-worse OS, p=0.0001; LILRA5-better OS, p=0.0086). In total, 50 differentially expressed genes are correlated with patients’ OS. Aiming to get better insight into the profile of the tumor microenvironment, we estimated levels of immune-cells infiltration in LUSC and identified 4 subtypes based on immune-cell infiltration levels. Protein-protein interaction (PPI) network was built based on differentially expressed genes, and PPI modules and hub-genes were identified. Weighted gene co-expression network analysis was conducted to identify significant modules and hub-genes in correlation to clinical traits. Differential analysis on miRNA-Seq data, obtained from 16 tumor and 4 healthy tissue samples, was conducted as well. 75 up-regulated and 47 down-regulated miRNAs were identified. Further, targets of differentially expressed miRNA were identified, following gene ontology analysis and miRNA-mRNA networks construction.

Dataset Information

Stage-specific prognostic biomarkers in melanoma.

Publications

Stage-specific prognostic biomarkers in melanoma.

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