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A three-gene signature and clinical outcome in esophageal squamous cell carcinoma.

ABSTRACT: It is increasingly apparent that cancer development depends not only on genetic alterations, but also on epigenetic changes involving histone modifications. GASC1, member of the histone demethylases affecting heterochromatin formation and transcriptional repression, has been found to be dysregulation in many types of cancers including breast cancer, prostate cancer, metastatic lung sarcomatoid carcinoma, and leukemia. In this study, we examined the expression of GASC1 and certain GASC1-targeted genes (KLF4, MYC, SOX2, PPARG, MDM2, and NANOG) and identified a three-gene prognostic signature (PPARG, MDM2, and NANOG), using risk scores based on immunohistochemical analyses of 149 tumor specimens from patients with esophageal squamous cell carcinoma (ESCC). The presence of a high-risk three-gene signature in the ESCC tumors was significantly associated with decreased overall survival (OS) of the patients. We validated the predictive value of the three-gene signature in a second independent cohort of 101 patients with ESCC in order to determine whether it had predictive value. The results were similar to those in 149 patients. According to multivariate Cox proportional hazards analyses, the predictive model of a three-gene signature was an independent predictor for OS (p = 0.005 in cohort 1, p = 0.025 in cohort 2). In addition, ROC analysis indicated that the predictive ability of the three-gene model was more robust than that of a single biomarker. Therefore, our three-gene signature is closely associated with OS among patients with ESCC and may serve as a predictor for the poor prognosis of ESCC patients.

SUBMITTER: Sun LL

PROVIDER: S-EPMC4477912 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundEsophageal squamous cell carcinoma (ESCC) is causing a high mortality rate due to the lack of efficient early prognosis markers and suitable therapeutic regimens. The prognostic role of genes responsible for the acquisition of radioresistance in ESCC has not been fully elucidated.AimTo establish a prognostic model by studying gene expression patterns pertinent to radioresistance in ESCC patients.MethodsDatasets were obtained from the Gene Expression Omnibus and The Cancer Genome Atlas databases. The edgeR, a Bioconductor package, was used to analyze mRNA expression between different groups. We screened genes specifically responsible for radioresistance to estimate overall survival. Pearson correlation analysis was performed to confirm whether the expression of those genes correlated with each other. Genes contributing to radioresistance and overall survival were assessed by the multivariate Cox regression model through the calculation of βi and risk score using the following formula: .ResultsWe identified three prognostic mRNAs (cathepsin S [CTSS], cluster of differentiation 180 [CD180], and SLP adapter and CSK-interacting membrane protein [SCIMP]) indicative of radioresistance. The expression of the three identified mRNAs was related to each other (r > 0.70 and P < 0.05). As to 1-year and 3-year overall survival prediction, the area under the time-dependent receiver operating characteristic curve of the signature consisting of the three mRNAs was 0.716 and 0.841, respectively. When stratifying patients based on the risk score derived from the signature, the high-risk group exhibited a higher death risk and shorter survival time than the low-risk group (P < 0.0001). Overall survival of the low-risk patients was significantly better than that of the high-risk patients (P = 0.018).ConclusionWe have developed a novel three-gene prognostic signature consisting of CTSS, CD180, and SCIMO for ESCC, which may facilitate the prediction of early prognosis of this malignancy.

Project description:Background:p53 isoform ?133p53 is directly transactivated by p53 and antagonizes p53 activities in cancer progression. However, its correlation with prognosis and cancer recurrence in esophageal squamous cell carcinoma (ESCC) is still unclear. Patients and Methods:Expression of ?133p53 and ?133p53/full-length p53 (FLp53) in tissues and serums of 180 ESCC patients was evaluated using qRT-PCR. Patients were divided into high- and low-expression groups according to the cutoff value determined by X-tile 3.6.1 software. Survival analysis was performed by the Kaplan-Meier method. Univariate and multivariate Cox survival analyses were applied to assess the hazard ratios (HRs). Results:Tissue ?133p53 expression and ?133p53/FLp53 ratio were significantly increased in ESCC tissue compared with adjacent normal tissue. Pre-operative ?133p53 expression and ?133p53/FLp53 ratio in tissue or serum samples were positively associated with TNM stage and post-operative recurrence. Kaplan-Meier curve and multivariate cox regression analyses revealed that the tissue and serum ?133p53/FLp53 ratios (cutoff value: 2.9160) were independent prognostic factors for overall survival (OS) and progression-free survival (PFS) in ESCC patients and showed no statistical difference in receiver-operating characteristic curve (ROC) analysis, while serum ?133p53 showed no significant prognostic value. More importantly, the serum ?133p53/FLp53 ratio in ESCC patients was significantly decreased within 72 h post tumor resection and patients with a consistently high serum ?133p53/FLp53 ratio (?2.9160) had higher recurrence rates than those with consistently low ratio values. In addition, dynamic detection in each follow-up timepoint showed that serum ?133p53/FLp53 ratios were higher than 2.9160 upon recurrence, and they even increased prior to radiologic progression. Conclusion:The serum ?133p53/FLp53 ratio can be a novel predictor for survival outcome and may serve as a real-time parameter for monitoring recurrence in ESCC patients after surgery.

Project description:Esophageal carcinoma (EC) is a common malignant cancer worldwide. Esophageal squamous cell carcinoma (ESCC), the main type of EC, is difficult to treat because of the widespread morbidity, high fatality rates, and low quality of life caused by postoperative complications and no specific molecular target. In this study, we screened genes to establish a prognostic model for ESCC. The transcriptome expression profiles of 81 ESCC tissues and 340 normal esophageal mucosal epithelium tissues were obtained from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) cohorts. The transcriptome expression datasets of 19 esophageal squamous carcinoma cell lines were downloaded from Cancer Cell Line Encyclopedia (CCLE). The R software Limma package was used to identify 6,231 differentially expressed genes and 647 differentially expressed immune-related genes between normal and ESCC tissues. Gene functional analysis was performed using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Weighted gene co-expression network analysis (WGCNA) was used to screen out 18 immune-related prognostic genes. We then established the prognostic and risk signature using these genes, and the patients were divided into low-risk and high-risk groups. Compared with high-risk group patients, the low-risk group patients had longer overall survival. M1 macrophages and resting dendritic cells were differentially distributed between the low-risk and high-risk groups and were related to patient survival. We also examined the functional immune cell and immune molecule levels in low-risk and high-risk group patients, with significant differences in the tumor microenvironment between the two groups. To further verify the accuracy of the prognostic risk model, we performed area under the ROC curve (AUC) analysis. The AUC value was 0.931 for the prognostic risk, which was better than the microsatellite instability (MSI) and Tumor Immune Dysfunction and Exclusion (TIDE) scores. In conclusion, we found 18 immune-related prognostic genes related to the occurrence of ESCC and established a prognostic model for predicting disease severity.

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A three-gene signature and clinical outcome in esophageal squamous cell carcinoma.

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