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A six-microRNA signature can better predict overall survival of patients with esophagus adenocarcinoma.

ABSTRACT: Background:The microRNAs (miRNAs) have been validated as prognostic markers in many cancers. Here, we aimed at developing a miRNA-based signature for predicting the prognosis of esophagus adenocarcinoma (EAC). Methods:The RNA-sequencing data set of EAC was downloaded from The Cancer Genome Atlas (TCGA). Eighty-four patients with EAC were classified into a training set and a test set randomly. Using univariate Cox regression analysis and the least absolute shrinkage and selection operator (LASSO), we identified prognostic factors and constructed a prognostic miRNA signature. The accuracy of the signature was evaluated by the receiver operating characteristic (ROC) curve. Result:In general, in the training set, six miRNAs (hsa-mir-425, hsa-let-7b, hsa-mir-23a, hsa-mir-3074, hsa-mir-424 and hsa-mir-505) displayed good prognostic power as markers of overall survival for EAC patients. Relative to patients in the low-risk group, those assigned to the high-risk group according to their risk scores of the designed miRNA model displayed reduced overall survival. This 6-miRNA model was validated in test and entire set. The area under curve (AUC) for ROC at 3 years was 0.959, 0.840, and 0.868 in training, test, and entire set, respectively. Molecular functional analysis and pathway enrichment analysis indicated that the target messenger RNAs associated with 6-miRNA signature were closely related to several pathways involved in carcinogenesis, especially cell cycle. Conclusion:In summary, a novel 6-miRNA expression-based prognostic signature derived from the EAC data of TCGA was constructed and validated for predicting the prognosis of EAC.

SUBMITTER: Lan T

PROVIDER: S-EPMC6661144 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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A six-microRNA signature can better predict overall survival of patients with esophagus adenocarcinoma.

Lan Tian T Lu Yunyan Y Xiao Zunqiang Z Xu Haibin H He Junling J Hu Zujian Z Mao Weimin W

PeerJ 20190725

<h4>Background</h4>The microRNAs (miRNAs) have been validated as prognostic markers in many cancers. Here, we aimed at developing a miRNA-based signature for predicting the prognosis of esophagus adenocarcinoma (EAC).<h4>Methods</h4>The RNA-sequencing data set of EAC was downloaded from The Cancer Genome Atlas (TCGA). Eighty-four patients with EAC were classified into a training set and a test set randomly. Using univariate Cox regression analysis and the least absolute shrinkage and selection o ...[more]

PMID: 31380150

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Project description:BackgroundLung cancer is the leading cause of cancer-related deaths worldwide. Lung adenocarcinoma (LUAD) is one of the main subtypes of lung cancer. Hundreds of metabolic genes are altered consistently in LUAD; however, their prognostic role remains to be explored. This study aimed to establish a molecular signature that can predict the prognosis in patients with LUAD based on metabolic gene expression.MethodsThe transcriptome expression profiles and corresponding clinical information of LUAD were obtained from The Cancer Genome Atlas and Gene Expression Omnibus databases. The differentially expressed genes (DEGs) between LUAD and paired non-tumor samples were identified by the Wilcoxon rank sum test. Univariate Cox regression analysis and the lasso Cox regression model were used to construct the best-prognosis molecular signature. A nomogram was established comprising the prognostic model for predicting overall survival. To validate the prognostic ability of the molecular signature and the nomogram, the Kaplan-Meier survival analysis, Cox proportional hazards model, and receiver operating characteristic analysis were used.ResultsThe six-gene molecular signature (PFKP, PKM, TPI1, LDHA, PTGES, and TYMS) from the DEGs was constructed to predict the prognosis. The molecular signature demonstrated a robust independent prognostic ability in the training and validation sets. The nomogram including the prognostic model had a greater predictive accuracy than previous systems. Furthermore, a gene set enrichment analysis revealed several significantly enriched metabolic pathways, which suggests a correlation of the molecular signature with metabolic systems and may help explain the underlying mechanisms.ConclusionsOur study identified a novel six-gene metabolic signature for LUAD prognosis prediction. The molecular signature could reflect the dysregulated metabolic microenvironment, provide potential biomarkers for predicting prognosis, and indicate potential novel metabolic molecular-targeted therapies.

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Project description:A six-gene signature predicts survival of patients with localized pancreatic ductal adenocarcinoma Pancreatic ductal adenocarcinoma (PDAC), comprising over 90% of all pancreatic cancers, remains a lethal disease with an estimated 232,000 new cases, 227,000 deaths per year worldwide, and a less than 5% five-year survival rate. Currently the standard of care for the 20% of patients with localized disease is surgery followed by chemotherapy, and in some cases radiation. Unfortunately despite the use of adjuvant therapy, median survival remains at best 23 months. It is important to note however, that up to 27% of patients with resected PDAC can survive for five years. However, in these studies examining actual long-term survivors, only two have found that adjuvant therapy was associated with improved survival. In addition, randomized controlled trials of gemcitabine-based chemotherapy demonstrate an improvement in median survival of at best 3 months. One possible conclusion from these studies is that tumor biology dictates outcome and that our current adjuvant therapy has only a modest impact on altering a patient's course.Hypothesizing that the dismal outcome of patients with localized disease is due to the presence of micrometastasic disease, current clinical investigation has focused on preoperative or neoadjuvant therapy. This approach, where patients who cannot tolerate the stress of therapy or develop metastatic disease during treatment are spared surgery, has demonstrated an overall survival of 34 months in this highly selected patient population. Therefore the ability to select patients who would most benefit from a neoadjuvant approach may be important. One way to do this is to define a prognostic gene signature that can identify patients with more aggressive tumor biology upfront. reference x sample The 30 Nebraska and UNC samples were not analyzed with clinical data so it is not provided. One of the PE samples is missing some clinical data.

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A six-microRNA signature can better predict overall survival of patients with esophagus adenocarcinoma.

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A six-microRNA signature can better predict overall survival of patients with esophagus adenocarcinoma.

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