LncRNA profile study reveals a three-lncRNA signature associated with the survival of esophageal squamous cell carcinoma patients
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA232519 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Objective: Globally, esophageal cancer is among the most deadly cancer forms. Long non-coding RNAs (lncRNA) are frequently found to have important regulatory roles. We aim to assess the lncRNA expression profile of esophageal squamous cell carcinoma (ESCC) and identify prognosis related lncRNAs. Design: LncRNA expression profiles were studied by microarray in paired tumor and normal tissues from 119 ESCC patients, and validated by qRT-PCR. The 119 patients were subsequently divided randomly into training (n=60) and test (n=59) groups. A prognostic signature was developed from the training group using a random forest supervised classification algorithm and a nearest shrunken centroid algorithm, and validated in test group and further in an independent cohort (n=60). The independence of the signature in survival prediction was evaluated by Multivariable Cox regression analysis. Results: LncRNAs showed significantly altered expression in ESCC tissues. From the training group, we identified a three-lncRNA signature (including the lncRNAs ENST00000435885•1, XLOC_013014, and ENST00000547963•1) which classified the patients into two groups with significantly different overall survival (median survival 19•2 months vs. not reached, p<0•0001). The signature was applied to the test group (median survival 21•5 months vs. not reached, p=0•0030) and independent cohort (median survival 25•8 months vs. not reached, p=0•0187) and showed similar prognostic values in both. Multivariable Cox regression analysis showed that the signature was an independent prognostic factor for ESCC patients. Stratified analysis suggested that the signature was prognostic within clinical stages. Conclusions: Our results suggest that the three-lncRNA signature can serve as a novel biomarker for the prognosis of ESCC patients. Application of it allows for more accurate survival prediction. The lncRNA expression profiles of cancer and adjacent normal tissues form 119 ESCC patients were studied by microarray and an lncRNA signature that can perdict the survival of ESCC patients was identified.
2014-03-07 | E-GEOD-53624 | biostudies-arrayexpress
Project description:Objective: Globally, esophageal cancer is among the most deadly cancer forms. Long non-coding RNAs (lncRNA) are frequently found to have important regulatory roles. We aim to assess the lncRNA expression profile of esophageal squamous cell carcinoma (ESCC) and identify prognosis related lncRNAs. Design: LncRNA expression profiles were studied by microarray in paired tumor and normal tissues from 119 ESCC patients, and validated by qRT-PCR. The 119 patients were subsequently divided randomly into training (n=60) and test (n=59) groups. A prognostic signature was developed from the training group using a random forest supervised classification algorithm and a nearest shrunken centroid algorithm, and validated in test group and further in an independent cohort (n=60). The independence of the signature in survival prediction was evaluated by Multivariable Cox regression analysis. Results: LncRNAs showed significantly altered expression in ESCC tissues. From the training group, we identified a three-lncRNA signature (including the lncRNAs ENST00000435885•1, XLOC_013014, and ENST00000547963•1) which classified the patients into two groups with significantly different overall survival (median survival 19•2 months vs. not reached, p<0•0001). The signature was applied to the test group (median survival 21•5 months vs. not reached, p=0•0030) and independent cohort (median survival 25•8 months vs. not reached, p=0•0187) and showed similar prognostic values in both. Multivariable Cox regression analysis showed that the signature was an independent prognostic factor for ESCC patients. Stratified analysis suggested that the signature was prognostic within clinical stages. Conclusions: Our results suggest that the three-lncRNA signature can serve as a novel biomarker for the prognosis of ESCC patients. Application of it allows for more accurate survival prediction. The lncRNA expression profiles of cancer and adjacent normal tissues form 119 ESCC patients were studied by microarray and an lncRNA signature that can perdict the survival of ESCC patients was identified.
2014-03-07 | E-GEOD-53622 | biostudies-arrayexpress
Project description:Objective: Globally, esophageal cancer is among the most deadly cancer forms. Long non-coding RNAs (lncRNA) are frequently found to have important regulatory roles. We aim to assess the lncRNA expression profile of esophageal squamous cell carcinoma (ESCC) and identify prognosis related lncRNAs. Design: LncRNA expression profiles were studied by microarray in paired tumor and normal tissues from 119 ESCC patients, and validated by qRT-PCR. The 119 patients were subsequently divided randomly into training (n=60) and test (n=59) groups. A prognostic signature was developed from the training group using a random forest supervised classification algorithm and a nearest shrunken centroid algorithm, and validated in test group and further in an independent cohort (n=60). The independence of the signature in survival prediction was evaluated by Multivariable Cox regression analysis. Results: LncRNAs showed significantly altered expression in ESCC tissues. From the training group, we identified a three-lncRNA signature (including the lncRNAs ENST00000435885•1, XLOC_013014, and ENST00000547963•1) which classified the patients into two groups with significantly different overall survival (median survival 19•2 months vs. not reached, p<0•0001). The signature was applied to the test group (median survival 21•5 months vs. not reached, p=0•0030) and independent cohort (median survival 25•8 months vs. not reached, p=0•0187) and showed similar prognostic values in both. Multivariable Cox regression analysis showed that the signature was an independent prognostic factor for ESCC patients. Stratified analysis suggested that the signature was prognostic within clinical stages. Conclusions: Our results suggest that the three-lncRNA signature can serve as a novel biomarker for the prognosis of ESCC patients. Application of it allows for more accurate survival prediction.
2014-03-07 | GSE53624 | GEO
Project description:Objective: Globally, esophageal cancer is among the most deadly cancer forms. Long non-coding RNAs (lncRNA) are frequently found to have important regulatory roles. We aim to assess the lncRNA expression profile of esophageal squamous cell carcinoma (ESCC) and identify prognosis related lncRNAs. Design: LncRNA expression profiles were studied by microarray in paired tumor and normal tissues from 119 ESCC patients, and validated by qRT-PCR. The 119 patients were subsequently divided randomly into training (n=60) and test (n=59) groups. A prognostic signature was developed from the training group using a random forest supervised classification algorithm and a nearest shrunken centroid algorithm, and validated in test group and further in an independent cohort (n=60). The independence of the signature in survival prediction was evaluated by Multivariable Cox regression analysis. Results: LncRNAs showed significantly altered expression in ESCC tissues. From the training group, we identified a three-lncRNA signature (including the lncRNAs ENST00000435885•1, XLOC_013014, and ENST00000547963•1) which classified the patients into two groups with significantly different overall survival (median survival 19•2 months vs. not reached, p<0•0001). The signature was applied to the test group (median survival 21•5 months vs. not reached, p=0•0030) and independent cohort (median survival 25•8 months vs. not reached, p=0•0187) and showed similar prognostic values in both. Multivariable Cox regression analysis showed that the signature was an independent prognostic factor for ESCC patients. Stratified analysis suggested that the signature was prognostic within clinical stages. Conclusions: Our results suggest that the three-lncRNA signature can serve as a novel biomarker for the prognosis of ESCC patients. Application of it allows for more accurate survival prediction.
2014-03-07 | GSE53622 | GEO
Project description:Long noncoding RNAs (lncRNAs) are emerging as key regulators in cancer and play complicate and critical roles in regulating various key biological processes including chromatin modification, transcription and post-transcriptional processing. We identified a novel transcript, lncRNA NMR, which was upregulated in esophageal squamous cell carcinoma (ESCC) and significantly associated with overall survival of ESCC patients and and is identical to ENST00000432429.1 in GENCODE v13 or ENST00000432429.5 in Ensembl release 83. Here, we sought to determine the alterations of trancriptome after shRNA-mediated knockdown and transient overexpression of lncRNA NMR in ESCC KYSE70 and KYSE450 cell lines．
2018-07-01 | GSE101743 | GEO
Project description:We have investigated expressed microRNA in cryo-preserved esophageal cancer tissues using advanced microRNA microarray techniques. Our microarray analyses reveal a unique microRNA expression signature composed of 40 genes which can distinguish normal from malignant esophageal tissue. Some microRNAs could be correlated with the different clinico-pathological classifications. For example, high hsa-miR-103, -107, -23b expression correlated with poor overall disease-free survival of esophageal cancer patients. These results indicate that microRNA expression profiles are important diagnostic and prognostic markers of esophageal cancer, which might be analyzed simply using economical approaches such as RT-PCR. Keywords: microRNA, esophageal squamous cell carcinoma cancer vs adjacent normal tissues
2010-05-26 | E-GEOD-6188 | biostudies-arrayexpress
Project description:We have investigated expressed microRNA in cryo-preserved esophageal cancer tissues using advanced microRNA microarray techniques. Our microarray analyses reveal a unique microRNA expression signature composed of 40 genes which can distinguish normal from malignant esophageal tissue. Some microRNAs could be correlated with the different clinico-pathological classifications. For example, high hsa-miR-103, -107, -23b expression correlated with poor overall disease-free survival of esophageal cancer patients. These results indicate that microRNA expression profiles are important diagnostic and prognostic markers of esophageal cancer, which might be analyzed simply using economical approaches such as RT-PCR. Keywords: microRNA, esophageal squamous cell carcinoma
2008-02-18 | GSE6188 | GEO
Project description:Systems biology approaches can help understand pathogenesis of complex human diseases like cancers for identification of potential new therapeutic targets. Here in this study, we performed genome-wide screening for mRNA and lncRNA profiles in esophageal cancer to identify the novel cancer-related mRNA and lncRNA in esophageal squamous cell carcinoma (ESCC). We identified 3000 up-regulated/2517 down-regulated mRNAs and 402 up-regulated/741 down-regulated lncRNAs. Further functional analysis revealed differentially expressed genes (DEGs) of mRNA and lncRNA are related to different pathways. mRNA pathways are mainly involved in cell cycles while lncRNA pathways are for regulation and metabolic procession. Differentially expressed mRNAs/lncRNAs were validated with qPCR. At last, mRNA and lncRNA co-expression network were built and highly-connected networks were identified, which may provide a mechanism of mRNA expression regulation by lncRNA. To our knowledge, this is the first study to explore the co-expression networks and the lncRNA-mRNA networks could be therapeutic targets for ESCC treatments.
2019-02-23 | GSE111011 | GEO
Project description:Esophageal cancer presents significant challenges due to limited treatment options and poor prognosis, particularly in advanced stages. Dysregulated long non-coding RNAs (lncRNAs) are implicated in cancer progression and treatment resistance. This study investigated the roles of dysregulated lncRNA, identified through lncRNA-seq, and its downstream target gene in esophageal squamous cell carcinoma（ESCC).
2024-10-01 | GSE248518 | GEO
Project description:A seven-lncRNA signature was identified in the training set, which is significantly associated with overall survival (OS) (Hazard Ratio [HR]: 3.535, 95% confidence interval [CI]: 2.113-5.915, P < 0.001) and disease-free survival (DFS) (Hazard Ratio [HR]: 2.413, 95% confidence interval [CI]: 1.573-3.703, P < 0.001). Patients in high-risk group have shorter overall survival (HR: 3.555, 95% CI: 2.195-5.757, p < 0.001) and disease-free survival (HR: 2.537, 95% CI: 1.646-3.909, p < 0.001) in the training set, and we found the same conclusion in the independent set for OS (HR 2.665, p < 0.001) and DFS (HR 2.360, p = 0.001). Combination of the signature and TNM staging system was more powerful than TNM staging system alone in predicting outcomes in both the training set (AUC: 0.772 vs 0.681, p = 0.002) and in the independent set (AUC: 0.772 vs 0.660, p = 0.003).
2020-02-10 | GSE92986 | GEO