ABSTRACT: LncRNA profile study reveals a three-lncRNA signature associated with the survival of esophageal squamous cell carcinoma patients (independent set)
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.
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.
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.
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.
Project description:LncRNA profile study reveals a three-lncRNA signature associated with the survival of esophageal squamous cell carcinoma patients (original)
Project description:Esophageal cancer is a highly malignant and prevalent cancer worldwide. Current TNM staging system is insufficient for prognosis of esophagus squamous cell carcinoma (ESCC) patients. The aim of this study is to evaluate miRNA expression profile of ESCC and identify a miRNA signature which robustly predict the survival of ESCC patients. MiRNA expression profiles of paired frozen tissues from 119 ESCC patients were assessed by microarray. After normalization of microarray data, the patients were randomly divided into a training set (n=60) and a test set (n=59). From the training set, we identified a four-miRNA prognostic signature (including hsa-miR-218-5p, hsa-miR-142-3p, hsa-miR-150-5p, and hsa-miR-205-5p) using random forest supervised classification algorithm and nearest shrunken centroid algorithm. This signature distinguished the patients into high-risk or low-risk groups whose overall survival differed significantly (5-year survival 7.4% vs. 66.7%, p<0.001). Prognostic value of this signature was validated in the test set (5-year survival 18.8% vs. 46.5%, p=0.025) and further in an independent cohort of 58 patients assessed by a different platform (5-year survival 11.4% vs. 56.7%, p=0.003). Furthermore, multivariable Cox regression analysis revealed that this signature is an independent prognostic factor for ESCC patients. Moreover, stratified analysis showed that this signature was able to predict survival within TNM stages. The expression level of the four miRNAs measured by microarray was verified by qRT-PCR and showed high level of positive correlation (Pearson correlation coefficient>0.75, p<0.001 for all). Our results suggest that the four-miRNA signature can serve as a reliable biomarker to predict the survival of ESCC patients. the miRNA expression profiles of cancer and adjacent normal tissues form 119 ESCC patients were used to identify a miRNA signature that can perdict the survival of ESCC patients.
Project description:The differential expression profile of lncRNAs and mRNAs in esophageal squamous cell carcinoma in high-incidence areas of China was constructed and co-expression correlation analysis was performed. The expression profile of lncRNAs in ESCC tissues was significantly different from that in adjacent normal tissues. Co-expression analysis revealed that lncRNA may be involved in the occurrence and development of esophageal cancer, thus providing a new basis for the diagnosis and treatment of esophageal cancer.
Project description:Esophageal cancer is a highly malignant and prevalent cancer worldwide. Current TNM staging system is insufficient for prognosis of esophagus squamous cell carcinoma (ESCC) patients. The aim of this study is to evaluate miRNA expression profile of ESCC and identify a miRNA signature which robustly predict the survival of ESCC patients. MiRNA expression profiles of paired frozen tissues from 119 ESCC patients were assessed by microarray. After normalization of microarray data, the patients were randomly divided into a training set (n=60) and a test set (n=59). From the training set, we identified a four-miRNA prognostic signature (including hsa-miR-218-5p, hsa-miR-142-3p, hsa-miR-150-5p, and hsa-miR-205-5p) using random forest supervised classification algorithm and nearest shrunken centroid algorithm. This signature distinguished the patients into high-risk or low-risk groups whose overall survival differed significantly (5-year survival 7.4% vs. 66.7%, p<0.001). Prognostic value of this signature was validated in the test set (5-year survival 18.8% vs. 46.5%, p=0.025) and further in an independent cohort of 58 patients assessed by a different platform (5-year survival 11.4% vs. 56.7%, p=0.003). Furthermore, multivariable Cox regression analysis revealed that this signature is an independent prognostic factor for ESCC patients. Moreover, stratified analysis showed that this signature was able to predict survival within TNM stages. The expression level of the four miRNAs measured by microarray was verified by qRT-PCR and showed high level of positive correlation (Pearson correlation coefficient>0.75, p<0.001 for all). Our results suggest that the four-miRNA signature can serve as a reliable biomarker to predict the survival of ESCC patients.