Nine-long non-coding ribonucleic acid signature can improve the survival prediction of colorectal cancer.

BACKGROUND: Investigating molecular biomarkers that accurately predict prognosis is of considerable clinical significance. Accumulating evidence suggests that long non-coding ribonucleic acids (lncRNAs) are frequently aberrantly expressed in colorectal cancer (CRC). AIM: To elucidate the prognostic function of multiple lncRNAs serving as biomarkers in CRC. METHODS: We performed lncRNA expression profiling using the lncRNA mining approach in large CRC cohorts from The Cancer Genome Atlas (TCGA) database. Receiver operating characteristic analysis was performed to identify the optimal cutoff point at which patients could be classified into the high-risk or low-risk groups. Based on the Cox coefficient of the individual lncRNAs, we identified a nine-lncRNA signature that was associated with the survival of CRC patients in the training set (n = 175). The prognostic value of this nine-lncRNA signature was validated in the testing set (n = 174) and TCGA set (n = 349). The prognostic models, consisting of these nine CRC-specific lncRNAs, performed well for risk stratification in the testing set and TCGA set. Time-dependent receiver operating characteristic analysis indicated that this predictive model had good performance. RESULTS: Multivariate Cox regression and stratification analysis demonstrated that this nine-lncRNA signature was independent of other clinical features in predicting overall survival. Functional enrichment analysis of Kyoto Encyclopedia of Genes and Genomes pathways and Gene Ontology terms further indicated that these nine prognostic lncRNAs were closely associated with carcinogenesis-associated pathways and biological functions in CRC. CONCLUSION: A nine-lncRNA expression signature was identified and validated that could improve the prognosis prediction of CRC, thereby providing potential prognostic biomarkers and efficient therapeutic targets for patients with CRC.

Prognostic thirteen-long non-coding RNAs (IncRNAs) could improve the survival prediction of gastric cancer / El pronóstico de 13 largos RNA no codificantes (IncRNA) podría mejorar la predicción de supervivencia del cáncer gástrico

OBJECTIVE: Accumulating evidence has demonstrated that long non-coding RNAs (lncRNAs) play important regulatory roles in the tumorigenesis and progression of gastric cancer (GC). The aim of this study was to construct the prognostic predictive model of lncRNAs signature and improve the survival prediction of GC. PATIENTS AND METHODS: The expression profiling of lncRNAs in large GC cohorts was performed from The Cancer Genome Atlas (TCGA) databases using the lncRNAs-mining approach, including training data set (N=160) and testing data set (N=159). A 13-lncRNAs signature significantly associated with overall survival (OS) in the training data set was selected. The prognostic value of this 13-lncRNAs signature was then confirmed in the test validation set and the entire validation set, respectively. RESULTS: Based on lncRNA expression profiling of 319 patients with stomach adenocarcinoma (STAD), prognostic 13-lncRNAs signature was found to be significantly associated with the prognosis of GC. Compared to patients with low-risk scores, patients with high-risk scores had a significantly shorter survival time. Moreover, functional enrichment analysis indicated that this 13-lncRNAs signature was potentially involved in multiple biological processes, such as DNA replication and cell cycle signaling pathway. CONCLUSIONS: The prognostic model of the 13-lncRNAs signature established by our study could improve the survival prediction of GC to a greater extent

OBJETIVO: Las pruebas acumuladas demostraron que los ARN no codificantes de larga duración (ARNlC) desempeñaban los importantes papeles reguladores en la tumorigénesis y la progresión del cáncer gástrico (CG). El objetivo de este estudio fue construir el modelo predictivo de pronóstico de la firma de los lncRNA y mejorar la predicción de supervivencia del GC. PACIENTES Y MÉTODOS: El perfil de expresión de los lncARN en grandes cohortes de GC se realizó a partir de las bases de datos del Atlas del Genoma del Cáncer (TCGA) utilizando el enfoque de minería de lncARN, incluyendo el conjunto de datos de entrenamiento (N=160) y el conjunto de datos de pruebas (N=159). Se eligió la firma de 13 lncARN significativamente asociada con la supervivencia general (OS) en la serie de capacitación. El valor pronóstico de esta firma de 13-lncARN se confirmó luego en la serie de validación de pruebas y en toda la serie de validación, respectivamente. RESULTADOS: Basado en el perfil de expresión de lncRNA de 319 pacientes con adenocarcinoma de estómago (STAD), se encontró que la firma de 13-lncRNA de pronóstico estaba significativamente asociada con el pronóstico de GC. En comparación con los pacientes con puntuaciones de bajo riesgo, los pacientes con puntuaciones de alto riesgo tuvieron un tiempo de supervivencia significativamente más corto. Además, el análisis de enriquecimiento funcional indicó que esta firma de 13-lncARN estaba potencialmente involucrada en múltiples procesos biológicos, como la replicación del ADN y la vía de señalización del ciclo celular. CONCLUSIONES: El modelo de pronóstico de la firma de 13-lncARN establecido por nuestro estudio podría mejorar mejor la predicción de supervivencia del GC

Expression and prognostic value of Chromobox family members in gastric cancer.

BACKGROUND: The Chromobox (CBX) protein family, which is a crucial part of the epigenetic regulatory complex, plays an important role in the occurrence and development of cancer; however, the function and prognostic value of CBX family members in gastric cancer is not clear. METHODS: we investigated the relationship between CBX members and gastric cancer using a range of tools and databases: Oncomine, Kaplan-Meier plotter, cBioPortal, ULCAN, Metascape, and GEPIA. RESULTS: The results showed that, relative to normal gastric tissue, mRNA expression levels of CBX1-6 were significantly higher in gastric cancer tissue, whereas the level of CBX7 was significantly lower. Furthermore, overexpression of CBX3-6 and underexpression of CBX7 mRNAs was significantly related to the poor prognosis and survival of gastric cancer patients, making these CBX family members useful biomarkers. Finally, overexpression of CBX1 mRNA was significantly related to the poor prognosis of gastric cancer patients treated with adjuvant 5-fluorouracil-based chemotherapy. CONCLUSIONS: The members of the CBX family can be used as prognosis and survival biomarkers for gastric cancer and CBX1 may be a biomarker for choosing the chemotherapy regimen of gastric cancer patients.

Prognostic thirteen-long non-coding RNAs (IncRNAs) could improve the survival prediction of gastric cancer.

OBJECTIVE: Accumulating evidence has demonstrated that long non-coding RNAs (lncRNAs) play important regulatory roles in the tumorigenesis and progression of gastric cancer (GC). The aim of this study was to construct the prognostic predictive model of lncRNAs signature and improve the survival prediction of GC. PATIENTS AND METHODS: The expression profiling of lncRNAs in large GC cohorts was performed from The Cancer Genome Atlas (TCGA) databases using the lncRNAs-mining approach, including training data set (N=160) and testing data set (N=159). A 13-lncRNAs signature significantly associated with overall survival (OS) in the training data set was selected. The prognostic value of this 13-lncRNAs signature was then confirmed in the test validation set and the entire validation set, respectively. RESULTS: Based on lncRNA expression profiling of 319 patients with stomach adenocarcinoma (STAD), prognostic 13-lncRNAs signature was found to be significantly associated with the prognosis of GC. Compared to patients with low-risk scores, patients with high-risk scores had a significantly shorter survival time. Moreover, functional enrichment analysis indicated that this 13-lncRNAs signature was potentially involved in multiple biological processes, such as DNA replication and cell cycle signaling pathway. CONCLUSIONS: The prognostic model of the 13-lncRNAs signature established by our study could improve the survival prediction of GC to a greater extent.