Analysis and application of RNA binding protein gene pairs to predict the prognosis of gastric cancer.

Background: RNA-binding proteins (RBPs) are closely related to tumors, but little is known about the mechanism of RBPs in tumorigenesis and progression of gastric cancer (GC). As genes do not usually act alone in the pathway deregulation, gene pair combinations are more likely to become stable and accurate biomarkers. The purpose of our research is to establish a novel signature based on RBP gene pairs to predict the prognosis of gastric cancer patients. Methods: We downloaded genetic and clinical information from the TCGA and GEO database. TCGA and GSE13911 were used for screening differentially expressed genes (DEGs). The RBP genes were gathered from previous studies and employed to screen out DE-RBP genes after intersecting with DEGs. Samples were classified according to the relative expression of each pair of DE-RBP genes. The univariate Cox regression analysis and random forest were used to identify hub gene pairs to construct signature for predicting the prognosis of gastric cancer. Time-dependent ROC curves and KM survival curves were performed to evaluate the signature. GSEA was performed in TCGA training cohort and GSE62254 testing cohort to analyze enrichment pathways. Finally, the influence of these gene pairs on the prognosis of GC patients was further elucidated respectively through the combination of high and low expression of the two genes in each hub gene pair. Results: We screened out 6 hub RBP gene pairs (COL5A2/FEN1, POP1/GFRA1, EXO1/PLEKHS1, SLC39A10/CHI3L1, MMP7/PPP1R1 B and SLC5A6/BYSL) to predict the prognosis of patients with gastric cancer. Using the optimal cut-off value to divide patients into high-risk and low-risk groups in the training and testing cohort, we found that the overall survival (OS) of the low-risk group was higher than that of the high-risk group (P < 0.05). The area under the ROC curves for 1, 3, and 5 years were (0.659, 0.744, 0.758) and (0.624, 0.650, 0.653) in two cohorts. Univariate and multivariate Cox regression analysis showed that 6 RBP gene pairs signature were independent prognostic factors for gastric cancer (P < 0.05). In addition, the prognostic survival analysis showed that COL5A2-high/FEN1-low, POP1-low/GFRA1-high, EXO1-low/PLEKHS1-low,SLC39A10-high/CHI3L1-low, MMP7-high/PPP1R1 B-low, SLC5A6-low/BYSL-low had worse OS (P < 0.05). And the gene correlation analysis showed that there was no obvious correlation between the genes in each gene pairs except SLC5A6/BYSL and POP1/GFRA1. Finally, GSEA analysis showed that the high-risk group was enriched in tumor migration, invasion and growth-related pathways. Conclusion: Our study identified a novel 6 RBP gene pairs signature to predict the prognosis of gastric cancer patients and provide potential targets for clinical gene therapy.

The TGF-ß/Smad2/3 signaling pathway is involved in Musashi2-induced invasion and metastasis of colorectal cancer.

To identify Musashi2 as an effective biomarker regulated by the TGF-ß/Smad2/3 signaling pathway for the precise diagnosis and treatment of colorectal cancer (CRC) through bioinformatic tools and experimental verification. The Cancer Genome Atlas, Timer, and Kaplan-Meier analyses were performed to clarify the expression of Musashi2 and its influence on the prognosis of CRC. Transforming growth factor beta 1 (TGF-ß1) was used to activate the TGF-ß/Smad2/3 signaling pathway to identify whether it could regulate the expression and function of Musashi2. Western blot analysis and quantitative PCR analyses were conducted to verify the expression of Musashi2. Cell counting kit-8 (CCK8), EdU, wound healing, and Transwell assays were conducted to reveal the role of Musashi2 in the proliferation, migration, and invasion of CRC. Musashi2 was upregulated in CRC and promoted proliferation and metastasis. TGF-ß1 increased the expression of Musashi2, while the antagonist inducer of type II TGF-ß receptor degradation-1 (ITD-1) decreased the expression. CCK8 and EdU assays demonstrated that inhibition of Musashi2 or use of ITD-1 lowered proliferation ability. The Transwell and wound healing assays showed that the migration and invasion abilities of CRC cells could be regulated by Musashi2. The above functions could be enhanced by TGF-ß1 by activating the TGF-ß/Smad2/3 signaling pathway and reversed by ITD-1. A positive correlation was found between Musashi2 and the TGF-ß/Smad2/3 signaling pathway. TGF-ß1 activates the TGF-ß/Smad2/3 pathway to stimulate the expression of Musashi2, which promotes the progression of CRC. Musashi2 might become a target gene for the development of new antitumor drugs.

Clinicopathological characteristics and prognosis of gastric signet ring cell carcinoma.

BACKGROUND: The clinicopathological features and prognosis of gastric signet ring cell carcinoma (GSRC) remain controversial, particularly with regard to sensitivity to postoperative adjuvant therapy. AIM: To compare the pathological features of GSRC with those of gastric adenocarcinoma of different degrees of differentiation and the differences in survival prognosis between the different disease processes. METHODS: By screening gastric cancer patients from 2010 to 2015 in the database of Surveillance, Epidemiology and End Results, and collecting the clinicopathological and prognostic data of gastric cancer patients who underwent surgery from January 2014 to December 2016 in the Second Affiliated Hospital of Nanchang University, we analyzed the general pathological characteristics of GSRC by the chi-square test. Univariate and multivariate analyses were conducted to compare the factors affecting the survival and prognosis of early and advanced gastric adenocarcinoma. The Kaplan-Meier curves were plotted to reveal the survival difference between early and advanced GSRC and different differentiated types of gastric adenocarcinoma. The prognosis model of advanced GSRC was established with R software, and the area under curve (AUC) and C-index were used to assess the accuracy of the model. RESULTS: Analysis of pathological features revealed that signet ring-cell carcinoma (SRC) was more frequently seen in younger (< 60 years), female, and White patients compared to non-SRC patients. SRC was less commonly associated with early gastric cancer (EGC) (23.60% vs 39.10%), lower N0 (38.61% vs 61.03%), and larger tumour sizes > 5 cm (31.15% vs 27.10%) compared to the differentiated type, while the opposite was true compared to the undifferentiated type. Survival prognostic analysis found no significant difference in the prognosis of SRC patients among EGC patients. In contrast, among advanced gastric cancer (AGC) patients, the prognosis of SRC patients was correlated with age, race, tumour size, AJCC stage, T-stage, and postoperative adjuvant therapy. The predictive model showed that the 3-year AUC was 0.787, 5-year AUC was 0.806, and C-index was 0.766. Compared to non-SRC patients, patients with SRC had a better prognosis in EGC [hazard ratio (HR): 0.626, 95% confidence interval (CI): 0.427-0.919, P < 0.05] and a worse prognosis in AGC (HR: 1.139, 95%CI: 1.030-1.258, P < 0.05). When non-SRC was divided into differentiated and undifferentiated types for comparison, it was found that in EGC, SRC had a better prognosis than differentiated and undifferentiated types, while there was no significant difference between differentiated and undifferentiated types. In AGC, there was no significant difference in prognosis between SRC and undifferentiated types, both of which were worse than differentiated types. A prognostic analysis of postoperative adjuvant therapy for SRC in patients with AGC revealed that adjuvant postoperative radiotherapy or chemotherapy significantly improved patient survival (34.6% and 36.2% vs 18.6%, P < 0.05). CONCLUSION: The prognosis of SRC is better than that of undifferentiated type, especially in EGC, and its prognosis is even better than that of differentiated type. SRC patients can benefit from early detection, surgical resection, and aggressive adjuvant therapy.

The Hypoxic Landscape Stratifies Gastric Cancer Into 3 Subtypes With Distinct M6a Methylation and Tumor Microenvironment Infiltration Characteristics.

The interaction between hypoxia and RNA N6-methyladenosine (m6A) is an emerging focus of investigation. However, alterations in m6A modifications at distinct hypoxia levels remain uncharacterized in gastric cancer (GC). Unsupervised hierarchical clustering was performed to stratify samples into different clusters. Differentially expressed gene analysis, univariate Cox proportional hazards regression analysis, and hazard ratio calculations were used to establish an m6A score to quantify m6A regulator modification patterns. After using an algorithm integrating Least absolute shrinkage and selection operator (LASSO) and bootstrapping, we identified the best candidate predictive genes. Thence, we established an m6A-related hypoxia pathway gene prognostic signature and built a nomogram to evaluate its predictive ability. The area under the curve (AUC) value of the nomogram was 0.811, which was higher than that of the risk score (AUC=0.695) and stage (AUC=0.779), suggesting a high credibility of the nomogram. Furthermore, the clinical response of anti-PD-1/CTLA-4 immunotherapy between high- and low-risk patients showed a significant difference. Our study successfully explored a brand-new GC pathological classification based on hypoxia pathway genes and the quantification of m6A modification patterns. Comprehensive immune analysis and validation demonstrated that hypoxia clusters were reliable, and our signature could provide a new approach for clinical decision-making and immunotherapeutic strategies for GC patients.

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

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.

Impact of Site-Specific Metastases on Surgical Value and Survival among Metastatic Colorectal Cancer Patients.

We aimed to explore the potential prognostic impact of the metastatic site on the management approach and prognosis of stage IV colorectal cancer patients with synchronous metastases. Synchronous metastatic colorectal cancer patients reported to the Surveillance, Epidemiology, and End Results Program database between 2010 and 2013 were included in this study. Overall survival (OS) was compared between patients with different treatment options using risk-adjusted Cox proportional hazard regression models. Overall, 17,776 patients with stage IV colorectal cancer were identified. Of these patients, 2,052 (11.5%) underwent surgical resection for tumors at both the primary and metastatic sites. Patients who underwent surgical resection of both primary and metastatic sites with liver, lung, and simultaneous liver and lung metastases had a longer median OS (P < 0.001) than patients who underwent nonsurgical treatments. Cox regression analysis revealed that surgical resection of both primary and metastatic sites was associated with a significantly enhanced OS (P < 0.001). Colorectal cancer patients with hepatic or pulmonary metastases, who underwent metastasectomy, even in selected patients with both hepatic and pulmonary metastases after multidisciplinary evaluation, could have a better survival benefit than patients who underwent nonsurgical treatments.