Establishment of a 7-miRNA–Based Risk Score System for Predicting Prognosis of Pancreatic Cancer

Abstract Background Pancreatic cancer (PC) is one of the most common cancers and the leading cause of cancer-related death worldwide. Exploring novel predictive biomarkers for PC patients’ prognosis is in urgent need. Methods In the present study, we conducted Cox proportional hazards regression to identify critical prognosis-associated lncRNAs (PALncs) in TCGA PC dataset. Based on the results of multivariate analysis, a PALnc-based risk score system was established, and validated in GSE62452 dataset. The validity and reliability of the risk score system for prognosis of PC were evaluated through ROC analysis. And function enrichment analyses for the PALncs were also performed. Result In the multivariate analysis, four PALncs (LINC00476, C9orf163, LINC00346 and DSCR9) were screened out to develop a risk score system, which showed a high AUC at 3 and 5 years overall survival (0.785 at 3 year OS, 0.863 at 5 year OS) in TCGA datasets. And the ROC analysis of the risk score system for RFS in TCGA dataset revealed that AUC for RFS was 0.799 at 3 years and 0.909 at 5 years. Further, the AUC for OS in the validation cohort was 0.705 at 3 years and 0.959 at 5 years. Furthermore, the functional enrichment analysis revealed that these PALncs may be involved in various pathways related to cancer, including Ras family activation, autophagy in cancer, MAPK signaling pathway, HIF-1 signaling pathway, PI3K-Akt signaling pathway, etc. And correlation analysis of these tumor infiltrating immune cells and risk score system revealed that the infiltration level of B cell naïve, plasma cells, and CD8+ T cells are negatively correlated to the risk score system, while macrophages M2 positively correlated to the risk score system. Conclusion Our study established a four PALncs based risk score system, which reflects immune cell infiltration and predicts patient survival for PC.

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Comprehensive Analysis of Autophagy-Associated lncRNAs Reveal Potential Prognostic Prediction in Pancreatic Cancer

Frontiers in Oncology ◽

10.3389/fonc.2021.596573 ◽

2021 ◽

Vol 11 ◽

Author(s):

Guangyu Chen ◽

Gang Yang ◽

Junyu Long ◽

Jinshou Yang ◽

Cheng Qin ◽

...

Keyword(s):

Pancreatic Cancer ◽

Risk Score ◽

Expression Profile ◽

Cox Regression ◽

Risk Groups ◽

Cancer Genome ◽

Low Risk ◽

Score System ◽

Prognostic Prediction ◽

Risk Score System

Pancreatic cancer (PC) is a highly malignant tumor in the digestive system. Both long noncoding RNAs (lncRNAs) and autophagy play vital roles in the development and progress of PC. Here, we constructed a prognostic risk score system based on the expression profile of autophagy-associated lncRNAs for prognostic prediction in PC patients. Firstly, we extracted the expression profile of lncRNA and clinical information from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases. The autophagy-associated genes were from The Human Autophagy Database. Through Cox regression and survival analysis, we screened out seven autophagy-associated lncRNAs and built the risk score system in which the patients with PC were distinguished into high- and low-risk groups in both training and validation datasets. PCA plot displayed distinct discrimination, and risk score system displayed independently predictive value for PC patient survival time by multivariate Cox regression. Then, we built a lncRNA and mRNA co-expression network via Cytoscape and Sankey diagram. Finally, we analyzed the function of lncRNAs in high- and low-risk groups by gene set enrichment analysis (GSEA). The results showed that autophagy and metabolism might make significant effects on PC patients of low-risk groups. Taken together, our study provides a new insight to understand the role of autophagy-associated lncRNAs and finds novel therapeutic and prognostic targets in PC.

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Establishment of a Prognostic Prediction System Based on Tumor Microenvironment of Pancreatic Cancer

10.21203/rs.3.rs-955286/v1 ◽

2021 ◽

Author(s):

Bo Liu ◽

Tingting Fu ◽

Ping He ◽

Ke Xu

Keyword(s):

Pancreatic Cancer ◽

Regression Analysis ◽

Risk Score ◽

Cox Regression ◽

External Validation ◽

Prediction System ◽

Score System ◽

Cox Regression Analysis ◽

Prognostic Prediction ◽

Risk Score System

Abstract Purpose: Pancreatic cancer (PC) is an inflammatory tumor. Tumor microenvironment (TME) plays an important role in the development of PC. This study aims to explore hub genes of TME and establish a prognostic prediction system for PC.Methods: High throughput RNA-sequencing and clinical data of PC were downloaded from TCGA and ICGC database, respectively. PC Patients were divided into High- and low-score group by using stromal, immune scores system based on ESTIMATE. Differentially expressed genes (DEGs) between High- and low-score patients were screened and survival related DEGs were identified as candidate genes by univariate COX regression analysis. Final variables for establishment of the prognostic prediction system were determined by LASSO analysis and multivariate COX regression analysis. The predictive power of the prognostic system was evaluated by internal and external validation. Results: A total of 210 candidate genes were identified by stromal, immune scores system and survival analyses. Finally, the prognostic risk score system was constructed by the following genes: FAM57B, HTRA3, CXCL10, GABRP, SPRR1B, FAM83A, LY6D. In process of internal validation, Harrell's C-index of this prognostic risk score system was 0.73, and the area under the receiver operating characteristic curve (AUC) value of 1-year, 2-year and 3-year OS period was 0.67, 0.76 and 0.86, respectively. In the external validation set, the survival prediction C-index was 0.71, and the AUC was 0.81, 0.72, 0.78 at 1-year, 2-year and 3-year, respectively.Conclusion: This prognostic risk score system based on TME demonstrated a good predictive capacity to the prognosis of PC.

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A risk score system for identification of patients with upper-GI bleeding suitable for outpatient management

Gastrointestinal Endoscopy ◽

10.1016/s0016-5107(04)00362-1 ◽

2004 ◽

Vol 59 (7) ◽

pp. 772-781 ◽

Cited By ~ 22

Author(s):

Pedro Almela ◽

Adolfo Benages ◽

Salvador Peiró ◽

Ramón Añón ◽

Miguel Minguez Pérez ◽

...

Keyword(s):

Risk Score ◽

Gi Bleeding ◽

Outpatient Management ◽

Score System ◽

Upper Gi Bleeding ◽

Upper Gi ◽

Risk Score System

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The pulmonary embolism risk score system reduces the incidence and mortality of pulmonary embolism after gastric bypass

Surgery ◽

10.1016/j.surg.2009.07.011 ◽

2009 ◽

Vol 146 (4) ◽

pp. 678-685 ◽

Cited By ~ 7

Author(s):

Joseph A. Caruana ◽

Paul M. Anain ◽

Dang Tuan Pham

Keyword(s):

Pulmonary Embolism ◽

Gastric Bypass ◽

Risk Score ◽

Score System ◽

Incidence And Mortality ◽

Risk Score System

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Risk score system for late aortic events in patients with uncomplicated type B aortic dissection

Journal of Thoracic and Cardiovascular Surgery ◽

10.1016/j.jtcvs.2019.06.019 ◽

2020 ◽

Vol 159 (6) ◽

pp. 2173-2183.e1 ◽

Cited By ~ 4

Author(s):

Akihito Matsushita ◽

Minoru Tabata ◽

Wahei Mihara ◽

Takeshi Shimamoto ◽

Tatsuhiko Komiya ◽

...

Keyword(s):

Aortic Dissection ◽

Risk Score ◽

Type B ◽

Type B Aortic Dissection ◽

Score System ◽

Risk Score System

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Serum ghrelin level is associated with cardiovascular risk score

Romanian Journal Of Internal Medicine ◽

10.1515/rjim-2015-0019 ◽

2015 ◽

Vol 53 (2) ◽

pp. 140-145 ◽

Cited By ~ 2

Author(s):

Dana Pop ◽

P. Peter ◽

Alexandra Dădârlat ◽

Adela Sitar-Tăut ◽

D. Zdrenghea

Keyword(s):

Risk Factors ◽

Cardiovascular Risk ◽

Cardiovascular Risk Factors ◽

Risk Score ◽

Wide Distribution ◽

Score System ◽

Cardiology Department ◽

Significant Difference ◽

Risk Score System ◽

Serum Ghrelin

Abstract Ghrelin, a newly discovered bioactive peptide, was originally reported to induce growth hormone release. Recent studies have shown beneficial hemodynamic effects of ghrelin in the cardiovascular system to support the wide distribution of its receptors in cardiovascular tissues. The aim of the study was to determine whether cardiovascular risk factors influence plasma ghrelin levels. Methods. We evaluated in the Rehabilitation Hospital Cluj-Napoca, Cardiology - Department 88 consecutive subjects, 65 (73.86%) being women, with mean age 61.7±10.33 years. We assessed the presence of cardiovascular risk factors (obesity, arterial hypertension, diabetes mellitus, metabolic syndrome, smoking and lipid fractions). Plasma ghrelin levels were determined with a commercial ELISA kit (pg/ml). Results. After the evaluation of cardiovascular risk factors, we found no statistically significant difference between ghrelin levels in the patients with vs those without cardiovascular risk factors (p>0.05). A negative correlation was found between ghrelin levels and age, r = −0.32 (p <0.05). Using the HeartScore Internet tool we calculated the cardiovascular risk for each patient according to the risk score system (SCORE) for high cardiovascular risk countries. Statistically, the risk of fatal cardiovascular events in the next 10 years was indirectly correlated with the ghrelin levels in each patient - correlation between ghrelin levels and SCORE system r=−0.25, p=0.015. In conclusion, low serum ghrelin concentrations are associated with an increased global cardiovascular risk, calculated based on the European SCORE scale. However, we could not demonstrate a direct relationship between any of the major risk factors and ghrelin.

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