Development and validation of glycolysis‐related prognostic score for prediction of prognosis and chemosensitivity of pancreatic ductal adenocarcinoma

Zhang, Xiuping; Chen, Qinjunjie; Liu, Qu; Wang, Yang; Wang, Fei; Zhao, Zhiming; Zhao, Guodong; Lau, Wan Yee; Gao, Yinghong; Liu, Rong

doi:10.1111/jcmm.16573

Cited by 9 publications

(11 citation statements)

References 53 publications

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“…Owing to its insidious onset, rapid progression, and high malignancy, only 9.7% of patients are diagnosed early ( 26 ). The 5-year overall survival rate increased from 3% in the 1970s to 9% in 2020 ( 27 ). The 5-year survival rate for patients with advanced disease is still 3% ( 27 ).…”

Section: Discussionmentioning

confidence: 99%

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AQP5 Is a Novel Prognostic Biomarker in Pancreatic Adenocarcinoma

et al. 2022

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BackgroundPancreatic adenocarcinoma (PAAD) is a highly malignant tumor with a poor prognosis. The identification of effective molecular markers is of great significance for diagnosis and treatment. Aquaporins (AQPs) are a family of water channel proteins that exhibit several properties and play regulatory roles in human carcinogenesis. However, the association between Aquaporin-5 (AQP5) expression and prognosis and tumor-infiltrating lymphocytes in PAAD has not been reported.MethodsAQP5 mRNA expression, methylation, and protein expression data in PAAD were analyzed using GEPIA, UALCAN, HAP, METHSURV, and UCSC databases. AQP5 expression in PAAD patients and cell lines from our cohort was examined using immunohistochemistry and Western blotting. The LinkedOmics database was used to study signaling pathways related to AQP5 expression. TIMER and TISIDB were used to analyze correlations among AQP5, tumor-infiltrating immune cells, and immunomodulators. Survival was analyzed using TCGA and Kaplan–Meier Plotter databases.ResultsIn this study, we investigated AQP5 expression in PAAD and determined whether the expression of AQP5 is a strong prognostic biomarker for PAAD. We searched and analyzed public cancer databases (GEO, TCGA, HAP, UALCAN, GEPIA, etc.) to conclude that AQP5 expression levels were upregulated in PAAD. Kaplan–Meier curve analysis showed that high AQP5 expression positively correlated with poor prognosis. Using TIMER and TISIDB, we found that the expression of AQP5 was associated with different tumor-infiltrating immune cells, especially macrophages. We found that hypomethylation of the AQP5 promoter region was responsible for its high expression in PAAD.ConclusionsAQP5 can serve as a novel biomarker to predict prognosis and immune infiltration in PAAD.

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Section: Discussionmentioning

confidence: 99%

“…The 5-year overall survival rate increased from 3% in the 1970s to 9% in 2020 ( 27 ). The 5-year survival rate for patients with advanced disease is still 3% ( 27 ). The incidence of PAAD is likely to increase in the future owing to lifestyle changes, such as alcohol consumption, high-fat diets, and high-glucose diets.…”

Section: Discussionmentioning

confidence: 99%

AQP5 Is a Novel Prognostic Biomarker in Pancreatic Adenocarcinoma

et al. 2022

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“…In the present study, GSEA showed HCC tissues from patients at high risk for poor prognosis were enriched in glycolysis-related genes. Glycolysis-related pathways have been associated with recurrence in liver cancer ( Zhang et al, 2018 ).…”

Section: Discussionmentioning

confidence: 99%

A Glycolysis-Related Gene Signature Correlates With the Characteristics of the Tumor Immune Microenvironment and Predicts Prognosis in Patients With Hepatocellular Carcinoma

Yang

Zhang

Duan

et al. 2022

Front. Mol. Biosci.

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Aim: To develop a glycolysis-related gene signature that correlated with the characteristics of the tumor immune microenvironment and had good predictive power for overall survival (OS) in hepatocellular carcinoma (HCC).Methods: Gene expression profiles, RNA sequencing data, clinical characteristics and survival information for 407 patients with HCC and 58 healthy controls were downloaded from the TCGA database. GSEA 4.1.0 software was used to evaluate the glycolysis-related pathways enriched in HCC compared to normal liver tissue. Univariate Cox, Least Absolute Shrinkage, Selection Operator, and two-step multivariate Cox analyses were used to construct a glycolysis-related gene signature for prognostic prediction. The glycolysis-related gene signature was combined with clinical characteristics to generate a nomogram. Tumor-infiltrating immune cell profiles and PD-L1 protein expression in HCC tissues were investigated.Results: The gene expression profiles of HCC tissues were enriched in glycolysis-related pathways. A glycolysis-related gene signature was used to categorize patients as high-risk or low-risk, where high-risk patients had significantly worse OS. Receiver operating characteristic curves confirmed the predictive capability of the glycolysis-related gene signature for OS (AUC >0.80). There was a significant difference in M0 macrophage (p = 0.017), dendritic cell (p = 0.043), B cell (p = 0.0018), CD4 T cell (p = 0.003), Treg (p = 0.01) and mast cell (p = 0.02) content and PD-L1 protein expression (p = 0.019) between HCC tissues in patients in the high-risk and low-risk groups.Conclusion: We established a glycolysis-related gene signature for OS in HCC that was predictive in training and test TCGA cohorts and correlated with the characteristics of the HCC tumor immune microenvironment. The glycolysis-related gene signature may guide clinical decision-making concerning patient selection for immunotherapy in HCC.

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“…Dai Shang-nan et al reported that glycolysis promotes the progression of pancreatic cancer and reduces cancer cell sensitivity to gemcitabine [ 18 ]. Zhang et al established a glycolysis-related prognostic formula to predict the chemosensitivity of patients with PDAC [ 19 ]. The result from our study also illustrates the emergency role of the glycolysis pathway in PDAC using GSVA.…”

Section: Discussionmentioning

confidence: 99%

Identification and Validation of Three PDAC Subtypes and Individualized GSVA Immune Pathway-Related Prognostic Risk Score Formula in Pancreatic Ductal Adenocarcinoma Patients

Zhang

Wang

Peng

et al. 2021

Journal of Oncology

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Background. With the progress of precision medicine treatment in pancreatic ductal adenocarcinoma (PDAC), individualized cancer-related medical examination and prediction are of great importance in this high malignant tumor and tumor-immune microenvironment with changed pathways highly enrolled in the carcinogenesis of PDAC. Methods. High-throughput data of pancreatic ductal adenocarcinoma were downloaded from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) database. After batch normalization, the enrichment pathway and relevant scores were identified by the enrichment of immune-related pathway signature using gene set variation analysis (GSVA). Then, cancerous subtype in TCGA and GEO samples was defined through the NMF methods by cancertypes packages in R software, respectively. Subsequently, the significance between the characteristics of each TCGA sample and cancer type and the significant prognosis-related pathway with risk score formula is calculated through t-test and univariate Cox analysis. Next, the prognostic value of gained risk score formula and each significant prognosis-related pathway were validated in TCGA and GEO samples by survival analysis. The pivotal hub genes in the enriched significant prognosis-related pathway are identified and validated, and the TIMER database was used to identify the potential role of hub genes in the PDAC immune environment. The potential role of hub genes is promoting the transdifferentiation of cancer-associated fibroblasts. Results. The enrichment pathway and relevant scores were identified by GSVA, and 3 subtypes of pancreatic ductal adenocarcinoma were defined in TCGA and GEO samples. The clinical stage, tumor node metastasis classification, and tumor grade are strongly relative to the subtype above in TCGA samples. A risk formula about GSVA significant pathway “GSE45365_WT_VS_IFNAR_KO_CD11B_DC_MCMV_INFECTION_DN ∗ 0.80 + HALLMARK_GLYCOLYSIS ∗ 16.8 + GSE19888_CTRL_VS_T_CELL_MEMBRANES_ACT_MAST_CELL_DN ∗ 14.4” was identified and validated in TCGA and GEO samples through survival analysis with significance. DCN, VCAN, B4GALT7, SDC1, SDC2, B3GALT6, B3GAT3, SDC3, GPC1, and XYLT2 were identified as hub genes in these GSVA significant pathways and validated in silico. Conclusions. Three pancreatic ductal adenocarcinoma subtypes are identified, and an individualized GSVA immune pathway score-related prognostic risk score formula with 10 hub genes is identified and validated. The predicted function of the 10 upregulated hub genes in tumor-immune microenvironment was promoting the infiltration of cancer-associated fibroblasts. These findings will contribute to the precision medicine of pancreatic ductal adenocarcinoma treatment and tumor immune-related basic research.

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Development and validation of glycolysis‐related prognostic score for prediction of prognosis and chemosensitivity of pancreatic ductal adenocarcinoma

Cited by 9 publications

References 53 publications

AQP5 Is a Novel Prognostic Biomarker in Pancreatic Adenocarcinoma

AQP5 Is a Novel Prognostic Biomarker in Pancreatic Adenocarcinoma

A Glycolysis-Related Gene Signature Correlates With the Characteristics of the Tumor Immune Microenvironment and Predicts Prognosis in Patients With Hepatocellular Carcinoma

Identification and Validation of Three PDAC Subtypes and Individualized GSVA Immune Pathway-Related Prognostic Risk Score Formula in Pancreatic Ductal Adenocarcinoma Patients

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