Comprehensive analysis to identify DNA damage response-related lncRNA pairs as a prognostic and therapeutic biomarker in gastric cancer

Yuan Yang; Lingshan Zhou; Xi Gou; Guozhi Wu; Ya Zheng; Min Liu; Zhaofeng Chen; Yuping Wang; Rui Ji; Qinghong Guo; Yongning Zhou

doi:10.3934/mbe.2022026

Mathematical Biosciences and Engineering (Jan 2022)

Comprehensive analysis to identify DNA damage response-related lncRNA pairs as a prognostic and therapeutic biomarker in gastric cancer

Yuan Yang,
Lingshan Zhou,
Xi Gou ,
Guozhi Wu,
Ya Zheng,
Min Liu,
Zhaofeng Chen ,
Yuping Wang,
Rui Ji,
Qinghong Guo,
Yongning Zhou

Affiliations

Yuan Yang: 1. The First Clinical Medical College, Lanzhou University, Lanzhou 730000, China 2. Department of Gastroenterology, The First Hospital of Lanzhou University, Lanzhou 730000, China 3. Gansu Key Laboratory of Gastroenterology, Lanzhou University, Lanzhou 730000, China
Lingshan Zhou: 4. Department of Geriatrics Ward 2, The First Hospital of Lanzhou University, Lanzhou 730000, China
Xi Gou: 2. Department of Gastroenterology, The First Hospital of Lanzhou University, Lanzhou 730000, China 3. Gansu Key Laboratory of Gastroenterology, Lanzhou University, Lanzhou 730000, China
Guozhi Wu: 1. The First Clinical Medical College, Lanzhou University, Lanzhou 730000, China 2. Department of Gastroenterology, The First Hospital of Lanzhou University, Lanzhou 730000, China 3. Gansu Key Laboratory of Gastroenterology, Lanzhou University, Lanzhou 730000, China
Ya Zheng: 2. Department of Gastroenterology, The First Hospital of Lanzhou University, Lanzhou 730000, China 3. Gansu Key Laboratory of Gastroenterology, Lanzhou University, Lanzhou 730000, China
Min Liu: 2. Department of Gastroenterology, The First Hospital of Lanzhou University, Lanzhou 730000, China 3. Gansu Key Laboratory of Gastroenterology, Lanzhou University, Lanzhou 730000, China
Zhaofeng Chen: 2. Department of Gastroenterology, The First Hospital of Lanzhou University, Lanzhou 730000, China 3. Gansu Key Laboratory of Gastroenterology, Lanzhou University, Lanzhou 730000, China
Yuping Wang: 2. Department of Gastroenterology, The First Hospital of Lanzhou University, Lanzhou 730000, China 3. Gansu Key Laboratory of Gastroenterology, Lanzhou University, Lanzhou 730000, China
Rui Ji: 2. Department of Gastroenterology, The First Hospital of Lanzhou University, Lanzhou 730000, China 3. Gansu Key Laboratory of Gastroenterology, Lanzhou University, Lanzhou 730000, China
Qinghong Guo: 2. Department of Gastroenterology, The First Hospital of Lanzhou University, Lanzhou 730000, China 3. Gansu Key Laboratory of Gastroenterology, Lanzhou University, Lanzhou 730000, China
Yongning Zhou: 2. Department of Gastroenterology, The First Hospital of Lanzhou University, Lanzhou 730000, China 3. Gansu Key Laboratory of Gastroenterology, Lanzhou University, Lanzhou 730000, China

DOI: https://doi.org/10.3934/mbe.2022026
Journal volume & issue: Vol. 19, no. 1
pp. 595 – 611

Abstract

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Objective: Gastric cancer (GC) is the fifth most common malignancy and the fourth leading cause of cancer-related mortality worldwide. The identification of valuable predictive signatures to improve the prognosis of patients with GC is becoming a realistic prospect. DNA damage response-related long noncoding ribonucleic acids (drlncRNAs) play an important role in the development of cancers. However, their prognostic and therapeutic values remain sparse in gastric cancer (GC). Methods: We obtained the transcriptome data and clinical information from The Cancer Genome Atlas Stomach Adenocarcinoma (TCGA-STAD) cohort. Co-expression network analyses were performed to discover functional modules using the igaph package. Subsequently, lncRNA pairs were identified by bioinformation analysis, and prognostic pairs were determined by univariate analysis, respectively. In addition, we utilized least absolute shrinkage and selection operator (LASSO) cox regression analysis to construct the risk model based on lncRNA pairs. Then, we distinguished between the high- or low- risk groups from patients with GC based on the optimal model. Finally, we reevaluated the association between risk score and overall survival, tumor immune microenvironment, specific tumor-infiltrating immune cells related biomarkers, and the sensitivity of chemotherapeutic agents. Results: 32 drlncRNA pairs were obtained, and a 17-drlncRNA pairs signature was constructed to predict the overall survival of patients with GC. The ROC was 0.797, 0.812 and 0.821 at 1, 2, 3 years, respectively. After reclassifying these patients into different risk-groups, we could differentiate between them based on negative overall survival outcome, specialized tumor immune infiltration status, higher expressed immune cell related biomarkers, and a lower chemotherapeutics sensitivity. Compared with previous models, our model showed better performance with a higher ROC value. Conclusion: The prognostic and therapeutic signature established by novel lncRNA pairs could provide promising prediction value, and guide individual treatment strategies in the future.

Published in Mathematical Biosciences and Engineering

ISSN: 1551-0018 (Online)
Publisher: AIMS Press
Country of publisher: United States
LCC subjects: Technology: Chemical technology: Biotechnology; Science: Mathematics
Website: https://www.aimspress.com/journal/MBE

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