A novel immune-related lncRNA pair signature for prognostic prediction and immune response evaluation in gastric cancer: a bioinformatics and biological validation study

Cancer Cell International

Lie Wang¹  Biting Zhou²  Shaojun Yu³  Muxing Kang⁴  Jia Qi⁴  Jun Wang⁴  Jing Chen⁴  Xiaoli Jin⁴  Le Shi⁴  Beidi Wang⁴  Guofeng Chen⁴  Jian Chen⁴  Linghua Zhu⁵  Jinghong Xu⁶ 

[1] Bone Marrow Transplantation Center of the First Affiliated Hospital, Institute of Immunology, Zhejiang University School of Medicine, 310000, Hangzhou, Zhejiang, China;Cancer Institute (Key Laboratory of Cancer Prevention and Intervention, China National Ministry of Education, Key Laboratory of Molecular Biology in Medical Sciences, Zhejiang Province, China), The Second Affiliated Hospital, Zhejiang University School of Medicine, 310000, Hangzhou, Zhejiang, China;Department of Colorectal Surgery and Oncology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 310000, Hangzhou, Zhejiang, China;Department of Gastroenterology Surgery, The Second Affiliated Hospital, Zhejiang University School of Medicine, 310000, Hangzhou, Zhejiang, China;Department of General Surgery, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, 310000, Hangzhou, Zhejiang, China;Department of Pathology, the Second Affiliated Hospital, Zhejiang University School of Medicine, 310000, Hangzhou, Zhejiang, China;

关键词: Gastric cancer;    TCGA;    Immune-related lncRNA pair;    LASSO;    Prognostic prediction;    Immune response;   

DOI  :  10.1186/s12935-022-02493-2

来源: Springer

【 摘 要 】

BackgroundGastric cancer (GC), the most commonly diagnosed cancer worldwide with poor 5-year survival rate in advanced stages. Although immune-related and survival-related biomarkers, which typically comprise aberrantly expressed long non-coding RNAs (lncRNAs) and genes, have been identified, there are no reports of immune-related lncRNA pair (IRLP) signatures for GC.MethodsIn this study, we acquired lncRNA expression profiles from The Cancer Genome Atlas (TCGA) and used the least absolute shrinkage and selection operator (LASSO) Cox proportional hazards model (iteration = 1000) to develop a IRLP prognostic signature. The area under curve (AUC) was used to assess the prognosis predictive power. The multivariate Cox regression analysis was performed to identify whether this signature was an independent prognostic factor. The immune cell infiltration analysis was performed between the two risk groups. Last, molecular experiments were performed to explore LINC01082 is involved in the development of GC.ResultsWe acquired lncRNA expression profiles and used the LASSO Cox model to develop an 18-IRLP signature with a strong prognostic predictive power. The 5-year AUC values of the training, validation, and overall TCGA datasets were 0.77, 0.86, and 0.80, respectively. The different prognostic outcomes between the high- and low-risk groups were determined using our 18-IRLP signature. Moreover, our 18-IRLP signature was an independent prognostic factor as per the multivariate Cox regression analysis, and showed better prognostic evaluation than the traditional TNM staging system as well as other clinical features. We also found differences in cancer-associated fibroblast and macrophage M2 infiltration and the expression of PD-L1, CTLA4, LAG3, and HLA were also observed between the two risk groups (P < 0.05). Analysis of biological functions revealed that target genes of the lncRNAs in the IRLP signature were enriched in focal adhesion and regulation of actin cytoskeleton. Finally, as one of significant candidates of IRLP signature, overexpression of LINC01082 suppressed the invasion ability of GC cells as well as PD-L1 expression profiles.ConclusionsOur novel 18-IRLP signature provides new insights regarding immunological biomarkers, imparts a better understanding of the tumor immune microenvironment, and can be used for predicting prognosis and evaluating immune response in GC.

【 授权许可】

CC BY