Abstract
The tumor immune microenvironment of lung cancer is associated with prognosis and immunotherapy efficacy. Long noncoding RNAs are identified as prognostic biomarkers associated with immune functions. We constructed a signature comprising differentially expressed immune-related lncRNAs to predict the prognosis of patients with lung adenocarcinoma. We established the immune-related lncRNA signature by pairing immune-related lncRNAs regardless of expression level and lung adenocarcinoma patients were divided into high- and low-risk groups. The prognosis of patients in the two groups was significantly different; The immune-related lncRNA signature could serve as an independent lung adenocarcinoma prognostic indicator. The signature correlated negatively with B cell, CD4+ T cell, M2 macrophage, neutrophil, and monocyte immune infiltration. Patients with low risk scores had a higher abundance of immune cells and stromal cells around the tumor. Gene set enrichment analysis showed that samples from low-risk group were more active in the IgA production in intestinal immune network and the T and B cell receptor signaling pathway. High-risk groups had significant involvement of the cell cycle, DNA replication, adherens junction, actin cytoskeleton regulation, pathways in cancer, and TGF-β signaling pathways. High risk scores correlated significantly negatively with high CTLA-4 and HAVCR2 expression and higher median inhibitory concentration of common anti-tumor chemotherapeutics (e.g., cisplatin, paclitaxel, gemcitabine) and targeted therapy (e.g., erlotinib and gefitinib). We identified a reliable immune-related lncRNA lung adenocarcinoma prognosis model, and the immune-related lncRNA signature showed promising clinical prediction value.
Highlights
According to the latest research, lung cancer is the leading malignant tumor in China and even in the world. [1,2,3] Lung adenocarcinoma (LUAD) is the major type of non–small cell lung cancer (NSCLC) [4]
We identified DEirlncRNAs using a multi-step approach (Figure 1)
In the present study, we only needed to know which irlncRNA expression level was higher in the DEirlncRNA pair, rather than the specific expression www.aging-us.com level of each DEirlncRNA, which rendered this model applicable to all forms of gene expression levels
Summary
According to the latest research, lung cancer is the leading malignant tumor in China and even in the world. [1,2,3] Lung adenocarcinoma (LUAD) is the major type of non–small cell lung cancer (NSCLC) [4]. Clinical studies have reported that the tumor immune microenvironment is involved in tumorigenesis [5] and plays vital roles in the prognosis of patients. Long noncoding RNAs (lncRNAs) are a type of noncoding RNA molecules with transcripts of >200 nucleotides [9] They can regulate the expression of downstream genes by physically interacting with DNA, RNA, or protein. Utilizing immune-related lncRNA (irlncRNAs) to predict the prognosis of patients has become a research hotspot. We used an improved modeling algorithm to construct a prognosis model based on differentially expressed immune-related lncRNAs (DEirlncRNAs) pairs without needing to accurately measure the expression levels, which avoided normalization during the conversion between data and may be indicative of the prognostic markers in LUAD patients
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