The acidic microenvironment (AME), like hypoxia, inflammation, or immunoreaction, is a hallmark of the tumor microenvironment (TME). This work aimed to develop a prediction signature dependent on AME-associated lncRNAs in order to predict the prognosis of LC individuals.
We downloaded RNA-seq information and the corresponding clinical and predictive data from The Cancer Genome Atlas (TCGA) dataset and conducted univariate and multivariate Cox regression analyses to identify AME-associated lncRNAs for the construction of a prediction signature The Kaplan-Meier technique was utilized to determine the overall survival (OS) rate of the high (H)-risk and low (L)-risk groups. Using gene set enrichment analysis (GSEA) the functional variations between the H- and L-risk groups were investigated. The association between the prediction signature and immunological state was investigated using single-sample GSEA (ssGSEA). Additionally, the association between the predicted signature and the therapeutic response of LC individuals was evaluated. Lastly, quantitative reverse transcription polymerase chain reaction (qRT-PCR) was performed to verify the risk model.
We generated a signature comprised of seven AME-associated lncRNAs (LINC01116, AC002511.2, LINC00426, ARHGAP31-AS1, LINC01060, TMCC1-AS1, AC012065.1). The H-risk group had a worse prognosis than the L- risk group. The AME-associated lncRNA signature might determine the prognosis of individuals with LC independently. The AME-related lncRNA signature shows a greater predictive effectiveness than clinic-pathological factors, with an area under the receiver operating characteristic (ROC) curve of 0.806%. When participants were categorized based on several clinico-pathological characteristics, the OS of high-risk individuals was shorter compared to low-risk patients. GSEA demonstrated that the metabolism of different acids and the PPAR signaling pathway are closely associated with low-risk individuals. The prognostic signature was substantially associated with the immunological status of LC individuals, as determined by ssGSEA. High risk individuals were more sensitive to some immunotherapies (including anti-TNFSF4 anti-SIRPA, anti-CD276 and anti-TNFSF15) and some conventional chemotherapy drugs (including lapatinib and paclitaxel). Finally, the expression levels of the seven lncRNAs comprising the signature were tested by qRT-PCR.
A basis for the mechanism of AME-associated lncRNAs in LC is provided by the prediction signature, which also offers clinical therapeutic recommendations for LC individuals.