Table_3_A new acidic microenvironment related lncRNA signature predicts the prognosis of liver cancer patients.docx (149.63 kB)

Table_3_A new acidic microenvironment related lncRNA signature predicts the prognosis of liver cancer patients.docx

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posted on 2022-10-31, 05:14 authored by Peng Jiang, Wenbo Xue, Cheng Xi, Lin Zhuang, Zhiping Yuan, Zhilin Liu, Tao Sun, Xuezhong Xu, Yulin Tan, Wei Ding

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.