Identified Gefitinib Metabolism-Related lncRNAs can be Applied to Predict Prognosis, Tumor Microenvironment, and Drug Sensitivity in Non-Small Cell Lung Cancer

Abstract

Gefitinib has shown promising efficacy in the treatment of patients with locally advanced or metastatic EGFR-mutated non-small cell lung cancer (NSCLC). Molecular biomarkers for gefitinib metabolism-related lncRNAs have not yet been elucidated. Here, we downloaded relevant genes and matched them to relevant lncRNAs. We then used univariate, LASSO, and multivariate regression to screen for significant genes to construct prognostic models. We investigated TME and drug sensitivity by risk score data. All lncRNAs with differential expression were selected for GO/KEGG analysis. Imvigor210 cohort was used to validate the value of the prognostic model. Finally, we performed a stemness indices difference analysis. lncRNA-constructed prognostic models were significant in the high-risk and low-risk subgroups. Immune pathways were identified in both groups at low risk. The higher the risk score the greater the value of exclusion, MDSC, and CAF. PRRophetic algorithm screened a total of 58 compounds. In conclusion, the prognostic model we constructed can accurately predict OS in NSCLC patients. Two groups of low-risk immune pathways are beneficial to patients. Gefitinib metabolism was again validated to be related to cytochrome P450 and lipid metabolism. Finally, drugs that might be used to treat NSCLC patients were screened.

Prognostic model and immunotherapy prediction based on molecular chaperone-related lncRNAs in lung adenocarcinoma

“…Yue, N. et al ( Yue et al, 2020 ) found that the high expression of lncRNA pSMG3-AS1 played a carcinogenic role in the development of LUAD. At the same time, recent studies have also shown that it is possible to predict the prognosis of cancer patients by exploring the potential relationship between coding genes and lncRNAs ( Wang et al, 2019b ; Ye et al, 2022 ). In this study, we were inspired by the mechanism by which both molecular chaperones and lncRNAs can be involved in the occurrence and development of LUAD.…”

Risk score = LncRNAs associated with doxorubicin metabolism can be used as molecular markers for immune microenvironment and immunotherapy in non-small cell lung cancer

“…The formula for the Cox proportional hazards model is as follows [ [14] , [15] , [16] ]: h (t, X) = h (t) exp (β X + β X + … + β X) …”

“…13 immune functions and corresponding gene sets studied by Ye et al were downloaded [ 20 ]. “limma”, “GSVA”, “GSEABase”, “Pheatmap” and “reshape2” packages of R software were used to analyze the co-expression between immune function gene sets and HGR/LGR in the training group, test group, and all patients to obtain the correlation of immune function in HRG and LRG.…”

LncRNAs has been identified as regulators of Myeloid-derived suppressor cells in lung cancer

“…Their findings revealed that lncRNA-ATB promoted lung cancer progression by inhibiting miR-200a expression and reversed the promotion of b-linked protein expression to promote apoptosis in NSCLC cells (116).The newly discovered lncRNA SET binding factor 2 antisense RNA 1 (LncRNA SBF2-AS1) is involved in the progression of many cancers like lung, breast, hepatocellular carcinoma, thyroid, gastric, colorectal cancers and others (118). Interestingly, Weilong Ye et al identified 13 lncRNAs related to Gefitinib metabolism and applied them to build the prognostic model of NSCLC patients (119). This proves that lncRNA studies are not limited to particular tumour tissue, and more and more studies have proposed new ideas for the diagnosis, treatment and prognosis of lncRNAs.…”

“…Interestingly, Weilong Ye et al. identified 13 lncRNAs related to Gefitinib metabolism and applied them to build the prognostic model of NSCLC patients ( 119 ). This proves that lncRNA studies are not limited to particular tumour tissue, and more and more studies have proposed new ideas for the diagnosis, treatment and prognosis of lncRNAs.…”