A novel anoikis-related gene signature predicts in lung adenocarcinoma

Abstract

Objective: To generate a prognostic model prognosis based on anoikis-related genes (ANRGs) expression for Lung adenocarcinoma (LUAD), an exploration of the prognostic value of ANRGs in LUAD was conducted.

Methods: Based on the expression matrix of genes from the TCGA database, we built the co-expressed modules by weighted gene co-expression network analysis (WGCNA). Then we identified the differentially expressed ANRGs (DE-ANGs) between LUAD and normal samples by the WGCNA results, DEGs, and the 345 ANRGs. The biofunction of the DE-ANRGs was interpreted using the GO and KEGG databases. Univariate and multivariate regression models were used to verify whether the risk model could serve as an independent prognostic factor. A nomogram was utilized to predict overall survival (OS) in LUAD.

Results: The expression of 56 DE-ANRGs was significantly different in tumor tissues. We established a 4-ANRG prognostic signature. In the TCGA cohort and the external GSE31210 validation cohort, the OS of the high-risk group was lower than that of the low-risk group significantly. Moreover, the prediction performance of the risk model was excellently verified by the ROC curve. In addition, both univariate COX and multivariate Cox analyses indicated that risk score could act as an independent prognostic factor for LUAD patients. The calibration curve and C-index demonstrated that the nomogram was satisfactory in predicting 1, 3- and 5-year survival in LUAD patients.

Conclusions: Our study developed a novel prognostic signature of 4 ANRGs with Excellent prognostic performance for LUAD patients.

Keywords

Lung adenocarcinoma / Prognostic signature / Anoikis / Risk score

References

[1] XuL, LiW, YangT, et al. Immune-related RNA-binding protein-based signature with predictive and prognostic implications in patients with lung adenocarcinoma. Front Mol Biosci. 2022;9:807622.

[2] BiKW, WeiXG, QinXX, et al. BTK has potential to Be a prognostic factor for lung adenocarcinoma and an indicator for tumor microenvironment remodeling: a study based on TCGA data mining. Front Oncol. 2020;10:424.

[3] SiegelRL, MillerKD, FuchsHE, et al. Cancer statistics, 2021. CA A Cancer J Clin. 2021;71(1):7–33.

[4] BuchheitCL, WeigelKJ, SchaferZT. Cancer cell survival during detachment from the ECM: multiple barriers to tumour progression. Nat Rev Cancer. 2014;14(9):632–641.

[5] PaoliP, Giannoni E, ChiarugiP. Anoikis molecular pathways and its role in cancer progression. Biochim Biophys Acta. 2013;1833(12):3481–3498.

[6] LiL, HeZ, ZhuC, et al. MiR-137 promotes anoikis through modulating the AKT signaling pathways in Pancreatic Cancer. J Cancer. 2020;11(21):6277–6285.

[7] WangW, ShenXB, HuangDB, et al. Peroxiredoxin 4 suppresses anoikis and augments growth and metastasis of hepatocellular carcinoma cells through the β-catenin/ID2 pathway. Cell Oncol. 2019;42(6):769–781.

[8] ChenS, GuJ, ZhangQ, et al. Development of biomarker signatures associated with anoikis to predict prognosis in endometrial carcinoma patients. J Oncol. 2021;2021:3375297.

[9] ChiH, JiangP, XuK, et al. A novel anoikis-related gene signature predicts prognosis in patients with head and neck squamous cell carcinoma and reveals immune infiltration. Front Genet. 2022;13:984273.

[10] HuH, YangM, DongW, et al. A pyroptosis-related gene panel for predicting the prognosis and immune microenvironment of cervical cancer. Front Oncol. 2022;12:873725.

[11] WangS, SuW, ZhongC, et al. An eight-CircRNA assessment model for predicting biochemical recurrence in prostate cancer. Front Cell Dev Biol. 2020;8:599494.

[12] WangG, LiuX, WangD, et al. Identification and development of subtypes with poor prognosis in pan-gynecological cancer based on gene expression in the glycolysischolesterol synthesis Axis. Front Oncol. 2021;11:636565.

[13] YangH, WangK, LiB, et al. The prognostic role of blood inflammatory biomarkers and EGFR mutation status in stage IIIA/N2 non-small cell lung cancer patients treated with trimodality therapy. Front Oncol. 2021;11:707041.

[14] ZhangS, TongYX, ZhangXH, et al. A novel and validated nomogram to predict overall survival for gastric neuroendocrine neoplasms. J Cancer. 2019;10(24):5944–5954.

[15] ChenW, LinW, WuL, et al. A novel prognostic predictor of immune microenvironment and therapeutic response in kidney renal clear cell carcinoma based on necroptosis-related gene signature. Int J Med Sci. 2022;19(2):377–392.

[16] GeP, WangW, LiL, et al. Profiles of immune cell infiltration and immune-related genes in the tumor microenvironment of colorectal cancer. Biomed Pharmacother. 2019;118:109228.

[17] LiXT, YangJJ, WuYL, et al. Toward innovative combinational immunotherapy: a systems biology perspective. Cancer Treat Rev. 2018;68:1–8.

[18] LowJL, WalshRJ, AngY, et al. The evolving immuno-oncology landscape in advanced lung cancer: first-line treatment of non-small cell lung cancer. Ther Adv Med Oncol. 2019;11:1758835919870360.

[19] WangB, JingT, JinW, et al. KIAA1522 potentiates TNFα-NFκB signaling to antagonize platinum-based chemotherapy in lung adenocarcinoma. J Exp Clin Cancer Res. 2020;39(1):170.

[20] SunZ, ZhaoY, WeiY, et al. Identification and validation of an anoikis-associated gene signature to predict clinical character, stemness, IDH mutation, and immune filtration in glioblastoma. Front Immunol. 2022;13:939523.

[21] IkedaJ, OdaT, InoueM, et al. Expression of CUB domain containing protein (CDCP1) is correlated with prognosis and survival of patients with adenocarcinoma of lung. Cancer Sci. 2009;100(3):429–433.

[22] CarboneC, PiroG, MerzV, et al. Angiopoietin-like proteins in angiogenesis, inflammation and cancer. Int J Mol Sci. 2018;19(2).

[23] ZhaoJ, LiuJ, WuN, et al. ANGPTL4 overexpression is associated with progression and poor prognosis in breast cancer. Oncol Lett. 2020;20(3):2499–2505.

[24] KangYT, LiCT, TangSC, et al. Nickel chloride regulates ANGPTL4 via the HIF-1α-mediated TET1 expression in lung cells. Toxicol Lett. 2021;352:17–25.

[25] GaoL, ZhangL. Construction and comprehensive analysis of a ceRNA network to reveal potential prognostic biomarkers for lung adenocarcinoma. BMC Cancer. 2021;21(1):849.

[26] ZhangM, ZhuK, PuH, et al. An immune-related signature predicts survival in patients with lung adenocarcinoma. Front Oncol. 2019;9:1314.

[27] HouJ, YaoC. Potential prognostic biomarkers of lung adenocarcinoma based on bioinformatic analysis. BioMed Res Int. 2021;2021:8859996.

[28] WangX, YangJ, GaoX. Identification of key genes associated with lung adenocarcinoma by bioinformatics analysis. Sci Prog. 2021;104(1):36850421997276.

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2024 2024 The Authors. Publishing services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd.