The Evaluation of Prognostic Value and Immune Characteristics of Ferroptosis-Related Genes in Lung Squamous Cell Carcinoma
Jialin Su, Shuhua Tan, HouwuGong, Yongzhong Luo, Tianli Cheng, Hua Yang, Xiaoping Wen, Zhou Jiang, Yuning Li, Lemeng Zhang
The Evaluation of Prognostic Value and Immune Characteristics of Ferroptosis-Related Genes in Lung Squamous Cell Carcinoma
Background The purpose of our study was to construct a prognostic model based on ferroptosis-related gene signature to improve the prognosis prediction of lung squamous carcinoma (LUSC).
Methods The mRNA expression profiles and clinical data of LUSC patients were downloaded. LUSC-related essential differentially expressed genes were integrated for further analysis. Prognostic gene signatures were identified through random forest regression and univariate Cox regression analyses for constructing a prognostic model. Finally, in a preliminary experiment, we used the reverse transcription-quantitative polymerase chain reaction assay to verify the relationship between the expression of three prognostic gene features and ferroptosis.
Results Fifty-six ferroptosis-related essential genes were identified by using integrated analysis. Among these, three prognostic gene signatures (HELLS, POLR2H, and POLE2) were identified, which were positively affected by LUSC prognosis but negatively affected by immune cell infiltration. Significant overexpression of immune checkpoint genes occurred in the high-risk group. In preliminary experiments, we confirmed that the occurrence of ferroptosis can reduce three prognostic gene signature expression.
Conclusions The three ferroptosis-related genes could predict the LUSC prognostic risk of antitumor immunity.
lung squamous carcinoma / ferroptosis / prognostic model / immune infiltration / antitumor immunity
[1] |
Denisov EV, Schegoleva AA, Gervas PA. et al. Premalignant lesions of squamous cell carcinoma of the lung: the molecular make-up and factors affecting their progression. Lung Cancer 2019; 135: 21-28
|
[2] |
Friedlaender A, Banna G, Malapelle U, Pisapia P, Addeo A. Next generation sequencing and genetic alterations in squamous cell lung carcinoma: where are we today?. Front Oncol 2019; 9: 166
|
[3] |
Cardona AF, Ricaurte L, Zatarain-Barrón ZL, Arrieta O. Squamous cell lung cancer: genomic evolution and personalized therapy. Salud Publica Mex 2019; 61(03) 329-338
|
[4] |
Socinski MA, Obasaju C, Gandara D. et al. Current and emergent therapy options for advanced squamous cell lung cancer. J Thorac Oncol 2018; 13(02) 165-183
|
[5] |
Chen Y, Zitello E, Guo R, Deng Y.The function of LncRNAs and their role in the prediction
|
[6] |
Ruiz-Cordero R, Devine WP. Targeted therapy and checkpoint immunotherapy in lung cancer. Surg Pathol Clin 2020; 13(01) 17-33
|
[7] |
Wang Y, Wei Z, Pan K, Li J, Chen Q. The function and mechanism of ferroptosis in cancer. Apoptosis 2020; 25(11-12): 786-798
|
[8] |
Xu T, Ding W, Ji X. et al. Molecular mechanisms of ferroptosis and its role in cancer therapy. J Cell Mol Med 2019; 23(08) 4900-4912
|
[9] |
Mou Y, Wang J, Wu J. et al. Ferroptosis, a new form of cell death: opportunities and challenges in cancer. J Hematol Oncol 2019; 12(01) 34
|
[10] |
Liang JY, Wang DS, Lin HC. et al. A novel ferroptosis-related gene signature for overall survival prediction in patients with hepatocellular carcinoma. Int J Biol Sci 2020; 16(13) 2430-2441
|
[11] |
Yu H, Han Z, Xu Z, An C, Xu L, Xin H. RNA sequencing uncovers the key long non-coding RNAs and potential molecular mechanism contributing to XAV939-mediated inhibition of non-small cell lung cancer. Oncol Lett 2019; 17(06) 4994-5004
|
[12] |
Doll S, Freitas FP, Shah R. et al. FSP1 is a glutathione-independent ferroptosis suppressor. Nature 2019; 575(7784): 693-698
|
[13] |
Li C, Wang X, Qin R, Zhong Z, Sun C. Identification of a ferroptosis gene set that mediates the prognosis of squamous cell carcinoma of the head and neck. Front Genet 2021; 12: 698040
|
[14] |
Li H, Zhang X, Yi C. et al. Ferroptosis-related gene signature predicts the prognosis in Oral squamous cell carcinoma patients. BMC Cancer 2021; 21(01) 835
|
[15] |
Han F, Li W, Chen T. et al. Ferroptosis-related genes for predicting prognosis of patients with laryngeal squamous cell carcinoma. Eur Arch Otorhinolaryngol 2021; 278(08) 2919-2925
|
[16] |
Wang GX, Tu HC, Dong Y. et al. ΔNp63 inhibits oxidative stress-induced cell death, including ferroptosis, and cooperates with the bcl-2 family to promote clonogenic survival. Cell Rep 2017; 21(10) 2926-2939
|
[17] |
Goldman M, Craft B, Hastie M. et al. The UCSC Xena platform for public and private cancer genomics data visualization and interpretation. Nat Biotechnol2019; x: x
|
[18] |
Harrow J, Frankish A, Gonzalez JM. et al. GENCODE: the reference human genome annotation for The ENCODE Project. Genome Res 2012; 22(09) 1760-1774
|
[19] |
Smyth GK.Limma: linear models for microarray data. In: Bioinformatics and computational biology solutions using R and Bioconductor. 2013
|
[20] |
Shi B, Ding J, Qi J, Gu Z. Characteristics and prognostic value of potential dependency genes in clear cell renal cell carcinoma based on a large-scale CRISPR-Cas9 and RNAi screening database DepMap. Int J Med Sci 2021; 18(09) 2063-2075
|
[21] |
Ho KH, Huang TW, Liu AJ, Shih CM, Chen KC. Cancer essential genes stratified lung adenocarcinoma patients with distinct survival outcomes and identified a subgroup from the terminal respiratory unit type with different proliferative signatures in multiple cohorts. Cancers (Basel) 2021; 13 (09) x
|
[22] |
Zhou N, Bao J. FerrDb: a manually curated resource for regulators and markers of ferroptosis and ferroptosis-disease associations. Database (Oxford) 2020; 2020: x
|
[23] |
Yu G, Wang LG, Han Y, He QY. clusterProfiler: an R package for comparing biological themes among gene clusters. OMICS 2012; 16(05) 284-287
|
[24] |
Breiman L,Cutler A. randomForest: Breiman and Cutler's random forests for classification and regression. 2008
|
[25] |
Lin H, Zelterman D. Modeling Survival Data: Extending the Cox Model. Taylor & Francis Group; 2000
|
[26] |
Li T, Fan J, Wang B. et al. TIMER: a web server for comprehensive analysis of tumor-infiltrating immune cells. Cancer Res 2017; 77(21) e108-e110
|
[27] |
Uhlen M, Zhang C, Lee S. et al. A pathology atlas of the human cancer transcriptome. Science2017; 357 (6352): eaan2507
|
[28] |
Newman AM, Liu CL, Green MR. et al. Robust enumeration of cell subsets from tissue expression profiles. Nat Methods 2015; 12(05) 453-457
|
[29] |
Mayakonda A, Lin DC, Assenov Y, Plass C, Koeffler HP. Maftools: efficient and comprehensive analysis of somatic variants in cancer. Genome Res 2018; 28(11) 1747-1756
|
[30] |
Li Y, Gu J, Xu F, Zhu Q, Ge D, Lu C. Transcriptomic and functional network features of lung squamous cell carcinoma through integrative analysis of GEO and TCGA data. Sci Rep 2018; 8(01) 15834
|
[31] |
Latunde-Dada GO. Ferroptosis: role of lipid peroxidation, iron and ferritinophagy. Biochim Biophys Acta, Gen Subj 2017; 1861(08) 1893-1900
|
[32] |
Han K, Wang J, Qian K, Zhao T, Liu X, Zhang Y. Construction of a prognostic model for non-small-cell lung cancer based on ferroptosis-related genes. Biosci Rep2021; 41 (05) BSR20210527
|
[33] |
Li S, Liu Y, Li J, Zhao X, Yu D. Mechanisms of ferroptosis and application to head and neck squamous cell carcinoma treatments. DNA Cell Biol 2021; 40(06) 720-732
|
[34] |
Diao X, Guo C, Liu L, Wang G, Li S. Identification and validation of an individualized prognostic signature of lung squamous cell carcinoma based on ferroptosis-related genes. Thorac Cancer 2021; 12(23) 3236-3247
|
[35] |
Shi ZZ, Tao H, Fan ZW, Song SJ, Bai J. Prognostic and immunological role of key genes of ferroptosis in pan-cancer. Front Cell Dev Biol 2021; 9: 748925
|
[36] |
Cui J, Wang J, Shen Y, Lin D. Suppression of HELLS by miR-451a represses mTOR pathway to hinder aggressiveness of SCLC. Genes Genomics 2021; 43(02) 105-114
|
[37] |
Yano M, Ouchida M, Shigematsu H. et al. Tumor-specific exon creation of the HELLS/SMARCA6 gene in non-small cell lung cancer. Int J Cancer 2004; 112(01) 8-13
|
[38] |
Zhu W, Li LL, Songyang Y, Shi Z, Li D. Identification and validation of HELLS (helicase, lymphoid-specific) and ICAM1 (intercellular adhesion molecule 1) as potential diagnostic biomarkers of lung cancer. PeerJ 2020; 8: e8731
|
[39] |
Li J, Wang J, Yu J. et al. Knockdown of POLE2 expression suppresses lung adenocarcinoma cell malignant phenotypes in vitro. Oncol Rep 2018; 40(05) 2477-2486
|
[40] |
Dong A, Wang ZW, Ni N, Li L, Kong XY. Similarity and difference of pathogenesis among lung cancer subtypes suggested by expression profile data. Pathol Res Pract 2021; 220: 153365
|
[41] |
Zhao J, Bao W, Cai W. Immune infiltration landscape in lung squamous cell carcinoma implications. Biomed Res Int 2020; 2020: 5981870
|
[42] |
Xu F, Lin H, He P. et al. A TP53-associated gene signature for prediction of prognosis and therapeutic responses in lung squamous cell carcinoma. OncoImmunology 2020; 9(01) 1731943
|
[43] |
Wan L, Chen X, Deng J. et al. Plasma exosome-derived B-cell translation gene 1: a predictive marker for the prognosis in patients with non-small cell lung cancer. J Cancer 2021; 12(05) 1538-1547
|
[44] |
Song Z, Chen X, Shi Y. et al. Evaluating the potential of T cell receptor repertoires in predicting the prognosis of resectable non-small cell lung cancers. Mol Ther Methods Clin Dev 2020; 18: 73-83
|
[45] |
Cao L, Che X, Qiu X. et al. M2 macrophage infiltration into tumor islets leads to poor prognosis in non-small-cell lung cancer. Cancer Manag Res 2019; 11: 6125-6138
|
[46] |
Arrieta O, Aviles-Salas A, Orozco-Morales M. et al. Association between CD47 expression, clinical characteristics and prognosis in patients with advanced non-small cell lung cancer. Cancer Med 2020; 9(07) 2390-2402
|
[47] |
Yang QF, Wu D, Wang J. et al. Development and validation of an individualized immune prognostic model in stage I-III lung squamous cell carcinoma. Sci Rep 2021; 11(01) 12727
|
[48] |
Liu T, Luo H, Zhang J, Hu X, Zhang J. Molecular identification of an immunity- and ferroptosis-related gene signature in non-small cell lung cancer. BMC Cancer 2021; 21(01) 783
|
[49] |
Koutsoukos K, Mountzios G. Novel therapies for advanced squamous cell carcinoma of the lung. Future Oncol 2016; 12(05) 659-667
|
[50] |
Cheng X, Yin H, Fu J. et al. Aggregate analysis based on TCGA: TTN missense mutation correlates with favorable prognosis in lung squamous cell carcinoma. J Cancer Res Clin Oncol 2019; 145(04) 1027-1035
|
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