The coefficient of the risk factors in multivariate Cox regression model
Risk factor
Coefficient value
HR value
95% CI (Low)
95% CI (High)
p-value
ADAM19
0.035
1.035
1.012
1.059
0.003
ICAM3
–0.169
0.845
0.719
0.993
0.041
WIPF1
–0.029
0.972
0.941
1.004
0.083
LAP3
0.012
1.012
1.005
1.019
0.001
The first column indicates the risk gene, the second column indicates the coefficient value corresponding to its risk gene, the third column indicates the HR value, and the fourth and fifth columns show the HR value’s low and high 95% confidence interval, the last column shows the p-value
All authors disclosed no relevant relationships. The authors reported no potential conflict of interest.
Ethical approval
Not applicable.
Consent to participate
Not applicable.
Consent to publication
Not applicable.
Availability of data and materials
The datasets collected in this research are from accessible databases. The article contains the accession number and the names of the databases. All code for data cleaning and analysis associated with the current submission is available at https://github.com/liuzhe93/M1_NSCLC. The raw data supporting the conclusions of this manuscript will be made available by the authors, without undue reservation, to any qualified researcher.
Funding
This research was substantially sponsored by the research projects [No. 32170654; No. 32000464] supported by the National Natural Science Foundation of China and was substantially supported by the Shenzhen Research Institute, City University of Hong Kong. This project is substantially funded by the Strategic Interdisciplinary Research Grant of City University of Hong Kong [No. 2021SIRG036]. The work described in this paper was substantially supported by the grant from the Health and Medical Research Fund, the Food and Health Bureau, The Government of the Hong Kong Special Administrative Region [07181426]. The work described in this paper was partially supported by the grants from City University of Hong Kong [CityU 11203520, CityU 11203221]. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Wang M, Herbst RS, Boshoff C. Toward personalized treatment approaches for non-small-cell lung cancer.Nat Med. 2021;27:1345–56. [DOI] [PubMed]
Zhang B, Birer SR, Dvorkin M, Shruti J, Byers L. New Therapies and Biomarkers: Are We Ready for Personalized Treatment in Small Cell Lung Cancer?Am Soc Clin Oncol Educ Book. 2021;41:1–10. [DOI] [PubMed]
Jeon DS, Kim HC, Kim SH, Kim T, Kim HK, Moon MH, et al. Five-Year Overall Survival and Prognostic Factors in Patients with Lung Cancer: Results from the Korean Association of Lung Cancer Registry (KALC-R) 2015.Cancer Res Treat. 2023;55:103–11. [DOI] [PubMed] [PMC]
Tian Y, Ma J, Jing X, Zhai X, Li Y, Guo Z, et al. Radiation therapy for extensive-stage small-cell lung cancer in the era of immunotherapy.Cancer Lett. 2022;541:215719. [DOI] [PubMed]
Herbst RS, Morgensztern D, Boshoff C. The biology and management of non-small cell lung cancer.Nature. 2018;553:446–54. [DOI] [PubMed]
Sun S, Guo W, Wang Z, Wang X, Zhang G, Zhang H, et al. Development and validation of an immune-related prognostic signature in lung adenocarcinoma.Cancer Med. 2020;9:5960–75. [DOI] [PubMed] [PMC]
Casanova-Acebes M, Dalla E, Leader AM, LeBerichel J, Nikolic J, Morales BM, et al. Tissue-resident macrophages provide a pro-tumorigenic niche to early NSCLC cells.Nature. 2021;595:578–84. [DOI] [PubMed] [PMC]
Wang H, Yung MMH, Ngan HYS, Chan KKL, Chan DW. The Impact of the Tumor Microenvironment on Macrophage Polarization in Cancer Metastatic Progression.Int J Mol Sci. 2021;22:6560. [DOI] [PubMed] [PMC]
Ho DW, Tsui Y, Chan L, Sze KM, Zhang X, Cheu JW, et al. Single-cell RNA sequencing shows the immunosuppressive landscape and tumor heterogeneity of HBV-associated hepatocellular carcinoma.Nat Commun. 2021;12:3684. [DOI] [PubMed] [PMC]
Leader AM, Grout JA, Maier BB, Nabet BY, Park MD, Tabachnikova A, et al. Single-cell analysis of human non-small cell lung cancer lesions refines tumor classification and patient stratification.Cancer Cell. 2021;39:1594–609.e12. [DOI] [PubMed] [PMC]
Boutilier AJ, Elsawa SF. Macrophage Polarization States in the Tumor Microenvironment.Int J Mol Sci. 2021;22:6995. [DOI] [PubMed] [PMC]
Zhao S, Mi Y, Guan B, Zheng B, Wei P, Gu Y, et al. Tumor-derived exosomal miR-934 induces macrophage M2 polarization to promote liver metastasis of colorectal cancer.J Hematol Oncol. 2020;13:156. [DOI] [PubMed] [PMC]
Najafi M, Goradel NH, Farhood B, Salehi E, Nashtaei MS, Khanlarkhani N, et al. Macrophage polarity in cancer: A review.J Cell Biochem. 2019;120:2756–65. [DOI] [PubMed]
Langfelder P, Horvath S. WGCNA: an R package for weighted correlation network analysis.BMC Bioinformatics. 2008;9:559. [DOI] [PubMed] [PMC]
Niemira M, Collin F, Szalkowska A, Bielska A, Chwialkowska K, Reszec J, et al. Molecular Signature of Subtypes of Non-Small-Cell Lung Cancer by Large-Scale Transcriptional Profiling: Identification of Key Modules and Genes by Weighted Gene Co-Expression Network Analysis (WGCNA).Cancers (Basel). 2019;12:37. [DOI] [PubMed] [PMC]
Rezaei Z, Ranjbaran J, Safarpour H, Nomiri S, Salmani F, Chamani E, et al. Identification of early diagnostic biomarkers via WGCNA in gastric cancer.Biomed Pharmacother. 2022;145:112477. [DOI] [PubMed]
Yin X, Wang P, Yang T, Li G, Teng X, Huang W, et al. Identification of key modules and genes associated with breast cancer prognosis using WGCNA and ceRNA network analysis.Aging (Albany NY). 2020;13:2519–38. [DOI] [PubMed] [PMC]
Bai K, He S, Shu L, Wang W, Lin S, Zhang Q, et al. Identification of cancer stem cell characteristics in liver hepatocellular carcinoma by WGCNA analysis of transcriptome stemness index.Cancer Med. 2020;9:4290–8. [DOI] [PubMed] [PMC]
Ding M, Li F, Wang B, Chi G, Liu H. A comprehensive analysis of WGCNA and serum metabolomics manifests the lung cancer-associated disordered glucose metabolism.J Cell Biochem. 2019;120:10855–63. [DOI] [PubMed]
Tian Z, He W, Tang J, Liao X, Yang Q, Wu Y, et al. Identification of Important Modules and Biomarkers in Breast Cancer Based on WGCNA.Onco Targets Ther. 2020;13:6805–17. [DOI] [PubMed] [PMC]
Hsu C, Juan H, Huang H. Functional Analysis and Characterization of Differential Coexpression Networks.Sci Rep. 2015;5:13295. [DOI] [PubMed] [PMC]
Heyer LJ, Kruglyak S, Yooseph S. Exploring expression data: identification and analysis of coexpressed genes.Genome Res. 1999;9:1106–15. [DOI] [PubMed] [PMC]
Zhang Y, Wang D, Peng M, Tang L, Ouyang J, Xiong F, et al. Single-cell RNA sequencing in cancer research.J Exp Clin Cancer Res. 2021;40:81. [DOI] [PubMed] [PMC]
Zhang L, Li Z, Skrzypczynska KM, Fang Q, Zhang W, O’Brien SA, et al. Single-Cell Analyses Inform Mechanisms of Myeloid-Targeted Therapies in Colon Cancer.Cell. 2020;181:442–59.e29. [DOI] [PubMed]
Peng J, Sun B, Chen C, Zhou J, Chen Y, Chen H, et al. Single-cell RNA-seq highlights intra-tumoral heterogeneity and malignant progression in pancreatic ductal adenocarcinoma.Cell Res. 2019;29:725–38. [DOI] [PubMed] [PMC]
Maynard A, McCoach CE, Rotow JK, Harris L, Haderk F, Kerr DL, et al. Therapy-Induced Evolution of Human Lung Cancer Revealed by Single-Cell RNA Sequencing.Cell. 2020;182:1232–51.e22. [DOI] [PubMed] [PMC]
Puram SV, Tirosh I, Parikh AS, Patel AP, Yizhak K, Gillespie S, et al. Single-Cell Transcriptomic Analysis of Primary and Metastatic Tumor Ecosystems in Head and Neck Cancer.Cell. 2017;171:1611–24.e24. [DOI] [PubMed] [PMC]
Zheng H, Liu H, Ge Y, Wang X. Integrated single-cell and bulk RNA sequencing analysis identifies a cancer associated fibroblast-related signature for predicting prognosis and therapeutic responses in colorectal cancer.Cancer Cell Int. 2021;21:552. [DOI] [PubMed] [PMC]
Wang Z, Zhang J, Dai F, Li B, Cheng Y. Integrated analysis of single-cell RNA-seq and bulk RNA-seq unveils heterogeneity and establishes a novel signature for prognosis and tumor immune microenvironment in ovarian cancer.J Ovarian Res. 2023;16:12. [DOI] [PubMed] [PMC]
Bao X, Shi R, Zhao T, Wang Y, Anastasov N, Rosemann M, et al. Integrated analysis of single-cell RNA-seq and bulk RNA-seq unravels tumour heterogeneity plus M2-like tumour-associated macrophage infiltration and aggressiveness in TNBC.Cancer Immunol Immunother. 2021;70:189–202. [DOI] [PubMed] [PMC]
Wang R, Xiao Y, Pan M, Chen Z, Yang P. Integrative Analysis of Bulk RNA-Seq and Single-Cell RNA-Seq Unveils the Characteristics of the Immune Microenvironment and Prognosis Signature in Prostate Cancer.J Oncol. 2022;2022:6768139. [DOI] [PubMed] [PMC]
Colaprico A, Silva TC, Olsen C, Garofano L, Cava C, Garolini D, et al. TCGAbiolinks: an R/Bioconductor package for integrative analysis of TCGA data.Nucleic Acids Res. 2016;44:e71. [DOI] [PubMed] [PMC]
Tomida S, Takeuchi T, Shimada Y, Arima C, Matsuo K, Mitsudomi T, et al. Relapse-related molecular signature in lung adenocarcinomas identifies patients with dismal prognosis.J Clin Oncol. 2009;27:2793–9. [DOI] [PubMed]
Okayama H, Kohno T, Ishii Y, Shimada Y, Shiraishi K, Iwakawa R, et al. Identification of genes upregulated in ALK-positive and EGFR/KRAS/ALK-negative lung adenocarcinomas.Cancer Res. 2012;72:100–11. [DOI] [PubMed]
Yamauchi M, Yamaguchi R, Nakata A, Kohno T, Nagasaki M, Shimamura T, et al. Epidermal growth factor receptor tyrosine kinase defines critical prognostic genes of stage I lung adenocarcinoma.PLoS One. 2012;7:e43923. [DOI] [PubMed] [PMC]
Han Y, Wang Y, Dong X, Sun D, Liu Z, Yue J, et al. TISCH2: expanded datasets and new tools for single-cell transcriptome analyses of the tumor microenvironment.Nucleic Acids Res. 2023;51:D1425–31. [DOI] [PubMed] [PMC]
Song Q, Hawkins GA, Wudel L, Chou P, Forbes E, Pullikuth AK, et al. Dissecting intratumoral myeloid cell plasticity by single cell RNA-seq.Cancer Med. 2019;8:3072–85. [DOI] [PubMed] [PMC]
Wang F, Zhang Y, Hao Y, Li X, Qi Y, Xin M, et al. Characterizing the Metabolic and Immune Landscape of Non-small Cell Lung Cancer Reveals Prognostic Biomarkers Through Omics Data Integration.Front Cell Dev Biol. 2021;9:702112. [DOI] [PubMed] [PMC]
Newman AM, Liu CL, Green MR, Gentles AJ, Feng W, Xu Y, et al. Robust enumeration of cell subsets from tissue expression profiles.Nat Methods. 2015;12:453–7. [DOI] [PubMed] [PMC]
Hao Y, Hao S, Andersen-Nissen E, Mauck WM 3rd, Zheng S, Butler A, et al. Integrated analysis of multimodal single-cell data.Cell. 2021;184:3573–87.e29. [DOI] [PubMed] [PMC]
Stuart T, Butler A, Hoffman P, Hafemeister C, Papalexi E, Mauck WM 3rd, et al. Comprehensive Integration of Single-Cell Data.Cell. 2019;177:1888–902.e21. [DOI] [PubMed] [PMC]
Butler A, Hoffman P, Smibert P, Papalexi E, Satija R. Integrating single-cell transcriptomic data across different conditions, technologies, and species.Nat Biotechnol. 2018;36:411–20. [DOI] [PubMed] [PMC]
Satija R, Farrell JA, Gennert D, Schier AF, Regev A. Spatial reconstruction of single-cell gene expression data.Nat Biotechnol. 2015;33:495–502. [DOI] [PubMed] [PMC]
McGinnis CS, Murrow LM, Gartner ZJ. DoubletFinder: Doublet Detection in Single-Cell RNA Sequencing Data Using Artificial Nearest Neighbors.Cell Syst. 2019;8:329–37.e4. [DOI] [PubMed] [PMC]
Aran D, Looney AP, Liu L, Wu E, Fong V, Hsu A, et al. Reference-based analysis of lung single-cell sequencing reveals a transitional profibrotic macrophage.Nat Immunol. 2019;20:163–72. [DOI] [PubMed] [PMC]
Aibar S, González-Blas CB, Moerman T, Huynh-Thu VA, Imrichova H, Hulselmans G, et al. SCENIC: single-cell regulatory network inference and clustering.Nat Methods. 2017;14:1083–6. [DOI] [PubMed] [PMC]
Tran AN, Dussaq AM, Kennell T Jr, Willey CD, Hjelmeland AB. HPAanalyze: an R package that facilitates the retrieval and analysis of the Human Protein Atlas data.BMC Bioinformatics. 2019;20:463. [DOI] [PubMed] [PMC]
Uhlén M, Fagerberg L, Hallström BM, Lindskog C, Oksvold P, Mardinoglu A, et al. Proteomics. Tissue-based map of the human proteome.Science. 2015;347:1260419. [DOI] [PubMed]
Thul PJ, Åkesson L, Wiking M, Mahdessian D, Geladaki A, Blal HA, et al. A subcellular map of the human proteome.Science. 2017;356:eaal3321. [DOI] [PubMed]
Sjöstedt E, Zhong W, Fagerberg L, Karlsson M, Mitsios N, Adori C, et al. An atlas of the protein-coding genes in the human, pig, and mouse brain.Science. 2020;367:eaay5947. [DOI] [PubMed]
Karlsson M, Zhang C, Méar L, Zhong W, Digre A, Katona B, et al. A single-cell type transcriptomics map of human tissues.Sci Adv. 2021;7:eabh2169. [DOI] [PubMed] [PMC]
Uhlen M, Zhang C, Lee S, Sjöstedt E, Fagerberg L, Bidkhori G, et al. A pathology atlas of the human cancer transcriptome.Science. 2017;357:eaan2507. [DOI] [PubMed]
Uhlen M, Karlsson MJ, Zhong W, Tebani A, Pou C, Mikes J, et al. A genome-wide transcriptomic analysis of protein-coding genes in human blood cells.Science. 2019;366:eaax9198. [DOI] [PubMed]
Uhlén M, Karlsson MJ, Hober A, Svensson A, Scheffel J, Kotol D, et al. The human secretome.Sci Signal. 2019;12:eaaz0274. [DOI] [PubMed]
Zhou Y, Zhou B, Pache L, Chang M, Khodabakhshi AH, Tanaseichuk O, et al. Metascape provides a biologist-oriented resource for the analysis of systems-level datasets.Nat Commun. 2019;10:1523. [DOI] [PubMed] [PMC]
Ritchie ME, Phipson B, Wu D, Hu Y, Law CW, Shi W, et al. limma powers differential expression analyses for RNA-sequencing and microarray studies.Nucleic Acids Res. 2015;43:e47. [DOI] [PubMed] [PMC]
Subramanian A, Tamayo P, Mootha VK, Mukherjee S, Ebert BL, Gillette MA, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles.Proc Natl Acad Sci U S A. 2005;102:15545–50. [DOI] [PubMed] [PMC]
Liberzon A, Birger C, Thorvaldsdóttir H, Ghandi M, Mesirov JP, Tamayo P. The Molecular Signatures Database (MSigDB) hallmark gene set collection.Cell Syst. 2015;1:417–25. [DOI] [PubMed] [PMC]
Schabath MB, Cote ML. Cancer Progress and Priorities: Lung Cancer.Cancer Epidemiol Biomarkers Prev. 2019;28:1563–79. [DOI] [PubMed] [PMC]
Sharma R. Mapping of global, regional and national incidence, mortality and mortality-to-incidence ratio of lung cancer in 2020 and 2050.Int J Clin Oncol. 2022;27:665–75. [DOI] [PubMed] [PMC]
Gelatti ACZ, Drilon A, Santini FC. Optimizing the sequencing of tyrosine kinase inhibitors (TKIs) in epidermal growth factor receptor (EGFR) mutation-positive non-small cell lung cancer (NSCLC).Lung Cancer. 2019;137:113–22. [DOI] [PubMed] [PMC]
Ruiz-Cordero R, Devine WP. Targeted Therapy and Checkpoint Immunotherapy in Lung Cancer.Surg Pathol Clin. 2020;13:17–33. [DOI] [PubMed]
Rotow J, Bivona TG. Understanding and targeting resistance mechanisms in NSCLC.Nat Rev Cancer. 2017;17:637–58. [DOI] [PubMed]
Sankar K, Gadgeel SM, Qin A. Molecular therapeutic targets in non-small cell lung cancer.Expert Rev Anticancer Ther. 2020;20:647–61. [DOI] [PubMed]
Planchard D, Besse B, Groen HJM, Hashemi SMS, Mazieres J, Kim TM, et al. Phase 2 Study of Dabrafenib Plus Trametinib in Patients With BRAF V600E-Mutant Metastatic NSCLC: Updated 5-Year Survival Rates and Genomic Analysis.J Thorac Oncol. 2022;17:103–15. [DOI] [PubMed]
Reck M, Rodríguez-Abreu D, Robinson AG, Hui R, Csőszi T, Fülöp A, et al. Five-Year Outcomes With Pembrolizumab Versus Chemotherapy for Metastatic Non-Small-Cell Lung Cancer With PD-L1 Tumor Proportion Score ≥ 50.J Clin Oncol. 2021;39:2339–49. [DOI] [PubMed] [PMC]
Shapouri-Moghaddam A, Mohammadian S, Vazini H, Taghadosi M, Esmaeili S, Mardani F, et al. Macrophage plasticity, polarization, and function in health and disease.J Cell Physiol. 2018;233:6425–40. [DOI] [PubMed]
Wang Y, Wang X, Yu J, Ma F, Li Z, Zhou Y, et al. Targeting monoamine oxidase A-regulated tumor-associated macrophage polarization for cancer immunotherapy.Nat Commun. 2021;12:3530. [DOI] [PubMed] [PMC]
An Y, Yang Q. Tumor-associated macrophage-targeted therapeutics in ovarian cancer.Int J Cancer. 2021;149:21–30. [DOI] [PubMed]
Dai E, Han L, Liu J, Xie Y, Kroemer G, Klionsky DJ, et al. Autophagy-dependent ferroptosis drives tumor-associated macrophage polarization via release and uptake of oncogenic KRAS protein.Autophagy. 2020;16:2069–83. [DOI] [PubMed] [PMC]
Primakoff P, Myles DG. The ADAM gene family: surface proteins with adhesion and protease activity.Trends Genet. 2000;16:83–7. [DOI] [PubMed]
Blobel CP. ADAMs: key components in EGFR signalling and development.Nat Rev Mol Cell Biol. 2005;6:32–43. [DOI] [PubMed]
Wang J, Gong M, Xiong Z, Zhao Y, Xing D. ADAM19 and TUBB1 Correlate with Tumor Infiltrating Immune Cells and Predicts Prognosis in Osteosarcoma.Comb Chem High Throughput Screen. 2023;26:135–48. [DOI] [PubMed]
Melenhorst WB, van den Heuvel MC, Timmer A, Huitema S, Bulthuis M, Timens W, et al. ADAM19 expression in human nephrogenesis and renal disease: associations with clinical and structural deterioration.Kidney Int. 2006;70:1269–78. [DOI] [PubMed]
Dehmel T, Janke A, Hartung H, Goebel H, Wiendl H, Kieseier BC. The cell-specific expression of metalloproteinase-disintegrins (ADAMs) in inflammatory myopathies.Neurobiol Dis. 2007;25:665–74. [DOI] [PubMed]
Wang J, Nie W, Xie X, Bai M, Ma Y, Jin L, et al. MicroRNA-874-3p/ADAM (A Disintegrin and Metalloprotease) 19 Mediates Macrophage Activation and Renal Fibrosis After Acute Kidney Injury.Hypertension. 2021;77:1613–26. [DOI] [PubMed]
Dijkstra A, Postma DS, Noordhoek JA, Lodewijk ME, Kauffman HF, ten Hacken NH, et al. Expression of ADAMs (“a disintegrin and metalloprotease”) in the human lung.Virchows Arch. 2009;454:441–9. [DOI] [PubMed]
Shan N, Shen L, Wang J, He D, Duan C. MiR-153 inhibits migration and invasion of human non-small-cell lung cancer by targeting ADAM19.Biochem Biophys Res Commun. 2015;456:385–91. [DOI] [PubMed]
Wang Y, Lian Y, Ge C. MiR-145 changes sensitivity of non-small cell lung cancer to gefitinib through targeting ADAM19.Eur Rev Med Pharmacol Sci. 2019;23:5831–39. [DOI] [PubMed]
Kim YG, Kim MJ, Lim J, Lee M, Kim JS, Yoo YD. ICAM-3-induced cancer cell proliferation through the PI3K/Akt pathway.Cancer Lett. 2006;239:103–10. [DOI] [PubMed]
Chung YM, Kim B, Park C, Huh SJ, Kim J, Park JK, et al. Increased expression of ICAM-3 is associated with radiation resistance in cervical cancer.Int J Cancer. 2005;117:194–201. [DOI] [PubMed]
Cassol E, Cassetta L, Rizzi C, Gabuzda D, Alfano M, Poli G. Dendritic cell-specific intercellular adhesion molecule-3 grabbing nonintegrin mediates HIV-1 infection of and transmission by M2a-polarized macrophages in vitro.AIDS. 2013;27:707–16. [DOI] [PubMed] [PMC]
Saha B, Kodys K, Szabo G. Hepatitis C Virus-Induced Monocyte Differentiation Into Polarized M2 Macrophages Promotes Stellate Cell Activation via TGF-β.Cell Mol Gastroenterol Hepatol. 2016;2:302–16.e8. [DOI] [PubMed] [PMC]
Ahn K, Choi JY, Kim J, Hwang S, Kim W, Park JK, et al. ICAM-3 endows anticancer drug resistance against microtubule-damaging agents via activation of the ICAM-3-AKT/ERK-CREB-2 pathway and blockage of apoptosis.Biochem Biophys Res Commun. 2013;441:507–13. [DOI] [PubMed]
Park JK, Park SH, So K, Bae IH, Yoo YD, Um H. ICAM-3 enhances the migratory and invasive potential of human non-small cell lung cancer cells by inducing MMP-2 and MMP-9 via Akt and CREB.Int J Oncol. 2010;36:181–92. [PubMed]
Fang C, Zhang J, Yang H, Peng L, Wang K, Wang Y, et al. Leucine aminopeptidase 3 promotes migration and invasion of breast cancer cells through upregulation of fascin and matrix metalloproteinases-2/9 expression.J Cell Biochem. 2019;120:3611–20. [DOI] [PubMed]
Tian S, Chen S, Shao B, Cai H, Zhou Y, Zhou Y, et al. Expression of leucine aminopeptidase 3 (LAP3) correlates with prognosis and malignant development of human hepatocellular carcinoma (HCC).Int J Clin Exp Pathol. 2014;7:3752–62. [PubMed] [PMC]
Wang X, Shi L, Deng Y, Qu M, Mao S, Xu L, et al. Inhibition of leucine aminopeptidase 3 suppresses invasion of ovarian cancer cells through down-regulation of fascin and MMP-2/9.Eur J Pharmacol. 2015;768:116–22. [DOI] [PubMed]
Zhang T, Shen X, Liu R, Zhu G, Bishop J, Xing M. Epigenetically upregulated WIPF1 plays a major role in BRAF V600E-promoted papillary thyroid cancer aggressiveness.Oncotarget. 2017;8:900–14. [DOI] [PubMed] [PMC]
Pan Y, Lu F, Xiong P, Pan M, Zhang Z, Lin X, et al. WIPF1 antagonizes the tumor suppressive effect of miR-141/200c and is associated with poor survival in patients with PDAC.J Exp Clin Cancer Res. 2018;37:167. [DOI] [PubMed] [PMC]
Shlien A, Malkin D. Copy number variations and cancer.Genome Med. 2009;1:62. [DOI] [PubMed] [PMC]
Shao X, Lv N, Liao J, Long J, Xue R, Ai N, et al. Copy number variation is highly correlated with differential gene expression: a pan-cancer study.BMC Med Genet. 2019;20:175. [DOI] [PubMed] [PMC]
Stewart DJ. Wnt signaling pathway in non-small cell lung cancer.J Natl Cancer Inst. 2014;106:djt356. [DOI] [PubMed]
Xu R, Cao X, Zhang B, Wang J, Wang L, Sun W. BLACAT1 is negatively associated with prognosis in patients with NSCLC and inhibits cell progression, metastasis and epithelial-mesenchymal transition through down-regulating Wnt/β-catenin signaling pathway.Eur Rev Med Pharmacol Sci. 2019;23:6217–25. [DOI] [PubMed]
He Y, Jiang X, Duan L, Xiong Q, Yuan Y, Liu P, et al. LncRNA PKMYT1AR promotes cancer stem cell maintenance in non-small cell lung cancer via activating Wnt signaling pathway.Mol Cancer. 2021;20:156. [DOI] [PubMed] [PMC]
Thompson JC, Davis C, Deshpande C, Hwang W, Jeffries S, Huang A, et al. Gene signature of antigen processing and presentation machinery predicts response to checkpoint blockade in non-small cell lung cancer (NSCLC) and melanoma.J Immunother Cancer. 2020;8:e000974. [DOI] [PubMed] [PMC]
Valavanidis A, Vlachogianni T, Fiotakis K, Loridas S. Pulmonary oxidative stress, inflammation and cancer: respirable particulate matter, fibrous dusts and ozone as major causes of lung carcinogenesis through reactive oxygen species mechanisms.Int J Environ Res Public Health. 2013;10:3886–907. [DOI] [PubMed] [PMC]
Zabłocka-Słowińska K, Płaczkowska S, Skórska K, Prescha A, Pawełczyk K, Porębska I, et al. Oxidative stress in lung cancer patients is associated with altered serum markers of lipid metabolism.PLoS One. 2019;14:e0215246. [DOI] [PubMed] [PMC]
