Identification of immune cell-related biomarkers in lung adenocarcinoma using weighted gene co-expression network analysis_Chinese Journal of Clinical Thoracic and Cardiovascular Surgery

Authors：

HE Dongyuan ,  CHEN Bo , LIANG Jingyao , YE Haibo , YI Xiaoxing , LIANG Guangni

Department of Thoracic Surgery, The First People’s Hospital of Yulin, Yulin, 537000, Guangxi, P. R. China;

Corresponding?author：

CHEN Bo, Email: chenbo_202102@163.com

Keywords：

The Cancer Genome Atlas; lung adenocarcinoma; weighted gene co-expression network analysis; immunotherapy; biomarker; prognosis; immune infiltration

DOI：

10.7507/1007-4848.202404024

Video：

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Objective To identify immune cell-related biomarkers in lung adenocarcinoma (LUAD) using weighted gene co-expression network analysis (WGCNA). Methods Based on data from The Cancer Genome Atlas (TCGA) database, a gene co-expression network was constructed for the TCGA-LUAD dataset using the "WGCNA" R package, and genes were clustered into different modules. Concurrently, the Estimation of STromal and Immune cells in MAlignant Tumours using Expression data (ESTIMATE) algorithm was applied to the tumor samples in the TCGA-LUAD dataset. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed to evaluate the biological functions of genes within the most significantly correlated module. Candidate hub genes from the key module were intersected with a protein-protein interaction (PPI) network to identify the final hub genes. The prognostic performance of these hub genes and their correlation with immune cell infiltration were validated using Kaplan-Meier curves and the Tumor IMmune Estimation Resource (TIMER) algorithm. Finally, a multivariate Cox regression analysis was conducted on the identified hub genes to construct a prognostic risk model. Results In the co-expression network, the brown module was found to be highly correlated with the ImmuneScore, StromalScore, and ESTIMATE Score. Five immune-related hub genes were identified: CD53, PLEK, SPI1, IL10RA, and C3AR1. Enrichment analysis of the brown module revealed that its genes were primarily enriched in GO terms such as "regulation of innate immune response" and KEGG pathways like the "NF-kappa B signaling pathway". Furthermore, the expression levels of these five hub genes were significantly and positively correlated with the infiltration abundance of various immune cells. The immune relevance of the model was validated by the Immunophenoscore (IPS) and the Tumor Immune Dysfunction and Exclusion (TIDE) score. Moreover, the established RiskScore demonstrated significant potential in predicting the response to immunotherapy. Conclusion These five immune-related key genes may serve as novel and effective potential therapeutic targets for LUAD immunotherapy, facilitating the development of personalized diagnosis and treatment strategies for patients with LUAD.

Citation： HE Dongyuan, CHEN Bo, LIANG Jingyao, YE Haibo, YI Xiaoxing, LIANG Guangni. Identification of immune cell-related biomarkers in lung adenocarcinoma using weighted gene co-expression network analysis. Chinese Journal of Clinical Thoracic and Cardiovascular Surgery, 2026, 33(5): 751-758. doi: 10.7507/1007-4848.202404024 Copy

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11.	Jin Y, Wang Z, He D, et al. Identification of novel subtypes based on ssGSEA in immune-related prognostic signature for tongue squamous cell carcinoma. Cancer Med, 2021, 10(23): 8693-8707.
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15.	Ghandi M, Huang FW, Jané-Valbuena J, et al. Next-generation characterization of the Cancer Cell Line Encyclopedia. Nature, 2019, 569(7757): 503-508.
16.	Yan C, Niu Y, Ma L, et al. System analysis based on the cuproptosis-related genes identifies LIPT1 as a novel therapy target for liver hepatocellular carcinoma. J Transl Med, 2022, 20(1): 452.
17.	Barretina J, Caponigro G, Stransky N, et al. The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity. Nature, 2012, 483(7391): 603-607.
18.	Kao TJ, Wu CC, Phan NN, et al. Prognoses and genomic analyses of proteasome 26S subunit, ATPase (PSMC) family genes in clinical breast cancer. Aging (Albany NY), 2021, 13(14): 17970.
19.	Guo JN, Chen D, Deng SH, et al. Identification and quantification of immune infiltration landscape on therapy and prognosis in left- and right-sided colon cancer. Cancer Immunol Immunother, 2022, 71(6): 1313-1330.
20.	Jiang P, Gu S, Pan D, et al. Signatures of T cell dysfunction and exclusion predict cancer immunotherapy response. Nat Med, 2018, 24(10): 1550-1558.
21.	Rui R, Zhou L, He S. Cancer immunotherapies: advances and bottlenecks. Front Immunol, 2023, 14: 1212476.
22.	Dieci MV, Miglietta F, Guarneri V. Immune infiltrates in breast cancer: recent updates and clinical implications. Cells, 2021, 10(2): 223.
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24.	Ding FP, Tian JY, Wu J, et al. Identification of key genes as predictive biomarkers for osteosarcoma metastasis using translational bioinformatics. Cancer Cell Int, 2021, 21(1): 640.
25.	Bai M, Pan Q, Sun C. Tumor purity coexpressed genes related to immune microenvironment and clinical outcomes of lung adenocarcinoma. J Oncol, 2021, 2021: 9548648.
26.	Gao N, Ye B. SPI1-induced upregulation of lncRNA SNHG6 promotes non-small cell lung cancer via miR-485-3p/VPS45 axis. Biomed Pharmacother, 2020, 129: 110239.
27.	Cheng S, Li Z, Zhang W, et al. Identification of IL10RA by weighted correlation network analysis and in vitro validation of its association with prognosis of metastatic melanoma. Front Cell Dev Biol, 2021, 8: 630790.
28.	Qu J, Zhao Q, Yang L, et al. Identification and characterization of prognosis-related genes in the tumor microenvironment of esophageal squamous cell carcinoma. Int Immunopharmacol, 2021, 96: 107616.
29.	Petitprez F, Meylan M, de Reyniès A, et al. The tumor microenvironment in the response to immune checkpoint blockade therapies. Front Immunol, 2020, 11: 784.
30.	Ok?a K, Farber DL, Zou W. Tissue-resident memory T cells in tumor immunity and immunotherapy. J Exp Med, 2021, 218(4): e20201605.
31.	Dunlock VE, Arp AB, Singh SP, et al. Tetraspanin CD53 controls T cell immunity through regulation of CD45RO stability, mobility, and function. Cell Rep, 2022, 39(13): 111006.
32.	Dunlock VE. Tetraspanin CD53: an overlooked regulator of immune cell function. Med Microbiol Immunol, 2020, 209(4): 545-552.
33.	Mao D, Zhou Z, Chen H, et al. Pleckstrin-2 promotes tumour immune escape from NK cells by activating the MT1-MMP-MICA signalling axis in gastric cancer. Cancer Lett, 2023, 572: 216351.
34.	Feng H, Wang T, Ye J, et al. SPI1 is a prognostic biomarker of immune infiltration and immunotherapy efficacy in clear cell renal cell carcinoma. Discov Oncol, 2022, 13(1): 134.
35.	Huang J, Chen W, Jie Z, et al. Comprehensive analysis of immune implications and prognostic value of SPI1 in gastric cancer. Front Oncol, 2022, 12: 820568.
36.	Lu G, Qiu Y. SPI1-mediated CXCL12 expression in bladder cancer affects the recruitment of tumor-associated macrophages. Mol Carcinog, 2024, 63(3): 448-460.
37.	Cabral-Marques O, Schimke LF, de Oliveira EB, et al. Flow cytometry contributions for the diagnosis and immunopathological characterization of primary immunodeficiency diseases with immune dysregulation. Front Immunol, 2019, 10: 2742.
38.	Grk M, Miskovic R, Jeremic I, et al. Association of IL10RA, IL10RB, and IL22RA polymorphisms/haplotypes with susceptibility to and clinical manifestations of SLE. Int J Mol Sci, 2023, 24(14): 11292.
39.	Tang Q, Zhang H, Tang R. Identification of two immune subtypes and four hub immune-related genes in ovarian cancer through multiple analysis. Medicine (Baltimore), 2023, 102(40): e35246.
40.	Prokoph N, Probst NA, Lee LC, et al. IL10RA modulates crizotinib sensitivity in NPM1-ALK+ anaplastic large cell lymphoma. Blood, 2020, 136(14): 1657-1669.
41.	Huang J, Zhou L, Deng K. Prognostic marker C3AR1 is associated with ovarian cancer cell proliferation and immunosuppression in the tumor microenvironment. J Ovarian Res, 2023, 16(1): 64.
42.	Chu G, Jiao W, Yang X, et al. C3, C3AR1, HLA-DRA, and HLA-E as potential prognostic biomarkers for renal clear cell carcinoma. Transl Androl Urol, 2020, 9(6): 2640-2656.
43.	Zou T, Liu W, Wang Z, et al. C3AR1 mRNA as a potential therapeutic target associates with clinical outcomes and tumor microenvironment in osteosarcoma. Front Med (Lausanne), 2021, 8: 642615.
44.	Yang Z, Tao Y, Xu X, et al. Bufalin inhibits cell proliferation and migration of hepatocellular carcinoma cells via APOBEC3F induced intestinal immune network for IgA production signaling pathway. Biochem Biophys Res Commun, 2018, 503(3): 2124-2131.
45.	Liu W, Gong X, Luo J, et al. A purified acidic polysaccharide from Sarcandra glabra as vaccine adjuvant to enhance anti-tumor effect of cancer vaccine. Carbohydr Polym, 2021, 263: 117967.
46.	Sun J, Jia H, Bao X, et al. Tumor exosome promotes Th17 cell differentiation by transmitting the lncRNA CRNDE-h in colorectal cancer. Cell Death Dis, 2021, 12(1): 123.
47.	Jin J, Lu Z, Wang X, et al. E3 ubiquitin ligase TRIM7 negatively regulates NF-kappa B signaling pathway by degrading p65 in lung cancer. Cell Signal, 2020, 69: 109543.
48.	Moradi-Marjaneh R, Hassanian SM, Fiuji H, et al. Toll like receptor signaling pathway as a potential therapeutic target in colorectal cancer. J Cell Physiol, 2018, 233(8): 5613-5622.
49.	Jiang C, Cao S, Li N, et al. PD-1 and PD-L1 correlated gene expression profiles and their association with clinical outcomes of breast cancer. Cancer Cell Int, 2019, 19: 233.
50.	Saglam O, Conejo-Garcia J. PD-1/PD-L1 immune checkpoint inhibitors in advanced cervical cancer. Integr Cancer Sci Ther, 2018, 5(2): 10.
51.	Rotte A. Combination of CTLA-4 and PD-1 blockers for treatment of cancer. J Exp Clin Cancer Res, 2019, 38(1): 255.
52.	Flaks-Manov N, Topaz M, Hoshen M, et al. Identifying patients at highest-risk: the best timing to apply a readmission predictive model. BMC Med Inform Decis Mak, 2019, 19(1): 118.
53.	Alby F, Fatigante M, Zucchermaglio C. Managing risk and patient involvement in choosing treatment for cancer: an analysis of two communication practices. Sociol Health Illn, 2017, 39(8): 1427-1447.

1. Bade BC, Dela Cruz CS. Lung cancer 2020: epidemiology, etiology, and prevention. Clin Chest Med, 2020, 41(1): 1-24.
2. Zhang Y, Luo G, Etxeberria J, et al. Global patterns and trends in lung cancer incidence: a population-based study. J Thorac Oncol, 2021, 16(6): 933-944.
3. Spella M, Stathopoulos GT. Immune resistance in lung adenocarcinoma. Cancers (Basel), 2021, 13(3): 384.
4. Sun R, Hou Z, Zhang Y, et al. Drug resistance mechanisms and progress in the treatment of EGFR-mutated lung adenocarcinoma. Oncol Lett, 2022, 24(5): 408.
5. Downs-Canner SM, Meier J, Vincent BG, et al. B cell function in the tumor microenvironment. Annu Rev Immunol, 2022, 40: 169-193.
6. Xia L, Oyang L, Lin J, et al. The cancer metabolic reprogramming and immune response. Mol Cancer, 2021, 20(1): 28.
7. Santarpia M, Aguilar A, Chaib I, et al. Non-small-cell lung cancer signaling pathways, metabolism, and PD-1/PD-L1 antibodies. Cancers (Basel), 2020, 12(6): 1475.
8. Janjigian YY, Bendell J, Calvo E, et al. CheckMate-032 study: efficacy and safety of nivolumab and nivolumab plus ipilimumab in patients with metastatic esophagogastric cancer. J Clin Oncol, 2018, 36(28): 2836-2844.
9. Herbst RS, Garon EB, Kim DW, et al. Long-term outcomes and retreatment among patients with previously treated, programmed death-ligand 1-positive, advanced non-small-cell lung cancer in the KEYNOTE-010 study. J Clin Oncol, 2020, 38(14): 1580-1590.
10. Wang CCN, Li CY, Cai JH, et al. Identification of prognostic candidate genes in breast cancer by integrated bioinformatic analysis. J Clin Med, 2019, 8(8): 1160.
11. Jin Y, Wang Z, He D, et al. Identification of novel subtypes based on ssGSEA in immune-related prognostic signature for tongue squamous cell carcinoma. Cancer Med, 2021, 10(23): 8693-8707.
12. Cumberlege J. Neighbourhood health. Practitioner, 1987, 231(1432): 977.
13. Wei E, Reisinger A, Li J, et al. Integration of scRNA-Seq and TCGA RNA-Seq to analyze the heterogeneity of HPV+ and HPV- cervical cancer immune cells and establish molecular risk models. Front Oncol, 2022, 12: 860900.
14. Shen A, Ye Y, Chen F, et al. Integrated multi-omics analysis identifies CD73 as a prognostic biomarker and immunotherapy response predictor in head and neck squamous cell carcinoma. Front Immunol, 2022, 13: 969034.
15. Ghandi M, Huang FW, Jané-Valbuena J, et al. Next-generation characterization of the Cancer Cell Line Encyclopedia. Nature, 2019, 569(7757): 503-508.
16. Yan C, Niu Y, Ma L, et al. System analysis based on the cuproptosis-related genes identifies LIPT1 as a novel therapy target for liver hepatocellular carcinoma. J Transl Med, 2022, 20(1): 452.
17. Barretina J, Caponigro G, Stransky N, et al. The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity. Nature, 2012, 483(7391): 603-607.
18. Kao TJ, Wu CC, Phan NN, et al. Prognoses and genomic analyses of proteasome 26S subunit, ATPase (PSMC) family genes in clinical breast cancer. Aging (Albany NY), 2021, 13(14): 17970.
19. Guo JN, Chen D, Deng SH, et al. Identification and quantification of immune infiltration landscape on therapy and prognosis in left- and right-sided colon cancer. Cancer Immunol Immunother, 2022, 71(6): 1313-1330.
20. Jiang P, Gu S, Pan D, et al. Signatures of T cell dysfunction and exclusion predict cancer immunotherapy response. Nat Med, 2018, 24(10): 1550-1558.
21. Rui R, Zhou L, He S. Cancer immunotherapies: advances and bottlenecks. Front Immunol, 2023, 14: 1212476.
22. Dieci MV, Miglietta F, Guarneri V. Immune infiltrates in breast cancer: recent updates and clinical implications. Cells, 2021, 10(2): 223.
23. Marchetti P, Antonov A, Anemona L, et al. New immunological potential markers for triple negative breast cancer: IL18R1, CD53, TRIM, Jaw1, LTB, PTPRCAP. Discov Oncol, 2021, 12(1): 6.
24. Ding FP, Tian JY, Wu J, et al. Identification of key genes as predictive biomarkers for osteosarcoma metastasis using translational bioinformatics. Cancer Cell Int, 2021, 21(1): 640.
25. Bai M, Pan Q, Sun C. Tumor purity coexpressed genes related to immune microenvironment and clinical outcomes of lung adenocarcinoma. J Oncol, 2021, 2021: 9548648.
26. Gao N, Ye B. SPI1-induced upregulation of lncRNA SNHG6 promotes non-small cell lung cancer via miR-485-3p/VPS45 axis. Biomed Pharmacother, 2020, 129: 110239.
27. Cheng S, Li Z, Zhang W, et al. Identification of IL10RA by weighted correlation network analysis and in vitro validation of its association with prognosis of metastatic melanoma. Front Cell Dev Biol, 2021, 8: 630790.
28. Qu J, Zhao Q, Yang L, et al. Identification and characterization of prognosis-related genes in the tumor microenvironment of esophageal squamous cell carcinoma. Int Immunopharmacol, 2021, 96: 107616.
29. Petitprez F, Meylan M, de Reyniès A, et al. The tumor microenvironment in the response to immune checkpoint blockade therapies. Front Immunol, 2020, 11: 784.
30. Ok?a K, Farber DL, Zou W. Tissue-resident memory T cells in tumor immunity and immunotherapy. J Exp Med, 2021, 218(4): e20201605.
31. Dunlock VE, Arp AB, Singh SP, et al. Tetraspanin CD53 controls T cell immunity through regulation of CD45RO stability, mobility, and function. Cell Rep, 2022, 39(13): 111006.
32. Dunlock VE. Tetraspanin CD53: an overlooked regulator of immune cell function. Med Microbiol Immunol, 2020, 209(4): 545-552.
33. Mao D, Zhou Z, Chen H, et al. Pleckstrin-2 promotes tumour immune escape from NK cells by activating the MT1-MMP-MICA signalling axis in gastric cancer. Cancer Lett, 2023, 572: 216351.
34. Feng H, Wang T, Ye J, et al. SPI1 is a prognostic biomarker of immune infiltration and immunotherapy efficacy in clear cell renal cell carcinoma. Discov Oncol, 2022, 13(1): 134.
35. Huang J, Chen W, Jie Z, et al. Comprehensive analysis of immune implications and prognostic value of SPI1 in gastric cancer. Front Oncol, 2022, 12: 820568.
36. Lu G, Qiu Y. SPI1-mediated CXCL12 expression in bladder cancer affects the recruitment of tumor-associated macrophages. Mol Carcinog, 2024, 63(3): 448-460.
37. Cabral-Marques O, Schimke LF, de Oliveira EB, et al. Flow cytometry contributions for the diagnosis and immunopathological characterization of primary immunodeficiency diseases with immune dysregulation. Front Immunol, 2019, 10: 2742.
38. Grk M, Miskovic R, Jeremic I, et al. Association of IL10RA, IL10RB, and IL22RA polymorphisms/haplotypes with susceptibility to and clinical manifestations of SLE. Int J Mol Sci, 2023, 24(14): 11292.
39. Tang Q, Zhang H, Tang R. Identification of two immune subtypes and four hub immune-related genes in ovarian cancer through multiple analysis. Medicine (Baltimore), 2023, 102(40): e35246.
40. Prokoph N, Probst NA, Lee LC, et al. IL10RA modulates crizotinib sensitivity in NPM1-ALK+ anaplastic large cell lymphoma. Blood, 2020, 136(14): 1657-1669.
41. Huang J, Zhou L, Deng K. Prognostic marker C3AR1 is associated with ovarian cancer cell proliferation and immunosuppression in the tumor microenvironment. J Ovarian Res, 2023, 16(1): 64.
42. Chu G, Jiao W, Yang X, et al. C3, C3AR1, HLA-DRA, and HLA-E as potential prognostic biomarkers for renal clear cell carcinoma. Transl Androl Urol, 2020, 9(6): 2640-2656.
43. Zou T, Liu W, Wang Z, et al. C3AR1 mRNA as a potential therapeutic target associates with clinical outcomes and tumor microenvironment in osteosarcoma. Front Med (Lausanne), 2021, 8: 642615.
44. Yang Z, Tao Y, Xu X, et al. Bufalin inhibits cell proliferation and migration of hepatocellular carcinoma cells via APOBEC3F induced intestinal immune network for IgA production signaling pathway. Biochem Biophys Res Commun, 2018, 503(3): 2124-2131.
45. Liu W, Gong X, Luo J, et al. A purified acidic polysaccharide from Sarcandra glabra as vaccine adjuvant to enhance anti-tumor effect of cancer vaccine. Carbohydr Polym, 2021, 263: 117967.
46. Sun J, Jia H, Bao X, et al. Tumor exosome promotes Th17 cell differentiation by transmitting the lncRNA CRNDE-h in colorectal cancer. Cell Death Dis, 2021, 12(1): 123.
47. Jin J, Lu Z, Wang X, et al. E3 ubiquitin ligase TRIM7 negatively regulates NF-kappa B signaling pathway by degrading p65 in lung cancer. Cell Signal, 2020, 69: 109543.
48. Moradi-Marjaneh R, Hassanian SM, Fiuji H, et al. Toll like receptor signaling pathway as a potential therapeutic target in colorectal cancer. J Cell Physiol, 2018, 233(8): 5613-5622.
49. Jiang C, Cao S, Li N, et al. PD-1 and PD-L1 correlated gene expression profiles and their association with clinical outcomes of breast cancer. Cancer Cell Int, 2019, 19: 233.
50. Saglam O, Conejo-Garcia J. PD-1/PD-L1 immune checkpoint inhibitors in advanced cervical cancer. Integr Cancer Sci Ther, 2018, 5(2): 10.
51. Rotte A. Combination of CTLA-4 and PD-1 blockers for treatment of cancer. J Exp Clin Cancer Res, 2019, 38(1): 255.
52. Flaks-Manov N, Topaz M, Hoshen M, et al. Identifying patients at highest-risk: the best timing to apply a readmission predictive model. BMC Med Inform Decis Mak, 2019, 19(1): 118.
53. Alby F, Fatigante M, Zucchermaglio C. Managing risk and patient involvement in choosing treatment for cancer: an analysis of two communication practices. Sociol Health Illn, 2017, 39(8): 1427-1447.

Chinese Journal of Clinical Thoracic and Cardiovascular Surgery

Identification of immune cell-related biomarkers in lung adenocarcinoma using weighted gene co-expression network analysis

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