The prognostic genes of idiopathic pulmonary fibrosis based on the RRA algorithm combined with GEO data mining_Chinese Journal of Respiratory and Critical Care Medicine

Authors：

ZHAI Qingqing , ZHANG Wen ,  ZHU Guangjun

Department of Respiratory Medicine, Xuzhou Hospital of Traditional Chinese Medicine, Jiangsu, Xuzhou, 221000, P. R. China;

Corresponding?author：

ZHU Guangjun, Email: 1973662071@qq.com

Keywords：

Idiopathic pulmonary fibrosis; prognostic gene; robust rank aggregation; bioinformatics analysis

DOI：

10.7507/1671-6205.202505041

Video：

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Abstract Full text Figures/Tables Video References Cited by

Objective To screen the prognostic related genes specific to idiopathic pulmonary fibrosis (IPF), understand the pathogenesis of IPF and provide potential therapeutic targets, as well as provide a data basis for the related research focusing on the functional verification and clinical transformation potential of prognostic gene targets. Methods Transcriptome datasets of multiple disease groups diagnosed in accordance with the IPF diagnostic criteria from the Gene Expression Omnibus (GEO) were included. Difference analyses were conducted between disease groups and control groups for datasets of different data types respectively. The difference analysis results of the up-regulated genes and down-regulated genes were respectively summarized and analyzed using the robust rank aggregation (RRA) algorithm. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and survival analyses were performed on the top 30 up-regulated genes in the ranking. Results Among the GO analysis results of the top 30 upregulated genes in the ranking, the key biological processes and mechanisms of IPF were mainly extracellular matrix (ECM) remodeling and abnormal differentiation and repair of epithelial cells. In the KEGG analysis results, the IPF-related signaling pathways include the relaxin signaling pathway, ECM-receptor interaction, and transforming growth factor-β (TGF-β) signaling pathway. Among them, the seven genes with positive significance in survival analysis were as follows: complement factor H (CFH), collagen type I alpha 1 chain (COL1A1), keratin 14 (KRT14), lymphocyte antigen 6 family member D (LY6D), matrix metallopeptidase1 (MMP1), matrix metallopeptidase 7 (MMP7), Versican (VCAN). Conclusions CFH, COL1A1, KRT14, LY6D, MMP1, MMP7, and VCAN are potential prognostic genes related to IPF. Among them, MMP7 has the greatest potential.

Citation： ZHAI Qingqing, ZHANG Wen, ZHU Guangjun. The prognostic genes of idiopathic pulmonary fibrosis based on the RRA algorithm combined with GEO data mining. Chinese Journal of Respiratory and Critical Care Medicine, 2026, 25(3): 186-195. doi: 10.7507/1671-6205.202505041 Copy

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2.	Spagnolo P, Maher TM. A long and winding road: drug development in idiopathic pulmonary fibrosis. Am J Respir Crit Care Med, 2024, 209(9): 1072-1073.
3.	歐陽小荔, 彭紅. 特發性肺纖維化預后的影響因素. 中國呼吸與危重監護雜志, 2021, 20(11): 824-830.
4.	吳詩, 劉驊, 殷世家, 等. POSTN、KL-6、SP-A及SP-D作為特發性肺纖維化血清標志物的比較研究. 中國呼吸與危重監護雜志, 2025, 24(3): 179-185.
5.	Fan G, Liu J, Wu Z, et al. Development and validation of the prognostic model based on autophagy-associated genes in idiopathic pulmonary fibrosis. Front Immunol, 2022, 13: 1049361.
6.	Chen H, Xia Z, Qing B, et al. Analysis of necroptosis-related prognostic genes and immune infiltration in idiopathic pulmonary fibrosis. Front Immunol, 2023, 14: 1119139.
7.	He Y, Yao T, Zhang Y, et al. Pyroptosis-related signatures predict immune characteristics and prognosis in IPF. Heliyon, 2024, 10(1): e23683.
8.	Zhu H, Zhou A, Zhang M, et al. Comprehensive analysis of an endoplasmic reticulum stress-related gene prediction model and immune infiltration in idiopathic pulmonary fibrosis. Front Immunol, 2023, 14: 1305025.
9.	Liu B, Zhang X, Liu Z, et al. A novel model for predicting prognosis in patients with idiopathic pulmonary fibrosis based on endoplasmic reticulum stress-related genes. Cell Biol Int, 2024, 48(4): 483-495.
10.	Gao H, Sun Z, Hu X, et al. Identification of glycolysis-related gene signatures for prognosis and therapeutic targeting in idiopathic pulmonary fibrosis. Front Pharmacol, 2025, 16: 1486357.
11.	Li Y, Deng Y, He J. A novel prognostic index based on the analysis of glycolysis-related genes in idiopathic pulmonary fibrosis. Medicine (Baltimore), 2023, 102(11): e33330.
12.	He Y, Shang Y, Li Y, et al. An 8-ferroptosis-related genes signature from Bronchoalveolar Lavage Fluid for prognosis in patients with idiopathic pulmonary fibrosis. BMC Pulm Med, 2022, 22(1): 15.
13.	Li M, Wang K, Zhang Y, et al. Ferroptosis-related genes in bronchoalveolar lavage fluid serves as prognostic biomarkers for idiopathic pulmonary fibrosis. Front Med (Lausanne), 2021, 8: 693959.
14.	Jing C, Fu R, Liu X, et al. A comprehensive cuproptosis score and associated gene signatures reveal prognostic and immunological features of idiopathic pulmonary fibrosis. Front Immunol, 2023, 14: 1268141.
15.	Zhao J, Wang C, Fan R, et al. A prognostic model based on clusters of molecules related to epithelial-mesenchymal transition for idiopathic pulmonary fibrosis. Front Genet, 2022, 13: 1109903.
16.	Lu Y, Chen J, Tang K, et al. Development and validation of the prognostic index based on inflammation-related gene analysis in idiopathic pulmonary fibrosis. Front Mol Biosci, 2021, 8: 667459.
17.	Yin YQ, Peng F, Situ HJ, et al. Construction of prediction model of inflammation related genes in idiopathic pulmonary fibrosis and its correlation with immune microenvironment. Front Immunol, 2022, 13: 1010345.
18.	Chen H, Xia Z, Qing B, et al. Molecular characterization of PANoptosis-related genes associated with immune infiltration and prognosis in idiopathic pulmonary fibrosis. Int Immunopharmacol, 2024, 143(Pt 3): 113572.
19.	Lin K, Wang T, Tang Q, et al. IL18R1-Related Molecules as biomarkers for asthma severity and prognostic markers for idiopathic pulmonary fibrosis. J Proteome Res, 2023, 22(10): 3320-3331.
20.	Liu J, Gu L, Li W. The Prognostic value of integrated analysis of inflammation and hypoxia-related genes in idiopathic pulmonary fibrosis. Front Immunol, 2022, 13: 730186.
21.	Zheng J, Dong H, Zhang T, et al. Development and validation of a novel gene signature for predicting the prognosis of idiopathic pulmonary fibrosis based on three epithelial-mesenchymal transition and immune-related genes. Front Genet, 2022, 13: 865052.
22.	Huang T, Zhou HF. A novel 5-methylcytosine- and immune-related prognostic signature is a potential marker of idiopathic pulmonary fibrosis. Comput Math Methods Med, 2022, 2022: 1685384.
23.	Zhong C, Lei Y, Zhang J, et al. Prognostic Function and immunologic landscape of a predictive model based on five senescence-related genes in IPF bronchoalveolar lavage fluid. Biomedicines, 2024, 12(6): 1246.
24.	Lyu Y, Guo C, Zhang H. Fatty acid metabolism-related genes in bronchoalveolar lavage fluid unveil prognostic and immune infiltration in idiopathic pulmonary fibrosis. Front Endocrinol (Lausanne), 2022, 13: 1001563.
25.	Ji Q, Jiang L, Gao F, et al. Predictive and personalized approaches for idiopathic pulmonary fibrosis: a Wnt-related gene set scoring framework integrating single-cell sequencing, spatial transcriptomics, and machine learning for diagnosis and prognosis. Funct Integr Genomics, 2025, 25(1): 62.
26.	Hou J, Yang Y, Han X. Machine learning and single-cell analysis identify molecular features of IPF-associated fibroblast subtypes and their implications on IPF prognosis. Int J Mol Sci, 2023, 25(1): 94.
27.	Zhao J, Jing C, Fan R, et al. Prognostic model of fibroblasts in idiopathic pulmonary fibrosis by combined bulk and single-cell RNA-sequencing. Heliyon, 2024, 10(14): e34519.
28.	Bao Y, Yang S, Zhao H, et al. A prognostic model of idiopathic pulmonary fibrosis constructed based on macrophage and mitochondria-related genes. BMC Pulm Med, 2024, 24(1): 176.
29.	Zhang H, Yang Y, Cao Y, et al. IPF-related new macrophage subpopulations and diagnostic biomarker identification - combine machine learning with single-cell analysis. Respir Res, 2024, 25(1): 241.
30.	Cai H, Chen S, Li X, et al. The Combined model of CX3CR1-related immune infiltration genes to evaluate the prognosis of idiopathic pulmonary fibrosis. Front Immunol, 2022, 13: 837188.
31.	Huang G, Huang S, Cui H. Corrigendum: Effect of M6A regulators on diagnosis, subtype classification, prognosis and novel therapeutic target development of idiopathic pulmonary fibrosis. Front Pharmacol, 2022, 13: 1117317.
32.	Zhang J, Zhang Y, Wang Z, et al. Genes related to N6-methyladenosine in the diagnosis and prognosis of idiopathic pulmonary fibrosis. Front Genet, 2022, 13: 1102422.
33.	Wang Z, Shen L, Wang J, et al. Prognostic analysis of m6A-related genes as potential biomarkers in idiopathic pulmonary fibrosis. Front Genet, 2022, 13: 1059325.
34.	Zhou M, Ouyang J, Zhang G, et al. Prognostic value of tripartite motif (TRIM) family gene signature from bronchoalveolar lavage cells in idiopathic pulmonary fibrosis. BMC Pulm Med, 2022, 22(1): 467.
35.	Kolde R, Laur S, Adler P, et al. Robust rank aggregation for gene list integration and meta-analysis. Bioinformatics, 2012, 28(4): 573-580.
36.	Mei Q, Liu Z, Zuo H, et al. Idiopathic pulmonary fibrosis: an update on pathogenesis. Front Pharmacol, 2021, 12: 797292.
37.	Yan J, Wang SY, Su Q, et al. Targeted immunotherapy rescues pulmonary fibrosis by reducing activated fibroblasts and regulating alveolar cell profile. Nat Commun, 2025, 16(1): 3748.
38.	Pillai M, Lafortune P, Dabo A, et al. Small-molecule activation of protein phosphatase 2A counters bleomycin-induced fibrosis in mice. ACS Pharmacol Transl Sci, 2023, 6(11): 1659-1672.
39.	Gong H, Lyu X, Liu Y, et al. Eupatilin inhibits pulmonary fibrosis by activating Sestrin2/PI3K/Akt/mTOR dependent autophagy pathway. Life Sci, 2023, 334: 122218.
40.	Bibaki E, Tsitoura E, Vasarmidi E, et al. miR-185 and miR-29a are similarly expressed in the bronchoalveolar lavage cells in IPF and lung cancer but common targets DNMT1 and COL1A1 show disease specific patterns. Mol Med Rep, 2018, 17(5): 7105-7112.
41.	Tsitoura E, Trachalaki A, Vasarmidi E, et al. Collagen 1a1 expression by airway macrophages increases in fibrotic ILDs and is associated with FVC decline and increased mortality. Front Immunol, 2021, 12: 645548.
42.	Blumer S, Khan P, Artysh N, et al. The use of cultured human alveolar basal cells to mimic honeycomb formation in idiopathic pulmonary fibrosis. Respir Res, 2024, 25(1): 26.
43.	Gao S, Wei Y, Li C, et al. A novel lncRNA ABCE1-5 regulates pulmonary fibrosis by targeting KRT14. Am J Physiol Cell Physiol, 2025, 328(5): C1487-c1500.
44.	Islam S, Watanabe H. Versican: A dynamic regulator of the extracellular matrix. J Histochem Cytochem, 2020, 68(11): 763-775.
45.	Rosas IO, Richards TJ, Konishi K, et al. MMP1 and MMP7 as potential peripheral blood biomarkers in idiopathic pulmonary fibrosis. PLoS Med, 2008, 5(4): e93.
46.	Checa M, Ruiz V, Monta?o M, et al. MMP-1 polymorphisms and the risk of idiopathic pulmonary fibrosis. Hum Genet, 2008, 124(5): 465-472.
47.	Pardo A, Selman M, Kaminski N. Approaching the degradome in idiopathic pulmonary fibrosis. Int J Biochem Cell Biol, 2008, 40(6-7): 1141-1155.
48.	Peng Z, Konai MM, Avila-Cobian LF, et al. MMP-1 and ADAM10 as targets for therapeutic intervention in idiopathic pulmonary fibrosis. ACS Pharmacol Transl Sci, 2022, 5(8): 548-554.
49.	Selman M, Pardo A. Idiopathic pulmonary fibrosis: an epithelial/fibroblastic cross-talk disorder. Respir Res, 2002, 3(1): 3.
50.	Jaffar J, Wong M, Fishbein GA, et al. Matrix metalloproteinase-7 is increased in lung bases but not apices in idiopathic pulmonary fibrosis. ERJ Open Res, 2022, 8(4): 00191-2022.
51.	Araújo M, Beltr?o M, Sokhatska O, et al. Serum metalloproteinase-7 as a biomarker of progressive pulmonary fibrosis. ERJ Open Res, 2024, 10(6): 00553-2024.
52.	Khan FA, Stewart I, Saini G, et al. A systematic review of blood biomarkers with individual participant data meta-analysis of matrix metalloproteinase-7 in idiopathic pulmonary fibrosis. Eur Respir J, 2022, 59(4): 2101612.
53.	Li RM, Tan DBA, Tedja C, et al. Pre-Treatment MMP7 predicts progressive idiopathic pulmonary fibrosis in antifibrotic treated patients. Respirology, 2025, 30(6): 504-514.
54.	Adegunsoye A, Alqalyoobi S, Linderholm A, et al. Circulating plasma biomarkers of survival in antifibrotic-treated patients with idiopathic pulmonary fibrosis. Chest, 2020, 158(4): 1526-1534.
55.	Dasgupta S. Idiopathic Pulmonary Fibrosis: In silico therapeutic potential of doxycycline, pirfenidone, and nintedanib, and the role of next-generation phenomics in drug discovery. Omics, 2025, 29(3): 87-95.
56.	Liu X, Yang M, Li J, et al. Identification of CFH and FHL2 as biomarkers for idiopathic pulmonary fibrosis. Front Med (Lausanne), 2024, 11: 1363643.
57.	Jin C, Li J, Li Q, et al. Contribution of cuproptosis and immune-related genes to idiopathic pulmonary fibrosis disease. Front Immunol, 2025, 16: 1458341.
58.	Ma D, Hua Y, Lu Y. Complement factor H drives idiopathic pulmonary fibrosis by autocrine C3 regulation, suppressing macrophage phagocytosis and enhancing fibrotic progression. Biochem Biophys Res Commun, 2025, 745: 151220.
59.	Duan J, Wang Y, Chen Y, et al. Silencing LY6D expression inhibits colon cancer in xenograft mice and regulates colon cancer stem cells' proliferation, stemness, invasion, and apoptosis via the MAPK pathway. Molecules, 2023, 28(23): 7776.
60.	Okimura S, Nishida N, Takahashi H, et al. Lymphocyte antigen 6 family member D (LY6D) affects stem cell phenotype and progression of pancreatic adenocarcinoma. Anticancer Res, 2024, 44(11): 4737-4749.

1. Podolanczuk AJ, Thomson CC, Remy-Jardin M, et al. Idiopathic pulmonary fibrosis: state of the art for 2023. Eur Respir J, 2023, 61(4): 2200957.
2. Spagnolo P, Maher TM. A long and winding road: drug development in idiopathic pulmonary fibrosis. Am J Respir Crit Care Med, 2024, 209(9): 1072-1073.
3. 歐陽小荔, 彭紅. 特發性肺纖維化預后的影響因素. 中國呼吸與危重監護雜志, 2021, 20(11): 824-830.
4. 吳詩, 劉驊, 殷世家, 等. POSTN、KL-6、SP-A及SP-D作為特發性肺纖維化血清標志物的比較研究. 中國呼吸與危重監護雜志, 2025, 24(3): 179-185.
5. Fan G, Liu J, Wu Z, et al. Development and validation of the prognostic model based on autophagy-associated genes in idiopathic pulmonary fibrosis. Front Immunol, 2022, 13: 1049361.
6. Chen H, Xia Z, Qing B, et al. Analysis of necroptosis-related prognostic genes and immune infiltration in idiopathic pulmonary fibrosis. Front Immunol, 2023, 14: 1119139.
7. He Y, Yao T, Zhang Y, et al. Pyroptosis-related signatures predict immune characteristics and prognosis in IPF. Heliyon, 2024, 10(1): e23683.
8. Zhu H, Zhou A, Zhang M, et al. Comprehensive analysis of an endoplasmic reticulum stress-related gene prediction model and immune infiltration in idiopathic pulmonary fibrosis. Front Immunol, 2023, 14: 1305025.
9. Liu B, Zhang X, Liu Z, et al. A novel model for predicting prognosis in patients with idiopathic pulmonary fibrosis based on endoplasmic reticulum stress-related genes. Cell Biol Int, 2024, 48(4): 483-495.
10. Gao H, Sun Z, Hu X, et al. Identification of glycolysis-related gene signatures for prognosis and therapeutic targeting in idiopathic pulmonary fibrosis. Front Pharmacol, 2025, 16: 1486357.
11. Li Y, Deng Y, He J. A novel prognostic index based on the analysis of glycolysis-related genes in idiopathic pulmonary fibrosis. Medicine (Baltimore), 2023, 102(11): e33330.
12. He Y, Shang Y, Li Y, et al. An 8-ferroptosis-related genes signature from Bronchoalveolar Lavage Fluid for prognosis in patients with idiopathic pulmonary fibrosis. BMC Pulm Med, 2022, 22(1): 15.
13. Li M, Wang K, Zhang Y, et al. Ferroptosis-related genes in bronchoalveolar lavage fluid serves as prognostic biomarkers for idiopathic pulmonary fibrosis. Front Med (Lausanne), 2021, 8: 693959.
14. Jing C, Fu R, Liu X, et al. A comprehensive cuproptosis score and associated gene signatures reveal prognostic and immunological features of idiopathic pulmonary fibrosis. Front Immunol, 2023, 14: 1268141.
15. Zhao J, Wang C, Fan R, et al. A prognostic model based on clusters of molecules related to epithelial-mesenchymal transition for idiopathic pulmonary fibrosis. Front Genet, 2022, 13: 1109903.
16. Lu Y, Chen J, Tang K, et al. Development and validation of the prognostic index based on inflammation-related gene analysis in idiopathic pulmonary fibrosis. Front Mol Biosci, 2021, 8: 667459.
17. Yin YQ, Peng F, Situ HJ, et al. Construction of prediction model of inflammation related genes in idiopathic pulmonary fibrosis and its correlation with immune microenvironment. Front Immunol, 2022, 13: 1010345.
18. Chen H, Xia Z, Qing B, et al. Molecular characterization of PANoptosis-related genes associated with immune infiltration and prognosis in idiopathic pulmonary fibrosis. Int Immunopharmacol, 2024, 143(Pt 3): 113572.
19. Lin K, Wang T, Tang Q, et al. IL18R1-Related Molecules as biomarkers for asthma severity and prognostic markers for idiopathic pulmonary fibrosis. J Proteome Res, 2023, 22(10): 3320-3331.
20. Liu J, Gu L, Li W. The Prognostic value of integrated analysis of inflammation and hypoxia-related genes in idiopathic pulmonary fibrosis. Front Immunol, 2022, 13: 730186.
21. Zheng J, Dong H, Zhang T, et al. Development and validation of a novel gene signature for predicting the prognosis of idiopathic pulmonary fibrosis based on three epithelial-mesenchymal transition and immune-related genes. Front Genet, 2022, 13: 865052.
22. Huang T, Zhou HF. A novel 5-methylcytosine- and immune-related prognostic signature is a potential marker of idiopathic pulmonary fibrosis. Comput Math Methods Med, 2022, 2022: 1685384.
23. Zhong C, Lei Y, Zhang J, et al. Prognostic Function and immunologic landscape of a predictive model based on five senescence-related genes in IPF bronchoalveolar lavage fluid. Biomedicines, 2024, 12(6): 1246.
24. Lyu Y, Guo C, Zhang H. Fatty acid metabolism-related genes in bronchoalveolar lavage fluid unveil prognostic and immune infiltration in idiopathic pulmonary fibrosis. Front Endocrinol (Lausanne), 2022, 13: 1001563.
25. Ji Q, Jiang L, Gao F, et al. Predictive and personalized approaches for idiopathic pulmonary fibrosis: a Wnt-related gene set scoring framework integrating single-cell sequencing, spatial transcriptomics, and machine learning for diagnosis and prognosis. Funct Integr Genomics, 2025, 25(1): 62.
26. Hou J, Yang Y, Han X. Machine learning and single-cell analysis identify molecular features of IPF-associated fibroblast subtypes and their implications on IPF prognosis. Int J Mol Sci, 2023, 25(1): 94.
27. Zhao J, Jing C, Fan R, et al. Prognostic model of fibroblasts in idiopathic pulmonary fibrosis by combined bulk and single-cell RNA-sequencing. Heliyon, 2024, 10(14): e34519.
28. Bao Y, Yang S, Zhao H, et al. A prognostic model of idiopathic pulmonary fibrosis constructed based on macrophage and mitochondria-related genes. BMC Pulm Med, 2024, 24(1): 176.
29. Zhang H, Yang Y, Cao Y, et al. IPF-related new macrophage subpopulations and diagnostic biomarker identification - combine machine learning with single-cell analysis. Respir Res, 2024, 25(1): 241.
30. Cai H, Chen S, Li X, et al. The Combined model of CX3CR1-related immune infiltration genes to evaluate the prognosis of idiopathic pulmonary fibrosis. Front Immunol, 2022, 13: 837188.
31. Huang G, Huang S, Cui H. Corrigendum: Effect of M6A regulators on diagnosis, subtype classification, prognosis and novel therapeutic target development of idiopathic pulmonary fibrosis. Front Pharmacol, 2022, 13: 1117317.
32. Zhang J, Zhang Y, Wang Z, et al. Genes related to N6-methyladenosine in the diagnosis and prognosis of idiopathic pulmonary fibrosis. Front Genet, 2022, 13: 1102422.
33. Wang Z, Shen L, Wang J, et al. Prognostic analysis of m6A-related genes as potential biomarkers in idiopathic pulmonary fibrosis. Front Genet, 2022, 13: 1059325.
34. Zhou M, Ouyang J, Zhang G, et al. Prognostic value of tripartite motif (TRIM) family gene signature from bronchoalveolar lavage cells in idiopathic pulmonary fibrosis. BMC Pulm Med, 2022, 22(1): 467.
35. Kolde R, Laur S, Adler P, et al. Robust rank aggregation for gene list integration and meta-analysis. Bioinformatics, 2012, 28(4): 573-580.
36. Mei Q, Liu Z, Zuo H, et al. Idiopathic pulmonary fibrosis: an update on pathogenesis. Front Pharmacol, 2021, 12: 797292.
37. Yan J, Wang SY, Su Q, et al. Targeted immunotherapy rescues pulmonary fibrosis by reducing activated fibroblasts and regulating alveolar cell profile. Nat Commun, 2025, 16(1): 3748.
38. Pillai M, Lafortune P, Dabo A, et al. Small-molecule activation of protein phosphatase 2A counters bleomycin-induced fibrosis in mice. ACS Pharmacol Transl Sci, 2023, 6(11): 1659-1672.
39. Gong H, Lyu X, Liu Y, et al. Eupatilin inhibits pulmonary fibrosis by activating Sestrin2/PI3K/Akt/mTOR dependent autophagy pathway. Life Sci, 2023, 334: 122218.
40. Bibaki E, Tsitoura E, Vasarmidi E, et al. miR-185 and miR-29a are similarly expressed in the bronchoalveolar lavage cells in IPF and lung cancer but common targets DNMT1 and COL1A1 show disease specific patterns. Mol Med Rep, 2018, 17(5): 7105-7112.
41. Tsitoura E, Trachalaki A, Vasarmidi E, et al. Collagen 1a1 expression by airway macrophages increases in fibrotic ILDs and is associated with FVC decline and increased mortality. Front Immunol, 2021, 12: 645548.
42. Blumer S, Khan P, Artysh N, et al. The use of cultured human alveolar basal cells to mimic honeycomb formation in idiopathic pulmonary fibrosis. Respir Res, 2024, 25(1): 26.
43. Gao S, Wei Y, Li C, et al. A novel lncRNA ABCE1-5 regulates pulmonary fibrosis by targeting KRT14. Am J Physiol Cell Physiol, 2025, 328(5): C1487-c1500.
44. Islam S, Watanabe H. Versican: A dynamic regulator of the extracellular matrix. J Histochem Cytochem, 2020, 68(11): 763-775.
45. Rosas IO, Richards TJ, Konishi K, et al. MMP1 and MMP7 as potential peripheral blood biomarkers in idiopathic pulmonary fibrosis. PLoS Med, 2008, 5(4): e93.
46. Checa M, Ruiz V, Monta?o M, et al. MMP-1 polymorphisms and the risk of idiopathic pulmonary fibrosis. Hum Genet, 2008, 124(5): 465-472.
47. Pardo A, Selman M, Kaminski N. Approaching the degradome in idiopathic pulmonary fibrosis. Int J Biochem Cell Biol, 2008, 40(6-7): 1141-1155.
48. Peng Z, Konai MM, Avila-Cobian LF, et al. MMP-1 and ADAM10 as targets for therapeutic intervention in idiopathic pulmonary fibrosis. ACS Pharmacol Transl Sci, 2022, 5(8): 548-554.
49. Selman M, Pardo A. Idiopathic pulmonary fibrosis: an epithelial/fibroblastic cross-talk disorder. Respir Res, 2002, 3(1): 3.
50. Jaffar J, Wong M, Fishbein GA, et al. Matrix metalloproteinase-7 is increased in lung bases but not apices in idiopathic pulmonary fibrosis. ERJ Open Res, 2022, 8(4): 00191-2022.
51. Araújo M, Beltr?o M, Sokhatska O, et al. Serum metalloproteinase-7 as a biomarker of progressive pulmonary fibrosis. ERJ Open Res, 2024, 10(6): 00553-2024.
52. Khan FA, Stewart I, Saini G, et al. A systematic review of blood biomarkers with individual participant data meta-analysis of matrix metalloproteinase-7 in idiopathic pulmonary fibrosis. Eur Respir J, 2022, 59(4): 2101612.
53. Li RM, Tan DBA, Tedja C, et al. Pre-Treatment MMP7 predicts progressive idiopathic pulmonary fibrosis in antifibrotic treated patients. Respirology, 2025, 30(6): 504-514.
54. Adegunsoye A, Alqalyoobi S, Linderholm A, et al. Circulating plasma biomarkers of survival in antifibrotic-treated patients with idiopathic pulmonary fibrosis. Chest, 2020, 158(4): 1526-1534.
55. Dasgupta S. Idiopathic Pulmonary Fibrosis: In silico therapeutic potential of doxycycline, pirfenidone, and nintedanib, and the role of next-generation phenomics in drug discovery. Omics, 2025, 29(3): 87-95.
56. Liu X, Yang M, Li J, et al. Identification of CFH and FHL2 as biomarkers for idiopathic pulmonary fibrosis. Front Med (Lausanne), 2024, 11: 1363643.
57. Jin C, Li J, Li Q, et al. Contribution of cuproptosis and immune-related genes to idiopathic pulmonary fibrosis disease. Front Immunol, 2025, 16: 1458341.
58. Ma D, Hua Y, Lu Y. Complement factor H drives idiopathic pulmonary fibrosis by autocrine C3 regulation, suppressing macrophage phagocytosis and enhancing fibrotic progression. Biochem Biophys Res Commun, 2025, 745: 151220.
59. Duan J, Wang Y, Chen Y, et al. Silencing LY6D expression inhibits colon cancer in xenograft mice and regulates colon cancer stem cells' proliferation, stemness, invasion, and apoptosis via the MAPK pathway. Molecules, 2023, 28(23): 7776.
60. Okimura S, Nishida N, Takahashi H, et al. Lymphocyte antigen 6 family member D (LY6D) affects stem cell phenotype and progression of pancreatic adenocarcinoma. Anticancer Res, 2024, 44(11): 4737-4749.

Chinese Journal of Respiratory and Critical Care Medicine

The prognostic genes of idiopathic pulmonary fibrosis based on the RRA algorithm combined with GEO data mining

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