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Shajari, Neda, Ramezani, Amin, Tahmasebi, Ahmad, Anbardar, Mohammad Hossein, Roshanizadeh, Zahra, Ghaderi, Abbas. (1403). Feature Selection Algorithms Combined with Experimental Validation Reveal COL10A1 and TMPRSS4 Genes as Potential Diagnostic Biomarkers in Pancreatic Ductal Adenocarcinoma. سامانه مدیریت نشریات علمی, (), -. doi: 10.30476/mejc.2024.102622.2100
Neda Shajari; Amin Ramezani; Ahmad Tahmasebi; Mohammad Hossein Anbardar; Zahra Roshanizadeh; Abbas Ghaderi. "Feature Selection Algorithms Combined with Experimental Validation Reveal COL10A1 and TMPRSS4 Genes as Potential Diagnostic Biomarkers in Pancreatic Ductal Adenocarcinoma". سامانه مدیریت نشریات علمی, , , 1403, -. doi: 10.30476/mejc.2024.102622.2100
Shajari, Neda, Ramezani, Amin, Tahmasebi, Ahmad, Anbardar, Mohammad Hossein, Roshanizadeh, Zahra, Ghaderi, Abbas. (1403). 'Feature Selection Algorithms Combined with Experimental Validation Reveal COL10A1 and TMPRSS4 Genes as Potential Diagnostic Biomarkers in Pancreatic Ductal Adenocarcinoma', سامانه مدیریت نشریات علمی, (), pp. -. doi: 10.30476/mejc.2024.102622.2100
Shajari, Neda, Ramezani, Amin, Tahmasebi, Ahmad, Anbardar, Mohammad Hossein, Roshanizadeh, Zahra, Ghaderi, Abbas. Feature Selection Algorithms Combined with Experimental Validation Reveal COL10A1 and TMPRSS4 Genes as Potential Diagnostic Biomarkers in Pancreatic Ductal Adenocarcinoma. سامانه مدیریت نشریات علمی, 1403; (): -. doi: 10.30476/mejc.2024.102622.2100

Feature Selection Algorithms Combined with Experimental Validation Reveal COL10A1 and TMPRSS4 Genes as Potential Diagnostic Biomarkers in Pancreatic Ductal Adenocarcinoma

Middle East Journal of Cancer
مقالات آماده انتشار، پذیرفته شده، انتشار آنلاین از تاریخ 29 آبان 1403    اصل مقاله (1.05 M)
نوع مقاله: Original Article(s)
شناسه دیجیتال (DOI): 10.30476/mejc.2024.102622.2100
نویسندگان
Neda Shajari1، 2؛ Amin Ramezani2؛ Ahmad Tahmasebi3؛ Mohammad Hossein Anbardar4؛ Zahra Roshanizadeh1، 2؛ Abbas Ghaderi* 1، 2
1Department of Immunology, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran
2Shiraz Institute for Cancer Research, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran
3Institute of Biotechnology, Shiraz University, Shiraz, Iran
4Department of Pathology, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran
چکیده
Background: Pancreatic adenocarcinoma (PAAD) is often diagnosed at a late stage, preventing curative surgery. Early detection is crucial for improving patient outcomes. This study aims to discover potential biomarkers for identifying asymptomatic PAAD tumors.
Methods: In this case-control study, two gene expression datasets of PAAD and normal samples were collected from GEO and TCGA databases. Independent analyses of these datasets were conducted, leading to the identification of genes common to both datasets. Gene ontology and pathway enrichment analyses for the feature genes were conducted. Following our strict criteria, three feature genes for experimental validation were selected. The reliability of the selected feature genes was determined through quantitative real-time polymerase chain reaction (qRT-PCR). Data were analyzed using GraphPad Prism 8 software, employing the Mann-Whitney test and unpaired t-test.  A P-value of <0.05 was considered statistically significant.
Results: A total number of 33 genes common to both GEO and TCGA datasets were identified. Gene ontology and pathway enrichment methods revealed that the selected genes were primarily associated with proteolysis and extracellular matrix organization. Based on our criteria, three feature genes (COL10A1, CTHRC1, and TMPRSS4) were selected for experimental validation. The results of qRT-PCR on independent patient samples demonstrated that the expression levels of COL10A1 and TMPRSS4 were significantly upregulated in PAAD tissues as compared with normal pancreatic tissues. In contrast, CTHRC1 expression levels did not change significantly in PAAD in comparison with normal samples.
Conclusions: Our findings suggest that COL10A1 and TMPRSS4 can be attractive biomarkers for the mRNA-based diagnosis of PAAD.

تازه های تحقیق

Neda Shajari (Google Scholar)

Abbas Ghaderi (Google Scholar)

کلیدواژه‌ها
Pancreatic neoplasms؛ Gene expression profiling؛ Biomarkers؛ Diagnosis
مراجع
  1. Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin. 2021;71(3):209-49. doi: 10.3322/caac.21660. PMID: 33538338.
  2. Wood LD, Canto MI, Jaffee EM, Simeone DM. Pancreatic cancer: Pathogenesis, screening, diagnosis, and treatment. Gastroenterology. 2022;163(2):386-402.e1. doi: 10.1053/j.gastro.2022.03.056. PMID: 35398344; PMCID: PMC9516440.
  3. Klein AP. Pancreatic cancer epidemiology: understanding the role of lifestyle and inherited risk factors. Nat Rev Gastroenterol Hepatol. 2021;18(7):493-502. doi: 10.1038/s41575-021-00457-x. PMID: 34002083; PMCID: PMC9265847.
  4. Amaral MJ, Oliveira RC, Donato P, Tralhão JG. Pancreatic cancer biomarkers: Oncogenic mutations, tissue and liquid biopsies, and radiomics-A review. Dig Dis Sci. 2023;68(7):2811-23. doi: 10.1007/s10620-023-07904-6. PMID: 36988759; PMCID: PMC10293428.
  5. Karandish F, Mallik S. Biomarkers and targeted therapy in pancreatic cancer. Biomark Cancer. 2016;8(Suppl 1):27-35. doi: 10.4137/BiC.s34414. PMID: 27147897; PMCID: PMC4847554.
  6. Zhang Y, Jiang L, Song L. Meta-analysis of diagnostic value of serum Carbohydrate antigen 199 in pancreatic cancer. Minerva Med. 2016;107(1):62-9. PMID: 26824636.
  7. Athar A, Füllgrabe A, George N, Iqbal H, Huerta L, Ali A, et al. ArrayExpress update - from bulk to single-cell expression data. Nucleic Acids Res. 2019;47(D1):D711-d5. doi: 10.1093/nar/gky964. PMID: 30357387; PMCID: PMC6323929.
  8. van IJzendoorn DGP, Szuhai K, Briaire-de Bruijn IH, Kostine M, Kuijjer ML, Bovée JVMG. Machine learning analysis of gene expression data reveals novel diagnostic and prognostic biomarkers and identifies therapeutic targets for soft tissue sarcomas. PLoS Comput Biol. 2019;15(2):e1006826. doi: 10.1371/journal.pcbi.1006826. PMID: 30785874; PMCID: PMC6398862.
  9. Irizarry RA, Hobbs B, Collin F, Beazer-Barclay YD, Antonellis KJ, Scherf U, et al. Exploration, normalization, and summaries of high density oligonucleotide array probe level data. Biostatistics. 2003;4(2):249-64. doi: 10.1093/biostatistics/4.2.249. PMID: 12925520.
  10. 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(7):e47. doi: 10.1093/nar/gkv007. PMID: 25605792; PMCID: PMC4402510.
  11. Leek JT, Johnson WE, Parker HS, Jaffe AE, Storey JD. The sva package for removing batch effects and other unwanted variation in high-throughput experiments. Bioinformatics. 2012;28(6):882-3. doi: 10.1093/bioinformatics/bts034. PMID: 22257669; PMCID: PMC3307112.
  12. 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(8):e71. doi: 10.1093/nar/gkv1507. PMID: 26704973; PMCID: PMC4856967.
  13. Tahmasebi A, Niazi A, Akrami S. Integration of meta-analysis, machine learning and systems biology approach for investigating the transcriptomic response to drought stress in Populus species. Sci Rep. 2023;13(1):847. doi: 10.1038/s41598-023-27746-6. PMID: 36646724; PMCID: PMC9842770.
  14. Raudvere U, Kolberg L, Kuzmin I, Arak T, Adler P, Peterson H, et al. g:Profiler: a web server for functional enrichment analysis and conversions of gene lists (2019 update). Nucleic Acids Res. 2019;47(W1):W191-w8. doi: 10.1093/nar/gkz369. PMID: 31066453; PMCID: PMC6602461.
  15. Charitou T, Bryan K, Lynn DJ. Using biological networks to integrate, visualize and analyze genomics data. Genet Sel Evol. 2016;48:27. doi: 10.1186/s12711-016-0205-1. PMID: 27036106; PMCID: PMC4818439.
  16. Tang Z, Li C, Kang B, Gao G, Li C, Zhang Z. GEPIA: a web server for cancer and normal gene expression profiling and interactive analyses. Nucleic Acids Res. 2017;45(W1):W98-w102. doi: 10.1093/nar/gkx247. PMID: 28407145; PMCID: PMC5570223.
  17. Ramezani A. CtNorm: Real time PCR cycle of threshold (Ct) normalization algorithm. J Microbiol Methods. 2021;187:106267. doi: 10.1016/j.mimet.2021.106267. PMID: 34116107.
  18. Islam S, Kitagawa T, Baron B, Abiko Y, Chiba I, Kuramitsu Y. ITGA2, LAMB3, and LAMC2 may be the potential therapeutic targets in pancreatic ductal adenocarcinoma: an integrated bioinformatics analysis. Sci Rep. 2021;11(1):10563. doi: 10.1038/s41598-021-90077-x. PMID: 34007003; PMCID: PMC8131351.
  19. Wen Z, Sun J, Luo J, Fu Y, Qiu Y, Li Y, et al. COL10A1-DDR2 axis promotes the progression of pancreatic cancer by regulating MEK/ERK signal transduction. Front Oncol. 2022;12:1049345. doi: 10.3389/fonc.2022.1049345. PMID: 36530986; PMCID: PMC9750160.
  20. Li J, Wang X, Zheng K, Liu Y, Li J, Wang S, et al. The clinical significance of collagen family gene expression in esophageal squamous cell carcinoma. PeerJ. 2019;7:e7705. doi: 10.7717/peerj.7705. PMID: 31598423; PMCID: PMC6779144.
  21. Huang H, Li T, Ye G, Zhao L, Zhang Z, Mo D, et al. High expression of COL10A1 is associated with poor prognosis in colorectal cancer. Onco Targets Ther. 2018;11:1571-81. doi: 10.2147/ott.S160196. PMID: 29593423; PMCID: PMC5865565.
  22. Liang Y, Xia W, Zhang T, Chen B, Wang H, Song X, et al. Upregulated collagen COL10A1 remodels the extracellular matrix and promotes malignant progression in lung adenocarcinoma. Front Oncol. 2020;10:573534. doi: 10.3389/fonc.2020.573534. PMID: 33324550; PMCID: PMC7726267.
  23. Andriani F, Landoni E, Mensah M, Facchinetti F, Miceli R, Tagliabue E, et al. Diagnostic role of circulating extracellular matrix-related proteins in non-small cell lung cancer. BMC Cancer. 2018;18(1):899. doi: 10.1186/s12885-018-4772-0. PMID: 30227835; PMCID: PMC6145327.
  24. Xie Z, Zhou Z, Yang S, Zhang S, Shao B. Epigenetic regulation and therapeutic targets in the tumor microenvironment. Mol Biomed. 2023;4(1):17. doi: 10.1186/s43556-023-00126-2. PMID: 37273004; PMCID: PMC10241773.
  25. Li Y, Li X, Deng M, Ye C, Peng Y, Lu Y. Cancer-associated fibroblasts hinder lung squamous cell carcinoma oxidative stress-induced apoptosis via METTL3 mediated m(6)A methylation of COL10A1. Oxid Med Cell Longev. 2022;2022:4320809. doi: 10.1155/2022/4320809. PMID: 36246404; PMCID: PMC9560815.
  26. Xu Q, Zheng J, Su Z, Chen B, Gu S. COL10A1 promotes tumorigenesis by modulating CD276 in pancreatic adenocarcinoma. BMC Gastroenterol. 2023;23(1):397. doi: 10.1186/s12876-023-03045-2. PMID: 37974070; PMCID: PMC10652574.
  27. Azuma M. Co-signal molecules in T-cell activation : Historical overview and perspective. Adv Exp Med Biol. 2019;1189:3-23. doi: 10.1007/978-981-32-9717-3_1. PMID: 31758529.
  28. Mei D, Zhu Y, Zhang L, Wei W. The role of CTHRC1 in regulation of multiple signaling and tumor progression and metastasis. Mediators Inflamm. 2020;2020:9578701. doi: 10.1155/2020/9578701. PMID: 32848510; PMCID: PMC7441421.
  29. Jiang N, Cui Y, Liu J, Zhu X, Wu H, Yang Z, et al. Multidimensional roles of collagen triple helix repeat containing 1 (CTHRC1) in malignant cancers. J Cancer. 2016;7(15):2213-20. doi: 10.7150/jca.16539. PMID: 27994657; PMCID: PMC5166530.
  30. Liu W, Fu XL, Yang JY, Yang MW, Tao LY, Liu DJ, et al. Elevated expression of CTHRC1 predicts unfavorable prognosis in patients with pancreatic ductal adenocarcinoma. Am J Cancer Res. 2016;6(8):1820-7. PMID: 27648368; PMCID: PMC5004082.
  31. Lee J, Song J, Kwon ES, Jo S, Kang MK, Kim YJ, et al. CTHRC1 promotes angiogenesis by recruiting Tie2-expressing monocytes to pancreatic tumors. Exp Mol Med. 2016;48(9):e261. doi: 10.1038/emm.2016.87. PMID: 27686285; PMCID: PMC5050301.
  32. Kim S. TMPRSS4, a type II transmembrane serine protease, as a potential therapeutic target in cancer. Exp Mol Med. 2023;55(4):716-24. doi: 10.1038/s12276-023-00975-5. PMID: 37009799; PMCID: PMC10167312.
  33. Exposito F, Villalba M, Redrado M, de Aberasturi AL, Cirauqui C, Redin E, et al. Targeting of TMPRSS4 sensitizes lung cancer cells to chemotherapy by impairing the proliferation machinery. Cancer Lett. 2019;453:21-33. doi: 10.1016/j.canlet.2019.03.013. PMID: 30905815.
  34. Jin J, Shen X, Chen L, Bao LW, Zhu LM. TMPRSS4 promotes invasiveness of human gastric cancer cells through activation of NF-κB/MMP-9 signaling. Biomed Pharmacother. 2016;77:30-6. doi: 10.1016/j.biopha.2015.11.002. PMID: 26796262.
  35. Wang CH, Guo ZY, Chen ZT, Zhi XT, Li DK, Dong ZR, et al. TMPRSS4 facilitates epithelial-mesenchymal transition of hepatocellular carcinoma and is a predictive marker for poor prognosis of patients after curative resection. Sci Rep. 2015;5:12366. doi: 10.1038/srep12366. PMID: 26190376; PMCID: PMC4507176.
  36. Bhasin MK, Ndebele K, Bucur O, Yee EU, Otu HH, Plati J, et al. Meta-analysis of transcriptome data identifies a novel 5-gene pancreatic adenocarcinoma classifier. Oncotarget. 2016;7(17):23263-81. doi: 10.18632/oncotarget.8139. PMID: 26993610; PMCID: PMC5029625.
  37. Gu J, Huang W, Zhang J, Wang X, Tao T, Yang L, et al. TMPRSS4 Promotes Cell Proliferation and Inhibits Apoptosis in Pancreatic Ductal Adenocarcinoma by Activating ERK1/2 Signaling Pathway. Front Oncol. 2021;11:628353. doi: 10.3389/fonc.2021.628353. PMID: 33816264; PMCID: PMC8012900.
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