Huy Hoang Dang, Hoang Dang Khoa Ta, Truc T. T. Nguyen, Gangga Anuraga, Chih-Yang Wang, Kuen-Haur Lee, Nguyen Quoc Khanh Le
As lung cancer remains the leading cause of cancer deaths globally, characterizing the tumor molecular profiles is crucial to tailoring treatments for individuals at advanced stages. Cancer cells exhibit strong dependence on iron for their proliferation, and several iron-regulatory proteins have been proposed as either oncogenes or tumor suppressive genes. This study aims to evaluate the prospective therapeutic and prognostic values of the sideroflexin (SFXN) gene family, whose functions involve mitochondrial iron metabolism, in lung adenocarcinoma (LUAD). Differential expression analysis using TIMER and UALCAN tools was first employed to compare SFXNs expression levels between normal and LUAD tissues. Next, SFXNs’ prognostic values, biological significance, and potential as immunotherapy candidates were examined from GEPIA, cBioPortal, MetaCore, Cytoscape, and TIMER databases. It was found that all members of SFXN family, except SFXN3, were differentially expressed in LUAD compared to normal samples and within different stages of LUAD. Survival analysis then revealed SFXN1 to be related to worse overall survival outcome in patients with LUAD. Furthermore, several correlations between expression of SFXN1 and immune infiltration cells were discovered. To conclude, our study provides evidence of SFXN family gene’s relevance to the prognosis and immunotherapeutic targets of LUAD. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.
International Ph.D. Program for Cell Therapy and Regeneration Medicine, College of Medicine, Taipei Medical University, Taipei, 11031, Taiwan; Ph.D. Program for Cancer Molecular Biology and Drug Discovery, College of Medical Science and Technology, Taipei Medical University and Academia Sinica, Taipei, 11031, Taiwan; Graduate Institute of Cancer Biology and Drug Discovery, College of Medical Science and Technology, Taipei Medical University, Taipei, 11031, Taiwan; Translational Medicine Division, Graduate Institute of Biomedical Informatics, Taipei Medical University, Taipei, 110, Taiwan; Memory and Dementia Unit, Hospital 30-4, Ho Chi Minh City, 70000, Viet Nam; Department of Statistics, Faculty of Science and Technology, Universitas PGRI Adi Buana, East Java, Surabaya, 60234, Indonesia; Cancer Center, Wan Fang Hospital, Taipei Medical University, Taipei, 11031, Taiwan; Professional Master Program in Artificial Intelligence in Medicine, College of Medicine, Taipei Medical University, Taipei, 106, Taiwan; Research Center for Artificial Intelligence in Medicine, Taipei Medical University, Taipei, 106, Taiwan; Translational Imaging Research Center, Taipei Medical University Hospital, Taipei, 110, Taiwan
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