Dynamine 3 as a diagnostic and prognostic biomarker in pancreatic cancer: Implications for early detection and targeted therapy

被引:0
作者
Yay, Fatih [1 ]
Yildirim, Hasan cagri [2 ]
Kus, Fatih [3 ]
Yalcin, Suayib [3 ]
机构
[1] Nigde Omer Halisdemir Univ Training & Res Hosp, Clin Biochem Lab, Nigde, Turkiye
[2] Nigde Omer Halisdemir Univ Training & Res Hosp, Dept Med Oncol, Nigde, Turkiye
[3] Hacettepe Univ, Fac Med, Deparment Med Oncol, Ankara, Turkiye
关键词
Pancreatic adenocarcinoma; dynamine; 3; bioinformatic; miRNA; immune infiltration; SET ENRICHMENT ANALYSIS; WEB SERVER; EXPRESSION; CARCINOMA; GROWTH; TISSUE; GENES; CELLS; DNM3;
D O I
10.1080/1354750X.2025.2458104
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
BackgroundDynamins are defined as a group of molecules with GTPase activity. Among them, DNM3 has gained recognition in oncology for its tumor suppressor role. Based on this, the aim of this study is to investigate the effects of the DNM3 gene in patients diagnosed with pancreatic cancer using bioinformatics databases.Materials and MethodsFor differential gene expression analysis, TCGA TARGET GTEx study on the UCSC Xena and GEO datasets were utilized; for the analysis of changes in gene expression according to clinical and pathological characteristics, UALCAN was employed; for Overall Survival (OS) analysis, Kaplan-Meier Plotter was used; for gene alteration analysis, cBioPortal was utilized; for immune cell infiltration analysis, Tumor Immune Estimation Resource (TIMER) and TIMER2.0 were employed; for enrichment analyses Enrichr was used; for Gene Set Correlation Enrichment Analysis Gscore was used on GSE15471; for essentiality of DNM3 gene in pancratic cancer cell lines DepMap was used; and for the detection of miRNAs, miRDB was utilized; ENCORI was used for gene-miRNA correlation and miRNA prognosis analyses.ResultsIn the pancreatic adenocarcinoma (PAAD) cohort, DNM3 gene expression was higher in tumor samples, and there was no significant difference in expression among cancer stages. High levels of DNM3 gene expression were associated with longer OS in PAAD. A weak positive correlation was observed between DNM3 gene expression and B-Cell and CD4+ T Cell infiltrations, while a moderate positive correlation was found with CD8+ T Cell, Macrophage, Neutrophil, and Dendritic Cell infiltrations in TIMER. NK cell by QUANTISEQ, CD 4+ T Cell by TIMER, T cell regulatory (Tregs) by CIBERSORT-ABS infiltrations were positively associated with DNM3 gene expression and decreased risk in prognosis. Common lymphoid progenitor by XCELL and MDSC by TIDE infiltrations were negatively associated with DNM3 gene expression and increased risk of prognosis. Macrophage M1 by QUANTISEQ was positively associated with DNM3 gene expression and increased risk in prognosis. DNM3 gene appears to be associated with various pathways related to inflammation and the immune system. Amplification of the DNM3 gene was detected in 5 out of 175 patients. Enrichment was observed in pathways such as bacterial invasion of epithelial cells, endocytosis, endocrine and other factor-regulated calcium reabsorption, synaptic vesicle cycle, and phospholipase D signaling pathway. According to Gscore, DNM3 gene was associated with Fc epsilon RI signaling pathway, HALLMARK MTORC1 SIGNALING, HALLMARK EPITHELIAL MESENCHYMAL TRANSITION gene sets. According to ENCORI, DNM3 gene was negatively correlated with hsa-miR-203a-3p and increased expression of this miRNA was associated with adverse prognosis in PAAD.ConclusionsThe DNM3 gene may play a tumor suppressor role in pancreatic cancer, similar to its role in other malignancies. The contribution of immune cells may also be significant in this effect. However, in vitro studies are needed to elucidate the mechanisms triggered in pancreatic cancer.
引用
收藏
页码:147 / 166
页数:20
相关论文
共 89 条
[1]   The Gene Ontology knowledgebase in 2023 [J].
Aleksander, Suzi A. ;
Balhoff, James ;
Carbon, Seth ;
Cherry, J. Michael ;
Drabkin, Harold J. ;
Ebert, Dustin ;
Feuermann, Marc ;
Gaudet, Pascale ;
Harris, Nomi L. ;
Hill, David P. ;
Lee, Raymond ;
Mi, Huaiyu ;
Moxon, Sierra ;
Mungall, Christopher J. ;
Muruganugan, Anushya ;
Mushayahama, Tremayne ;
Sternberg, Paul W. ;
Thomas, Paul D. ;
Van Auken, Kimberly ;
Ramsey, Jolene ;
Siegele, Deborah A. ;
Chisholm, Rex L. ;
Fey, Petra ;
Aspromonte, Maria Cristina ;
Nugnes, Maria Victoria ;
Quaglia, Federica ;
Tosatto, Silvio ;
Giglio, Michelle ;
Nadendla, Suvarna ;
Antonazzo, Giulia ;
Attrill, Helen ;
dos Santos, Gil ;
Marygold, Steven ;
Strelets, Victor ;
Tabone, Christopher J. ;
Thurmond, Jim ;
Zhou, Pinglei ;
Ahmed, Saadullah H. ;
Asanitthong, Praoparn ;
Luna Buitrago, Diana ;
Erdol, Meltem N. ;
Gage, Matthew C. ;
Ali Kadhum, Mohamed ;
Li, Kan Yan Chloe ;
Long, Miao ;
Michalak, Aleksandra ;
Pesala, Angeline ;
Pritazahra, Armalya ;
Saverimuttu, Shirin C. C. ;
Su, Renzhi .
GENETICS, 2023, 224 (01)
[2]   xCell: digitally portraying the tissue cellular heterogeneity landscape [J].
Aran, Dvir ;
Hu, Zicheng ;
Butte, Atul J. .
GENOME BIOLOGY, 2017, 18
[3]   Gene Ontology: tool for the unification of biology [J].
Ashburner, M ;
Ball, CA ;
Blake, JA ;
Botstein, D ;
Butler, H ;
Cherry, JM ;
Davis, AP ;
Dolinski, K ;
Dwight, SS ;
Eppig, JT ;
Harris, MA ;
Hill, DP ;
Issel-Tarver, L ;
Kasarskis, A ;
Lewis, S ;
Matese, JC ;
Richardson, JE ;
Ringwald, M ;
Rubin, GM ;
Sherlock, G .
NATURE GENETICS, 2000, 25 (01) :25-29
[4]  
Badea L, 2008, HEPATO-GASTROENTEROL, V55, P2016
[5]   Estimating the population abundance of tissue-infiltrating immune and stromal cell populations using gene expression [J].
Becht, Etienne ;
Giraldo, Nicolas A. ;
Lacroix, Laetitia ;
Buttard, Benedicte ;
Elarouci, Nabila ;
Petitprez, Florent ;
Selves, Janick ;
Laurent-Puig, Pierre ;
Sautes-Fridman, Catherine ;
Fridman, Wolf H. ;
de Reynies, Aurelien .
GENOME BIOLOGY, 2016, 17
[6]   Assessing the significance of chromosomal aberrations in cancer: Methodology and application to glioma [J].
Beroukhim, Rameen ;
Getz, Gad ;
Nghiemphu, Leia ;
Barretina, Jordi ;
Hsueh, Teli ;
Linhart, David ;
Vivanco, Igor ;
Lee, Jeffrey C. ;
Huang, Julie H. ;
Alexander, Sethu ;
Du, Jinyan ;
Kau, Tweeny ;
Thomas, Roman K. ;
Shah, Kinial ;
Soto, Horacio ;
Perner, Sven ;
Prensner, John ;
Debiasi, Ralph M. ;
Demichelis, Francesca ;
Hatton, Charlie ;
Rubin, Mark A. ;
Garraway, Levi A. ;
Nelson, Stan F. ;
Liau, Linda ;
Mischel, Paul S. ;
Cloughesy, Tim F. ;
Meyerson, Matthew ;
Golub, Todd A. ;
Lander, Eric S. ;
Mellinghoff, Ingo K. ;
Sellers, William R. .
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2007, 104 (50) :20007-20012
[7]   Transcriptomic analysis of pancreatic adenocarcinoma specimens obtained from Black and White patients [J].
Biel, Thomas G. G. ;
Petrovskaya, Svetlana ;
Mascia, Francesca ;
Ju, Tongzhong ;
Fashoyin-Aje, Lola ;
Herremans, Kelly M. M. ;
Riner, Andrea N. N. ;
Underwood, Patrick W. W. ;
Gerber, Michael H. H. ;
Donoghue, Martha ;
Trevino, Jose G. G. ;
Rao, V. Ashutosh .
PLOS ONE, 2023, 18 (02)
[8]   UALCAN: An update to the integrated cancer data analysis platform [J].
Chandrashekar, Darshan Shimoga ;
Karthikeyan, Santhosh Kumar ;
Korla, Praveen Kumar ;
Patel, Henalben ;
Shovon, Ahmedur Rahman ;
Athar, Mohammad ;
Netto, George J. ;
Qin, Zhaohui S. ;
Kumar, Sidharth ;
Manne, Upender ;
Creighton, Chad J. ;
Varambally, Sooryanarayana .
NEOPLASIA, 2022, 25 :18-27
[9]   Gene set correlation enrichment analysis for interpreting and annotating gene expression profiles<mode/> [J].
Chang, Lan-Yun ;
Lee, Meng-Zhan ;
Wu, Yujia ;
Lee, Wen-Kai ;
Ma, Chia-Liang ;
Chang, Jun-Mao ;
Chen, Ciao-Wen ;
Huang, Tzu-Chun ;
Lee, Chia-Hwa ;
Lee, Jih-Chin ;
Tseng, Yu-Yao ;
Lin, Chun-Yu .
NUCLEIC ACIDS RESEARCH, 2024, 52 (03) :E17
[10]   Enrichr: interactive and collaborative HTML']HTML5 gene list enrichment analysis tool [J].
Chen, Edward Y. ;
Tan, Christopher M. ;
Kou, Yan ;
Duan, Qiaonan ;
Wang, Zichen ;
Meirelles, Gabriela Vaz ;
Clark, Neil R. ;
Ma'ayan, Avi .
BMC BIOINFORMATICS, 2013, 14