ETV4 plays a role on the primary events during the adenoma-adenocarcinoma progression in colorectal cancer.

作者: Anelisa Ramão , Anelisa Ramão , Omar Feres , Rodrigo Alexandre Panepucci , Jessica Rodrigues Plaça

DOI: 10.1186/S12885-021-07857-X

关键词:

摘要: Colorectal cancer (CRC) is one of the most common cancers worldwide; it fourth leading cause death in world and third Brazil. Mutations APC, DCC, KRAS TP53 genes have been associated with progression sporadic CRC, occurring at defined pathological stages tumor consequently modulating several corresponding signaling pathways. Therefore, identification gene signatures that occur each stage during CRC critical can present an impact on diagnosis prognosis patient. In this study, our main goal was to determine these signatures, by evaluating expression paired colorectal adenoma adenocarcinoma samples identify novel genetic markers association adenoma-adenocarcinoma transition. Ten were subjected microarray analysis. addition, mutations investigated DNA sequencing adenoma, adenocarcinoma, normal tissue, peripheral blood from ten patients. Gene analysis revealed a signature 689 differentially expressed (DEG) (fold-change> 2, p< 0.05), between analyzed. pathway using DEG identified important pathways such as remodeling extracellular matrix epithelial-mesenchymal Among DEG, ETV4 stood out samples, further confirmed set TCGA database. Subsequent vitro siRNA assays against resulted decrease cell proliferation, colony formation migration HT29 SW480 lines. pathogenic mutations, exclusively adenocarcinomas samples. Our study high potential be used biomarkers special emphasis gene, which demonstrated involvement proliferation migration.

参考文章(67)
Chi-Ming Chu, Chung-Tay Yao, Yu-Tien Chang, Hsiu-Ling Chou, Yu-Ching Chou, Kang-Hua Chen, Harn-Jing Terng, Chi-Shuan Huang, Chia-Cheng Lee, Sui-Lun Su, Yao-Chi Liu, Fu-Gong Lin, Thomas Wetter, Chi-Wen Chang, Gene Expression Profiling of Colorectal Tumors and Normal Mucosa by Microarrays Meta-Analysis Using Prediction Analysis of Microarray, Artificial Neural Network, Classification, and Regression Trees Disease Markers. ,vol. 2014, pp. 634123- 634123 ,(2014) , 10.1155/2014/634123
Masayoshi Yamada, Shigeki Sekine, Takahisa Matsuda, Masayuki Yoshida, Hirokazu Taniguchi, Ryoji Kushima, Taku Sakamoto, Takeshi Nakajima, Yutaka Saito, Takayuki Akasu, Dome-type carcinoma of the colon; a rare variant of adenocarcinoma resembling a submucosal tumor: a case report BMC Gastroenterology. ,vol. 12, pp. 21- 21 ,(2012) , 10.1186/1471-230X-12-21
Anthony G Clementz, Allison Rogowski, Kinnari Pandya, Lucio Miele, Clodia Osipo, NOTCH-1 and NOTCH-4 are novel gene targets of PEA3 in breast cancer: novel therapeutic implications Breast Cancer Research. ,vol. 13, pp. 1- 18 ,(2011) , 10.1186/BCR2900
Fumihiro Higashino, Koichi Yoshida, Yukako Fujinaga, Koichi Kamio, Kei Fujinaga, Isolation of a cDNA encoding the adenovirus E1A enhancer binding protein: a new human member of the ets oncogene family Nucleic Acids Research. ,vol. 21, pp. 547- 553 ,(1993) , 10.1093/NAR/21.3.547
Yoav Benjamini, Yosef Hochberg, Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing Journal of the Royal Statistical Society: Series B (Methodological). ,vol. 57, pp. 289- 300 ,(1995) , 10.1111/J.2517-6161.1995.TB02031.X
Mark D Robinson, Davis J McCarthy, Gordon K Smyth, None, edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. ,vol. 26, pp. 139- 140 ,(2010) , 10.1093/BIOINFORMATICS/BTP616
B.M. Bolstad, R.A Irizarry, M. Astrand, T.P. Speed, A comparison of normalization methods for high density oligonucleotide array data based on variance and bias Bioinformatics. ,vol. 19, pp. 185- 193 ,(2003) , 10.1093/BIOINFORMATICS/19.2.185
P. C. Hollenhorst, M. W. Ferris, M. A. Hull, H. Chae, S. Kim, B. J. Graves, Oncogenic ETS proteins mimic activated RAS/MAPK signaling in prostate cells Genes & Development. ,vol. 25, pp. 2147- 2157 ,(2011) , 10.1101/GAD.17546311