Caixia Han1, Shujiao He1, Ruiqi Wang2, Xuefeng Gao1, Hong Wang2, Jingqiao Qiao1, Xiangyu Meng1, Yonghui Li3, Li Yu4. 1. Department of Hematology-Oncology, International Cancer Center, Shenzhen University General Hospital, Shenzhen University Health Science Center, 1098 Xueyuan Ave, Shenzhen, 518060, China. 2. Medicine School, Nankai University, 94 Weijin Road, Tianjin, 300071, China. 3. Department of Hematology-Oncology, International Cancer Center, Shenzhen University General Hospital, Shenzhen University Health Science Center, 1098 Xueyuan Ave, Shenzhen, 518060, China. Yonghuililab@163.com. 4. Department of Hematology-Oncology, International Cancer Center, Shenzhen University General Hospital, Shenzhen University Health Science Center, 1098 Xueyuan Ave, Shenzhen, 518060, China. liyu301@vip.163.com.
Abstract
BACKGROUND: Rho GTPase activating protein 9 (ARHGAP9) is expressed in various types of cancers and can inactivate Rho GTPases that mainly regulate cytoskeletal dynamics. However, the exact role of ARHGAP9 in acute myeloid leukemia (AML) has yet to be clarified. METHODS: We compared the transcriptional expression, prognosis, differentially expressed genes, functional enrichment, and hub genes in AML patients on the basis of the data published in the following databases: UALCAN, GEPIA, Gene Expression Omnibus, the Human Protein Atlas, Cancer Cell Line Encyclopedia, LinkedOmics, Metascape, and String. Data from the Cancer Genome Atlas database was used to evaluate the correlations between ARHGAP9 expression and various clinicopathological parameters, as well as the significantly different genes associated with ARHGAP9 expression. RESULTS: We found that ARHGAP9 expression was higher in the tissues and cell lines extracted from patients with AML than corresponding control tissues and other cancer types. ARHGAP9 overexpression was associated with decreased overall survival (OS) in AML. Compared with the ARHGAP9low group, the ARHGAP9high group, which received only chemotherapy, showed significantly worse OS and event-free survival (EFS); however, no significant difference was observed after treatment with autologous or allogeneic hematopoietic stem cell transplantation (auto/allo-HSCT). The ARHGAP9high patients undergoing auto/allo-HSCT also had a significantly better prognosis with respect to OS and EFS than those receiving only chemotherapy. Most overlapping genes of the significantly different genes and co-expression genes exhibited enriched immune functions, suggesting the immune regulation potential of ARHGAP9 in AML. A total of 32 hub genes were identified from the differentially expressed genes, within which the KIF20A had a significant prognostic value for AML. CONCLUSIONS: ARHGAP9 overexpression was associated with poor OS in AML patients and can be used as a prognostic biomarker. AML patients with ARHGAP9 overexpression can benefit from auto/allo-HSCT rather than chemotherapy.
BACKGROUND: Rho GTPase activating protein 9 (ARHGAP9) is expressed in various types of cancers and can inactivate Rho GTPases that mainly regulate cytoskeletal dynamics. However, the exact role of ARHGAP9 in acute myeloid leukemia (AML) has yet to be clarified. METHODS: We compared the transcriptional expression, prognosis, differentially expressed genes, functional enrichment, and hub genes in AML patients on the basis of the data published in the following databases: UALCAN, GEPIA, Gene Expression Omnibus, the Human Protein Atlas, Cancer Cell Line Encyclopedia, LinkedOmics, Metascape, and String. Data from the Cancer Genome Atlas database was used to evaluate the correlations between ARHGAP9 expression and various clinicopathological parameters, as well as the significantly different genes associated with ARHGAP9 expression. RESULTS: We found that ARHGAP9 expression was higher in the tissues and cell lines extracted from patients with AML than corresponding control tissues and other cancer types. ARHGAP9 overexpression was associated with decreased overall survival (OS) in AML. Compared with the ARHGAP9low group, the ARHGAP9high group, which received only chemotherapy, showed significantly worse OS and event-free survival (EFS); however, no significant difference was observed after treatment with autologous or allogeneic hematopoietic stem cell transplantation (auto/allo-HSCT). The ARHGAP9high patients undergoing auto/allo-HSCT also had a significantly better prognosis with respect to OS and EFS than those receiving only chemotherapy. Most overlapping genes of the significantly different genes and co-expression genes exhibited enriched immune functions, suggesting the immune regulation potential of ARHGAP9 in AML. A total of 32 hub genes were identified from the differentially expressed genes, within which the KIF20A had a significant prognostic value for AML. CONCLUSIONS: ARHGAP9 overexpression was associated with poor OS in AML patients and can be used as a prognostic biomarker. AML patients with ARHGAP9 overexpression can benefit from auto/allo-HSCT rather than chemotherapy.
Authors: F C Yang; S J Atkinson; Y Gu; J B Borneo; A W Roberts; Y Zheng; J Pennington; D A Williams Journal: Proc Natl Acad Sci U S A Date: 2001-04-24 Impact factor: 11.205
Authors: Leo D Wang; Scott B Ficarro; John N Hutchinson; Roland Csepanyi-Komi; Phi T Nguyen; Eva Wisniewski; Jessica Sullivan; Oliver Hofmann; Erzsebet Ligeti; Jarrod A Marto; Amy J Wagers Journal: Blood Date: 2016-06-30 Impact factor: 22.113
Authors: Jordi Barretina; Giordano Caponigro; Nicolas Stransky; Kavitha Venkatesan; Adam A Margolin; Sungjoon Kim; Christopher J Wilson; Joseph Lehár; Gregory V Kryukov; Dmitriy Sonkin; Anupama Reddy; Manway Liu; Lauren Murray; Michael F Berger; John E Monahan; Paula Morais; Jodi Meltzer; Adam Korejwa; Judit Jané-Valbuena; Felipa A Mapa; Joseph Thibault; Eva Bric-Furlong; Pichai Raman; Aaron Shipway; Ingo H Engels; Jill Cheng; Guoying K Yu; Jianjun Yu; Peter Aspesi; Melanie de Silva; Kalpana Jagtap; Michael D Jones; Li Wang; Charles Hatton; Emanuele Palescandolo; Supriya Gupta; Scott Mahan; Carrie Sougnez; Robert C Onofrio; Ted Liefeld; Laura MacConaill; Wendy Winckler; Michael Reich; Nanxin Li; Jill P Mesirov; Stacey B Gabriel; Gad Getz; Kristin Ardlie; Vivien Chan; Vic E Myer; Barbara L Weber; Jeff Porter; Markus Warmuth; Peter Finan; Jennifer L Harris; Matthew Meyerson; Todd R Golub; Michael P Morrissey; William R Sellers; Robert Schlegel; Levi A Garraway Journal: Nature Date: 2012-03-28 Impact factor: 49.962
Authors: Yingyao Zhou; Bin Zhou; Lars Pache; Max Chang; Alireza Hadj Khodabakhshi; Olga Tanaseichuk; Christopher Benner; Sumit K Chanda Journal: Nat Commun Date: 2019-04-03 Impact factor: 14.919
Authors: Boon K Ang; Chun Y Lim; Sharon S Koh; Neelamegam Sivakumar; Shahrizan Taib; Kim B Lim; Sohail Ahmed; Guna Rajagopal; Siew H Ong Journal: J Mol Signal Date: 2007-02-06
Authors: Juliana Xavier-Ferrucio; Lauremília Ricon; Karla Vieira; Ana Leda Longhini; Mariana Lazarini; Carolina Louzão Bigarella; Gilberto Franchi; Diane S Krause; Sara T O Saad Journal: Stem Cell Res Date: 2017-11-23 Impact factor: 2.020
Authors: Shahinda S R Alsayed; Amreena Suri; Anders W Bailey; Samuel Lane; Eryn L Werry; Chiang-Ching Huang; Li-Fang Yu; Michael Kassiou; Simone Treiger Sredni; Hendra Gunosewoyo Journal: RSC Med Chem Date: 2021-08-23