机构:[1]Department of Clinical Laboratory, First Affiliated Hospital of Kunming Medical University, Kunming, China昆明医科大学附属第一医院[2]Yunnan Key Laboratory of Laboratory Medicine, Kunming, China[3]Yunnan Innovation Team of Clinical Laboratory and Diagnosis, Kunming, China[4]Department of Hematology, First Affiliated Hospital of Kunming Medical University, Hematology Research Center of Yunnan Province, Kunming, China内科科室血液内科昆明医科大学附属第一医院
Background: Myelodysplastic syndrome (MDS) is a group of hematological malignancies that may progress to acute myeloid leukemia (AML). Bioinformatics-based analysis of high-frequency mutation genes in MDS-related patients is still relatively rare, so we conducted our research to explore whether high-frequency mutation genes in MDS-related patients can play a reference role in clinical guidance and prognosis. Methods: Next generation sequencing (NGS) technology was used to detect 32 mutations in 64 MDSrelated patients. We classified the patients' genes and analyzed them by Gene Ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, protein-protein interaction (PPI) analysis, and then calculated the gene survival curve of high-frequency mutations. Results: We discovered 32 mutant genes such as ASXL1, DNMT3A, KRAS, NRAS, TP53, SF3B1, and SRSF2. The overall survival (OS) of these genes decreased significantly after DNMT3A, ASXL1, RUNX1, and U2AF1 occurred mutation. These genes play a significant role in biological processes, not only in MDS but also in the occurrence and development of other diseases. Through retrospective analysis, genes associated with MDS-related diseases were identified, and their effects on the disease were predicted. Conclusions: Thirty-two mutant genes were determined in MDS and when mutations occur in DNMT3A, ASXL1, RUNX1, and U2AF1, their survival time decreases significantly. This results providing a theoretical basis for clinical and scientific research and broadening the scope of research on MDS.
基金:
This work was supported by Yunnan Joint Special
Fund Subsidized Projects [2017FE468(-035)], YunnanHealth Science and Technology Project (2018NS0129),
and Scientific Research Fund Project of Yunnan Provincial
Department of Education (2020J0172).
第一作者机构:[1]Department of Clinical Laboratory, First Affiliated Hospital of Kunming Medical University, Kunming, China[2]Yunnan Key Laboratory of Laboratory Medicine, Kunming, China[3]Yunnan Innovation Team of Clinical Laboratory and Diagnosis, Kunming, China
共同第一作者:
通讯作者:
通讯机构:[4]Department of Hematology, First Affiliated Hospital of Kunming Medical University, Hematology Research Center of Yunnan Province, Kunming, China[*1]Department of Hematology, First Affiliated Hospital of Kunming Medical University, Hematology Research Center of Yunnan Province, 295 Xichang Road, Kunming 650032, China
推荐引用方式(GB/T 7714):
Wu Kun,Nie Bo,Li Liyin,et al.Bioinformatics analysis of high frequency mutations in myelodysplastic syndrome-related patients[J].ANNALS OF TRANSLATIONAL MEDICINE.2021,9(19):doi:10.21037/atm-21-4094.
APA:
Wu, Kun,Nie, Bo,Li, Liyin,Yang, Xin,Yang, Jinrong...&Zeng, Yun.(2021).Bioinformatics analysis of high frequency mutations in myelodysplastic syndrome-related patients.ANNALS OF TRANSLATIONAL MEDICINE,9,(19)
MLA:
Wu, Kun,et al."Bioinformatics analysis of high frequency mutations in myelodysplastic syndrome-related patients".ANNALS OF TRANSLATIONAL MEDICINE 9..19(2021)