NDLI: Mutation spectrum, expression profiling, and prognosis evaluation of Fanconi anemia signaling pathway genes for 4259 patients with myelodysplastic syndromes or acute myeloid leukemia

Content Provider	Springer Nature : BioMed Central
Author	Chang, Lixian Zhang, Li Zhao, Beibei Cheng, Xuelian Wan, Yang Zhang, Ranran Yuan, Weiping Gao, Xingjie Zhu, Xiaofan
Abstract	Background Individuals diagnosed with Fanconi anemia (FA), an uncommon disorder characterized by chromosomal instability affecting the FA signaling pathway, exhibit heightened vulnerability to the onset of myelodysplastic syndromes (MDS) or acute myeloid leukemia (AML). Methods Herein, we employed diverse bioinformatics and statistical analyses to investigate the potential associations between the expression/mutation patterns of FA pathway genes and MDS/AML. Results The study included 4295 samples, comprising 3235 AML and 1024 MDS from our and nine other online cohorts. We investigated the distinct proportion of race, age, French-American-British, and gender factors. Compared to the FA wild-type group, we observed a decrease in the expression of FNACD2, FANCI, and RAD51C in the FA mutation group. The FA mutation group exhibited a more favorable clinical overall survival prognosis. We developed a random forest classifier and a decision tree based on FA gene expression for cytogenetic risk assessment. Furthermore, we created an FA-related Nomogram to predict survival rates in AML patients. Conclusions This investigation facilitates a deeper understanding of the functional links between FA and MDS/AML.
Related Links	https://bmcmedgenomics.biomedcentral.com/counter/pdf/10.1186/s12920-023-01730-5.pdf
Ending Page	15
Page Count	15
Starting Page	1
File Format	HTM / HTML
ISSN	17558794
DOI	10.1186/s12920-023-01730-5
Journal	BMC Medical Genomics
Issue Number	1
Volume Number	16
Language	English
Publisher	BioMed Central
Publisher Date	2023-11-16
Access Restriction	Open
Subject Keyword	Human Genetics Microarrays Gene Expression Fanconi anemia pathway AML MDS Expression Mutation
Content Type	Text
Resource Type	Article
Subject	Genetics (clinical) Genetics
Journal Impact Factor	2.1/2023
5-Year Journal Impact Factor	2.5/2023

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