Global protein expression profiling in stem cell factor stimulated human Acute megakaryoblastic leukemia cells identifies CFL1, GSN and CCT8 as prognostic biomarkers for Acute Myeloid Leukemia.
Anand Kuttanparambil Ravi, Gopika Gopan, Sudhakar Arumugam, Aiswarya SethumadhavaniD, Maheswaran ManiiD
Abstract
Abstract Background: The stem cell factor receptor or c-Kit is a type III receptor tyrosine kinase, activated by its ligand Stem cell factor (SCF). Up on activation, c-kit induces signaling pathways that regulates blood cell proliferation, survival, differentiation, and migration. Several studies reported that c-Kit/SCF signaling, contributes to the development and progression of acute myeloid leukemia (AML) in patients. However, the downstream proteins regulated by c-kit activation and their clinical significance in AML remain poorly explored. Methods: Human Acute megakaryoblastic leukemia (Mo7e) cells, were-stimulated with SCF and global protein expression were profiled using two-dimensional gel electrophoresis coupled with MALDI-TOF and LC-MS/MS. Differentially expressed proteins were functionally characterized and validated using patient data from the TCGA-LAML and matched normal data from GTEx, GEO datasets, and quantitative RT-PCR. Their diagnostic and prognostic significance was assessed using ROC, Cox regression, LASSO, Kaplan Meier survival analyses, and a prognostic nomogram model. Results: Proteomic profiling identified 14 differentially expressed proteins in SCF-stimulated Mo7e cells, which are predicted to involved in cytoskeletal organization, protein folding, metabolism, vesicular trafficking, and translational regulation. Transcriptomic analysis of the TCGA-LAML cohort revealed significant dysregulation of CFL1, CCT8, HSP90B1, MDH2, EIF5A, GSN, and TPI1. Integrated ROC, Cox regression, and LASSO analyses identified CFL1, CCT8, and GSN as the most robust prognostic biomarkers associated with poor overall survival in LAML patients. Their expression patterns were validated in independent GEO datasets and by qRT-PCR in SCF stimulated Mo7e cells. Finally, a three-gene nomogram model was developed and validated to predict the overall survival probability of AML patients at 1-, 3-, and 5-year time points. Conclusions: This study identifies CFL1, CCT8, and GSN as key downstream effectors of c-Kit signaling as prognostic biomarkers for AML. These findings provide mechanistic insights into c-Kit-driven leukemogenesis and establish a clinically relevant three-gene signature for AML risk stratification and potential therapeutic targeting.
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