Characterization of stem cell landscape and assessing the stemness degree to aid clinical therapeutics in hematologic malignancies.

Autor: Feng YD; Department of Hematology, The Second Affiliated Hospital of Xi'an Jiaotong University, 157 West 5Th Road, Xi'an, 710004, China., Du J; Department of Stomatology, The Third Affiliated Hospital of Xi'an Medical University, 277 West Youyi Road, Xi'an, 710068, China., Chen HL; Department of Hematology, The Second Affiliated Hospital of Xi'an Jiaotong University, 157 West 5Th Road, Xi'an, 710004, China., Shen Y; Department of Hematology, The Second Affiliated Hospital of Xi'an Jiaotong University, 157 West 5Th Road, Xi'an, 710004, China., Jia YC; Department of Hematology, The Second Affiliated Hospital of Xi'an Jiaotong University, 157 West 5Th Road, Xi'an, 710004, China., Zhang PY; Department of Hematology, The Second Affiliated Hospital of Xi'an Jiaotong University, 157 West 5Th Road, Xi'an, 710004, China., He A; Department of Hematology, The Second Affiliated Hospital of Xi'an Jiaotong University, 157 West 5Th Road, Xi'an, 710004, China., Yang Y; Department of Hematology, The Second Affiliated Hospital of Xi'an Jiaotong University, 157 West 5Th Road, Xi'an, 710004, China. yangyun108@mail.xjtu.edu.cn.
Jazyk: angličtina
Zdroj: Scientific reports [Sci Rep] 2024 Oct 10; Vol. 14 (1), pp. 23743. Date of Electronic Publication: 2024 Oct 10.
DOI: 10.1038/s41598-024-74806-6
Abstrakt: Hematological malignancies are a group of cancers that affect the blood, bone marrow, and lymphatic system. Cancer stem cells (CSCs) are believed to be responsible for the initiation, progression, and relapse of hematological malignancies. However, identifying and targeting CSCs presents many challenges. We aimed to develop a stemness index (HSCsi) to identify and guide the therapy targeting CSCs in hematological malignancies. We developed a novel one-class logistic regression (OCLR) algorithm to identify transcriptomic feature sets related to stemness in hematologic malignancies. We used the HSCsi to measure the stemness degree of leukemia stem cells (LSCs) and correlate it with clinical outcomes.We analyze the correlation of HSCsi with genes and pathways involved in drug resistance and immune microenvironment of acute myeloid leukemia (AML). HSCsi revealed stemness-related biological mechanisms in hematologic malignancies and effectively identify LSCs. The index also predicted survival and relapse rates of various hematologic malignancies. We also identified potential drugs and interventions targeting cancer stem cells (CSCs) of hematologic malignancies by the index. Moreover, we found a correlation between stemness and bone marrow immune microenvironment in AML. Our study provides a novel method and tool to assess the stemness degree of hematologic malignancies and its implications for clinical outcomes and therapeutic strategies. Our HSC stemness index can facilitate the precise stratification of hematologic malignancies, suggest possible targeted and immunotherapy options, and guide the selection of patients.
(© 2024. The Author(s).)
Databáze: MEDLINE
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