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

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.

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Publication Details

Journal
Scientific Reports
Published
2024-10-10
DOI
https://doi.org/10.1038/s41598-024-74806-6
Citations
3
Primary Topic
Cancer Cells and Metastasis
Type
article
Field-Weighted Citation Impact
0.85
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article

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

Aili He, Hongli Chen, Pengyu Zhang, Ying Shen et al.
3 citations
Scientific Reports
Cancer Cells and Metastasis
0.85
article

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

Aili He, Hongli Chen, Pengyu Zhang, Ying Shen, Yachun Jia, Yuandong Feng, Jin Du, Yun Yang
article en
3 citations

Abstract

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.

Scientific ReportsVol. 14(1)
Xi'an Medical University (CN), Second Affiliated Hospital of Xi'an Jiaotong University (CN)
Good health and well-being
Openalex Percentile: Top 22%
Cancer Cells and Metastasis
0.85
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