Single cell RNA sequencing improves the next generation of approaches to AML treatment: challenges and perspectives
Abstract Acute myeloid leukemia (AML) is caused by altered maturation and differentiation of myeloid blasts, as well as transcriptional/epigenetic alterations, all leading to excessive proliferation of malignant blood cells in the bone marrow. Tumor heterogeneity due to the acquisition of new somati...
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BMC
2025-01-01
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| Series: | Molecular Medicine |
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| Online Access: | https://doi.org/10.1186/s10020-025-01085-w |
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| author | Zahra Khosroabadi Samaneh Azaryar Hassan Dianat-Moghadam Zohreh Amoozgar Mohammadreza Sharifi |
| author_facet | Zahra Khosroabadi Samaneh Azaryar Hassan Dianat-Moghadam Zohreh Amoozgar Mohammadreza Sharifi |
| author_sort | Zahra Khosroabadi |
| collection | DOAJ |
| description | Abstract Acute myeloid leukemia (AML) is caused by altered maturation and differentiation of myeloid blasts, as well as transcriptional/epigenetic alterations, all leading to excessive proliferation of malignant blood cells in the bone marrow. Tumor heterogeneity due to the acquisition of new somatic alterations leads to a high rate of resistance to current therapies or reduces the efficacy of hematopoietic stem cell transplantation (HSCT), thus increasing the risk of relapse and mortality. Single-cell RNA sequencing (scRNA-seq) will enable the classification of AML and guide treatment approaches by profiling patients with different facets of the same disease, stratifying risk, and identifying new potential therapeutic targets at the time of diagnosis or after treatment. ScRNA-seq allows the identification of quiescent stem-like cells, and leukemia stem cells responsible for resistance to therapeutic approaches and relapse after treatment. This method also introduces the factors and mechanisms that enhance the efficacy of the HSCT process. Generated data of the transcriptional profile of the AML could even allow the development of cancer vaccines and CAR T-cell therapies while saving valuable time and alleviating dangerous side effects of chemotherapy and HSCT in vivo. However, scRNA-seq applications face various challenges such as a large amount of data for high-dimensional analysis, technical noise, batch effects, and finding small biological patterns, which could be improved in combination with artificial intelligence models. |
| format | Article |
| id | doaj-art-b4fbe941b1034e7381528b2a294ca5e5 |
| institution | Kabale University |
| issn | 1528-3658 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | BMC |
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| series | Molecular Medicine |
| spelling | doaj-art-b4fbe941b1034e7381528b2a294ca5e52025-02-02T12:29:25ZengBMCMolecular Medicine1528-36582025-01-0131112610.1186/s10020-025-01085-wSingle cell RNA sequencing improves the next generation of approaches to AML treatment: challenges and perspectivesZahra Khosroabadi0Samaneh Azaryar1Hassan Dianat-Moghadam2Zohreh Amoozgar3Mohammadreza Sharifi4Department of Genetics and Molecular Biology, School of Medicine, Isfahan University of Medical SciencesDepartment of Genetics and Molecular Biology, School of Medicine, Isfahan University of Medical SciencesDepartment of Genetics and Molecular Biology, School of Medicine, Isfahan University of Medical SciencesEdwin L. Steele Laboratories for Tumor Biology, Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical SchoolDepartment of Genetics and Molecular Biology, School of Medicine, Isfahan University of Medical SciencesAbstract Acute myeloid leukemia (AML) is caused by altered maturation and differentiation of myeloid blasts, as well as transcriptional/epigenetic alterations, all leading to excessive proliferation of malignant blood cells in the bone marrow. Tumor heterogeneity due to the acquisition of new somatic alterations leads to a high rate of resistance to current therapies or reduces the efficacy of hematopoietic stem cell transplantation (HSCT), thus increasing the risk of relapse and mortality. Single-cell RNA sequencing (scRNA-seq) will enable the classification of AML and guide treatment approaches by profiling patients with different facets of the same disease, stratifying risk, and identifying new potential therapeutic targets at the time of diagnosis or after treatment. ScRNA-seq allows the identification of quiescent stem-like cells, and leukemia stem cells responsible for resistance to therapeutic approaches and relapse after treatment. This method also introduces the factors and mechanisms that enhance the efficacy of the HSCT process. Generated data of the transcriptional profile of the AML could even allow the development of cancer vaccines and CAR T-cell therapies while saving valuable time and alleviating dangerous side effects of chemotherapy and HSCT in vivo. However, scRNA-seq applications face various challenges such as a large amount of data for high-dimensional analysis, technical noise, batch effects, and finding small biological patterns, which could be improved in combination with artificial intelligence models.https://doi.org/10.1186/s10020-025-01085-wAI modelAMLDrug resistanceSingle cell RNA sequencingTumor heterogeneity |
| spellingShingle | Zahra Khosroabadi Samaneh Azaryar Hassan Dianat-Moghadam Zohreh Amoozgar Mohammadreza Sharifi Single cell RNA sequencing improves the next generation of approaches to AML treatment: challenges and perspectives Molecular Medicine AI model AML Drug resistance Single cell RNA sequencing Tumor heterogeneity |
| title | Single cell RNA sequencing improves the next generation of approaches to AML treatment: challenges and perspectives |
| title_full | Single cell RNA sequencing improves the next generation of approaches to AML treatment: challenges and perspectives |
| title_fullStr | Single cell RNA sequencing improves the next generation of approaches to AML treatment: challenges and perspectives |
| title_full_unstemmed | Single cell RNA sequencing improves the next generation of approaches to AML treatment: challenges and perspectives |
| title_short | Single cell RNA sequencing improves the next generation of approaches to AML treatment: challenges and perspectives |
| title_sort | single cell rna sequencing improves the next generation of approaches to aml treatment challenges and perspectives |
| topic | AI model AML Drug resistance Single cell RNA sequencing Tumor heterogeneity |
| url | https://doi.org/10.1186/s10020-025-01085-w |
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