scPharm: Identifying Pharmacological Subpopulations of Single Cells for Precision Medicine in Cancers
Abstract Intratumour heterogeneity significantly hinders the efficacy of anticancer therapies. Compared with drug perturbation experiments, which yield pharmacological data at the bulk cell level, single‐cell RNA sequencing (scRNA‐seq) technology provides a means to capture molecular heterogeneity a...
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| Format: | Article |
| Language: | English |
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Wiley
2025-01-01
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| Series: | Advanced Science |
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| Online Access: | https://doi.org/10.1002/advs.202412419 |
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| author | Peng Tian Jie Zheng Keying Qiao Yuxiao Fan Yue Xu Tao Wu Shuting Chen Yinuo Zhang Bingyue Zhang Chiara Ambrogio Haiyun Wang |
| author_facet | Peng Tian Jie Zheng Keying Qiao Yuxiao Fan Yue Xu Tao Wu Shuting Chen Yinuo Zhang Bingyue Zhang Chiara Ambrogio Haiyun Wang |
| author_sort | Peng Tian |
| collection | DOAJ |
| description | Abstract Intratumour heterogeneity significantly hinders the efficacy of anticancer therapies. Compared with drug perturbation experiments, which yield pharmacological data at the bulk cell level, single‐cell RNA sequencing (scRNA‐seq) technology provides a means to capture molecular heterogeneity at single‐cell resolution. Here, scPharm is introduced, a computational framework that integrates pharmacological profiles with scRNA‐seq data to identify pharmacological subpopulations of cells within a tumour and prioritize tailored drugs. scPharm uses the normalized enrichment scores (NESs) determined from gene set enrichment analysis to assess the distribution of cell identity genes in drug response‐determined gene lists. Based on the strong correlation between the NES and drug response at single‐cell resolution, scPharm successfully identified the sensitive subpopulations in ER‐positive and HER2‐positive human breast cancer tissues, revealed dynamic changes in the resistant subpopulation of human PC9 cells treated with erlotinib, and expanded its ability to a mouse model. Its superior performance and computational efficiency are confirmed through comparative evaluations with other single‐cell prediction tools. Additionally, scPharm predicted combination drug strategies by gauging compensation or booster effects between drugs and evaluated drug toxicity in healthy cells in the tumour microenvironment. Overall, scPharm provides a novel approach for precision medicine in cancers by revealing therapeutic heterogeneity at single‐cell resolution. |
| format | Article |
| id | doaj-art-da6c6067159c49baa1ae2a8577dfa0e1 |
| institution | Kabale University |
| issn | 2198-3844 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advanced Science |
| spelling | doaj-art-da6c6067159c49baa1ae2a8577dfa0e12025-01-13T15:29:43ZengWileyAdvanced Science2198-38442025-01-01122n/an/a10.1002/advs.202412419scPharm: Identifying Pharmacological Subpopulations of Single Cells for Precision Medicine in CancersPeng Tian0Jie Zheng1Keying Qiao2Yuxiao Fan3Yue Xu4Tao Wu5Shuting Chen6Yinuo Zhang7Bingyue Zhang8Chiara Ambrogio9Haiyun Wang10Research Center for Translational Medicine Shanghai East Hospital School of Life Sciences and Technology Tongji University Shanghai 200092 ChinaResearch Center for Translational Medicine Shanghai East Hospital School of Life Sciences and Technology Tongji University Shanghai 200092 ChinaResearch Center for Translational Medicine Shanghai East Hospital School of Life Sciences and Technology Tongji University Shanghai 200092 ChinaResearch Center for Translational Medicine Shanghai East Hospital School of Life Sciences and Technology Tongji University Shanghai 200092 ChinaResearch Center for Translational Medicine Shanghai East Hospital School of Life Sciences and Technology Tongji University Shanghai 200092 ChinaResearch Center for Translational Medicine Shanghai East Hospital School of Life Sciences and Technology Tongji University Shanghai 200092 ChinaResearch Center for Translational Medicine Shanghai East Hospital School of Life Sciences and Technology Tongji University Shanghai 200092 ChinaResearch Center for Translational Medicine Shanghai East Hospital School of Life Sciences and Technology Tongji University Shanghai 200092 ChinaResearch Center for Translational Medicine Shanghai East Hospital School of Life Sciences and Technology Tongji University Shanghai 200092 ChinaDepartment of Molecular Biotechnology and Health Sciences Molecular Biotechnology Center University of Torino Torino 10126 ItalyResearch Center for Translational Medicine Shanghai East Hospital School of Life Sciences and Technology Tongji University Shanghai 200092 ChinaAbstract Intratumour heterogeneity significantly hinders the efficacy of anticancer therapies. Compared with drug perturbation experiments, which yield pharmacological data at the bulk cell level, single‐cell RNA sequencing (scRNA‐seq) technology provides a means to capture molecular heterogeneity at single‐cell resolution. Here, scPharm is introduced, a computational framework that integrates pharmacological profiles with scRNA‐seq data to identify pharmacological subpopulations of cells within a tumour and prioritize tailored drugs. scPharm uses the normalized enrichment scores (NESs) determined from gene set enrichment analysis to assess the distribution of cell identity genes in drug response‐determined gene lists. Based on the strong correlation between the NES and drug response at single‐cell resolution, scPharm successfully identified the sensitive subpopulations in ER‐positive and HER2‐positive human breast cancer tissues, revealed dynamic changes in the resistant subpopulation of human PC9 cells treated with erlotinib, and expanded its ability to a mouse model. Its superior performance and computational efficiency are confirmed through comparative evaluations with other single‐cell prediction tools. Additionally, scPharm predicted combination drug strategies by gauging compensation or booster effects between drugs and evaluated drug toxicity in healthy cells in the tumour microenvironment. Overall, scPharm provides a novel approach for precision medicine in cancers by revealing therapeutic heterogeneity at single‐cell resolution.https://doi.org/10.1002/advs.202412419intratumour heterogeneitypharmacological subpopulationsprecision medicinescPharm |
| spellingShingle | Peng Tian Jie Zheng Keying Qiao Yuxiao Fan Yue Xu Tao Wu Shuting Chen Yinuo Zhang Bingyue Zhang Chiara Ambrogio Haiyun Wang scPharm: Identifying Pharmacological Subpopulations of Single Cells for Precision Medicine in Cancers Advanced Science intratumour heterogeneity pharmacological subpopulations precision medicine scPharm |
| title | scPharm: Identifying Pharmacological Subpopulations of Single Cells for Precision Medicine in Cancers |
| title_full | scPharm: Identifying Pharmacological Subpopulations of Single Cells for Precision Medicine in Cancers |
| title_fullStr | scPharm: Identifying Pharmacological Subpopulations of Single Cells for Precision Medicine in Cancers |
| title_full_unstemmed | scPharm: Identifying Pharmacological Subpopulations of Single Cells for Precision Medicine in Cancers |
| title_short | scPharm: Identifying Pharmacological Subpopulations of Single Cells for Precision Medicine in Cancers |
| title_sort | scpharm identifying pharmacological subpopulations of single cells for precision medicine in cancers |
| topic | intratumour heterogeneity pharmacological subpopulations precision medicine scPharm |
| url | https://doi.org/10.1002/advs.202412419 |
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