Leveraging Single-Cell Multi-Omics to Decode Tumor Microenvironment Diversity and Therapeutic Resistance DOI Creative Commons
Hussein Sabit, Borros Arneth, Timothy M. Pawlik

и другие.

Pharmaceuticals, Год журнала: 2025, Номер 18(1), С. 75 - 75

Опубликована: Янв. 10, 2025

Recent developments in single-cell multi-omics technologies have provided the ability to identify diverse cell types and decipher key components of tumor microenvironment (TME), leading important advancements toward a much deeper understanding how heterogeneity contributes cancer progression therapeutic resistance. These are able integrate data from molecular genomic, transcriptomic, proteomics, metabolomics studies cells at resolution scale that give rise full cellular complexity TME. Understanding complex sometimes reciprocal relationships among cells, CAFs, immune ECs has led novel insights into their immense functions, which can consequences on behavior. In-depth uncovered evasion mechanisms, including exhaustion T metabolic reprogramming response hypoxia cells. Single-cell also revealed resistance such as stromal cell-secreted factors physical barriers extracellular matrix. Future examining specific pathways targeting approaches reduce TME will likely lead better outcomes with immunotherapies, drug delivery, etc., for treatments. incorporate data, spatial micro-environments, translation personalized therapies. This review emphasizes provide TME, revealing reprogramming, influences. aim guide development targeted therapies, highlighting role diversity shaping behavior treatment outcomes.

Язык: Английский

Leveraging Single-Cell Multi-Omics to Decode Tumor Microenvironment Diversity and Therapeutic Resistance DOI Creative Commons
Hussein Sabit, Borros Arneth, Timothy M. Pawlik

и другие.

Pharmaceuticals, Год журнала: 2025, Номер 18(1), С. 75 - 75

Опубликована: Янв. 10, 2025

Recent developments in single-cell multi-omics technologies have provided the ability to identify diverse cell types and decipher key components of tumor microenvironment (TME), leading important advancements toward a much deeper understanding how heterogeneity contributes cancer progression therapeutic resistance. These are able integrate data from molecular genomic, transcriptomic, proteomics, metabolomics studies cells at resolution scale that give rise full cellular complexity TME. Understanding complex sometimes reciprocal relationships among cells, CAFs, immune ECs has led novel insights into their immense functions, which can consequences on behavior. In-depth uncovered evasion mechanisms, including exhaustion T metabolic reprogramming response hypoxia cells. Single-cell also revealed resistance such as stromal cell-secreted factors physical barriers extracellular matrix. Future examining specific pathways targeting approaches reduce TME will likely lead better outcomes with immunotherapies, drug delivery, etc., for treatments. incorporate data, spatial micro-environments, translation personalized therapies. This review emphasizes provide TME, revealing reprogramming, influences. aim guide development targeted therapies, highlighting role diversity shaping behavior treatment outcomes.

Язык: Английский

Процитировано

4