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Advances in Single-Cell Techniques for Linking Phenotypes to Genotypes.
Chen, Hsiao-Chun; Ma, Yushu; Cheng, Jinxiong; Chen, Yu-Chih.
Affiliation
  • Chen HC; UPMC Hillman Cancer Center, University of Pittsburgh, 5115 Centre Ave, Pittsburgh, PA 15232, USA.
  • Ma Y; Department of Computational and Systems Biology, University of Pittsburgh, 3420 Forbes Avenue, Pittsburgh, PA 15260, USA.
  • Cheng J; UPMC Hillman Cancer Center, University of Pittsburgh, 5115 Centre Ave, Pittsburgh, PA 15232, USA.
  • Chen YC; Department of Computational and Systems Biology, University of Pittsburgh, 3420 Forbes Avenue, Pittsburgh, PA 15260, USA.
Article in En | MEDLINE | ID: mdl-39156821
ABSTRACT
Single-cell analysis has become an essential tool in modern biological research, providing unprecedented insights into cellular behavior and heterogeneity. By examining individual cells, this approach surpasses conventional population-based methods, revealing critical variations in cellular states, responses to environmental cues, and molecular signatures. In the context of cancer, with its diverse cell populations, single-cell analysis is critical for investigating tumor evolution, metastasis, and therapy resistance. Understanding the phenotype-genotype relationship at the single-cell level is crucial for deciphering the molecular mechanisms driving tumor development and progression. This review highlights innovative strategies for selective cell isolation based on desired phenotypes, including robotic aspiration, laser detachment, microraft arrays, optical traps, and droplet-based microfluidic systems. These advanced tools facilitate high-throughput single-cell phenotypic analysis and sorting, enabling the identification and characterization of specific cell subsets, thereby advancing therapeutic innovations in cancer and other diseases.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Cancer Heterog Plast Year: 2024 Document type: Article Affiliation country: United States Country of publication: Canada

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Cancer Heterog Plast Year: 2024 Document type: Article Affiliation country: United States Country of publication: Canada