Advances in Single-Cell Techniques for Linking Phenotypes to Genotypes

Cancer Heterogeneity and Plasticity 2024;1(1):0004 | https://doi.org/10.47248/chp2401010004

Review Open Access

Advances in Single-Cell Techniques for Linking Phenotypes to Genotypes

Hsiao-Chun Chen ^1,2 , Yushu Ma ^1,2 , Jinxiong Cheng ^1,3 , Yu-Chih Chen ^1,2,3,4

1. UPMC Hillman Cancer Center, University of Pittsburgh, Pittsburgh, PA 15232, USA
2. Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA 15260, USA
3. Department of Bioengineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA 15260, USA
4. CMU-Pitt Ph.D. Program in Computational Biology, University of Pittsburgh, Pittsburgh, PA 15260, USA

Correspondence: Yu-Chih Chen

Academic Editor(s): Dean Tang

Received: Jun 16, 2024 | Accepted: Jul 16, 2024 | Published: Jul 25, 2024

Cite this article: Chen H, Ma Y, Cheng J, Chen Y. Advances in Single-Cell Techniques for Linking Phenotypes to Genotypes. Cancer Heterog Plast 2024; 1(1):0004. https://doi.org/10.47248/chp2401010004

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.

Keywords

Cellular heterogeneity, single-cell analysis, selective cell retrieval, phenotype, genotype, microfluidics, droplets

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