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.
{"title":"Advances in Single-Cell Techniques for Linking Phenotypes to Genotypes.","authors":"Hsiao-Chun Chen, Yushu Ma, Jinxiong Cheng, Yu-Chih Chen","doi":"10.47248/chp2401010004","DOIUrl":"10.47248/chp2401010004","url":null,"abstract":"<p><p>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.</p>","PeriodicalId":520023,"journal":{"name":"Cancer heterogeneity and plasticity","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11328949/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142001648","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-01Epub Date: 2024-07-18DOI: 10.47248/chp2401010002
Xiaozhuo Liu
{"title":"Unmasking SMLR1: The hidden player in colorectal cancer's liver metastasis.","authors":"Xiaozhuo Liu","doi":"10.47248/chp2401010002","DOIUrl":"https://doi.org/10.47248/chp2401010002","url":null,"abstract":"","PeriodicalId":520023,"journal":{"name":"Cancer heterogeneity and plasticity","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11423924/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142336201","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-01Epub Date: 2024-07-18DOI: 10.47248/chp2401010001
Dean G Tang
{"title":"<i>Cancer Heterogeneity and Plasticity</i> - A new journal dedicated to understanding cancer cell states and interactions with the tumor microenvironment.","authors":"Dean G Tang","doi":"10.47248/chp2401010001","DOIUrl":"10.47248/chp2401010001","url":null,"abstract":"","PeriodicalId":520023,"journal":{"name":"Cancer heterogeneity and plasticity","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11449462/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142373998","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-01Epub Date: 2024-08-25DOI: 10.47248/chp2401010005
Anmbreen Jamroze, Xiaozhuo Liu, Dean G Tang
Most human cancers are heterogeneous consisting of cancer cells at different epigenetic and transcriptional states and with distinct phenotypes, functions, and drug sensitivities. This inherent cancer cell heterogeneity contributes to tumor resistance to clinical treatment, especially the molecularly targeted therapies such as tyrosine kinase inhibitors (TKIs) and androgen receptor signaling inhibitors (ARSIs). Therapeutic interventions, in turn, induce lineage plasticity (also called lineage infidelity) in cancer cells that also drives therapy resistance. In this Perspective, we focus our discussions on cancer cell lineage plasticity manifested as treatment-induced switching of epithelial cancer cells to basal/stem-like, mesenchymal, and neural lineages. We employ prostate cancer (PCa) as the prime example to highlight ARSI-induced lineage plasticity during and towards development of castration-resistant PCa (CRPC). We further discuss how the tumor microenvironment (TME) influences therapy-induced lineage plasticity. Finally, we offer an updated summary on the regulators and mechanisms driving cancer cell lineage infidelity, which should be therapeutically targeted to extend the therapeutic window and improve patients' survival.
{"title":"Treatment-induced stemness and lineage plasticity in driving prostate cancer therapy resistance.","authors":"Anmbreen Jamroze, Xiaozhuo Liu, Dean G Tang","doi":"10.47248/chp2401010005","DOIUrl":"10.47248/chp2401010005","url":null,"abstract":"<p><p>Most human cancers are heterogeneous consisting of cancer cells at different epigenetic and transcriptional states and with distinct phenotypes, functions, and drug sensitivities. This inherent cancer cell heterogeneity contributes to tumor resistance to clinical treatment, especially the molecularly targeted therapies such as tyrosine kinase inhibitors (TKIs) and androgen receptor signaling inhibitors (ARSIs). Therapeutic interventions, in turn, induce lineage plasticity (also called lineage infidelity) in cancer cells that also drives therapy resistance. In this Perspective, we focus our discussions on cancer cell lineage plasticity manifested as treatment-induced switching of epithelial cancer cells to basal/stem-like, mesenchymal, and neural lineages. We employ prostate cancer (PCa) as the prime example to highlight ARSI-induced lineage plasticity during and towards development of castration-resistant PCa (CRPC). We further discuss how the tumor microenvironment (TME) influences therapy-induced lineage plasticity. Finally, we offer an updated summary on the regulators and mechanisms driving cancer cell lineage infidelity, which should be therapeutically targeted to extend the therapeutic window and improve patients' survival.</p>","PeriodicalId":520023,"journal":{"name":"Cancer heterogeneity and plasticity","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11449474/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142373999","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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