{"title":"单细胞转录组测序技术在恶性细胞异质性分析中的探索与应用。","authors":"Wen Zhang, Tianliang Liu, Ting Liu, Yu Zhang, Zhenguo Zhao, Xinxin Zhang, Xiaoyang Li, Jiasheng Zhong, Zhicheng Li, Shifu Chen, Libin Xu","doi":"10.14336/AD.2025.0836","DOIUrl":null,"url":null,"abstract":"<p><p>Cancer remains a formidable global health burden owing to its persistently high incidence and mortality, highlighting the need to elucidate its underlying biological mechanisms. Such insights are crucial for refining diagnostic precision and therapeutic efficacy. Notably, human tumors represent highly heterogeneous ecosystems, comprising a dynamic interplay between malignant cells and non-malignant components, such as immune infiltrates and stromal elements. This cellular heterogeneity constitutes a major obstacle in tumor research. Recent technological advancements have enabled the development and application of novel tools for investigating tumor heterogeneity. In this context, single-cell sequencing technologies emerged as transformative tools for dissecting tumor architecture at a cellular resolution, offering unprecedented insights into the cellular diversity and molecular underpinnings of cancer. In particular, single-cell RNA sequencing (scRNA-seq) has been widely used to analyze the tumor microenvironment, particularly its immune components, thereby providing a valuable framework for understanding tumor-immune system interactions. However, the intrinsic heterogeneity of tumor cells has received comparatively less attention, with limited studies focusing on these malignant populations. Comprehensive profiling of tumor cells has become increasingly feasible as scRNA-seq technologies continue to evolve, offering higher throughput, increased cell capture efficiency, and more advanced analytical pipelines. Despite these advancements, current applications of scRNA-seq remain primarily focused on immune and stromal cell populations. Therefore, a paradigm shift is warranted, redirecting the investigative focus toward tumor cells and gaining deeper insights into tumorigenesis and therapeutic vulnerabilities.</p>","PeriodicalId":7434,"journal":{"name":"Aging and Disease","volume":" ","pages":""},"PeriodicalIF":6.9000,"publicationDate":"2025-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Exploration and Application of Malignant Cell Heterogeneity Analysis with Single-Cell Transcriptome Sequencing Technology.\",\"authors\":\"Wen Zhang, Tianliang Liu, Ting Liu, Yu Zhang, Zhenguo Zhao, Xinxin Zhang, Xiaoyang Li, Jiasheng Zhong, Zhicheng Li, Shifu Chen, Libin Xu\",\"doi\":\"10.14336/AD.2025.0836\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Cancer remains a formidable global health burden owing to its persistently high incidence and mortality, highlighting the need to elucidate its underlying biological mechanisms. Such insights are crucial for refining diagnostic precision and therapeutic efficacy. Notably, human tumors represent highly heterogeneous ecosystems, comprising a dynamic interplay between malignant cells and non-malignant components, such as immune infiltrates and stromal elements. This cellular heterogeneity constitutes a major obstacle in tumor research. Recent technological advancements have enabled the development and application of novel tools for investigating tumor heterogeneity. In this context, single-cell sequencing technologies emerged as transformative tools for dissecting tumor architecture at a cellular resolution, offering unprecedented insights into the cellular diversity and molecular underpinnings of cancer. In particular, single-cell RNA sequencing (scRNA-seq) has been widely used to analyze the tumor microenvironment, particularly its immune components, thereby providing a valuable framework for understanding tumor-immune system interactions. However, the intrinsic heterogeneity of tumor cells has received comparatively less attention, with limited studies focusing on these malignant populations. Comprehensive profiling of tumor cells has become increasingly feasible as scRNA-seq technologies continue to evolve, offering higher throughput, increased cell capture efficiency, and more advanced analytical pipelines. Despite these advancements, current applications of scRNA-seq remain primarily focused on immune and stromal cell populations. Therefore, a paradigm shift is warranted, redirecting the investigative focus toward tumor cells and gaining deeper insights into tumorigenesis and therapeutic vulnerabilities.</p>\",\"PeriodicalId\":7434,\"journal\":{\"name\":\"Aging and Disease\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":6.9000,\"publicationDate\":\"2025-07-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Aging and Disease\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.14336/AD.2025.0836\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"GERIATRICS & GERONTOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Aging and Disease","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.14336/AD.2025.0836","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"GERIATRICS & GERONTOLOGY","Score":null,"Total":0}
Exploration and Application of Malignant Cell Heterogeneity Analysis with Single-Cell Transcriptome Sequencing Technology.
Cancer remains a formidable global health burden owing to its persistently high incidence and mortality, highlighting the need to elucidate its underlying biological mechanisms. Such insights are crucial for refining diagnostic precision and therapeutic efficacy. Notably, human tumors represent highly heterogeneous ecosystems, comprising a dynamic interplay between malignant cells and non-malignant components, such as immune infiltrates and stromal elements. This cellular heterogeneity constitutes a major obstacle in tumor research. Recent technological advancements have enabled the development and application of novel tools for investigating tumor heterogeneity. In this context, single-cell sequencing technologies emerged as transformative tools for dissecting tumor architecture at a cellular resolution, offering unprecedented insights into the cellular diversity and molecular underpinnings of cancer. In particular, single-cell RNA sequencing (scRNA-seq) has been widely used to analyze the tumor microenvironment, particularly its immune components, thereby providing a valuable framework for understanding tumor-immune system interactions. However, the intrinsic heterogeneity of tumor cells has received comparatively less attention, with limited studies focusing on these malignant populations. Comprehensive profiling of tumor cells has become increasingly feasible as scRNA-seq technologies continue to evolve, offering higher throughput, increased cell capture efficiency, and more advanced analytical pipelines. Despite these advancements, current applications of scRNA-seq remain primarily focused on immune and stromal cell populations. Therefore, a paradigm shift is warranted, redirecting the investigative focus toward tumor cells and gaining deeper insights into tumorigenesis and therapeutic vulnerabilities.
期刊介绍:
Aging & Disease (A&D) is an open-access online journal dedicated to publishing groundbreaking research on the biology of aging, the pathophysiology of age-related diseases, and innovative therapies for conditions affecting the elderly. The scope encompasses various diseases such as Stroke, Alzheimer's disease, Parkinson’s disease, Epilepsy, Dementia, Depression, Cardiovascular Disease, Cancer, Arthritis, Cataract, Osteoporosis, Diabetes, and Hypertension. The journal welcomes studies involving animal models as well as human tissues or cells.