Jintong Shi, Xia Wei, Zhenzhen Xun, Xinyu Ding, Yao Liu, Lianxin Liu, Youqiong Ye
{"title":"网络门户 SpatialTME 将组织学图像与单细胞和空间转录组学整合在一起,用于探索肿瘤微环境。","authors":"Jintong Shi, Xia Wei, Zhenzhen Xun, Xinyu Ding, Yao Liu, Lianxin Liu, Youqiong Ye","doi":"10.1158/0008-5472.CAN-23-2650","DOIUrl":null,"url":null,"abstract":"<p><p>The tumor microenvironment (TME) represents a complex network in which tumor cells communicate not only with each other but also with stromal and immune cells. The intercellular interactions in the TME contribute to tumor initiation, progression, metastasis, and treatment outcome. Recent advances in spatial transcriptomics (ST) have revolutionized the molecular understanding of the TME at the spatial level. A comprehensive interactive analysis resource specifically designed for characterizing the spatial TME could facilitate further advances using ST. In this study, we collected 296 ST slides covering 19 cancer types and developed a computational pipeline to delineate the spatial structure along the malignant-boundary-nonmalignant axis. The pipeline identified differentially expressed genes and their functional enrichment, deconvoluted the cellular composition of the TME, reconstructed cell type-specific gene expression profiles at the sub-spot level, and performed cell-cell interaction analysis. Finally, the user-friendly database SpatialTME (http://www.spatialtme.yelab.site/) was constructed to provide search, visualization, and downloadable results. These detailed analyses are able to reveal the heterogeneous regulatory network of the spatial microenvironment and elucidate associations between spatial features and tumor development or response to therapy, offering a valuable resource to study the complex TME.</p><p><strong>Significance: </strong>SpatialTME provides spatial structure, cellular composition, expression, function, and cell-cell interaction information to enable investigations into the tumor microenvironment at the spatial level to advance understanding of cancer development and treatment.</p>","PeriodicalId":9441,"journal":{"name":"Cancer research","volume":null,"pages":null},"PeriodicalIF":12.5000,"publicationDate":"2024-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The Web-Based Portal SpatialTME Integrates Histological Images with Single-Cell and Spatial Transcriptomics to Explore the Tumor Microenvironment.\",\"authors\":\"Jintong Shi, Xia Wei, Zhenzhen Xun, Xinyu Ding, Yao Liu, Lianxin Liu, Youqiong Ye\",\"doi\":\"10.1158/0008-5472.CAN-23-2650\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>The tumor microenvironment (TME) represents a complex network in which tumor cells communicate not only with each other but also with stromal and immune cells. The intercellular interactions in the TME contribute to tumor initiation, progression, metastasis, and treatment outcome. Recent advances in spatial transcriptomics (ST) have revolutionized the molecular understanding of the TME at the spatial level. A comprehensive interactive analysis resource specifically designed for characterizing the spatial TME could facilitate further advances using ST. In this study, we collected 296 ST slides covering 19 cancer types and developed a computational pipeline to delineate the spatial structure along the malignant-boundary-nonmalignant axis. The pipeline identified differentially expressed genes and their functional enrichment, deconvoluted the cellular composition of the TME, reconstructed cell type-specific gene expression profiles at the sub-spot level, and performed cell-cell interaction analysis. Finally, the user-friendly database SpatialTME (http://www.spatialtme.yelab.site/) was constructed to provide search, visualization, and downloadable results. These detailed analyses are able to reveal the heterogeneous regulatory network of the spatial microenvironment and elucidate associations between spatial features and tumor development or response to therapy, offering a valuable resource to study the complex TME.</p><p><strong>Significance: </strong>SpatialTME provides spatial structure, cellular composition, expression, function, and cell-cell interaction information to enable investigations into the tumor microenvironment at the spatial level to advance understanding of cancer development and treatment.</p>\",\"PeriodicalId\":9441,\"journal\":{\"name\":\"Cancer research\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":12.5000,\"publicationDate\":\"2024-04-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Cancer research\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1158/0008-5472.CAN-23-2650\",\"RegionNum\":1,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ONCOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cancer research","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1158/0008-5472.CAN-23-2650","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ONCOLOGY","Score":null,"Total":0}
The Web-Based Portal SpatialTME Integrates Histological Images with Single-Cell and Spatial Transcriptomics to Explore the Tumor Microenvironment.
The tumor microenvironment (TME) represents a complex network in which tumor cells communicate not only with each other but also with stromal and immune cells. The intercellular interactions in the TME contribute to tumor initiation, progression, metastasis, and treatment outcome. Recent advances in spatial transcriptomics (ST) have revolutionized the molecular understanding of the TME at the spatial level. A comprehensive interactive analysis resource specifically designed for characterizing the spatial TME could facilitate further advances using ST. In this study, we collected 296 ST slides covering 19 cancer types and developed a computational pipeline to delineate the spatial structure along the malignant-boundary-nonmalignant axis. The pipeline identified differentially expressed genes and their functional enrichment, deconvoluted the cellular composition of the TME, reconstructed cell type-specific gene expression profiles at the sub-spot level, and performed cell-cell interaction analysis. Finally, the user-friendly database SpatialTME (http://www.spatialtme.yelab.site/) was constructed to provide search, visualization, and downloadable results. These detailed analyses are able to reveal the heterogeneous regulatory network of the spatial microenvironment and elucidate associations between spatial features and tumor development or response to therapy, offering a valuable resource to study the complex TME.
Significance: SpatialTME provides spatial structure, cellular composition, expression, function, and cell-cell interaction information to enable investigations into the tumor microenvironment at the spatial level to advance understanding of cancer development and treatment.
期刊介绍:
Cancer Research, published by the American Association for Cancer Research (AACR), is a journal that focuses on impactful original studies, reviews, and opinion pieces relevant to the broad cancer research community. Manuscripts that present conceptual or technological advances leading to insights into cancer biology are particularly sought after. The journal also places emphasis on convergence science, which involves bridging multiple distinct areas of cancer research.
With primary subsections including Cancer Biology, Cancer Immunology, Cancer Metabolism and Molecular Mechanisms, Translational Cancer Biology, Cancer Landscapes, and Convergence Science, Cancer Research has a comprehensive scope. It is published twice a month and has one volume per year, with a print ISSN of 0008-5472 and an online ISSN of 1538-7445.
Cancer Research is abstracted and/or indexed in various databases and platforms, including BIOSIS Previews (R) Database, MEDLINE, Current Contents/Life Sciences, Current Contents/Clinical Medicine, Science Citation Index, Scopus, and Web of Science.