Surveying brain tumor heterogeneity by single-cell RNA-sequencing of multi-sector biopsies
Abstract Brain tumors are among the most challenging human tumors for which the mechanisms driving progression and heterogeneity remain poorly understood. We combined single-cell RNA-seq with multi-sector biopsies to sample and analyze single-cell expression profiles of gliomas from 13 Chinese patie...
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Published in | National science review Vol. 7; no. 8; pp. 1306 - 1318 |
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Main Authors | , , , , , , , , , , , , , , , |
Format | Journal Article |
Language | English |
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Oxford University Press
01.08.2020
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Abstract | Abstract
Brain tumors are among the most challenging human tumors for which the mechanisms driving progression and heterogeneity remain poorly understood. We combined single-cell RNA-seq with multi-sector biopsies to sample and analyze single-cell expression profiles of gliomas from 13 Chinese patients. After classifying individual cells, we generated a spatial and temporal landscape of glioma that revealed the patterns of invasion between the different sub-regions of gliomas. We also used single-cell inferred copy number variations and pseudotime trajectories to inform on the crucial branches that dominate tumor progression. The dynamic cell components of the multi-region biopsy analysis allowed us to spatially deconvolute with unprecedented accuracy the transcriptomic features of the core and those of the periphery of glioma at single-cell level. Through this rich and geographically detailed dataset, we were also able to characterize and construct the chemokine and chemokine receptor interactions that exist among different tumor and non-tumor cells. This study provides the first spatial-level analysis of the cellular states that characterize human gliomas. It also presents an initial molecular map of the cross-talks between glioma cells and the surrounding microenvironment with single-cell resolution. |
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AbstractList | Brain tumors are among the most challenging human tumors for which the mechanisms driving progression and heterogeneity remain poorly understood. We combined single-cell RNA-seq with multi-sector biopsies to sample and analyze single-cell expression profiles of gliomas from 13 Chinese patients. After classifying individual cells, we generated a spatial and temporal landscape of glioma that revealed the patterns of invasion between the different sub-regions of gliomas. We also used single-cell inferred copy number variations and pseudotime trajectories to inform on the crucial branches that dominate tumor progression. The dynamic cell components of the multi-region biopsy analysis allowed us to spatially deconvolute with unprecedented accuracy the transcriptomic features of the core and those of the periphery of glioma at single-cell level. Through this rich and geographically detailed dataset, we were also able to characterize and construct the chemokine and chemokine receptor interactions that exist among different tumor and non-tumor cells. This study provides the first spatial-level analysis of the cellular states that characterize human gliomas. It also presents an initial molecular map of the cross-talks between glioma cells and the surrounding microenvironment with single-cell resolution. Abstract Brain tumors are among the most challenging human tumors for which the mechanisms driving progression and heterogeneity remain poorly understood. We combined single-cell RNA-seq with multi-sector biopsies to sample and analyze single-cell expression profiles of gliomas from 13 Chinese patients. After classifying individual cells, we generated a spatial and temporal landscape of glioma that revealed the patterns of invasion between the different sub-regions of gliomas. We also used single-cell inferred copy number variations and pseudotime trajectories to inform on the crucial branches that dominate tumor progression. The dynamic cell components of the multi-region biopsy analysis allowed us to spatially deconvolute with unprecedented accuracy the transcriptomic features of the core and those of the periphery of glioma at single-cell level. Through this rich and geographically detailed dataset, we were also able to characterize and construct the chemokine and chemokine receptor interactions that exist among different tumor and non-tumor cells. This study provides the first spatial-level analysis of the cellular states that characterize human gliomas. It also presents an initial molecular map of the cross-talks between glioma cells and the surrounding microenvironment with single-cell resolution. Brain tumors are among the most challenging human tumors for which the mechanisms driving progression and heterogeneity remain poorly understood. We combined single-cell RNA-seq with multi-sector biopsies to sample and analyze single-cell expression profiles of gliomas from 13 Chinese patients. After classifying individual cells, we generated a spatial and temporal landscape of glioma that revealed the patterns of invasion between the different sub-regions of gliomas. We also used single-cell inferred copy number variations and pseudotime trajectories to inform on the crucial branches that dominate tumor progression. The dynamic cell components of the multi-region biopsy analysis allowed us to spatially deconvolute with unprecedented accuracy the transcriptomic features of the core and those of the periphery of glioma at single-cell level. Through this rich and geographically detailed dataset, we were also able to characterize and construct the chemokine and chemokine receptor interactions that exist among different tumor and non-tumor cells. This study provides the first spatial-level analysis of the cellular states that characterize human gliomas. It also presents an initial molecular map of the cross-talks between glioma cells and the surrounding microenvironment with single-cell resolution.Brain tumors are among the most challenging human tumors for which the mechanisms driving progression and heterogeneity remain poorly understood. We combined single-cell RNA-seq with multi-sector biopsies to sample and analyze single-cell expression profiles of gliomas from 13 Chinese patients. After classifying individual cells, we generated a spatial and temporal landscape of glioma that revealed the patterns of invasion between the different sub-regions of gliomas. We also used single-cell inferred copy number variations and pseudotime trajectories to inform on the crucial branches that dominate tumor progression. The dynamic cell components of the multi-region biopsy analysis allowed us to spatially deconvolute with unprecedented accuracy the transcriptomic features of the core and those of the periphery of glioma at single-cell level. Through this rich and geographically detailed dataset, we were also able to characterize and construct the chemokine and chemokine receptor interactions that exist among different tumor and non-tumor cells. This study provides the first spatial-level analysis of the cellular states that characterize human gliomas. It also presents an initial molecular map of the cross-talks between glioma cells and the surrounding microenvironment with single-cell resolution. |
Author | Wu, Fan Fan, Xiaolong Tang, Fuchou Wu, Xinglong Qian, Zenghui Iavarone, Antonio Fan, Xiaoying Rasko, John EJ Guo, Qiufang Yu, Kai Hu, Yuqiong Su, Xiao-Dong Wang, Kuanyu Jiang, Tao Hu, Waner Chen, Jing |
Author_xml | – sequence: 1 givenname: Kai orcidid: 0000-0002-2561-8160 surname: Yu fullname: Yu, Kai – sequence: 2 givenname: Yuqiong surname: Hu fullname: Hu, Yuqiong – sequence: 3 givenname: Fan surname: Wu fullname: Wu, Fan – sequence: 4 givenname: Qiufang surname: Guo fullname: Guo, Qiufang – sequence: 5 givenname: Zenghui surname: Qian fullname: Qian, Zenghui – sequence: 6 givenname: Waner surname: Hu fullname: Hu, Waner – sequence: 7 givenname: Jing surname: Chen fullname: Chen, Jing – sequence: 8 givenname: Kuanyu surname: Wang fullname: Wang, Kuanyu – sequence: 9 givenname: Xiaoying surname: Fan fullname: Fan, Xiaoying – sequence: 10 givenname: Xinglong orcidid: 0000-0003-4373-2511 surname: Wu fullname: Wu, Xinglong – sequence: 11 givenname: John EJ surname: Rasko fullname: Rasko, John EJ – sequence: 12 givenname: Xiaolong surname: Fan fullname: Fan, Xiaolong – sequence: 13 givenname: Antonio surname: Iavarone fullname: Iavarone, Antonio email: ai2102@cumc.columbia.edu – sequence: 14 givenname: Tao orcidid: 0000-0002-7008-6351 surname: Jiang fullname: Jiang, Tao email: taojiang1964@163.com – sequence: 15 givenname: Fuchou surname: Tang fullname: Tang, Fuchou email: tangfuchou@pku.edu.cn – sequence: 16 givenname: Xiao-Dong surname: Su fullname: Su, Xiao-Dong email: xdsu@pku.edu.cn |
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Keywords | glioma single-cell RNA-seq multi-sector biopsy heterogeneity |
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Brain tumors are among the most challenging human tumors for which the mechanisms driving progression and heterogeneity remain poorly understood. We... Brain tumors are among the most challenging human tumors for which the mechanisms driving progression and heterogeneity remain poorly understood. We combined... |
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Title | Surveying brain tumor heterogeneity by single-cell RNA-sequencing of multi-sector biopsies |
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