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Dynamic heterogeneity of colorectal cancer during progression revealed clinical risk-associated cell types and regulations in single-cell resolution and spatial context

BACKGROUND: Tumor heterogeneity is contributed by tumor cells and the microenvironment. Dynamics of tumor heterogeneity during colorectal cancer (CRC) progression have not been elucidated. METHODS: Eight single-cell RNA sequencing (scRNA-seq) data sets of CRC were included. Milo was utilized to reve...

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Autores principales: Ke, Haoxian, Li, Zhihao, Li, Peisi, Ye, Shubiao, Huang, Junfeng, Hu, Tuo, Zhang, Chi, Yuan, Ming, Chen, Yuan, Wu, Xianrui, Lan, Ping
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10290555/
https://www.ncbi.nlm.nih.gov/pubmed/37360193
http://dx.doi.org/10.1093/gastro/goad034
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author Ke, Haoxian
Li, Zhihao
Li, Peisi
Ye, Shubiao
Huang, Junfeng
Hu, Tuo
Zhang, Chi
Yuan, Ming
Chen, Yuan
Wu, Xianrui
Lan, Ping
author_facet Ke, Haoxian
Li, Zhihao
Li, Peisi
Ye, Shubiao
Huang, Junfeng
Hu, Tuo
Zhang, Chi
Yuan, Ming
Chen, Yuan
Wu, Xianrui
Lan, Ping
author_sort Ke, Haoxian
collection PubMed
description BACKGROUND: Tumor heterogeneity is contributed by tumor cells and the microenvironment. Dynamics of tumor heterogeneity during colorectal cancer (CRC) progression have not been elucidated. METHODS: Eight single-cell RNA sequencing (scRNA-seq) data sets of CRC were included. Milo was utilized to reveal the differential abundance of cell clusters during progression. The differentiation trajectory was imputed by using the Palantir algorithm and metabolic states were assessed by using scMetabolism. Three spatial transcription sequencing (ST-seq) data sets of CRC were used to validate cell-type abundances and colocalization. Cancer-associated regulatory hubs were defined as communication networks affecting tumor biological behaviors. Finally, quantitative reverse transcription polymerase chain reaction and immunohistochemistry staining were performed for validation. RESULTS: TM4SF1(+), SOX4(+), and MKI67(+) tumor cells; CXCL12(+) cancer-associated fibroblasts; CD4(+) resident memory T cells; Treg; IgA(+) plasma cells; and several myeloid subsets were enriched in stage IV CRC, most of which were associated with overall survival of patients. Trajectory analysis indicated that tumor cells from patients with advanced-stage CRC were less differentiated, when metabolic heterogeneity showed a highest metabolic signature in terminal states of stromal cells, T cells, and myeloid cells. Moreover, ST-seq validated cell-type abundance in a spatial context and also revealed the correlation of immune infiltration between tertiary lymphoid structures and tumors followed by validation in our cohort. Importantly, analysis of cancer-associated regulatory hubs revealed a cascade of activated pathways including leukocyte apoptotic process, MAPK pathway, myeloid leukocyte differentiation, and angiogenesis during CRC progression. CONCLUSIONS: Tumor heterogeneity was dynamic during progression, with the enrichment of immunosuppressive Treg, myeloid cells, and fibrotic cells. The differential state of tumor cells was associated with cancer staging. Assessment of cancer-associated regulatory hubs suggested impaired antitumor immunity and increased metastatic ability during CRC progression.
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spelling pubmed-102905552023-06-25 Dynamic heterogeneity of colorectal cancer during progression revealed clinical risk-associated cell types and regulations in single-cell resolution and spatial context Ke, Haoxian Li, Zhihao Li, Peisi Ye, Shubiao Huang, Junfeng Hu, Tuo Zhang, Chi Yuan, Ming Chen, Yuan Wu, Xianrui Lan, Ping Gastroenterol Rep (Oxf) Original Article BACKGROUND: Tumor heterogeneity is contributed by tumor cells and the microenvironment. Dynamics of tumor heterogeneity during colorectal cancer (CRC) progression have not been elucidated. METHODS: Eight single-cell RNA sequencing (scRNA-seq) data sets of CRC were included. Milo was utilized to reveal the differential abundance of cell clusters during progression. The differentiation trajectory was imputed by using the Palantir algorithm and metabolic states were assessed by using scMetabolism. Three spatial transcription sequencing (ST-seq) data sets of CRC were used to validate cell-type abundances and colocalization. Cancer-associated regulatory hubs were defined as communication networks affecting tumor biological behaviors. Finally, quantitative reverse transcription polymerase chain reaction and immunohistochemistry staining were performed for validation. RESULTS: TM4SF1(+), SOX4(+), and MKI67(+) tumor cells; CXCL12(+) cancer-associated fibroblasts; CD4(+) resident memory T cells; Treg; IgA(+) plasma cells; and several myeloid subsets were enriched in stage IV CRC, most of which were associated with overall survival of patients. Trajectory analysis indicated that tumor cells from patients with advanced-stage CRC were less differentiated, when metabolic heterogeneity showed a highest metabolic signature in terminal states of stromal cells, T cells, and myeloid cells. Moreover, ST-seq validated cell-type abundance in a spatial context and also revealed the correlation of immune infiltration between tertiary lymphoid structures and tumors followed by validation in our cohort. Importantly, analysis of cancer-associated regulatory hubs revealed a cascade of activated pathways including leukocyte apoptotic process, MAPK pathway, myeloid leukocyte differentiation, and angiogenesis during CRC progression. CONCLUSIONS: Tumor heterogeneity was dynamic during progression, with the enrichment of immunosuppressive Treg, myeloid cells, and fibrotic cells. The differential state of tumor cells was associated with cancer staging. Assessment of cancer-associated regulatory hubs suggested impaired antitumor immunity and increased metastatic ability during CRC progression. Oxford University Press 2023-06-24 /pmc/articles/PMC10290555/ /pubmed/37360193 http://dx.doi.org/10.1093/gastro/goad034 Text en © The Author(s) 2023. Published by Oxford University Press and Sixth Affiliated Hospital of Sun Yat-sen University https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Ke, Haoxian
Li, Zhihao
Li, Peisi
Ye, Shubiao
Huang, Junfeng
Hu, Tuo
Zhang, Chi
Yuan, Ming
Chen, Yuan
Wu, Xianrui
Lan, Ping
Dynamic heterogeneity of colorectal cancer during progression revealed clinical risk-associated cell types and regulations in single-cell resolution and spatial context
title Dynamic heterogeneity of colorectal cancer during progression revealed clinical risk-associated cell types and regulations in single-cell resolution and spatial context
title_full Dynamic heterogeneity of colorectal cancer during progression revealed clinical risk-associated cell types and regulations in single-cell resolution and spatial context
title_fullStr Dynamic heterogeneity of colorectal cancer during progression revealed clinical risk-associated cell types and regulations in single-cell resolution and spatial context
title_full_unstemmed Dynamic heterogeneity of colorectal cancer during progression revealed clinical risk-associated cell types and regulations in single-cell resolution and spatial context
title_short Dynamic heterogeneity of colorectal cancer during progression revealed clinical risk-associated cell types and regulations in single-cell resolution and spatial context
title_sort dynamic heterogeneity of colorectal cancer during progression revealed clinical risk-associated cell types and regulations in single-cell resolution and spatial context
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10290555/
https://www.ncbi.nlm.nih.gov/pubmed/37360193
http://dx.doi.org/10.1093/gastro/goad034
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