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1.
Cell Syst ; 15(2): 180-192.e7, 2024 Feb 21.
Artigo em Inglês | MEDLINE | ID: mdl-38387441

RESUMO

Analyzing colocalization of single cells with heterogeneous molecular phenotypes is essential for understanding cell-cell interactions, and cellular responses to external stimuli and their biological functions in diseases and tissues. However, existing computational methodologies identified the colocalization patterns between predefined cell populations, which can obscure the molecular signatures arising from intercellular communication. Here, we introduce DeepCOLOR, a computational framework based on a deep generative model that recovers intercellular colocalization networks with single-cell resolution by the integration of single-cell and spatial transcriptomes. Along with colocalized population detection accuracy that is superior to existing methods in simulated dataset, DeepCOLOR identified plausible cell-cell interaction candidates between colocalized single cells and segregated cell populations defined by the colocalization relationships in mouse brain tissues, human squamous cell carcinoma samples, and human lung tissues infected with SARS-CoV-2. DeepCOLOR is applicable to studying cell-cell interactions behind various spatial niches. A record of this paper's transparent peer review process is included in the supplemental information.


Assuntos
Comunicação Celular , Revisão por Pares , Humanos , Animais , Camundongos , Fenótipo , SARS-CoV-2 , Análise de Célula Única
2.
EBioMedicine ; 103: 105102, 2024 May.
Artigo em Inglês | MEDLINE | ID: mdl-38614865

RESUMO

BACKGROUND: Cell-cell interaction factors that facilitate the progression of adenoma to sporadic colorectal cancer (CRC) remain unclear, thereby hindering patient survival. METHODS: We performed spatial transcriptomics on five early CRC cases, which included adenoma and carcinoma, and one advanced CRC. To elucidate cell-cell interactions within the tumour microenvironment (TME), we investigated the colocalisation network at single-cell resolution using a deep generative model for colocalisation analysis, combined with a single-cell transcriptome, and assessed the clinical significance in CRC patients. FINDINGS: CRC cells colocalised with regulatory T cells (Tregs) at the adenoma-carcinoma interface. At early-stage carcinogenesis, cell-cell interaction inference between colocalised adenoma and cancer epithelial cells and Tregs based on the spatial distribution of single cells highlighted midkine (MDK) as a prominent signalling molecule sent from tumour epithelial cells to Tregs. Interaction between MDK-high CRC cells and SPP1+ macrophages and stromal cells proved to be the mechanism underlying immunosuppression in the TME. Additionally, we identified syndecan4 (SDC4) as a receptor for MDK associated with Treg colocalisation. Finally, clinical analysis using CRC datasets indicated that increased MDK/SDC4 levels correlated with poor overall survival in CRC patients. INTERPRETATION: MDK is involved in the immune tolerance shown by Tregs to tumour growth. MDK-mediated formation of the TME could be a potential target for early diagnosis and treatment of CRC. FUNDING: Japan Society for the Promotion of Science (JSPS) Grant-in-Aid for Science Research; OITA Cancer Research Foundation; AMED under Grant Number; Japan Science and Technology Agency (JST); Takeda Science Foundation; The Princess Takamatsu Cancer Research Fund.


Assuntos
Neoplasias Colorretais , Midkina , Análise de Célula Única , Linfócitos T Reguladores , Microambiente Tumoral , Feminino , Humanos , Masculino , Carcinogênese/genética , Carcinogênese/imunologia , Comunicação Celular/imunologia , Neoplasias Colorretais/imunologia , Neoplasias Colorretais/genética , Neoplasias Colorretais/patologia , Neoplasias Colorretais/metabolismo , Neoplasias Colorretais/mortalidade , Perfilação da Expressão Gênica , Regulação Neoplásica da Expressão Gênica , Tolerância Imunológica , Linfócitos T Reguladores/imunologia , Linfócitos T Reguladores/metabolismo , Transcriptoma , Microambiente Tumoral/imunologia , Midkina/imunologia , Midkina/metabolismo
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