{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Gaglia G"],"funding":["NHLBI NIH HHS","NCI NIH HHS","NIGMS NIH HHS"],"pagination":["871-886.e10"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC10193529"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["41(5)"],"pubmed_abstract":["Lymphocytes are key for immune surveillance of tumors, but our understanding of the spatial organization and physical interactions that facilitate lymphocyte anti-cancer functions is limited. We used multiplexed imaging, quantitative spatial analysis, and machine learning to create high-definition maps of lung tumors from a Kras/Trp53-mutant mouse model and human resections. Networks of interacting lymphocytes (\"lymphonets\") emerged as a distinctive feature of the anti-cancer immune response. Lymphonets nucleated from small T cell clusters and incorporated B cells with increasing size. CXCR3-mediated trafficking modulated lymphonet size and number, but T cell antigen expression directed intratumoral localization. Lymphonets preferentially harbored TCF1<sup>+</sup> PD-1<sup>+</sup> progenit"],"journal":["Cancer cell"],"pubmed_title":["Lymphocyte networks are dynamic cellular communities in the immunoregulatory landscape of lung adenocarcinoma."],"pmcid":["PMC10193529"],"funding_grant_id":["T32 HL007627","P30 CA006516","R01 CA194005","R41 CA224503","P30 CA014051","U54 CA225088","K99 CA256497","R50 CA274277","U2C CA233262","T32 GM007748"],"pubmed_authors":["Sorger PK","Coy S","Crossland GE","Rammos D","Gaglia G","Warchol S","Nirmal AJ","Dai Y","Krueger R","Jaeger AM","Jacks T","Burger ML","Pfister H","Santagata S","Tavana SZ","Naranjo S","Ritch CC","Lin JR"],"additional_accession":[]},"is_claimable":false,"name":"Lymphocyte networks are dynamic cellular communities in the immunoregulatory landscape of lung adenocarcinoma.","description":"Lymphocytes are key for immune surveillance of tumors, but our understanding of the spatial organization and physical interactions that facilitate lymphocyte anti-cancer functions is limited. We used multiplexed imaging, quantitative spatial analysis, and machine learning to create high-definition maps of lung tumors from a Kras/Trp53-mutant mouse model and human resections. Networks of interacting lymphocytes (\"lymphonets\") emerged as a distinctive feature of the anti-cancer immune response. Lymphonets nucleated from small T cell clusters and incorporated B cells with increasing size. CXCR3-mediated trafficking modulated lymphonet size and number, but T cell antigen expression directed intratumoral localization. Lymphonets preferentially harbored TCF1<sup>+</sup> PD-1<sup>+</sup> progenit","dates":{"release":"2023-01-01T00:00:00Z","publication":"2023 May","modification":"2025-04-06T19:18:45.296Z","creation":"2024-11-06T13:10:46.63Z"},"accession":"S-EPMC10193529","cross_references":{"pubmed":["37059105"],"doi":["10.1016/j.ccell.2023.03.015"]}}