Marceaux et al. performed spatial multi-omics analysis across clinically annotated LUAD and LUSC cohorts of NSCLC, and stratified it into lymphoid-, myeloid-, and mixed-enriched subtypes, independent of driver mutations. CD14⁺CD4⁺ T cells were enriched in myeloid niches and absent in healthy lungs. CD4+ T cells acquired CD14 from HLA-DR⁺ myeloid cells via trogocytosis, forming an atypical myeloid-instructed phenotype. TNFα signaling was enriched in CD14+CD4+ T cell-high tumors. The addition of TNF⍺ enhanced trogocytosis and CD14+CD4+ T cells formation ex vivo. CD14+CD4+ T cells represent a distinct T cell population associated with poor prognosis in NSCLC.
Contributed by Shishir Pant
ABSTRACT: The tumor microenvironment is composed of diverse immune populations that can either support anti-tumor immunity or promote tumor progression. Myeloid cells are major drivers of immunosuppression, yet therapies targeting them have shown limited success. To uncover mechanisms underlying myeloid-driven immune suppression, we performed spatial multi-omics analyses of non-small cell lung cancer (NSCLC). Independent of oncogenic driver status, tumors stratify into lymphoid-enriched, myeloid-enriched, and mixed immune-infiltrated subtypes. In tumor and adjacent non-malignant lungs, we identify myeloid-instructed CD14+CD4+ T cells. These cells arise through trogocytosis adopting an atypical phenotype. In lymphoid-enriched tumors, high infiltration of CD14+CD4+ T cells correlates with poor patient survival. Spatial transcriptomics reveal enrichment of tumor necrosis factor alpha (TNF-α) signaling in CD14+CD4+-T-cell-rich tumors. Functional assays demonstrate that TNF-⍺ enhanced trogocytosis, promoting the formation of CD14+CD4+ T cells. These findings uncover a TNF-⍺-mediated mechanism of immunosuppression in the TME and highlight aberrant myeloid-T cell interactions as contributors to NSCLC progression.
Author Info: (1) Personalised Oncology Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC, Australia; Department of Medical Biology, The University of Mebourne, P
Author Info: (1) Personalised Oncology Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC, Australia; Department of Medical Biology, The University of Mebourne, Parkville, VIC, Australia. (2) Bioinformatics Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC, Australia. (3) Personalised Oncology Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC, Australia. (4) Personalised Oncology Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC, Australia. (5) Personalised Oncology Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC, Australia. (6) Personalised Oncology Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC, Australia; Department of Medical Biology, The University of Mebourne, Parkville, VIC, Australia. (7) Personalised Oncology Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC, Australia; Department of Medical Biology, The University of Mebourne, Parkville, VIC, Australia. (8) Personalised Oncology Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC, Australia. (9) Personalised Oncology Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC, Australia. (10) Advanced Technology and Biology Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC, Australia. (11) Bioinformatics Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC, Australia. (12) The Royal Melbourne Hospital, Parkville, VIC, Australia. (13) The Royal Melbourne Hospital, Parkville, VIC, Australia. (14) Department of Surgery, The University of Melbourne, Parkville, VIC, Australia; The Royal Melbourne Hospital, Parkville, VIC, Australia. (15) Bioinformatics Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC, Australia; School of Mathematics and Statistics, The University of Melbourne, Parkville, VIC, Australia. (16) Advanced Technology and Biology Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC, Australia; Department of Medical Biology, The University of Mebourne, Parkville, VIC, Australia. (17) Bioinformatics Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC, Australia; Department of Medical Biology, The University of Mebourne, Parkville, VIC, Australia. (18) Personalised Oncology Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC, Australia; Department of Medical Biology, The University of Mebourne, Parkville, VIC, Australia. Electronic address: labat@wehi.edu.au.
