Site-dependent Treg cell transcriptional reprograming in a metastatic colorectal cancer model holds prognostic significance
Aristin Revilla, S.; Verheem, A.; Frederiks, C. L.; Kim, Y.; Chalkiadakis, T.; Viergever, B.; Gyorffy, B.; Mocholi, E.; Kranenburg, O.; Prekovic, S.; Coffer, P. J.
Show abstract
In colorectal cancer (CRC), tumor-infiltrating regulatory T (Treg) cells suppress anti-tumor immunity, promoting immune evasion and tumor progression. Effective therapies require selectively targeting tumor-infiltrating Treg (TI-Treg) cells while preserving systemic Treg cells, necessitating insight into their adaptations within the tumor microenvironment. Here, CRC-organoids were implanted in the liver of Foxp3eGFP mice to investigate location-specific phenotypic differences in TI-Treg cells. Tumor tissue exhibited an increased proportion of Treg cells and a decrease of effector CD4 and CD8 T cells compared to matched healthy tissue. RNA sequencing of Treg cells isolated from the spleen, primary liver tumor transplant, or metastases identified gene expression profiles previously associated with CRC-related Treg cells in patients. Location-specific differences included elevated expression of WNT-pathway genes in peritoneal TI-Treg cells compared to liver counterparts. Higher expression of genes upregulated in liver TI-Treg cells correlated with poor CRC prognosis. Splenic Treg cells from tumor-bearing mice displayed distinct transcriptional profiles from both their healthy counterparts and TI-Treg cells, suggesting they represent a distinct CD4+ population. Taken together, these findings highlight TI-Treg cells heterogeneity across different tumor sites and the distinct nature of splenic Treg cells in tumor-bearing hosts.
Matching journals
The top 7 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- CD300e is a driver of the immunosuppressive tumor microenvironment and colorectal cancer progression via macrophage reprogramming 96%
- Tumor-agnostic transcriptome-based classifier identifies spatial infiltration patterns of CD8+ T cells in the tumor microenvironment and predicts clinical outcome in early- and late-phase clinical trials 95%
- Treatment of pancreatic cancer with irreversible electroporation and intratumoral CD40 antibody stimulates systemic immune responses that inhibit liver metastasis in an orthotopic model. 95%
Similar papers in this journal
- A Paradoxical Tumor Antigen Specific Response in the Liver 97%
- Single-Cell RNA Sequencing Reveals the Effects of Chemotherapy on Human Pancreatic Adenocarcinoma and its Tumor Microenvironment 95%
- GZMKhigh CD8+ T effector memory cells are associated with CD15high neutrophil abundance in early-stage colorectal tumors and predict poor clinical outcome. 95%
Similar papers in this journal
- Combining an alarmin HMGN1 peptide with PD-L1 blockade facilitates stem-like CD8+ T cell expansion and results in robust antitumor effects 95%
- Clonal spreading of tumor-infiltrating T cells underlies the robust antitumor immune responses 95%
- Microenvironmental correlates of immune checkpoint inhibitor response in human melanoma brain metastases revealed by T cell receptor and single-cell RNA sequencing 94%
Similar papers in this journal
- CD39+ conventional CD4+ T cells with exhaustion traits and cytotoxic potential infiltrate tumors and expand upon CTLA-4 blockade 95%
- Colon-specific immune microenvironment regulates cancer progression versus rejection 95%
- Tertiary lymphoid structure-related immune infiltrates in NSCLC tumor lesions correlate with low tumor-reactivity of TIL products 95%
Similar papers in this journal
- Tumor secreted extracellular vesicles regulate T-cell costimulation and can be manipulated to induce tumor-specific T-cell responses 96%
- Spatially resolved niche and tumor microenvironmental alterations in gastric cancer peritoneal metastases 95%
- Loss of Rnf43 accelerates Kras-mediated neoplasia and remodels the tumor immune microenvironment in pancreatic adenocarcinoma 93%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.