Peritoneal resident macrophages constitute an immunosuppressive environment in peritoneal metastasized colorectal cancer
Bibliographic record
Abstract
Patients with peritoneal metastasized colorectal cancer (PM-CRC) have a dismal prognosis. We hypothesized that an immunosuppressive environment in the peritoneal cavity underlies poor prognosis. We define the composition of the human peritoneal immune system (PerIS) using single-cell technologies in 18 patients with- and without PM-CRC, as well as in matched peritoneal metastases (n = 8). Here we show that the PerIS contains abundant immunosuppressive C1Q+VSIG4+ and SPP1+VSIG4+ peritoneal-resident macrophages (PRMs), as well as monocyte-like cavity macrophages (mono-CMs), which share features with tumor-associated macrophages, even in homeostasis. In PM-CRC, expression of immunosuppressive cytokines IL10 and VEGF increases, while simultaneously expression of antigen-presenting molecules decreases in PRMs. These intratumoral suppressive PRMs originate from the PerIS, and intraperitoneal depletion of PRMs in vivo using anti-CSF1R combined with anti-PD1 significantly reduces tumor burden and improves survival. Thus, PRMs define a metastatic site-specific immunosuppressive niche, and targeting PRMs is a promising treatment strategy for PM-CRC. Presence of peritoneal metastasis is associated with a decreased survival in patients with colorectal cancer. Here, the authors show that peritoneal-resident macrophages promote the formation of an immunosuppressive environment that facilitate peritoneal metastasis in colorectal cancer.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".