Tumor Cells Hijack Macrophage-Produced Complement C1q to Promote Tumor Growth
Bibliographic record
Abstract
Abstract Clear-cell renal cell carcinoma (ccRCC) possesses an unmet medical need, particularly at the metastatic stage, when surgery is ineffective. Complement is a key factor in tissue inflammation, favoring cancer progression through the production of complement component 5a (C5a). However, the activation pathways that generate C5a in tumors remain obscure. By data mining, we identified ccRCC as a cancer type expressing concomitantly high expression of the components that are part of the classical complement pathway. To understand how the complement cascade is activated in ccRCC and impacts patients' clinical outcome, primary tumors from three patient cohorts (n = 106, 154, and 43), ccRCC cell lines, and tumor models in complement-deficient mice were used. High densities of cells producing classical complement pathway components C1q and C4 and the presence of C4 activation fragment deposits in primary tumors correlated with poor prognosis. The in situ orchestrated production of C1q by tumor-associated macrophages (TAM) and C1r, C1s, C4, and C3 by tumor cells associated with IgG deposits, led to C1 complex assembly, and complement activation. Accordingly, mice deficient in C1q, C4, or C3 displayed decreased tumor growth. However, the ccRCC tumors infiltrated with high densities of C1q-producing TAMs exhibited an immunosuppressed microenvironment, characterized by high expression of immune checkpoints (i.e., PD-1, Lag-3, PD-L1, and PD-L2). Our data have identified the classical complement pathway as a key inflammatory mechanism activated by the cooperation between tumor cells and TAMs, favoring cancer progression, and highlight potential therapeutic targets to restore an efficient immune reaction to 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".