Essential role of NLRC5 in cancer immune surveillance and cancer immunoediting
Bibliographic record
Abstract
Abstract A key mechanism of immune escape from CD8 + T cell-mediated tumor control occurs via downregulation of NLRC5, the IFNγ-induced transcriptional activator of MHC class-I. As NLRC5 deficiency does not abrogate CD8 + T cell development, we investigated whether NLRC5-dependent antitumor immune mechanisms are required for immune surveillance. Development of 3-methylcholanthrene (MCA)-induced endogenous fibrosarcoma was studied in Nlrc5 -/- mice with Nlrc5 +/+ and Rag1 -/- mice serving as controls. Nlrc5 -/- and Rag1 -/- mice showed increased propensity to develop MCA-induced tumors with elevated growth rate compared to Nlrc5 +/+ mice, and displayed significantly reduced survival. Tumors from Nlrc5 +/+ and Nlrc5 -/- mice, but not from Rag1 -/- mice, contained necrotic areas and displayed T cell infiltration. Tumor cell lines established from MCA- induced tumors were evaluated for their sensitivity to immune-mediated growth control following implantation into immunocompetent C57BL/6 and immunodeficient Rag1 -/- hosts. Tumors formed by Nlrc5 +/+ tumor cell lines progressed unhindered in C57BL/6 hosts that reflected their immunoedited status, whereas cell lines from Nlrc5 -/- and Rag1 -/- tumors were efficiently controlled, indicating their non-immunoedited status. Proteomic analysis by mass spectrometry followed by pathway analysis revealed enrichment of granzyme-mediated cytolytic pathway in Nlrc5 +/+ tumors that were absent in Nlrc5 -/- tumors, which showed enrichment of humoral and innate immune pathways. Overall, our findings show that NLRC5 is required for robust tumor immune surveillance and tumor immunoediting and that compensatory humoral and innate immune mechanisms activated by the loss of NLRC5 are insufficient for cancer immune surveillance and cancer immunoediting.
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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".