NLRC5 elicits antitumor immunity by enhancing processing and presentation of tumor antigens to CD8<sup>+</sup> T lymphocytes
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Bibliographic record
Abstract
Cancers can escape immunesurveillance by diminishing the expression of MHC class-I molecules (MHC-I) and components of the antigen-processing machinery (APM). Developing new approaches to reverse these defects could boost the efforts to restore antitumor immunity. Recent studies have shown that the expression of MHC-I and antigen-processing molecules is transcriptionally regulated by NOD-like receptor CARD domain containing 5 (NLRC5). To investigate whether NLRC5 could be used to improve tumor immunogenicity, we established stable lines of B16-F10 melanoma cells expressing NLRC5 (B16-5), the T cell co-stimulatory molecule CD80 (B16-CD80) or both (B16-5/80). Cells harboring NLRC5 constitutively expressed MHC-I and LMP2, LMP7 and TAP1 genes of the APM. The B16-5 cells efficiently presented the melanoma antigenic peptide gp10025-33 to Pmel-1 TCR transgenic CD8(+) T cells and induced their proliferation. In the presence of CD80, B16-5 cells stimulated Pmel-1 cells even without the addition of gp100 peptide, indicating that NLRC5 facilitated the processing and presentation of endogenous tumor antigen. Upon subcutaneous implantation, B16-5 cells showed markedly reduced tumor growth in C57BL/6 hosts but not in immunodeficient hosts, indicating that the NLRC5-expressing tumor cells elicited antitumor immunity. Following intravenous injection, B16-5 and B16-5/80 cells formed fewer lung tumor foci compared to control cells. In mice depleted of CD8(+) T cells, B16-5 cells formed large subcutaneous and lung tumors. Finally, immunization with irradiated B16-5 cells conferred protection against challenge by parental B16 cells. Collectively, our findings indicate that NLRC5 could be exploited to restore tumor immunogenicity and to stimulate protective antitumor immunity.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it