Immunogenic stress and death of cancer cells: Contribution of antigenicity vs adjuvanticity to immunosurveillance
Bibliographic record
Abstract
Summary Cancer cells are subjected to constant selection by the immune system, meaning that tumors that become clinically manifest have managed to subvert or hide from immunosurveillance. Immune control can be facilitated by induction of autophagy, as well as by polyploidization of cancer cells. While autophagy causes the release of ATP, a chemotactic signal for myeloid cells, polyploidization can trigger endoplasmic reticulum stress with consequent exposure of the “eat‐me” signal calreticulin on the cell surface, thereby facilitating the transfer of tumor antigens into dendritic cells. Hence, both autophagy and polyploidization cause the emission of adjuvant signals that ultimately elicit immune control by CD8+ T lymphocytes. We investigated the possibility that autophagy and polyploidization might also affect the antigenicity of cancer cells by altering the immunopeptidome. Mass spectrometry led to the identification of peptides that were presented on major histocompatibility complex (MHC) class I molecules in an autophagy‐dependent fashion or that were specifically exposed on the surface of polyploid cells, yet lost upon passage of such cells through immunocompetent (but not immunodeficient) mice. However, the preferential recognition of autophagy‐competent and polyploid cells by the innate and cellular immune systems did not correlate with the preferential recognition of such peptides in vivo. Moreover, vaccination with such peptides was unable to elicit tumor growth‐inhibitory responses in vivo. We conclude that autophagy and polyploidy increase the immunogenicity of cancer cells mostly by affecting their adjuvanticity rather than their antigenicity.
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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".