The (1→6)-β-Glucan Moiety Represents a Cross-Reactive Epitope of Infection-Induced Malignancy Surveillance
Bibliographic record
Abstract
Exposure to pathogen-associated molecular patterns (PAMPs) by vaccination or infection is known to have beneficial effects on neoplastic diseases, although the underlying molecular mechanisms are so far unclear. In this article, we report that Abs against (1→6)-β-d-glucan, a typical microbial PAMP and a major target for high titer circulating natural Abs in healthy human subjects, cross-recognize a novel tumor-associated carbohydrate Ag on cancer cells. The (1→6)-β-glucan cross-reactive moiety is immunologically dominant in tumor cells, as C57BL/6 mice harboring EL-4 solid tumors produced anti-(1→6)-β-glucan Abs and the titer of which significantly correlated with enhanced survival and smaller tumor burden. Moreover, the (1→6)-β-glucan-specific Abs exhibited potent tumoricidal activities in vitro. C57BL/6 mice immunized with Candida albicans produced protective immunity against inoculated EL-4 tumors, which was attributed to the formation of (1→6)-β-glucan-specific Abs. Importantly, (1→6)-β-glucan-specific Abs significantly prolonged the survival and reduced the tumor size in mice inoculated with EL-4 tumors. Our results demonstrate that the (1→6)-β-glucan cross-reactive moiety represents a focal point between infection immunity and cancer surveillance, and natural Abs against this epitope may contribute to the first-line antitumor surveillance in humans. Our data also provide important explanation for the long-observed relationship between feverish infection and concurrent remission from 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".