Expression of MG7-Ag in patients with gastric cancer correlates with weaker T cell immune response and more proinflammatory cytokine secretion
Bibliographic record
Abstract
MG7-Ag is a human gastric-carcinoma-associated antigen with a high specificity. So far it is remained unclear whether MG7-Ag is correlated with the in vivo cellular immune response of patients with gastric cancer. In this study, we detected the expression of the T cell receptor (TCR) repertoire of T cell subpopulations and cytokines in tumor-infiltrating lymphocytes (TIL), peripheral blood lymphocytes (PBL), and residue benign mucosal lymphocytes (NML) of patients with gastric cancer using semiquantitative RT-PCR. Our data showed that the expanded clones in CD8(+) NML and TIL and CD4+ NML and PBL in MG7-Ag-positive patients were significantly fewer than those of MG7-Ag-negative patients (p = 0.0360; p = 0.0026; p = 0.0065 p = 0.0109, respectively). The levels of IL-8 in CD8(+) TIL and TNF in CD4(+) TIL from the MG7-Ag-positive group were significantly higher than those from the MG7-Ag-negative group (p = 0.0302; p = 0.0177, respectively). Taken together, the results demonstrated a weaker T cell immune response and more proinflammatory cytokine secretion in MG7-Ag-positive patients with gastric cancer than in MG7-Ag-negative ones. This likely contributes to the poor prognosis in MG7-Ag-positive gastric-cancer patients.
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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 | 0.001 |
| 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) | 0.002 | 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".