MISP Is Overexpressed in Intestinal Metaplasia and Gastric Cancer
Bibliographic record
Abstract
Gastric cancer is the fifth most common cancer and the fourth cause of global cancer mortality. The identification of new biomarkers and drug targets is crucial to allow the better prognosis and treatment of patients. The mitotic spindle positioning (MISP) protein has the function of correcting mitotic spindle positioning and centrosome clustering and has been implicated in the cytokinesis and migration of cancer cells. The goal of this work was to evaluate the expression and clinical relevance of MISP in gastric cancer. MISP expression was evaluated by immunohistochemistry in a single hospital series (n = 286) of gastric adenocarcinomas and compared with normal gastric mucosa and intestinal metaplasia, a preneoplastic lesion. MISP was detected on the membrane in 83% of the cases, being overexpressed in gastric cancer compared to normal gastric mucosa (n = 10). Its expression was negatively associated with diffuse and poorly cohesive types. On the other hand, it was strongly expressed in intestinal metaplasia where it was associated with MUC2 and CDX2 expression. Furthermore, when we silenced MISP in vitro, a significant decrease in the viability of gastric carcinoma cells was observed. In conclusion, MISP is overexpressed in gastric cancer, being associated with an intestinal phenotype in gastric carcinogenesis and having a role in cellular proliferation.
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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 | 0.001 | 0.001 |
| 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".