Expression of APPL1 Is Correlated with Clinicopathologic Characteristics and Poor prognosis in Patients with Gastric Cancer
Bibliographic record
Abstract
BACKGROUND: Although appl1 is overexpressed in many cancers, its status in gastric cancer (gc) is not known. In the present study, we used relevant pathologic and clinical data to investigate appl1 expression in patients with gc. METHODS: In 47 gc and 27 non-gc surgical specimens, immunohistochemistry was used to detect the expression of appl1, and reverse-transcriptase polymerase chain reaction (rt-pcr) was used to detect messenger rna (mrna). A scatterplot visualized the relationship between survival time and mrna expression in gc patients. The log-rank test and other survival statistics were used to determine the association of appl1 expression with the pathologic features of the cancer and clinical outcomes. RESULTS: In gc, appl1 was expressed in 28 of 47 specimens (59.6%), and in non-gc, it was expressed in 7 of 23 specimens (30.4%, p < 0.05). The expression of mrna in gc was 0.82 [95% confidence interval (ci): 0.78 to 0.86], and in non-gc, it was 0.73 (95% ci: 0.69 to 0.77; p < 0.05). Immunohistochemistry demonstrated that, in gc, appl1 expression was correlated with depth of infiltration (p = 0.005), lymph node metastasis (p = 0.017), and TNM stage (p = 0.022), but not with pathologic type (p = 0.41). Testing by rt-pcr demonstrated that, in gc, appl1 mrna expression was correlated with depth of infiltration (p = 0.042), lymph node metastasis (p = 0.031), and TNM stage (p = 0.04), but again, not with pathologic type (p = 0.98). The correlation coefficient between survival time and mrna expression was -0.83 (p < 0.01). Overexpression of appl1 protein (hazard ratio: 3.88; 95% ci: 1.07 to 14.09) and mrna (hazard ratio: 4.23; 95% ci: 3.09 to 15.11) was a risk factor for death in patients with gc. CONCLUSIONS: Expression of appl1 is increased in gc. Overexpression is prognostic for a lethal outcome.
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How this classification was reachedexpand
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 | 0.000 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".