HER3, but Not HER4, Plays an Essential Role in the Clinicopathology and Prognosis of Gastric Cancer: A Meta-Analysis
Bibliographic record
Abstract
BACKGROUND AND AIM: Human epidermal growth factor receptor (HER) family plays an important role in gastric cancer (GC), especially HER2. Too much attention has been paid to HER2; however, the functions of HER3 and HER4 overexpression in GC are always ignored. The clinicopathological and prognostic roles of HER3 and HER4 in GC are controversial. In this study, a systematic review and meta-analysis was conducted to evaluate the use of HER3 or HER4 as a predictor of clinicopathology and survival time in GC patients. METHODS: Eligible studies were searched on PubMed, Ovid, Web of Science, and Cochrane databases through multiple search strategies. Data collection and statistical analysis were carried out by the Revman 5.3 software. The Newcastle-Ottawa scale was used to assess the quality of included studies. RESULTS: A total of 448 studies about HER3 overexpression and GC, and 398 studies about HER4 overexpression and GC were searched. Of these, 5 eligible studies about HER3 including 1016 GC patients and 3 eligible studies about HER4 including 793 GC patients met the inclusion criteria. The results showed that HER3 and HER4 overexpression were significantly associated with depth of tumor invasion (OR = 0.44, 95%CI 0.29-0.67, P = 0.0002 and OR = 0.50, 95%CI 0.38-0.86, P = 0.007) and lymph node metastasis (OR = 0.40, 95%CI 0.20-0.77, P = 0.007 and OR = 0.57, 95%CI 0.38-0.86, P = 0.007), and HER3 overexpression reveals a tendency of later tumor node metastases (TNM) stage (OR = 0.50, 95%CI 0.22-1.15, P = 0.10) and predicts a worse survival time (RR = 0.71, 95%CI 0.61-0.84, P<0.00001), while HER4 overexpression had no correlation with TNM stage (OR = 0.60, 95%CI 0.20-1.78) and survival time (RR = 1.09, 95%CI 0.91-1.30). CONCLUSIONS: This meta-analysis indicated that HER3 plays an essential role in the clinicopathology and prognosis of GC. However, HER4 may not be an ideal prognostic factor for GC.
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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 | 0.014 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.046 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".