Effect of HER3 Overexpression on Survival Outcomes in Pancreatic Cancer Patients: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: Pancreatic cancer (PC) is a highly aggressive malignancy known for its late diagnosis and poor prognosis, making it one of the leading causes of cancer-related mortality worldwide. Identifying the molecular alterations involved in the prognosis of PC is essential. One such factor is HER3 overexpression, which can contribute to cancer cell survival, metastasis, and reduced overall survival (OS) in patients by activating cellular signaling pathways. This meta-analysis investigates the rate of HER3 overexpression in pancreatic cancer patients and examines how this overexpression affects their survival rates. MATERIALS AND METHODS: A comprehensive search was conducted across PubMed, Embase, Web of Science, and Scopus databases up to August 2024. Studies evaluating the association between HER3 overexpression and PC were collected following specific inclusion and exclusion criteria. The rate ratio (RR) with 95% confidence intervals (CI) was calculated. Heterogeneity and publication bias were evaluated, and the extent of HER3 overexpression in patients with PC was analyzed. Also, the studies' quality was evaluated using the Newcastle-Ottawa Quality Assessment Scale. The research protocol has been registered on PROSPERO under the registration number CRD42024584939. RESULTS: Four studies involving 345 patients with PC were selected for analysis to assess the role of HER3 overexpression on OS. Seven studies involving 536 patients were also included to evaluate the rate of HER3 overexpression in PC patients. Findings indicate that 47.8% of PC patients showed overexpression of HER3 (CI 95%: 34.1-61.9). Additionally, HER3 overexpression was significantly linked to a poorer overall survival rate of patients with PC (OR: 0.605, 95% CI: 0.401-0.913, P= 0.017). CONCLUSION: In summary, our results reveal that a significant proportion of PC patients show overexpression of HER3, suggesting its potential role as a target for immunotherapy. The findings also highlight the promise of HER3 as a prognostic biomarker in PC.
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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 | 0.011 | 0.024 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.030 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".