FOS-Like Antigen 1 Expression Was Associated With Survival of Hepatocellular Carcinoma Patients
Bibliographic record
Abstract
Background: Early diagnosis and proper management of hepatocellular carcinoma (HCC) improve patient prognosis. Several studies attempted to discover new genes to understand the pathogenesis and identify the prognostic and predictive factors in HCC patients, to improve patient's overall survival (OS) and maintain their physical and social activity. The transcription factor FOS-like antigen 1 (FOSL1) acts as one of the important prognostic factors in different tumors, and its overexpression correlates with tumors' progression and worse patient survival. However, its expression and molecular mechanisms underlying its dysregulation in human HCC remain poorly understood. Our study was conducted to evaluate the expression of FOSL1 in HCC tissues and its relationship with various clinicopathological parameters besides OS. Methods: This study is a retrospective cohort study conducted among 113 patients with a proven diagnosis of HCC, who underwent tumor resection and received treatment at South Egypt Cancer Institute. Immunohistochemistry for FOSL1 expression and survival curves were conducted followed by statistical analysis. Results: HCC occurred at older age group and affected males more than females. There was a statistically significant correlation between combined cytoplasmic and nuclear expression of FOSL1 and worse prognosis in HCC patients. There was a statistically significant correlation of FOSL1 expression with histological grade, lymphovascular embolization, and tumor budding where high expression indicated potential deterioration of HCC patients. There was statistically significant correlation between tumor size, tumor grade and FOSL1 expression with the cumulative OS. Conclusions: Combined cytoplasmic and nuclear FOSL1 expression has significant prognostic association with HCC and diagnostic importance, as it can identify cirrhosis and premalignant lesions that can progress to HCC. Furthermore, Kaplan-Meier survival analysis found that overexpressed FOSL1 was correlated with poor OS.
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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".