An endogenous DNA adduct as a prognostic biomarker for hepatocarcinogenesis and its prevention by Theaphenon E in mice
Bibliographic record
Abstract
-propanodeoxyguanosine (γ-OHPdG) is an endogenously formed mutagenic DNA adduct derived from lipid peroxidation. We examined the relationship of γ-OHPdG with hepatocarcinogenesis in two animal models and its potential role as a prognostic biomarker for recurrence in HCC patients. Bioassays were conducted in xeroderma pigmentosum group A knockout mice and diethylnitrosamine-injected mice, both prone to HCC development. γ-OHPdG levels in the livers of these animals were determined. The effects of antioxidant treatments on γ-OHPdG and hepatocarcinogenesis were examined. Using two independent sets of HCC specimens from patients, we examined the relationship between γ-OHPdG and survival or recurrence-free survival. γ-OHPdG levels in liver DNA showed an age-dependent increase and consistently correlated with HCC development in all three animal models. Theaphenon E treatment significantly decreased γ-OHPdG levels in the liver DNA of xeroderma pigmentosum group A knockout mice and remarkably reduced HCC incidence in these mice to 14% from 100% in the controls. It also effectively inhibited HCC development in the diethylnitrosamine-injected mice. Using clinical samples from two groups of patients, our study revealed that higher levels of γ-OHPdG are strongly associated with low survival (P < 0.0001) and low recurrence-free survival (P = 0.007). CONCLUSION: These results support γ-OHPdG as a mechanism-based, biologically relevant biomarker for predicting the risk of HCC and its recurrence. (Hepatology 2018;67:159-170).
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".