Potential role of oxidative DNA damage in the impact of PNPLA3 variant (rs 738409 C>G) in hepatocellular carcinoma risk
Bibliographic record
Abstract
The meta-analysis by Trépo et al., recently published in this journal,1 demonstrated an association between PNPLA3 minor rs738409 [G] allele gene variant and hepatocellular carcinoma (HCC). This study follows a previous meta-analysis in nonalcoholic fatty liver disease patients showing increased steatosis, necroinflammatory, and fibrosis scores in rs73840 GG, compared to other patients.2 The mechanisms linking PNPLA3 GG variant to oxidative DNA damage markers are unknown. A carcinogenic role of oxidative stress (OS) has been demonstrated in viral hepatitis and alcoholic cirrhosis. The increased hepatic level of ubiquitous oxidative DNA damage markers, such as 8-hydroxy-deoxy-guanosine (8-OHdG), was positively correlated with fibrosis, inflammatory stages, and HCC risk in chronic hepatitis C patients.3 Moreover, linoleic acid peroxide plasmatic level (HODEs) is increased in HCC patients, leading to an overproduction of proangiogenic and -inflammatory factors, such as vascular endothelial growth factor and interleukin-8.4 Consequently, we hypothesized that OS could play a role in the mechanisms linking PNPLA3 GG variant and increased HCC risk. To evaluate OS according to PNPLA3 status, we randomized 86 patients with cirrhosis from the CiRCE case-control study: 43 with PNPLA3 rs738409 CC status and 43 with GG status matched for gender, age, severity of cirrhosis, presence of B or C viral infection, and time between cirrhosis diagnosis and inclusion in the study. HODEs and 7α- and 7-β-hydroxycholesterol plasmatic levels did not differ between GG and CC patients. On the other hand, 8-OHdG concentration was higher in GG (21.3 ± 4.1 ng/mL) than in CC patients (19.5 ± 2.2 ng/mL; P < 0.031; Table 1). This increase suggests a relationship between PNPLA3 GG status and oxidative DNA damage susceptible to explain over-risk of cancer in patients with cirrhosis. These results must be confirmed in larger population studies stratified according to cirrhosis etiology. Understanding carcinogenic mechanisms of GG status could lead to identifying new therapeutic targets in the prevention of chronic worsening liver disease and liver cancer. Emeric Limagne1,2 Vanessa Cottet, Ph.D.3,4 Alexia Karen Cotte1,2 Samia Hamza1,3,4 Patrick Hillon, M.D., Ph.D.1,3,4 Norbert Latruffe, Ph.D.1,2* Dominique Delmas, Ph.D.1,5* for the CiRCE Study Group 1Université de Bourgogne Dijon, France 2EA 7270 Bioperoxyl Dijon, France 3INSERM U866 Equipe Recherches épidémiologique et clinique en cancérologie digestive 4Service d'hépatogastroenterologie CHU Dijon Dijon, France 5INSERM U866 Equipe Chimiothérapie Métabolisme Lipidique et Réponse Immunitaire Antitumorale Dijon, France The CiRCE Study Group includes: (1) CiRCE Coordination France: J.P. Bronowicki, V. Di Martino, M. Doffoel, P. Hillon (CiRCE coordinator), and G. Thieffin; CiRCE Coordination China: H. Wen, F.P. He, and X.M. Lu and P. Hillon and D. Vuitton; (2) Circe Scientific Board: J. Faivre (President), J.P. Cercueil, V. Cottet, D. Delmas, P. Ducoroy, L. Duvillard, M. Guenneugues, J.L. Guéant, F. Habersetzer, N. Latruffe, M. Manfait, P. Oudet, and G. Sockalingum; (3) CiRCE pharmacologists: P. Trechot, M.B. Valnet-Rabier, T. Trenque, and M. Tebacher-Alt.
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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) | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| 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".