A Novel Cuproptosis-Related Signature Identified DLAT as a Prognostic Biomarker for Hepatocellular Carcinoma Patients
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Bibliographic record
Abstract
Background: Hepatocellular carcinoma (HCC) is the most common type of liver cancers, with more than a million cases per year by 2025. Cuproptosis is a novel form of programmed cell death, and is caused by mitochondrial lipoylation and destabilization of iron-sulfur proteins triggered by copper, which was considered as a key player in various biological processes. However, the roles of cuproptosis-related genes (CRGs) in HCC remain largely unknown. Methods: In the present study, we constructed and validated a four CRGs signature for predicting the overall survival (OS) of HCC patients in both The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases. Results: Patients with high CRGs risk score showed shorter OS than those with low CRGs risk score. Functional analysis suggested that the CRGs-based prognostic signature was associated with metabolism remodeling which facilitated liver cancer progression. In addition, reduced infiltration of CD8 + T cells and increased macrophages were found in HCCs from patients with high CRGs risk score. As one of the four CRGs, higher expression of dihydrolipoamide S-acetyltransferase (DLAT) was accompanied by higher expression of program death ligand 1 (PD-L1) in HCC. Further, we confirmed that DLAT was up-regulated and correlated with poor prognosis in a clinical HCC cohort. Conclusion: In conclusion, our study constructed a four CRGs signature prognostic model and identified DLAT as an independent prognostic factor for HCC, thus providing new clues for understanding the association between cuproptosis and HCC. World J Oncol. 2022;13(5):299-310 doi: https://doi.org/10.14740/wjon1529
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 it