Transcriptomic characterization of cancer-testis antigens identifies MAGEA3 as a driver of tumor progression in hepatocellular carcinoma
Bibliographic record
Abstract
Cancer testis antigens (CTAs) are an extensive gene family with a unique expression pattern restricted to germ cells, but aberrantly reactivated in cancer tissues. Studies indicate that the expression (or re-expression) of CTAs within the MAGE-A family is common in hepatocellular carcinoma (HCC). However, no systematic characterization has yet been reported. The aim of this study is to perform a comprehensive profile of CTA de-regulation in HCC and experimentally evaluate the role of MAGEA3 as a driver of HCC progression. The transcriptomic analysis of 44 multi-regionally sampled HCCs from 12 patients identified high intra-tumor heterogeneity of CTAs. In addition, a subset of CTAs was significantly overexpressed in histologically poorly differentiated regions. Further analysis of CTAs in larger patient cohorts revealed high CTA expression related to worse overall survival and several other markers of poor prognosis. Functional analysis of MAGEA3 was performed in human HCC cell lines by gene silencing and in a genetic mouse model by overexpression of MAGEA3 in the liver. Knockdown of MAGEA3 decreased cell proliferation, colony formation and increased apoptosis. MAGEA3 overexpression was associated with more aggressive tumors in vivo. In conclusion MAGEA3 enhances tumor progression and should be considered as a novel therapeutic target in HCC.
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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) | 0.000 | 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) | 0.000 | 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".