Overexpression of MAGEA2 has a prognostic significance and is a potential therapeutic target for patients with lung cancer
Bibliographic record
Abstract
Melanoma-associated antigens (MAGE) are expressed in different type of cancers including lung cancer and have been shown to be functionally related to p53 tumor suppressor gene. Little is known about the relationship between MAGE genes and p53 aberrant expression in lung cancer. The aims of this study were to observe the expression of MAGEA2, examine the role of MAGEA2 in lung cancer survival, investigate its correlation between MAGEA2 and p53, and explore its clinicopathologic significance as a prognostic marker. Quantitative reverse transcription-polymerase chain reaction was performed to detect the expression of MAGEA2 using 36 primary tumors and 31 metastatic lymph nodes from patients with lung cancer. The role of MAGEA2 in cancer cell growth and in the regulation of p53 downstream genes were examined using small interfering RNA. The expression of MAGEA2 and p53 were analyzed immunohistochemically using tissue microarray from 353 resected lung specimens. High-level expression of MAGEA2 (High-MAGEA2) was confirmed in lung tumors with high frequency. Inhibiting MAGEA2 expression effectively suppressed cancer cell growth and decreased the expression of p53 downstream target genes in vitro. In adenocarcinoma, High-MAGEA2 was strongly associated with aberrant p53 expression (P<0.001) and was associated with worse clinical outcomes (5-year OS, 87.1% in low vs. 74.1% in high, P=0.014). Aberrant p53 expression was also significant worse prognostic factor (P=0.029). Among the adenocarcinoma patients with wild-type p53, High-MAGEA2 had poorer prognosis than low-level MAGEA2 groups (5-year OS, 90.1% vs. 72.1%, P=0.037), whereas had no difference in p53 aberrant tumors. On multivariate analysis, MAGEA2 was independently associated with survival (hazard ratio; 2.12, P=0.030). In conclusion, suppression of MAGEA2 in lung cancer cells significantly reduced the growth/survival of cancer cells. High-MAGEA2 was identified as an independent prognostic factor in lung adenocarcinoma. Specific inhibition of MAGEA2 may be a promising therapeutic strategy for patients with lung cancer.
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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".