Comprehensive Analysis Reveals the Potential Roles of Transcription Factor Dp-1 in Lung Adenocarcinoma
Bibliographic record
Abstract
Background: Transcription factor Dp-1 (TFDP1) was overexpressed and interacted with other genes to impact multiple signaling pathways in various human cancers. However, there is less research about the TFDP1 specific roles in lung adenocarcinoma (LUAD). Methods: We first explored TFDP1 expression levels and relative diseases from a pan-cancer perspective using the ONCOMINE, TIMER, and Open Targets Platform databases. Then, we used UALCAN, GEPIA 2, TCGA-LUAD data, and Kaplan-Meier plotter to examine TFDP1 clinicopathological features and prognosis in LUAD patients. Genomic alterations and DNA methylation analysis were performed by cBioPortal and MethSurv, respectively. Then, we used a cancer single-cell state atlas (CancerSEA) to find TFDP1 functions at a single-cell resolution. LinkedOmics was used to find TFDP1 coexpressed genes, biological processes, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Then, Gene Set Cancer Analysis (GSCA) was used to examine the drug resistence of TFDP1 in LUAD. Results: We found that TFDP1 was overexpressed in most human cancers and related to various diseases, including LUAD. Moreover, LUAD patients with high TFDP1 expression levels might be significantly associated with individual cancer stages and have a poor prognosis. Multivariate analysis revealed that the American Joint Committee on Cancer (AJCC) pathologic stage, AJCC stage T, and AJCC stage N were the independent prognostic factors. LUAD patients with TFDP1 alterations suggested poor overall survival (OS), and disease-free survival (DFS), while hypermethylation might lead to a good prognosis. TFDP1 and its coexpressed genes were enriched in multiple signaling pathways and biological processes involved in the cell cycle, spliceosome, and DNA replication. Furthermore, TFDP1 was strongly positively related to the half-maximal inhibitory concentration (IC50) values of multiple drugs. Conclusions: In summary, TFDP1 was a possible biomarker and potential therapeutic target for LUAD patients.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| 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) | 0.001 | 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".