Contributions of HOX genes to cancer hallmarks: Enrichment pathway analysis and review
Bibliographic record
Abstract
Homeobox genes function as master regulatory transcription factors during development, and their expression is often altered in cancer. The HOX gene family was initially studied intensively to understand how the expression of each gene was involved in forming axial patterns and shaping the body plan during embryogenesis. More recent investigations have discovered that HOX genes can also play an important role in cancer. The literature has shown that the expression of HOX genes may be increased or decreased in different tumors and that these alterations may differ depending on the specific HOX gene involved and the type of cancer being investigated. New studies are also emerging, showing the critical role of some members of the HOX gene family in tumor progression and variation in clinical response. However, there has been limited systematic evaluation of the various contributions of each member of the HOX gene family in the pathways that drive the common phenotypic changes (or "hallmarks") and that underlie the transformation of normal cells to cancer cells. In this review, we investigate the context of the engagement of HOX gene targets and their downstream pathways in the acquisition of competence of tumor cells to undergo malignant transformation and tumor progression. We also summarize published findings on the involvement of HOX genes in carcinogenesis and use bioinformatics methods to examine how their downstream targets and pathways are involved in each hallmark of the cancer phenotype.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".