Aberrant HMGA2 Expression Sustains Genome Instability That Promotes Metastasis and Therapeutic Resistance in Colorectal Cancer
Bibliographic record
Abstract
Colorectal cancer (CRC) is one of the most lethal cancers worldwide, accounting for nearly ~10% of all cancer diagnoses and deaths. Current therapeutic approaches have considerably increased survival for patients diagnosed at early stages; however, ~20% of CRC patients are diagnosed with late-stage, metastatic CRC, where 5-year survival rates drop to 6–13% and treatment options are limited. Genome instability is an enabling hallmark of cancer that confers increased acquisition of genetic alterations, mutations, copy number variations and chromosomal rearrangements. In that regard, research has shown a clear association between genome instability and CRC, as the accumulation of aberrations in cancer-related genes provides subpopulations of cells with several advantages, such as increased proliferation rates, metastatic potential and therapeutic resistance. Although numerous genes have been associated with CRC, few have been validated as predictive biomarkers of metastasis or therapeutic resistance. A growing body of evidence suggests a member of the High-Mobility Group A (HMGA) gene family, HMGA2, is a potential biomarker of metastatic spread and therapeutic resistance. HMGA2 is expressed in embryonic tissues and is frequently upregulated in aggressively growing cancers, including CRC. As an architectural, non-histone chromatin binding factor, it initiates chromatin decompaction to facilitate transcriptional regulation. HMGA2 maintains the capacity for stem cell renewal in embryonic and cancer tissues and is a known promoter of epithelial-to-mesenchymal transition in tumor cells. This review will focus on the known molecular mechanisms by which HMGA2 exerts genome protective functions that contribute to cancer cell survival and chemoresistance in CRC.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".