Colorectal Cancer: Pathogenesis and Targeted Therapy
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Colorectal cancer (CRC) ranks among the most prevalent malignant neoplasms globally. A growing body of evidence underscores the pivotal roles of genetic alterations and dysregulated epigenetic modifications in the pathogenesis of CRC. In recent years, the reprogramming of tumor cell metabolism has been increasingly acknowledged as a hallmark of cancer. Substantial evidence suggests a crosstalk between tumor cell metabolic reprogramming and epigenetic modifications, highlighting a complex interplay between metabolism and the epigenetic genome that warrants further investigation. Biomarkers associated with the pathogenesis and metabolic characteristics of CRC hold significant clinical implications. Nevertheless, elucidating the genetic, epigenetic, and metabolic landscapes of CRC continues to pose considerable challenges. Here, we attempt to summarize the key genes driving the onset and progression of CRC and the related epigenetic regulators, clarify the roles of gene expression and signaling pathways in tumor metabolism regulation, and explore the potential crosstalk between epigenetic events and tumor metabolic reprogramming, providing a comprehensive mechanistic explanation for the malignant progression of CRC. Finally, by integrating reliable targets from genetics, epigenetics, and metabolic processes that hold promise for translation into clinical practice, we aim to offer more strategies to overcome the bottlenecks in CRC treatment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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 it