From PIK3CA Mutations to Rational PI3K Inhibition for the Treatment of Colorectal Cancer
Bibliographic record
Abstract
Inhibitors of kinase PI3K have been in clinical development for several years but only two drugs, the alpha catalytic sub-unit specific inhibitor alpelisib and more recently inavolisib, also an inhibitor of the alpha catalytic sub-unit, have been approved for a cancer indication, in metastatic breast cancer. In colorectal cancer, despite a high prevalence of PIK3CA gene mutations, PI3K inhibitors have met with limited success, and development has mostly been halted or stagnated. Inherent resistance of colorectal cancer cells to PI3K inhibitors relate to the molecular alterations of this cancer, which include concomitant mutations and copy number alterations in other key players of the receptor tyrosine kinase pathways, including KRAS and BRAF. These have not been addressed adequately during clinical development of PI3K inhibitors. Most early trials examining PI3K inhibitors did not mandate for molecular alterations of PIK3CA as an inclusion criterion. These trials have sought to potentiate the action of other inhibitors of receptor tyrosine kinase pathways using PI3K inhibitors as a non-specific prevention against feedback resistance development. In addition, trials that included patients with PIK3CA-mutated cancers failed to consider mutations in other genes of the pathway, which may be related to primary or induced resistance. Other factors, such as the specific type of PIK3CA mutations arising in the catalytic domain, the helical domain, or other areas of the gene, which may affect the mutation functional repercussions and the inhibitor effectiveness, have not been fully taken into consideration. This review details the progress of PI3K inhibitors' development in colorectal cancer, addresses hurdles in development, and proposes areas for potential advancement.
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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) | 0.001 | 0.001 |
| 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".