Non-Invasive Imaging of Phosphoinositide-3-Kinase-Catalytic-Subunit-Alpha (PIK3CA) Promoter Modulation in Small Animal Models
Bibliographic record
Abstract
Activation of the PI3K/Akt pathway, a critical step for survival in cancer cells is often associated with decreased sensitivity to several chemotherapeutic drugs. PIK3CA gene amplification is observed in 16-24% of epithelial ovarian cancer (EOC) patients in conjunction with p53 mutations. A 900 bp long PIK3CA promoter is shown to be negatively regulated by p53 in ovarian surface epithelial cells but the consequence of chemotherapeutic drug treatments on this promoter in ovarian cancer cells is largely unknown. We aim to study the modulation of this promoter by cisplatin using an improved fusion reporter in ovarian cancer cells and tumor xenografts by non-invasive imaging approach. A PIK3CA sensor was developed using a bi-fusion reporter from a newly constructed library of bi- and tri-fusion vectors comprising of two mutant far red fluorescent proteins (mcherry/mch and tdTomato/tdt), a mutant firefly luciferase (fluc2), and a PET reporter protein (ttk). In vivo imaging of mice implanted with 293T cells transiently expressing these bi- and tri-fusion reporters along with respective controls revealed comparable activity of each reporter in the fusion background and fluc2-tdt as the most sensitive one. Repression of the PIK3CA sensor by drugs was inversely proportional to cellular p53 level in a germline (PA1) and in an EOC (A2780) cell line but not in a p53 deficient EOC (SKOV3) cell line. Bioluminescence imaging of tumor xenografts stably expressing the PIK3CA sensor in PA1 and A2780 cells exhibited attenuating activity without any change in SKOV3 tumors expressing the PIK3CA sensor after cisplatin treatment. Sequential mutation at p53 binding sites showed gradual increase in promoter activity and decreased effects of the drugs. These newly developed PIK3CA-fluc2-tdt and the mutant reporter sensors thus would be extremely useful for screening new drugs and for functional assessment of PIK3CA expression from intact cells to living subjects.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".