Correlation Between PIK3R1 Expression and Cell Growth in Human Breast Cancer Cell Line BT-474 and Clinical Outcomes
Bibliographic record
Abstract
Background: While mutations in the PIK3CA gene play important roles in human breast carcinogenesis, PIK3R1 gene alterations are recognized as actionable mutations for clinical cancer treatment. We aimed to elucidate the role of PIK3R1 in cell proliferation on breast carcinoma and to correlate the PIK3R1 expression with patients’ outcome using human tumor tissue arrays. Methods: Using human BT-474 (estrogen receptor (ER)+/human epidermal growth factor receptor 2 (HER2)-high) breast carcinoma cell line as in vitro model, the role of PIK3R1 in cell proliferation was elucidated by knock-down of the PIK3R1 gene (ΔPIK3R1) in this cell line. Between January 2000 to December 2015, the records of a cohort of 440 patients in our hospital were retrospectively reviewed, including patients’ survival. The correlations between PIK3R1 expression and patient prognosis, such as overall survival (OS) and disease-free survival (DFS), were elucidated by human breast cancer tumor tissue array immunostaining. Results: After the PIK3R1 gene was silenced in the BT-474 line, there was an increased cell number and a decrease in the G0G1-fraction, and increased S-fraction and the S+G2M-fraction for the ΔPIK3R1-BT-474 cell line, as compared to their cell wild type (WT) line. Western blot analysis showed that decreased PIK3R1 protein levels were accompanied by an increase of the p-AKT and p-mTOR proteins in the ΔPIK3R1-BT-474 cell line, compared to the equivalent WT line. Using a human tumor tissue array, patients with high-expressed PIK3R1 protein had better outcomes in terms of DFS and OS, compared to those with low-expressed PIK3R1 protein, when breast cancer was at an early stage (stage I/II), but not across all stages of breast cancer in human patients. Conclusions: We concluded that downregulated PIK3R1 in BT-474 cells resulted in an increased cell growth and upregulated AKT-mTOR signaling. Clinically, the high-expressed PIK3R1 protein in tumors correlates positively with patients’ outcome in stage I and II breast cancer.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".