BCL2A1 regulates Canady Helios Cold Plasma-induced cell death in triple-negative breast cancer
Bibliographic record
Abstract
Abstract Breast cancer is the leading cause of cancer death among women. Triple-negative breast cancer (TNBC) has a poor prognosis and frequently relapses early compared with other subtypes. The Cold Atmospheric Plasma (CAP) is a promising therapy for prognostically poor breast cancer such as TNBC. The Canady Helios Cold Plasma (CHCP) induces cell death in the TNBC cell line without thermal damage, however, the mechanism of cell death by CAP treatment is ambiguous and the mechanism of resistance to cell death in some subset of cells has not been addressed. We investigate the expression profile of 48 apoptotic and 35 oxidative gene markers after CHCP treatment in six different types of breast cancer cell lines including luminal A (ER+ PR+/−HER2−), luminal B (ER+PR+/−HER2+), (ER−PR−HER2+), basal-like: ER−PR−HER2− cells were tested with CHCP at different power settings and at 4 different incubation time. The expression levels of the gene markers were determined at 4 different intervals after the treatment. The protein expression of BCL2A1 was only induced after CHCP treatment in TNBC cell lines (p < 0.01), whereas the HER2-positive and ER, PR positive cell lines showed little or no expression of BCL2A1. The BCL2A1 and TNF-alpha expression levels showed a significant correlation within TNBC cell lines (p < 0.01). Silencing BCL2A1 mRNA by siRNA increased the potency of the CHCP treatment. A Combination of CHCP and CPI203, a BET bromodomain inhibitor, and a BCL2A1 antagonist increased the CHCP-induced cell death (p < 0.05). Our results revealed that BCL2A1 is a key gene for resistance during CHCP induced cell death. This resistance in TNBCs could be reversed with a combination of siRNA or BCL2A1 antagonist-CHCP therapy.
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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 | 0.000 | 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) | 0.003 | 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".