Assessment of Gene Expression Level of ATP Binding Cassette G Member 2 (ABCG2) Transporter in Newly Diagnosed Breast Cancer Patients Receiving Adjuvant Chemotherapy
Bibliographic record
Abstract
The efficacy of cancer chemotherapy is limited by cellular mechanisms of resistance that result in increased drug efflux of chemotherapeutic agents thereby reducing intracellular drug levels and causing drug resistance. Overexpression of some members of ATP binding cassette transporter superfamily, including ATP binding cassette G member 2 (ABCG2), which mediates energy-dependent transport of drugs out of the cells against concentration gradient, is one of the major mechanisms responsible for multidrug resistance in the treatment of breast cancer. In the current study, the expression of ABCG2 mRNA gene was evaluated in the peripheral blood of newly diagnosed breast cancer (NDBC) patients immediately before surgical resection of the breast and in extirpated breast tumors, then sequentially in the blood of patients after receiving three and six cycles of chemotherapy. Compared to normal breast, cancerous specimens expressed higher levels of ABCG2 gene expression (p<0.001). In addition, a gradual significant increase in the expression of peripheral blood ABCG2 gene of NDBC patients among different treatment periods was recorded. Furthermore, a significant positive correlation between peripheral blood ABCG2 gene expression of NDBC patients receiving chemotherapy and disease progression was found. In conclusion, assessment of ABCG2 gene expression may be a prerequisite in evaluating the effectiveness of chemotherapy-treated breast cancer patients.
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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) | 0.001 | 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".