Prospective Monitoring of Circulating Epithelial Tumor Cells (CETC) Reveals Changes in Gene Expression during Adjuvant Radiotherapy of Breast Cancer Patients
Bibliographic record
Abstract
Circulating epithelial tumor cells (CETC) are considered to be responsible for the formation of metastases. Therefore, their importance as prognostic and/or predictive markers in breast cancer is being intensively investigated. Here, the reliability of single cell expression analyses in isolated and collected CETC from whole blood samples of patients with early-stage breast cancer before and after radiotherapy (RT) using the maintrac® method was investigated. Single-cell expression analyses were performed with qRT-PCR on a panel of selected genes: GAPDH, EpCAM, NANOG, Bcl-2, TLR 4, COX-2, PIK3CA, Her-2/neu, Vimentin, c-Met, Ki-67. In all patients, viable CETC were detected prior to and at the end of radiotherapy. In 7 of the 9 (77.8%) subjects examined, the CETC number at the end of the radiotherapy series was higher than before. The majority of genes analyzed showed increased expression after completion of radiotherapy compared to baseline. Procedures and methods used in this pilot study proved to be feasible. The method is suitable for further investigation of the underlying molecular biological mechanisms occurring in cells surviving radiotherapy and possibly the development of radiation resistance.
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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 | 0.000 | 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".