GRP78 as a Novel Predictor of Responsiveness to Chemotherapy in Breast Cancer
Bibliographic record
Abstract
The discovery of predictive factors for chemoresistance is critical for improving adjuvant therapy for cancer patients. The 78-kDa glucose-regulated protein (GRP78), widely used as an indicator of the unfolded protein response (UPR), is induced in the tumor microenvironment. In vitro studies suggest that GRP78 confers chemoresistance to topoisomerase inhibitors, such as Adriamycin (doxorubicin). Here, we report on a retrospective cohort study of 127 stage II and III breast cancer patients who were treated with Adriamycin-based chemotherapy. Archival tumor specimens were available for analysis and the relationship of GRP78 expression level to "time to recurrence" (TTR), used as a surrogate marker for drug resistance, was examined. Our data show that 67% of the study subjects expressed high level of GRP78 in their tumors before the initiation of chemotherapy and suggest an association between GRP78 positivity and shorter TTR [hazard ratio (HR), 1.78; P = 0.16]. Interestingly, subgroup analysis reveals that the HR for the GRP78-positive group increased significantly among patients who did not receive further taxane treatment (HR, 3.00; P = 0.022) and among mastectomy patients (HR, 3.33; P = 0.027). The HR was even stronger among mastectomy patients who did not receive further taxane treatment (HR, 4.82; P = 0.010). The use of GRP78 as a predictor for chemoresponsiveness and the potential interaction of GRP78 and/or the UPR pathways with taxanes warrant larger studies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".