High HSP90 Expression Is Associated with Decreased Survival in Breast Cancer
Bibliographic record
Abstract
The heat shock protein HSP90 chaperones proteins implicated in breast cancer progression, including Her2/neu. HSP90-targeting agents are in clinical trials for breast cancer. HSP90 expression is high in breast cancer cell lines, yet no large studies have been conducted on expression in human tumors and the association with clinical/pathologic variables. Tissue microarrays containing 10 cell lines and primary specimens from 655 patients with 10-year follow-up were assessed using our automated quantitative analysis (AQUA) method; we used cytokeratin to define pixels as breast cancer (tumor mask) within the array spot and measured HSP90 expression within the mask using Cy5-conjugated antibodies. We similarly assessed estrogen receptor, progesterone receptor, and Her2/neu expression. HSP90 expression was more variable in human tumors than in cell lines (P < 0.0001). High HSP90 expression was associated with decreased survival (P = 0.0024). On multivariable analysis, high HSP90 expression remained an independent prognostic marker. High HSP90 expression was associated with high Her2/neu and estrogen receptor, large tumors, high nuclear grade, and lymph node involvement. Although HSP90 levels were high in all our cell lines, expression in tumors was more variable. High HSP90 expression in primary breast cancer defines a population of patients with decreased survival. Evaluation of HSP90 expression in early-stage breast cancer may identify a subset of patients requiring more aggressive or pathway-targeted treatment. Prospective studies are needed to confirm the prognostic role of HSP90, as well as the predictive role of HSP90 expression in patients treated with HSP90 inhibitors.
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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 | 0.001 |
| 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".