Abstract P6-05-05: Signaling Pathways Activated in Her 2 and ER Negative Breast Cancers
Bibliographic record
Abstract
Abstract Introduction: Breast cancer is the most common cancer in women (192,370 new cases in 2009) and the second leading cause of cancer death (40,000) among women in USA. Current multimodality treatment of breast cancer is based on the level of ER expression and Her 2 gene amplification. However, no effective treatment is currently available for breast cancers with low level expression of ER and no amplification of Her 2 gene. The aim of this study is to identify protein pathways activated in the breast cancer with negative expression of ER and Her 2. Method: Protein Pathway Array was used to assess the level of protein expression and phosphorylation in 71 paired fresh frozen breast samples (tumor and adjacent benign tissue). A total 159 antibodies were evaluated which represent most important signal transduction pathways involved in proliferation, apoptosis, angiogenesis, invasion and metastasis. Several potential therapeutic kinase proteins were also assessed. Results: A total 20 proteins (PCNA, phospho-PTEN, cyclin B1 cyclin E1, CDK6, E-cadherin, NFkB, ect) were differentially expressed between normal and tumor tissues based on the statistical analysis. In Her 2 negative tumors (n=37), 3 proteins were differentially expressed and among them, 2 were up-regulated (CDK6 and HSD1) and 1 was down-regulated (IGF). In ER negative tumors (n=18), 4 proteins (HSD, SK, TDP and Slug) was up-regulated and 1 proteins were down-regulated (E-cadherin). In triple negative tumors (n=13), one protein (E-cadherin) down-regulated and 2 proteins (TDP and HSD) were up-regulated. Furthermore, based on the expression pattern of these proteins, tumors negative for both ER and Her 2 (n=15) can be clustered into 3 groups Figure 1: Subclassification of breast cancers negative for ER and Her-2 based protein pattern. Hierarchical clustering analysis of 20 differentially expressed proteins in 15 ER/Her-2 negative breast cancers. The cancers can be separated into 3 subtypes. Red indicates overexpression, green underexpression, black no change, and gray no expression. Each column represents a protein. Each row represents a sample. Conclusion: Our study showed that distinct sets of signaling pathways activated in ER and Her 2 negative breast cancers. The increased expression of cell cycle progression proteins in Her 2 negative tumors suggests activation of cell proliferation via different growth promotion pathway. Similarly, different cell proliferation pathways are also activated in ER negative tumors. This finding may be used to design future clinical trial based on the activation of different signaling pathways. Citation Information: Cancer Res 2010;70(24 Suppl):Abstract nr P6-05-05.
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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) | 0.005 | 0.001 |
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".