Abstract P2-11-01: Molecular Profiling Identifies Differentially Expressed Genes between Normal Breast Tissue from <i>BRCA</i> Carriers and Women at Population Risk
Bibliographic record
Abstract
Abstract Background: Women found to carry a BRCA1 or BRCA2 gene mutation are at significant risk of future breast cancer (BC). Prophylactic mastectomy (PM) remains the most effective risk reducing strategy in that setting. Thus far, there are no data available identifying changes in gene expression profiles prior to the onset of BC in these women using microarray technology. Material and methods : In this pilot study, we prospectively collected PM specimens from BRCA1/2 mutation carriers (n=21), and reduction mammoplasty (RM) specimens from healthy controls at population risk of breast cancer (n=13). Samples were collected from all 4 quadrants (fresh frozen) and careful histological examination was conducted. Selected samples (most dense parenchymal tissue) were sent for microarray analyses (19K chip, http://www.uhnres.utoronto.ca/facilities/index.htm). We compared the molecular profiles of breast tissue obtained from these two groups using two approaches: 1) microarray analysis for a global assessment of gene expression, and 2) gene set analysis to identify differences based on cellular function and biologic themes. Results: Women in each group were of similar age (p=NS). No invasive cancer was identified. In histologically normal breast tissue, class comparison identified differential gene expression between RM and PM tissues. Gene set analysis of five collections including MSigDB C2, C4, cytobands, Stanford 5Mb chromosomal tiles and KEGG database identified 22 significant gene sets. Nine sets were overexpressed and 13 sets were underexpressed in PM tissues (FDR < 0.2; p < 0.012). We found overexpression of genes relating to proliferation and transcription specifically in the PM tissues enriched for Gene Ontology annotations. The top 200 genes ranked by SAM were also examined by pathway analysis that showed high enrichment for cancer related pathways. All three approaches implicated T cell receptor signaling and a TSG101-stathmin breast cancer related pathway as contributing to the differential molecular profiles between RM and PM tissues. Discussion: We have shown differential expression of single genes as well as cancer related biologic pathways (using microarray and gene set analyses) between normal breast tissue from BRCA1/2 mutation carriers (at high risk of BC) and healthy controls (at population risk of BC). These differences may represent early molecular defects of genetic pathways potentially involved in the early stages of breast carcinogenesis in women at hereditary high risk or may represent the result of BRCA1/2 haploinsufficiency. These results support the hypothesis that molecular pathways leading to BC formation are unique to BRCA1/2 carriers. This information may help the development of innovative preventive strategies for BRCA carriers in the future. Citation Information: Cancer Res 2010;70(24 Suppl):Abstract nr P2-11-01.
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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 | 0.001 | 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) | 0.003 | 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".