Abstract 3940: Identifying novel susceptibility genes in genomic aberrant regions in early-onset breast cancer
Bibliographic record
Abstract
Abstract Several genes have been implicated in hereditary breast cancer, but account for a fraction of all hereditary cases. We hypothesize that other genes are involved in susceptibility and progression of breast cancer and will be represented as chromosomal losses and gains that can be detected in tumors from breast cancer patients who are at high risk of carrying mutations in breast cancer susceptibility genes other than BRCA1 and BRCA2. We have focused on women with personal (diagnosis < 40 years) and family (at least one affected sister) histories of breast cancer and are not carriers of mutations in known cancer susceptibility genes. Blocks of formalin fixed and paraffin embedded (FFPE) tumor tissue from early age of onset breast cancer patients have been retrieved from the Ontario site of the Breast Cancer Family Registry. Each case is reviewed by a pathologist and tumor material is selected for micro-dissection. We have been using Illumina's high resolution genomic single nucleotide polymophism (SNP) microarrays to identify and characterize changes in germline and tumor DNA from women with early-onset breast cancer. By using SNPs to determine DNA copy numbers of the tumor and germline DNA from each case, we will differentiate changes in the genomes that are specific to the tumors. I have modified and optimized the protocols for which DNA is extracted and prepared from microdissected FFPE tumor cases prior to hybridization onto microarrays which improves the SNP call rate of FFPE. In a comparison of SNP microarray copy number analysis in cases for which we have archival and matching fresh frozen tumor DNAs, 80% deleted and amplified regions delineated in FFPE samples were detected in the matching fresh frozen reference. These results lead us to be confident that FFPE treated tumor tissues used in our study are a viable resource of for which novel genes involved in breast cancer can be discovered. On SNP microarrays, we have so far evaluated 25 early-onset cases for which both tumor and germline DNA have been hybridized. Recurrent regions of aberration include gains in 6p21.1 and 8q24 in 24% of cases and losses in 11q22.3 and 9q21.13 in 44% and 24% of cases, respectively. Interesting, our initial analysis shows gains in CCND1 and CCND3 in 14% and 24% of cases, implicating cell cycle regulation genes as frequently aberrant in copy number. With access to the germline DNA, normal variation can be accounted for, while regions of LOH can be found in the tumors. Validated recurrently amplified and deleted regions in tumor samples containing candidate genes, onco- and tumor suppressing genes will be further studied for their role in breast cancer through functional analysis. This study is very likely to have significance, not only for our understanding of hereditary breast cancer, but also for the more common non-hereditary form of breast cancer. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 3940. doi:10.1158/1538-7445.AM2011-3940
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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 | 0.001 |
| 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) | 0.005 | 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".