Abberations in bilateral breast cancer
Bibliographic record
Abstract
AACR Annual Meeting-- Apr 14-18, 2007; Los Angeles, CA 2963 Introduction: 0.7% of women diagnosed with breast cancer will develop a second primary cancer and, this scenario is called Bilateral Breast Cancer (BiBC). It has been reported that BiBC accounts for 2-11% of all breast cancer cases. BiBC has the greatest concordance with familial history and early onset of disease occurrence. Mutations in known genes such as BRCA1 , BRCA2 , TP53 , PTEN and CHEK2 account for one third of the hereditary breast cancer cases thus leaving the majority of the genetic culprits unidentified. Genetic instability is a characteristic of malignant cells. Paired organs, such as the breast, offer a unique opportunity to study the genetic causal events in breast cancer such that the cells that become malignant in both primary occurrences are identical in terms of original genetic make-up and exposure to environmental factors. Removing these variables will facilitate the discovery of genetic mechanisms that lead to the development of breast cancer. Recently, several groups have preliminarily investigated both familial and sporadic BiBC disease using low-resolution technology thus identifying large regions of chromosomal alteration ranging from several megabases to entire chromosomal arms, which encompass a large number of genes. >Hypothesis: Comparison of somatic genetic alterations in matched bilateral breast tumours and matched normal tissue will allow us to distinguish the discrete causal events from the random genetic changes that are associated with genetic instability in tumours. Relevant alterations would appear in both sets of tumours and would suggest a role in disease development. >Results: In this study, we use a whole genome tiling resolution array CGH platform (SMRT aCGH), which allows for breakpoint detection at approximately 80 kb resolution, to identify discrete regions of genetic alterations in ten pairs of BiBC. Genes within regions of alteration that are common to the first and second occurrence groups are assessed for downstream expression effects using the Affymetrix HuU133 plus 2.0 platform. A subset of cases have been further evaluated for copy number variation in the human population without cancer. >Conclusion: We have identified commonly altered regions in bilateral specimens and have corrleated the genes within these loci to expression patterns which may be valuable in defining the subset of patients who need to be monitored more carefully after the first malignancy.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.061 | 0.011 |
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".