Transcriptional signature of lymphoblastoid cell lines of<i>BRCA1</i>,<i>BRCA2</i>and non-<i>BRCA1/2</i>high risk breast cancer families
Bibliographic record
Abstract
// Marie-Christine Pouliot 1 , Charu Kothari 1 , Charles Joly-Beauparlant 1 , Yvan Labrie 1 , Geneviève Ouellette 1 , Jacques Simard 1 , Arnaud Droit 1 and Francine Durocher 1 1 CHU de Québec Research Centre-Université Laval, Department of Molecular Medicine, Québec, Canada Correspondence to: Francine Durocher, email: Francine.Durocher@crchudequebec.ulaval.ca Keywords: hereditary breast cancer, high-risk BRCA1/2 /X families, gene expression, RNA-seq, lymphoblastoid cell lines Received: September 28, 2016     Accepted: July 17, 2017     Published: August 12, 2017 ABSTRACT Approximately 25% of hereditary breast cancer cases are associated with a strong familial history which can be explained by mutations in BRCA1 or BRCA2 and other lower penetrance genes. The remaining high-risk families could be classified as BRCAX (non- BRCA1/2 ) families. Gene expression involving alternative splicing represents a well-known mechanism regulating the expression of multiple transcripts, which could be involved in cancer development. Thus using RNA-seq methodology, the analysis of transcriptome was undertaken to potentially reveal transcripts implicated in breast cancer susceptibility and development. RNA was extracted from immortalized lymphoblastoid cell lines of 117 women (affected and unaffected) coming from BRCA1 , BRCA2 and BRCAX families. Anova analysis revealed a total of 95 transcripts corresponding to 85 different genes differentially expressed (Bonferroni corrected p-value <0.01) between those groups. Hierarchical clustering allowed distinctive subgrouping of BRCA1/2 subgroups from BRCAX individuals. We found 67 transcripts, which could discriminate BRCAX from BRCA1/BRCA2 individuals while 28 transcripts discriminate affected from unaffected BRCAX individuals. To our knowledge, this represents the first study identifying transcripts differentially expressed in lymphoblastoid cell lines from major classes of mutation-related breast cancer subgroups, namely BRCA1 , BRCA2 and BRCAX. Moreover, some transcripts could discriminate affected from unaffected BRCAX individuals, which could represent potential therapeutic targets for breast cancer treatment.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".