Somatic mutations in early onset luminal breast cancer
Bibliographic record
Abstract
// Giselly Encinas 1, * , Veronica Y. Sabelnykova 2, * , Eduardo Carneiro de Lyra 3 , Maria Lucia Hirata Katayama 1 , Simone Maistro 1 , Pedro Wilson Mompean de Vasconcellos Valle 1 , Gláucia Fernanda de Lima Pereira 1 , Lívia Munhoz Rodrigues 1 , Pedro Adolpho de Menezes Pacheco Serio 1 , Ana Carolina Ribeiro Chaves de Gouvêa 1 , Felipe Correa Geyer 1 , Ricardo Alves Basso 3 , Fátima Solange Pasini 1 , Maria del Pilar Esteves Diz 1 , Maria Mitzi Brentani 1 , João Carlos Guedes Sampaio Góes 3 , Roger Chammas 1 , Paul C. Boutros 2, 4, 5 and Maria Aparecida Azevedo Koike Folgueira 1 1 Instituto do Cancer do Estado de Sao Paulo, Departamento de Radiologia e Oncologia, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, SP, Brazil 2 Ontario Institute for Cancer Research, Toronto, Canada 3 Instituto Brasileiro de Controle do Câncer, São Paulo, Brazil 4 Department of Medical Biophysics, University of Toronto, Toronto, Canada 5 Department of Pharmacology and Toxicology, University of Toronto, Toronto, Canada * These authors have contributed equally to this work Correspondence to: Maria Aparecida Azevedo Koike Folgueira, email: maria.folgueira@fm.usp.br Keywords: breast cancer; young patients; somatic mutation; germline mutation; luminal subtype Received: September 26, 2017 Accepted: March 06, 2018 Published: April 27, 2018 ABSTRACT Breast cancer arising in very young patients may be biologically distinct; however, these tumors have been less well studied. We characterized a group of very young patients (≤ 35 years) for BRCA germline mutation and for somatic mutations in luminal ( HER2 negative) breast cancer. Thirteen of 79 unselected very young patients were BRCA 1/2 germline mutation carriers. Of the non- BRCA tumors, eight with luminal subtype ( HER2 negative) were submitted for whole exome sequencing and integrated with 29 luminal samples from the COSMIC database or previous literature for analysis. We identified C to T single nucleotide variants (SNVs) as the most common base-change. A median of six candidate driver genes was mutated by SNVs in each sample and the most frequently mutated genes were PIK3CA, GATA3, TP53 and MAP2K4 . Potential cancer drivers affected in the present non- BRCA tumors include GRHL2, PIK3AP1, CACNA1E , SEMA6D , SMURF2 , RSBN1 and MTHFD2. Sixteen out of 37 luminal tumors (43%) harbored SNVs in DNA repair genes, such as ATR, BAP1, ERCC6, FANCD2, FANCL, MLH1 , MUTYH, PALB2, POLD1, POLE , RAD9A, RAD51 and TP53 , and 54% presented pathogenic mutations (frameshift or nonsense) in at least one gene involved in gene transcription. The differential biology of luminal early-age onset breast cancer needs a deeper genomic investigation.
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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) | 0.000 | 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) | 0.000 | 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".