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Record W2082887122 · doi:10.1038/nature11154

Sequence analysis of mutations and translocations across breast cancer subtypes

2012· article· en· W2082887122 on OpenAlexfundno aff
Shantanu Banerji, Kristian Cibulskis, Claudia Rangel‐Escareño, Kristin Brown, Scott L. Carter, A. Matsen Frederick, Michael S. Lawrence, Andrey Sivachenko, Carrie Sougnez, Lihua Zou, Maria L. Cortés, Juan Carlos Fernández-López, Shouyong Peng, Kristin Ardlie, Daniel Auclair, Verónica Bautista‐Piña, Fujiko Duke, Joshua M. Francis, Joonil Jung, Antonio Maffuz‐Aziz, Robert C. Onofrio, Melissa Parkin, Nam Pho, Valeria Quintanar‐Jurado, Alex H. Ramos, Rosa Rebollar‐Vega, Sergio Rodríguez‐Cuevas, Sandra Romero‐Córdoba, Steven E. Schumacher, Nicolas Stransky, Kristin Thompson, Laura Uribe-Figueroa, José Baselga, Rameen Beroukhim, Kornélia Polyák, Dennis C. Sgroi, Andrea L. Richardson, Gerardo Jiménez‐Sánchez, Eric S. Lander, Stacey Gabriel, Levi A. Garraway, Todd R. Golub, Jorge Meléndez-Zajgla, Alex Toker, Gad Getz, Alfredo Hidalgo‐Miranda, Matthew Meyerson

Bibliographic record

VenueNature · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer Genomics and Diagnostics
Canadian institutionsnot available
FundersNational Human Genome Research InstituteInstituto Nacional de Medicina GenómicaNational Cancer InstituteNational Institutes of HealthInstituto Carlos Slim de la SaludBroad InstituteUniversity of ManitobaHoward Hughes Medical Institute
KeywordsBreast cancerBiologyCancer researchFusion geneCancerAKT1Germline mutationGeneticsGATA3Targeted therapyGeneMutationPI3K/AKT/mTOR pathwayTranscription factor

Abstract

fetched live from OpenAlex

This paper reports one of the largest breast cancer whole-exome and whole-genome sequencing efforts so far, identifying previously unknown recurrent mutations in CBFB, deletions of RUNX1 and recurrent MAGI1–AKT3 fusion; the fusion suggests that the use of ATP-competitive AKT inhibitors should be evaluated in clinical trials. This paper reports one of the largest whole-exome sequencing efforts in human breast cancers so far, complemented by whole-genome sequences of 22 breast cancer/normal pairs. The authors analysed diverse subtypes from patients in Mexico and Vietnam and identified recurrent mutations in the CBFB transcription factor gene and deletions of its partner RUNX1, as well as a recurrent MAGI3–AKT3 fusion enriched in triple-negative breast cancers (those lacking oestrogen and progesterone receptors and ERBB2 expression). The fusion leads to constitutive activation of AKT kinase, which can be counteracted by treatment with a small-molecule inhibitor. Breast carcinoma is the leading cause of cancer-related mortality in women worldwide, with an estimated 1.38 million new cases and 458,000 deaths in 2008 alone1. This malignancy represents a heterogeneous group of tumours with characteristic molecular features, prognosis and responses to available therapy2,3,4. Recurrent somatic alterations in breast cancer have been described, including mutations and copy number alterations, notably ERBB2 amplifications, the first successful therapy target defined by a genomic aberration5. Previous DNA sequencing studies of breast cancer genomes have revealed additional candidate mutations and gene rearrangements6,7,8,9,10. Here we report the whole-exome sequences of DNA from 103 human breast cancers of diverse subtypes from patients in Mexico and Vietnam compared to matched-normal DNA, together with whole-genome sequences of 22 breast cancer/normal pairs. Beyond confirming recurrent somatic mutations in PIK3CA11, TP536, AKT112, GATA313 and MAP3K110, we discovered recurrent mutations in the CBFB transcription factor gene and deletions of its partner RUNX1. Furthermore, we have identified a recurrent MAGI3–AKT3 fusion enriched in triple-negative breast cancer lacking oestrogen and progesterone receptors and ERBB2 expression. The MAGI3–AKT3 fusion leads to constitutive activation of AKT kinase, which is abolished by treatment with an ATP-competitive AKT small-molecule inhibitor.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.008
GPT teacher head0.310
Teacher spread0.301 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1,203
Published2012
Admission routes1
Has abstractyes

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