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Record W3196473730 · doi:10.1038/s41467-021-25467-w

Single allele loss-of-function mutations select and sculpt conditional cooperative networks in breast cancer

2021· article· en· W3196473730 on OpenAlexafffund
Nathan F. Schachter, Jessica R. Adams, Patryk Skowron, Katelyn J. Kozma, Christian A. Lee, Nandini Raghuram, Joanna Yang, Amanda J. Loch, Wei Wang, Aaron Kucharczuk, Katherine L. Wright, Rita M. Quintana, Yeji An, Daniel Dotzko, Jennifer L. Gorman, Daria Wojtal, Juhi S. Shah, Paúl León-Goméz, Giovanna Pellecchia, Adam J. Dupuy, Charles M. Perou, Ittai Ben‐Porath, Rotem Karni, Eldad Zacksenhaus, Susan J. Done, Livia Garzia, A. Sorana Morrissy, Jüri Reimand, Michael D. Taylor, Sean E. Egan

Bibliographic record

VenueNature Communications · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer Genomics and Diagnostics
Canadian institutionsUniversity of CalgaryMcGill UniversityPrincess Margaret Cancer CentreSinai Health SystemLunenfeld-Tanenbaum Research InstituteUniversity Health NetworkUniversity of TorontoSickKids FoundationHospital for Sick ChildrenOntario Institute for Cancer Research
FundersCongressionally Directed Medical Research ProgramsNatural Sciences and Engineering Research Council of CanadaCanadian Cancer Society Research InstituteCanadian Institutes of Health ResearchTerry Fox FoundationCanadian International Development AgencyU.S. Department of DefenseInternational Development Research CentreGovernment of Canada
KeywordsBiologyHaploinsufficiencyGeneticsAlleleSuppressorBreast cancerGeneChromosomeCancer researchCancerPhenotype

Abstract

fetched live from OpenAlex

Abstract The most common events in breast cancer (BC) involve chromosome arm losses and gains. Here we describe identification of 1089 gene-centric common insertion sites (gCIS) from transposon-based screens in 8 mouse models of BC. Some gCIS are driver-specific, others driver non-specific, and still others associated with tumor histology. Processes affected by driver-specific and histology-specific mutations include well-known cancer pathways. Driver non-specific gCIS target the Mediator complex, Ca ++ signaling, Cyclin D turnover, RNA-metabolism among other processes. Most gCIS show single allele disruption and many map to genomic regions showing high-frequency hemizygous loss in human BC. Two gCIS, Nf1 and Trps1 , show synthetic haploinsufficient tumor suppressor activity. Many gCIS act on the same pathway responsible for tumor initiation, thereby selecting and sculpting just enough and just right signaling. These data highlight ~1000 genes with predicted conditional haploinsufficient tumor suppressor function and the potential to promote chromosome arm loss in BC.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.495
Threshold uncertainty score0.307

Codex and Gemma teacher scores by category

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

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.

Opus teacher head0.010
GPT teacher head0.278
Teacher spread0.268 · 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 teacher head, 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

Citations17
Published2021
Admission routes2
Has abstractyes

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