MétaCan
Menu
Back to cohort
Record W2471224563 · doi:10.1016/j.celrep.2016.06.051

Molecular Features of Subtype-Specific Progression from Ductal Carcinoma In Situ to Invasive Breast Cancer

2016· article· en· W2471224563 on OpenAlex
Robert Lesurf, Miriam R. R. Aure, Hanne Håberg Mørk, Valeria Vitelli, Torill Sauer, Jürgen Geisler, Solveig Hofvind, Elin Borgen, Anne‐Lise Børresen‐Dale, Olav Engebråten, Øystein Fodstad, Øystein Garred, Gry Aarum Geitvik, Rolf Kåresen, Bjørn Naume, Gunhild M. Mælandsmo, Hege G. Russnes, Ellen Schlichting, Thérese Sørlie, Ole Christian Lingjærde, Kristine Kleivi Sahlberg, Helle Kristine Skjerven, Britt Fritzman, Steinar Lundgren, Vessela N. Kristensen, Fredrik Wärnberg, Michael Hallett

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueCell Reports · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer Genomics and Diagnostics
Canadian institutionsMcGill UniversityMcGill University Health Centre
FundersNatural Sciences and Engineering Research Council of CanadaOslo universitetssykehus HFCanadian Institutes of Health ResearchKreftforeningenFaculty of Medicine, McGill UniversityMcGill UniversityU.S. Department of Defense
KeywordsBreast cancerBiologyTumor progressionDuctal carcinomaCancerDiseaseCancer researchCarcinoma in situIn situPathologyOncologyMedicineGenetics

Abstract

fetched live from OpenAlex

Breast cancer consists of at least five main molecular "intrinsic" subtypes that are reflected in both pre-invasive and invasive disease. Although previous studies have suggested that many of the molecular features of invasive breast cancer are established early, it is unclear what mechanisms drive progression and whether the mechanisms of progression are dependent or independent of subtype. We have generated mRNA, miRNA, and DNA copy-number profiles from a total of 59 in situ lesions and 85 invasive tumors in order to comprehensively identify those genes, signaling pathways, processes, and cell types that are involved in breast cancer progression. Our work provides evidence that there are molecular features associated with disease progression that are unique to the intrinsic subtypes. We additionally establish subtype-specific signatures that are able to identify a small proportion of pre-invasive tumors with expression profiles that resemble invasive carcinoma, indicating a higher likelihood of future disease progression.

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.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.089
Threshold uncertainty score0.397

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 head0.006
GPT teacher head0.227
Teacher spread0.221 · 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