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Record W4390174665 · doi:10.3390/genes15010027

The Mutational Spectrum of Pre- and Post-Neoadjuvant Chemotherapy Triple-Negative Breast Cancers

2023· article· en· W4390174665 on OpenAlexafffund
Adriana Aguilar‐Mahecha, Najmeh Alirezaie, Josiane Lafleur, Eric Bareke, Ewa Przybytkowski, Cathy Lan, Luca Cavallone, Myriam Salem, Manuela Pelmus, Olga Aleynikova, Celia M.T. Greenwood, Amanda Lovato, Cristiano Ferrario, Jean-François Boileau, Catalin Mihalcioiu, Josée-Anne Roy, Elizabeth Marcus, Federico Discepola, Jacek Majewski, Mark Basik

Bibliographic record

VenueGenes · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer Genomics and Diagnostics
Canadian institutionsHôpital du Sacré-Cœur de MontréalMcGill University Health CentreMcGill UniversityJewish General Hospital
FundersFonds de Recherche du Québec - SantéJewish General HospitalFondation de l'Hôpital général juifFondation du cancer du sein du QuébecUniversité de MontréalMcGill University Health CentreMcGill University
KeywordsChemotherapyTriple-negative breast cancerCancer researchBiologyExome sequencingBreast cancerMutationGeneCancerGenetics

Abstract

fetched live from OpenAlex

The response of triple-negative breast cancer (TNBC) patients to pre-operative (neoadjuvant chemotherapy) is a critical factor of their outcome. To determine the effects of chemotherapy on the tumor genome and to identify mutations associated with chemoresistance and sensitivity, we performed whole exome sequencing on pre/post-chemotherapy tumors and matched lymphocytes from 26 patients. We observed great inter-tumoral heterogeneity with no gene mutated recurrently in more than four tumors besides TP53. Although the degree of response to chemotherapy in residual tumors was associated with more subclonal changes during chemotherapy, there was minimal evolution between pre/post-tumors. Indeed, gene sets enriched for mutations in pre- and post-chemotherapy tumors were very similar and reflected genes involved in the biological process of neurogenesis. Somatically mutated genes present in chemosensitive tumors included COL1A2, PRMD15, APOBEC3B, PALB2 and histone protein encoding genes, while BRCA1, ATR, ARID1A, XRCC3 and genes encoding for tubulin-associated proteins were present in the chemoresistant tumors. We also found that the mutational spectrum of post-chemotherapy tumors was more reflective of matching metastatic tumor biopsies than pre-chemotherapy samples. These findings support a portrait of modest ongoing genomic instability with respect to single-nucleotide variants induced by or selected for by chemotherapy in TNBCs.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.411
Threshold uncertainty score0.228

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 head0.005
GPT teacher head0.239
Teacher spread0.234 · 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 designBench or experimental
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

Citations0
Published2023
Admission routes2
Has abstractyes

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