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Circulating tumor DNA (ctDNA) during and after neoadjuvant chemotherapy and prior to surgery is a powerful prognostic factor in triple-negative breast cancer (TNBC).

2019· article· en· W2947171618 on OpenAlexaff
Luca Cavallone, Adriana Aguilar, Mohammed Aldamry, Josiane Lafleur, Susie Brousse, Cathy Lan, Najmeh Alirezaie, Eric Bareke, Jacek Majewski, Manuela Pelmus, Cristiano Ferrario, Elizabeth A. Marcus, André Robidoux, Federico Discepola, Mark Basik

Bibliographic record

VenueJournal of Clinical Oncology · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer Genomics and Diagnostics
Canadian institutionsCentre Hospitalier de l’Université de MontréalMcGill UniversityJewish General Hospital
Fundersnot available
KeywordsMedicineChemotherapyDigital polymerase chain reactionBreast cancerOncologyTriple-negative breast cancerInternal medicineStage (stratigraphy)CancerNeoadjuvant therapyExomeExome sequencingMutationGenePolymerase chain reactionBiology

Abstract

fetched live from OpenAlex

594 Background: TNBC, the most aggressive form of breast cancer, is treated primarily with chemotherapy, even before surgery (neoadjuvant chemotherapy or NAC). The prognosis and need for adjuvant therapy depends greatly on the tumor response assessed by pathology (pCR). Highly sensitive and specific ctDNA assays have been shown to be of prognostic value in the metastatic settingbut not yet in earlier settings. Methods: Tissue was collected from 26 Q-CROC-03 clinical trial TNBC patients before, during and after NAC, prior to surgery. Whole exome sequencing on tumor tissues was used to select single nucleotide variants with high allele frequency (VAF), prioritizing TP53, to generateindividual digital droplet PCR (ddPCR) assays. An average of 5 variants (range 1-12) per patient were tested, for a total of 121 variants. A detection threshold was defined for each variant from a pool of normal controls. Median follow-up was 55 months. Results: ctDNA was detectable in 96% of patients at baseline, but 20% of the 121 variants were not detectable at any time point. At baseline, the mean VAF of all analyzed variants, but not of TP53 variants alone, was significantly correlated (p < 0.05) with tumor factors (tumor size, stage, grade, nodal status before and at surgery, RCB score) but not with patient age or BRCA1/2 mutation status. 87 variants (74%) were detected at baseline and their VAF fell by 86% after 1 cycle of chemotherapy (T1). The detection of ctDNA at T1 was associated with DFS (p = 0.027) while the detection of ctDNA at the last post-chemotherapy pre-surgery time point (T4) was strongly associated with pathological complete response (pCR) and both DFS (p = 0.013) and OS(p = 0.006). At this time point, 5 of 41 variants (12%) were detected in pCR patients vs 42 of 80 (53%) in non-pCR, while only 6 of the 15 (40%) non-pCR patients had detectable TP53 variants. Interestingly, for variants detected at baseline, the positive predictive value of T4 ctDNA for disease recurrence was 69%, similar to that of non-pCR, while the negative predictive value of no ctDNA at T4 was 89% for disease recurrence vs 80% for pCR. Conclusions: ctDNA detection after NAC prior to surgery is strongly predictive of disease-free survival and overall survival and is comparable to pCR as a prognostic factor in our cohort (NCT01276899).

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)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
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)0.0020.000

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 head0.023
GPT teacher head0.353
Teacher spread0.330 · 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".

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Citations8
Published2019
Admission routes1
Has abstractyes

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