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Record W4393075281 · doi:10.1158/1538-7445.am2024-2429

Abstract 2429: Longitudinal ctDNA monitoring using a high sensitivity tumor-informed assay in patients with metastatic HR+/HER2− breast cancer receiving endocrine therapy and CDK4/6 inhibitors

2024· article· en· W4393075281 on OpenAlexaff
Jesús Fuentes‐Antrás, Mitchell J. Elliott, Philippe Echelard, Aaron Dou, Zachary Veitch, Philippe L. Bédard, Eitan Amir, Michelle B. Nadler, Nicholas Meti, Nancy Gregorio, Elizabeth Shah, Emily Van de Laar, Celeste Yu, Lisa Gates, Clodagh Murray, Christopher G. Smith, A. Chevalier, Lillian L. Siu, Hal K. Berman, David W. Cescon

Bibliographic record

VenueCancer Research · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer Genomics and Diagnostics
Canadian institutionsSt Mary's Hospital CentrePrincess Margaret Cancer Centre
Fundersnot available
KeywordsMedicineMetastatic breast cancerOncologyInternal medicineEndocrine systemBreast cancerCancerFulvestrantCancer researchTamoxifenHormone

Abstract

fetched live from OpenAlex

Abstract BACKGROUND: ctDNA burden is prognostic and its dynamics during therapy may permit innovative strategies in metastatic breast cancer (mBC). Previous analyses have focused on driver genes, with limited sensitivity to quantify depth of response or detect early molecular progression. To enable sensitive, quantitative ctDNA monitoring, we analyzed samples from a cohort of HR+/HER2− mBC pts treated with endocrine therapy (ET) and CDK4/6 inhibitors (CDKi) using RaDaR, a patient-specific assay that tracks tumor-informed truncal variants independent of driver status with a limit of detection of 0.001%. METHODS: HR+/HER2− mBC pts receiving standard ET + CDKi were enrolled in a prospective observational cohort from 2018. Plasma samples were collected at baseline (BL), within 30 days (d), and ~q3 months (mo) with radiological scans. RaDaR was performed on all samples for pts with tissue available for WES (as per assay). Clinico-pathological variables were collected. Endpoints were time to treatment failure (TTF) and overall survival (OS). RESULTS: 51 pts were available for analysis. Median age was 60 years (range 38-88), 63% had visceral disease, and most pts were treated as first (75%) or second (20%) line. RaDaR was successful on 43 pts, with the rest dropping out due to failed WES (1) or panel failure (7). Archival tissue WES was used to design bespoke assays targeting a median 48 (23-52) variants in 248 samples, with a median of 5 samples/pt (2-14) collected over a median follow up of 27.8 (0.9-64.3) mo. ctDNA was detected in 91% (39/43) of BL and 70% (174/248) of all samples, with a median estimated variant allele fraction (eVAF) of 0.05%. Higher BL eVAFs were associated with liver disease (p=0.02) and with shorter TTF (p<0.01 adjusted by age and visceral disease) and OS (p<0.01). 36/39 pts had ≥1 sample with ctDNA decrease from BL, occurring within the first mo of therapy in 77% (24/31) of pts with available early samples. In 13 pts ctDNA became undetectable (‘suppressed’) at a median time (T) of 157 d (14-343). Among 25 pts with treatment failure (TF), the median T from the last negative/decreasing eVAF to TF was 163 d (0-943). Only 3 pts with TF had prior negative ctDNA, occurring with a median lead T of 198 d (119-595). Among ongoing pts, the median T from the last ctDNA decrease to last follow up was 317 d (163-1508), and from the last negative ctDNA sample was 352 d (163-993). CONCLUSION: RaDaR enabled sensitive ctDNA monitoring in 91% HR+/HER2− mBC pts on ET + CDK4/6i. ctDNA levels were prognostic and fell rapidly with therapy, but suppression occurred in less than one-third of pts, taking a median of 5.2 mo. Pts with negative/decreasing ctDNA may require less frequent clinical/radiographic tumor evaluations. Highly sensitive ctDNA tracking may inform prognostic assessments, follow up strategies, and innovative interventional trial designs. Citation Format: Jesus Fuentes-Antras, Mitchell J. Elliott, Philippe Echelard, Aaron Dou, Zachary Veitch, Philippe L. Bedard, Eitan Amir, Michelle B. Nadler, Nicholas Meti, Nancy Gregorio, Elizabeth Shah, Emily Van de Laar, Celeste Yu, Lisa Gates, Clodagh Murray, Christopher G. Smith, Amber Chevalier, Lillian L. Siu, Hal K. Berman, David W. Cescon. Longitudinal ctDNA monitoring using a high sensitivity tumor-informed assay in patients with metastatic HR+/HER2− breast cancer receiving endocrine therapy and CDK4/6 inhibitors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2429.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0010.000

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 head0.046
GPT teacher head0.360
Teacher spread0.314 · 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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Citations0
Published2024
Admission routes1
Has abstractyes

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