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Abstract A123: Circulating tumor DNA (ctDNA) genomic and epigenomic profiling (GuardantINFINITY) for diagnosis of DNA damage repair (DDR) loss of function (LOF) and response monitoring in the TRESR and ATTACC trials

2023· article· en· W4389227710 on OpenAlexaff
Ezra Y. Rosen, Joseph D. Schonhoft, Ian M. Silverman, Arielle Yablonovitch, Sunantha Sethuraman, Parham Nejad, Danielle Ulanet, Julia Yang, Insil Kim, Kezhen Fei, Yi Xu, Errin Lagow, Shile Zhang, Mingyang Cai, María Koehler, Benedito A. Carneiro, Stéphanie Lheureux, Michael Cecchini, Benjamin Herzberg, Jorge S. Reis‐Filho, Victoria Rimkunas, Timothy A. Yap

Bibliographic record

VenueMolecular Cancer Therapeutics · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer Genomics and Diagnostics
Canadian institutionsPrincess Margaret Cancer Centre
Fundersnot available
KeywordsOlaparibPALB2Cancer researchBiologyCHEK2BRCA2 ProteinInternal medicineOncologyGeneticsMedicineGermline mutationMutationGenePoly ADP ribose polymerase

Abstract

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Abstract Background First-generation panel-based ctDNA sequencing is widely used to identify actionable genomic alterations, but limited coverage and sensitivity hinder broader clinical utility, especially in cancers driven by DDR LOF. Further, tissue-free, variant-based approaches for response monitoring have several challenges, including the limited number and low variant allele frequencies (VAF) of monitorable variants and contamination from non-tumor-derived sources (eg, clonal hematopoiesis [CH]). Newer panels may address these challenges with broader coverage, optimized bioinformatics, and the integration of epigenetic analysis for molecular response (MR). Methods Blood samples were collected from 2 phase 1 studies (TRESR; NCT04497116 and ATTACC; NCT04972110) of the ataxia telangiectasia and Rad3-related (ATR) inhibitor camonsertib in combination with gemcitabine or PARPi (talazoparib, niraparib, or olaparib). Cell-free DNA and PBMCs were sequenced using the combined genomic (>800 genes) and methylation (15Mb) GuardantINFINITY platform. Results The study included 117 patients (pts) with ovarian (n=29), breast (n=18), pancreatic (n=18), prostate (n=16) and other (n=36) cancers, enrolled with pathogenic alterations in BRCA2 (n=41), ATM (n=32), BRCA1 (n=23), PALB2 (n=8) and other genes (n=13). Enrollment alterations identified by local NGS were confirmed in 83% (94/114) of pts excluding 3 enrolled by protein loss. 50% (5/10) of complex alterations (large deletions or rearrangements) with sufficient circulating tumor fraction (cTF) were confirmed. Among pts with breast, ovarian, prostate, or pancreatic cancers previously treated with PARPi and/or platinum and harboring BRCA1/2 or PALB2 alterations, reversions were detected in 31% (17/54), with 6 pts reverted by 1 or more large intragenic deletions. A CRC pt with a clonal biallelic sATM alteration had 2 missense reversions in cis, an event not previously reported to occur in ATM. In pts with matched PBMCs, confirmed CH alterations were detected in 79% (44/56), including 59% (33/56) with at least 1 CH variant over 1% VAF. 106 pts had evaluable paired samples at baseline and on-treatment (taken between 2-12 weeks on-treatment [median, 3 weeks]). Using mVAF of the Guardant360 74-gene subset or methylation-based cTF, 72% or 86% were monitorable, respectively. In the subset of evaluable pts with matched PBMC sequencing (n=54), after PBMC-informed CH filtering, monitorability was reduced from 69% to 61% between G360 mVAF and G360 mVAF-CH, respectively. PBMC-informed CH filtering improved the correlation between variant-based and methylation-based monitoring (G360 mVAF, R=0.89, p=1.1e-11 vs G360 mVAF-CH, R=0.95, p=3e-15; Pearson correlation). Correlation of ctDNA monitoring metrics with clinical outcomes is ongoing. Conclusions Broad panel coverage enabled accurate diagnosis of complex DDR LOF and detection of reversion alterations. Methylation-based cTF allows monitoring of most pts in this cohort and consistent with previous observations may avoid signal contamination from CH for robust MR analysis. Citation Format: Ezra Rosen, Joseph D Schonhoft, Ian M Silverman, Arielle Yablonovitch, Sunantha Sethuraman, Parham Nejad, Danielle Ulanet, Julia Yang, Insil Kim, Kezhen Fei, Yi Xu, Errin Lagow, Shile Zhang, Mingyang Cai, Maria Koehler, Benedito A Carneiro, Stephanie Lheureux, Michael Cecchini, Benjamin Herzberg, Jorge S Reis-Filho, Victoria Rimkunas, Timothy A Yap. Circulating tumor DNA (ctDNA) genomic and epigenomic profiling (GuardantINFINITY) for diagnosis of DNA damage repair (DDR) loss of function (LOF) and response monitoring in the TRESR and ATTACC trials [abstract]. In: Proceedings of the AACR-NCI-EORTC Virtual International Conference on Molecular Targets and Cancer Therapeutics; 2023 Oct 11-15; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2023;22(12 Suppl):Abstract nr A123.

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)0.002
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 score0.293
Threshold uncertainty score0.780

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.054
GPT teacher head0.326
Teacher spread0.272 · 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".

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Citations1
Published2023
Admission routes1
Has abstractyes

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