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Record W2740869922 · doi:10.1158/1538-7445.am2017-2473

Abstract 2473: Breast cancer whole genomes link homologous recombination deficiency (HRD) with therapeutic outcomes

2017· article· en· W2740869922 on OpenAlexaff
Eric Y. Stutheit-Zhao, Yaoqing Shen, Erin Pleasance, Martin Jones, Carolyn Ch’ng, Caralyn Reisle, Peter Eirew, Karen Mungall, Nina Thiessen, Yussanne Ma, Alexandra Fok, Andrew J. Mungall, Yongjun Zhao, Richard A. Moore, Diego Villa, Tamara Shenkier, Caroline Lohrisch, Stephen Chia, Stephen Yip, Karen A. Gelmon, Howard J. Lim, Sophie Sun, Kasmintan A. Schrader, Sean Young, Aly Karsan, Robyn Roscoe, Janessa Laskin, Marco A. Marra, Steven J.M. Jones

Bibliographic record

VenueCancer Research · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer Genomics and Diagnostics
Canadian institutionsUniversity of British ColumbiaBC Cancer AgencyCanada's Michael Smith Genome Sciences Centre
Fundersnot available
KeywordsBreast cancerOncologyCancerGenome instabilityMedicinePARP inhibitorGermline mutationInternal medicineGeneticsBiologyMutationGeneDNA

Abstract

fetched live from OpenAlex

Abstract Background: Homologous recombination deficiency (HRD) is common in cancer - germline BRCA1 & BRCA2 mutations account for 5-10% of breast cancers and confer 85% lifetime risk. HRD cancers exhibit genomic instability and sensitivity to platinum-based therapy and PARP inhibitors. While not all causes of HRD are known, recent sequencing efforts have revealed genome-wide somatic mutation signatures that characterize the HRD genomic instability phenotype, also known as “BRCA-ness”. This provides a promising new assay to predict sensitivity to platinum-based therapy. Here, we integrate two whole-genome sequencing metrics to assess their association with therapeutic outcomes in a breast cancer cohort. Methods: Whole-genome sequencing of 47 breast cancer tumors (100x coverage) and matched normals (60x) was performed on an Illumina HiSeq. Alignment, assembly, SNV calling, and loss of heterozygosity (LOH) detection were performed with BWA, ABySS, Strelka, and APOLLOH respectively. SNV signatures were deciphered by non-negative matrix factorization with Monte Carlo resampling. An HRD score comprised of LOH, telomeric allelic imbalance (TAI), and large scale transition (LST) counts was computed. Clinical endpoints were obtained by retrospective review of treatment and imaging reports. Analysis is ongoing in an independent validation cohort of 62 sequenced cases. Results: The HRD-linked SNV signature was significantly associated with radiographic clinical response (CR) to platinum-based therapy (p=0.015). Logistic regression demonstrated a 59% improved odds of CR to platinum-based therapy per 1000 somatic SNVs attributed to HRD (odds ratio 1.16-2.50). Tumors carried up to 10,246 such SNVs and all patients with CR were among the top quartile. The LOH-TAI-LST score was correlated with SNV signature (r=0.6, p=7×10-6) and associated with CR (p=0.025). Notably, elevated HRD signatures associated with CR were identified in tumors with wild-type BRCA1/BRCA2 or variants of unknown significance. Tumors with above median HRD signatures were associated with a 69-day longer time to treatment failure and an 18% daily decreased probability of treatment failure per 1000 HRD-attributed SNVs (hazard ratio 0.71-0.95, p = 0.007). Discussion: We found that HRD mutation signatures are associated with clinical response and longer time to treatment failure with platinum-based therapy. While similar benefits were observed in patients with somatic bi-allelic loss of BRCA1/BRCA2, such cases are less common (8% of our cohort) compared to those with elevated HRD signature. Thus, mutation signature methods may identify patients who stand to benefit from platinum-based therapy missed by BRCA screening alone. Citation Format: Eric Y. Zhao, Yaoqing Shen, Erin Pleasance, Katayoon Kasaian, Martin R. Jones, Carolyn Ch'ng, Caralyn Reisle, Peter Eirew, Karen Mungall, Nina Thiessen, Yussanne Ma, Alexandra Fok, Andrew J. Mungall, Yongjun Zhao, Richard Moore, Diego Villa, Tamara Shenkier, Caroline Lohrisch, Stephen Chia, Stephen Yip, Karen Gelmon, Howard Lim, Sophie Sun, Kasmintan A. Schrader, Sean Young, Aly Karsan, Robyn Roscoe, Janessa Laskin, Marco A. Marra, Steven J. Jones. Breast cancer whole genomes link homologous recombination deficiency (HRD) with therapeutic outcomes [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 2473. doi:10.1158/1538-7445.AM2017-2473

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)0.002
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 score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.048
GPT teacher head0.376
Teacher spread0.328 · 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".

Quick stats

Citations0
Published2017
Admission routes1
Has abstractyes

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