Validation of genomic and transcriptomic models of homologous recombination deficiency in a real-world pan-cancer cohort.


Journal

BMC cancer
ISSN: 1471-2407
Titre abrégé: BMC Cancer
Pays: England
ID NLM: 100967800

Informations de publication

Date de publication:
28 May 2022
Historique:
received: 29 12 2021
accepted: 11 05 2022
entrez: 1 6 2022
pubmed: 2 6 2022
medline: 7 6 2022
Statut: epublish

Résumé

With the introduction of DNA-damaging therapies into standard of care cancer treatment, there is a growing need for predictive diagnostics assessing homologous recombination deficiency (HRD) status across tumor types. Following the strong clinical evidence for the utility of DNA-sequencing-based HRD testing in ovarian cancer, and growing evidence in breast cancer, we present analytical validation of the Tempus HRD-DNA test. We further developed, validated, and explored the Tempus HRD-RNA model, which uses gene expression data from 16,750 RNA-seq samples to predict HRD status from formalin-fixed paraffin-embedded tumor samples across numerous cancer types. Genomic and transcriptomic profiling was performed using next-generation sequencing from Tempus xT, Tempus xO, Tempus xE, Tempus RS, and Tempus RS.v2 assays on 48,843 samples. Samples were labeled based on their BRCA1, BRCA2 and selected Homologous Recombination Repair pathway gene (CDK12, PALB2, RAD51B, RAD51C, RAD51D) mutational status to train and validate HRD-DNA, a genome-wide loss-of-heterozygosity biomarker, and HRD-RNA, a logistic regression model trained on gene expression. In a sample of 2058 breast and 1216 ovarian tumors, BRCA status was predicted by HRD-DNA with F1-scores of 0.98 and 0.96, respectively. Across an independent set of 1363 samples across solid tumor types, the HRD-RNA model was predictive of BRCA status in prostate, pancreatic, and non-small cell lung cancer, with F1-scores of 0.88, 0.69, and 0.62, respectively. We predict HRD-positive patients across many cancer types and believe both HRD models may generalize to other mechanisms of HRD outside of BRCA loss. HRD-RNA complements DNA-based HRD detection methods, especially for indications with low prevalence of BRCA alterations.

Sections du résumé

BACKGROUND BACKGROUND
With the introduction of DNA-damaging therapies into standard of care cancer treatment, there is a growing need for predictive diagnostics assessing homologous recombination deficiency (HRD) status across tumor types. Following the strong clinical evidence for the utility of DNA-sequencing-based HRD testing in ovarian cancer, and growing evidence in breast cancer, we present analytical validation of the Tempus HRD-DNA test. We further developed, validated, and explored the Tempus HRD-RNA model, which uses gene expression data from 16,750 RNA-seq samples to predict HRD status from formalin-fixed paraffin-embedded tumor samples across numerous cancer types.
METHODS METHODS
Genomic and transcriptomic profiling was performed using next-generation sequencing from Tempus xT, Tempus xO, Tempus xE, Tempus RS, and Tempus RS.v2 assays on 48,843 samples. Samples were labeled based on their BRCA1, BRCA2 and selected Homologous Recombination Repair pathway gene (CDK12, PALB2, RAD51B, RAD51C, RAD51D) mutational status to train and validate HRD-DNA, a genome-wide loss-of-heterozygosity biomarker, and HRD-RNA, a logistic regression model trained on gene expression.
RESULTS RESULTS
In a sample of 2058 breast and 1216 ovarian tumors, BRCA status was predicted by HRD-DNA with F1-scores of 0.98 and 0.96, respectively. Across an independent set of 1363 samples across solid tumor types, the HRD-RNA model was predictive of BRCA status in prostate, pancreatic, and non-small cell lung cancer, with F1-scores of 0.88, 0.69, and 0.62, respectively.
CONCLUSIONS CONCLUSIONS
We predict HRD-positive patients across many cancer types and believe both HRD models may generalize to other mechanisms of HRD outside of BRCA loss. HRD-RNA complements DNA-based HRD detection methods, especially for indications with low prevalence of BRCA alterations.

Identifiants

pubmed: 35643464
doi: 10.1186/s12885-022-09669-z
pii: 10.1186/s12885-022-09669-z
pmc: PMC9148513
doi:

Substances chimiques

RNA 63231-63-0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

587

Informations de copyright

© 2022. The Author(s).

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Auteurs

Benjamin D Leibowitz (BD)

Tempus Labs, 600 W Chicago Ave Ste #510, Chicago, IL, 60654, United States.

Bonnie V Dougherty (BV)

Tempus Labs, 600 W Chicago Ave Ste #510, Chicago, IL, 60654, United States.

Joshua S K Bell (JSK)

Tempus Labs, 600 W Chicago Ave Ste #510, Chicago, IL, 60654, United States.

Joshuah Kapilivsky (J)

Tempus Labs, 600 W Chicago Ave Ste #510, Chicago, IL, 60654, United States.

Jackson Michuda (J)

Tempus Labs, 600 W Chicago Ave Ste #510, Chicago, IL, 60654, United States.

Andrew J Sedgewick (AJ)

Tempus Labs, 600 W Chicago Ave Ste #510, Chicago, IL, 60654, United States.

Wesley A Munson (WA)

Tempus Labs, 600 W Chicago Ave Ste #510, Chicago, IL, 60654, United States.

Tushar A Chandra (TA)

Tempus Labs, 600 W Chicago Ave Ste #510, Chicago, IL, 60654, United States.

Jonathan R Dry (JR)

Tempus Labs, 600 W Chicago Ave Ste #510, Chicago, IL, 60654, United States.

Nike Beaubier (N)

Tempus Labs, 600 W Chicago Ave Ste #510, Chicago, IL, 60654, United States.

Catherine Igartua (C)

Tempus Labs, 600 W Chicago Ave Ste #510, Chicago, IL, 60654, United States.

Timothy Taxter (T)

Tempus Labs, 600 W Chicago Ave Ste #510, Chicago, IL, 60654, United States. tim@tempus.com.

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Classifications MeSH