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RNA sequencing-based single sample predictors of molecular subtype and risk of recurrence for clinical assessment of early-stage breast cancer

Staaf, Johan LU orcid ; Häkkinen, Jari LU orcid ; Hegardt, Cecilia LU ; Saal, Lao H LU orcid ; Kimbung, Siker LU ; Hedenfalk, Ingrid LU orcid ; Lien, Tonje ; Sørlie, Therese ; Naume, Bjørn and Russnes, Hege , et al. (2022) In npj Breast Cancer 8. p.1-17
Abstract

Multigene assays for molecular subtypes and biomarkers can aid management of early invasive breast cancer. Using RNA-sequencing we aimed to develop single-sample predictor (SSP) models for clinical markers, subtypes, and risk of recurrence (ROR). A cohort of 7743 patients was divided into training and test set. We trained SSPs for subtypes and ROR assigned by nearest-centroid (NC) methods and SSPs for biomarkers from histopathology. Classifications were compared with Prosigna in two external cohorts (ABiM, n = 100 and OSLO2-EMIT0, n = 103). Prognostic value was assessed using distant recurrence-free interval. Agreement between SSP and NC for PAM50 (five subtypes) was high (85%, Kappa = 0.78) for Subtype (four subtypes) very high (90%,... (More)

Multigene assays for molecular subtypes and biomarkers can aid management of early invasive breast cancer. Using RNA-sequencing we aimed to develop single-sample predictor (SSP) models for clinical markers, subtypes, and risk of recurrence (ROR). A cohort of 7743 patients was divided into training and test set. We trained SSPs for subtypes and ROR assigned by nearest-centroid (NC) methods and SSPs for biomarkers from histopathology. Classifications were compared with Prosigna in two external cohorts (ABiM, n = 100 and OSLO2-EMIT0, n = 103). Prognostic value was assessed using distant recurrence-free interval. Agreement between SSP and NC for PAM50 (five subtypes) was high (85%, Kappa = 0.78) for Subtype (four subtypes) very high (90%, Kappa = 0.84) and for ROR risk category high (84%, Kappa = 0.75, weighted Kappa = 0.90). Prognostic value was assessed as equivalent and clinically relevant. Agreement with histopathology was very high or high for receptor status, while moderate for Ki67 status and poor for Nottingham histological grade. SSP and Prosigna concordance was high for subtype (OSLO-EMIT0 83%, Kappa = 0.73 and ABiM 80%, Kappa = 0.72) and moderate and high for ROR risk category (68 and 84%, Kappa = 0.50 and 0.70, weighted Kappa = 0.70 and 0.78). Pooled concordance for emulated treatment recommendation dichotomized for chemotherapy was high (85%, Kappa = 0.66). Retrospective evaluation suggested that SSP application could change chemotherapy recommendations for up to 17% of postmenopausal ER+/HER2-/N0 patients with balanced escalation and de-escalation. Results suggest that NC and SSP models are interchangeable on a group-level and nearly so on a patient level and that SSP models can be derived to closely match clinical tests.

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organization
publishing date
type
Contribution to journal
publication status
published
subject
in
npj Breast Cancer
volume
8
article number
94
pages
1 - 17
publisher
Nature Publishing Group
external identifiers
  • pmid:35974007
  • scopus:85136213430
ISSN
2374-4677
DOI
10.1038/s41523-022-00465-3
project
Sweden Cancerome Analysis Network - Breast (SCAN-B): a large-scale multicenter infrastructure towards implementation of breast cancer genomic analyses in the clinical routine
language
English
LU publication?
yes
additional info
© 2022. The Author(s).
id
a9991213-4b18-4f50-80c2-c8e4ff49417f
date added to LUP
2022-08-23 12:43:39
date last changed
2024-06-28 11:15:19
@article{a9991213-4b18-4f50-80c2-c8e4ff49417f,
  abstract     = {{<p>Multigene assays for molecular subtypes and biomarkers can aid management of early invasive breast cancer. Using RNA-sequencing we aimed to develop single-sample predictor (SSP) models for clinical markers, subtypes, and risk of recurrence (ROR). A cohort of 7743 patients was divided into training and test set. We trained SSPs for subtypes and ROR assigned by nearest-centroid (NC) methods and SSPs for biomarkers from histopathology. Classifications were compared with Prosigna in two external cohorts (ABiM, n = 100 and OSLO2-EMIT0, n = 103). Prognostic value was assessed using distant recurrence-free interval. Agreement between SSP and NC for PAM50 (five subtypes) was high (85%, Kappa = 0.78) for Subtype (four subtypes) very high (90%, Kappa = 0.84) and for ROR risk category high (84%, Kappa = 0.75, weighted Kappa = 0.90). Prognostic value was assessed as equivalent and clinically relevant. Agreement with histopathology was very high or high for receptor status, while moderate for Ki67 status and poor for Nottingham histological grade. SSP and Prosigna concordance was high for subtype (OSLO-EMIT0 83%, Kappa = 0.73 and ABiM 80%, Kappa = 0.72) and moderate and high for ROR risk category (68 and 84%, Kappa = 0.50 and 0.70, weighted Kappa = 0.70 and 0.78). Pooled concordance for emulated treatment recommendation dichotomized for chemotherapy was high (85%, Kappa = 0.66). Retrospective evaluation suggested that SSP application could change chemotherapy recommendations for up to 17% of postmenopausal ER+/HER2-/N0 patients with balanced escalation and de-escalation. Results suggest that NC and SSP models are interchangeable on a group-level and nearly so on a patient level and that SSP models can be derived to closely match clinical tests.</p>}},
  author       = {{Staaf, Johan and Häkkinen, Jari and Hegardt, Cecilia and Saal, Lao H and Kimbung, Siker and Hedenfalk, Ingrid and Lien, Tonje and Sørlie, Therese and Naume, Bjørn and Russnes, Hege and Marcone, Rachel and Ayyanan, Ayyakkannu and Brisken, Cathrin and Malterling, Rebecka R and Asking, Bengt and Olofsson, Helena and Lindman, Henrik and Bendahl, Pär-Ola and Ehinger, Anna and Larsson, Christer and Loman, Niklas and Rydén, Lisa and Malmberg, Martin and Borg, Åke and Vallon-Christersson, Johan}},
  issn         = {{2374-4677}},
  language     = {{eng}},
  month        = {{08}},
  pages        = {{1--17}},
  publisher    = {{Nature Publishing Group}},
  series       = {{npj Breast Cancer}},
  title        = {{RNA sequencing-based single sample predictors of molecular subtype and risk of recurrence for clinical assessment of early-stage breast cancer}},
  url          = {{http://dx.doi.org/10.1038/s41523-022-00465-3}},
  doi          = {{10.1038/s41523-022-00465-3}},
  volume       = {{8}},
  year         = {{2022}},
}