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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.

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%, 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.

SUBMITTER: Staaf J

PROVIDER: S-EPMC9381586 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature

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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 J Häkkinen Jari J Hegardt Cecilia C Saal Lao H LH Kimbung Siker S Hedenfalk Ingrid I Lien Tonje T Sørlie Therese T Naume Bjørn B Russnes Hege H Marcone Rachel R Ayyanan Ayyakkannu A Brisken Cathrin C Malterling Rebecka R RR Asking Bengt B Olofsson Helena H Lindman Henrik H Bendahl Pär-Ola PO Ehinger Anna A Larsson Christer C Loman Niklas N Rydén Lisa L Malmberg Martin M Borg Åke Å Vallon-Christersson Johan J

NPJ breast cancer 20220816 1

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 coh ...[more]

PMID: 35974007

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Project description:ImportanceCurrent treatment cures most cases of early-stage, primary breast cancer. However, better techniques are required to identify which patients are at risk of relapse.ObjectiveTo assess the clinical validity of molecular relapse detection with circulating tumor DNA (ctDNA) analysis in early-stage breast cancer.Design, setting, and participantsThis prospective, multicenter, sample collection, validation study conducted at 5 United Kingdom medical centers from November 24, 2011, to October 18, 2016, assessed patients with early-stage breast cancer irrespective of hormone receptor and ERBB2 (formerly HER2 or HER2/neu) status who were receiving neoadjuvant chemotherapy followed by surgery or surgery before adjuvant chemotherapy. The study recruited 170 women, with mutations identified in 101 patients forming the main cohort. Secondary analyses were conducted on a combined cohort of 144 patients, including 43 patients previously analyzed in a proof of principle study.InterventionsPrimary tumor was sequenced to identify somatic mutations, and personalized tumor-specific digital polymerase chain reaction assays were used to monitor these mutations in serial plasma samples taken every 3 months for the first year of follow-up and subsequently every 6 months.Main outcomes and measuresThe primary end point was relapse-free survival analyzed with Cox proportional hazards regression models.ResultsIn the main cohort of 101 female patients (mean [SD] age, 54 [11] years) with a median follow-up of 35.5 months (interquartile range, 27.9-43.0 months), detection of ctDNA during follow-up was associated with relapse (hazard ratio, 25.2; 95% CI, 6.7-95.6; P < .001). Detection of ctDNA at diagnosis, before any treatment, was also associated with relapse-free survival (hazard ratio, 5.8; 95% CI, 1.2-27.1; P = .01). In the combined cohort, ctDNA detection had a median lead time of 10.7 months (95% CI, 8.1-19.1 months) compared with clinical relapse and was associated with relapse in all breast cancer subtypes. Distant extracranial metastatic relapse was detected by ctDNA in 22 of 23 patients (96%). Brain-only metastasis was less commonly detected by ctDNA (1 of 6 patients [17%]), suggesting relapse sites less readily detectable by ctDNA analysis.Conclusions and relevanceThe findings suggest that detection of ctDNA during follow-up is associated with a high risk of future relapse of early-stage breast cancer. Prospective studies are needed to assess the potential of molecular relapse detection to guide adjuvant therapy.

Dataset Information

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

Publications

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

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