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.

Chromatin insulation orchestrates matrix metalloproteinase gene cluster expression reprogramming in aggressive breast cancer tumors

“…In situ and invasive breast cancer clinical tissue gene expression pro ling. The study cohort included invasive and in situ BC tissues that were processed as described [30]. Cases without data about tumor size (T), relapse and/or follow-up under three years, or missing relapse data were removed from the analysis.…”

Perturbation and stability of PAM50 subtyping in population-based primary invasive breast cancer

“…The prognostic value of these molecular subtypes has repeatedly been demonstrated [9][10][11][12][13][14].…”

“…This step is important as inadequate normalization can result in erroneous classification [16][17][18][19][20][21]. Consequently, single sample predictors based on, e.g., gene rules have been reported recently to try to circumvent this issue [14,16]. Specific PAM50 subtypes have been shown to be enriched in different clinical subgroups of breast cancer, with respective characteristic association of the Basal subtype with TNBC, HER2E with ERnHER2p tumors, and LumA and LumB with the ERpHER2n clinical subgroup (see e.g., [22]).…”

“…The rationale behind this investigation is that the processes and genes represented in PAM50 may have different influence on subtyping depending on clinical subgroup which may explain results not normally expected like ERpHER2n tumors classified as PAM50 Basal. To achieve this, we used a recently reported population-based cohort of uniformly accrued primary breast cancers comprising 6233 patients analyzed by whole transcriptome RNA sequencing with available PAM50 NC subtypes and a presented rigorous NC classification strategy [14]. We illustrate that PAM50 subtyping is dependent on different biological processes in different clinical breast cancer subgroups, but also within subgroups and PAM50 subtypes themselves.…”

Choice of High-Throughput Proteomics Method Affects Data Integration with Transcriptomics and the Potential Use in Biomarker Discovery

“…Several advances have been achieved in the classification of BC, which is mostly done at the genomic or transcriptomic level. This includes transcriptomic analysis of large cohorts, including the TCGA [ 10 ] and the SCAN-B cohort [ 9 ] with more than 7700 transcriptomes in the latest published dataset [ 11 , 12 ], and the development of commercial multigene assays such as Prosigna™. However, the need for better tailoring of treatments to patients points to the direction of including more proteins for prediction.…”