Sequencing-based breast cancer diagnostics as an alternative to routine biomarkers

Abstract

Sequencing-based breast cancer diagnostics have the potential to replace routine biomarkers and provide molecular characterization that enable personalized precision medicine. Here we investigate the concordance between sequencing-based and routine diagnostic biomarkers and to what extent tumor sequencing contributes clinically actionable information. We applied DNA- and RNA-sequencing to characterize tumors from 307 breast cancer patients with replication in up to 739 patients. We developed models to predict status of routine biomarkers (ER, HER2,Ki-67, histological grade) from sequencing data. Non-routine biomarkers, including mutations in BRCA1, BRCA2 and ERBB2(HER2), and additional clinically actionable somatic alterations were also investigated. Concordance with routine diagnostic biomarkers was high for ER status (AUC = 0.95;AUC(replication) = 0.97) and HER2 status (AUC = 0.97;AUC(replication) = 0.92). The transcriptomic grade model enabled classification of histological grade 1 and histological grade 3 tumors with high accuracy (AUC = 0.98;AUC(replication) = 0.94). Clinically actionable mutations in BRCA1, BRCA2 and ERBB2(HER2) were detected in 5.5% of patients, while 53% had genomic alterations matching ongoing or concluded breast cancer studies. Sequencing-based molecular profiling can be applied as an alternative to histopathology to determine ER and HER2 status, in addition to providing improved tumor grading and clinically actionable mutations and molecular subtypes. Our results suggest that sequencing-based breast cancer diagnostics in a near future can replace routine biomarkers.

Figure 1

Classification performance of RNAseq-based prediction models for ER, PR, HER2 and Ki-67 as indicated by Receiver operating characteristic curves based on cross-validation for (A) ER, (B) PR, (C) HER2, (D) Ki-67. Boxplots of p(status = positive | RNAseq profile) (the probability of positive status of the marker (ER, PR or HER2) given the RNAseq expression profile data) from cross-validation for (E) ER, (F) PR, (G) HER2 and (H) predicted () Ki-67 score (% positively stained cells) given RNAseq expression profile data. Dotted red lines indicate optimal decision boundaries as determined by ROC analyses, corresponding to the point on the ROC curve with minimal distance to the top-left corner.

Figure 2. Transcriptomic tumor grade (TG) in comparison with histological grade and molecular subtype.

(A) ROC curve from cross-validation predictions of histological grade 1 and grade 3 using the TG model. (B) Sankey graph of the reclassification of histological grade 1–3 into low TG and high TG. (C) Proportion of intrinsic subtypes stratified by histological grade (HG) (1–3) and TG (low, high), where ‘HG2 & TG High’ represents HG 2 tumors reclassified as TG High, and ‘HG2 & TG Low’ represents HG 2 tumors reclassified as TG Low. (D) Clinical Ki-67 scores (% positively stained cells) for histological grade (HG) (1–3) and TG (low, high).

Figure 3

(A) Overview of HER2 status, molecular subtype and specific ERBB2 mutation for those individuals with detected ERBB2 (HER2) somatic mutations. All tumors with somatic mutations in ERBB2 (HER2) were found to be HER2-negative according to both routine pathology and RNAseq-based classification, indicating normal HER2 expression levels. (B) Overview of transcriptomic grade, ER status, HER2 status, molecular subtype and BRCA1/2 mutations status of those individuals with detected germline or somatic mutations in either BRCA1 or BRCA2. Tumors in patients with germline alterations in BRCA1 are predominantly of the Basal-like subtype. (Key: TG = transcriptomic grade. Status: 0 = negative/low; 1 = positive/high).

Figure 4. Overview of somatic alterations that are potentially actionable in the ClinSeq study.

(A) Each patient’s mutational profile was matched to the Dienstmann et al. knowledge base of actionable mutations including only breast cancer trials, excluding the ERBB2 amplification. Presence of a colored block in the intersection between an actionable mutation (rows in the heatmap) indicate a match between the somatic alterations in A patient (columns in the heatmap), Studies are classified as “Early” or “Late” from the Dienstmann et al. knowledge base, also indicated by color. The top panel of display transcriptomic grade status (“TG”), molecular subtype (“PAM50”), ER status (“ESR1”) and HER2 status (“ERBB2”). (B) Summary of the number of patients in the present study that were potentially eligible for targeted drugs for indication breast cancer stratified by early and late phase studies. (C) Summary of the number of patients in the present study that were potentially eligible for targeted drugs for any indication, stratified by early and late phase studies as well as approved treatments.