Development and validation of a gene expression score to account for tumour purity and improve prognostication in breast cancer

The prevalence of malignant cells in clinical specimens, or tumour purity, is affected by both intrinsic biological factors and extrinsic sampling bias. Molecular characterization of large clinical cohorts is typically performed on bulk samples; data analysis and interpretation can be biased by tumour purity variability. Transcription-based strategies to estimate tumour purity have been proposed, but no breast cancer specific method is available yet. We interrogated over 4400 expression profiles from 9 breast cancer datasets to develop and validate a 9-gene Breast Cancer Purity Score (BCPS). BCPS outperformed existing methods for estimating tumour content. Adjusting transcriptomic profiles using the BCPS reduce sampling bias and aid data interpretation. BCPS-estimated tumour purity improved prognostication in luminal breast cancer, correlated with pathologic complete response in on-treatment biopsies from triple-negative breast cancer patients undergoing neoadjuvant treatment and effectively stratified the risk of relapse in HER2+ residual disease post-neoadjuvant treatment. ### Competing Interest Statement The authors have declared no competing interest. * ANOVA : ANalysis Of VAriance AUC : Area under the ROC curve BCPS : Breast Cancer Purity Score CBX : Core-Biopsy DEFS : Distant Event-Free Survival EFS : Event-Free Survival FDR : False Discovery Rate FFPE : Formalin-Fixed, Paraffin-Embedded FNA : Fine-Needle Aspiration FPKM : Fragments Per Kilobase Million IDC : Invasive Ductal Carcinoma ILC : Invasive Lobular Cancer iTIL : intraepithelial Tumour-Infiltrating Lymphocyte OS : Overall Survival pCR : pathological Complete Response PDX : Patient-derived xenograft ROC : Receiver Operating Characteristic sTIL : stromal Tumour-Infiltrating Lymphocyte TME : Tumour Microenvironment VCA : Variance Component Analysis