Abstract Use of multigene predictive signatures pre-chemotherapy in core needle biopsy specimens in low-resource systems in not applied due to multiple reasons. We are seeking a method of cost-effective integration of gene expression analysis into initial breast cancer subtype assessment pre-chemotherapy.The aim of the analysis was to assess the heterogeneity of independent cores taken from primary tumor in the context of prediction of its clinical parameters by gene expression profiling.Material and methods. The study group consisted of 65 women with high-risk breast cancer, before preoperative chemotherapy, median age at the start of therapy 41,2 years (range 29-62 yr). Among the diagnosed breast cancers, 71% were grade 3 (G3), while G1 only in 3% of individuals. The most common breast cancer biological subtypes were triple negative breast cancer (38%), luminal B HER2-negative (defined as Ki67>20% or PR-negative, 24%) and HER2-positive tumors (23%) of tumors were of lobular histology. In core needle biopsies taken before preoperative breast cancer chemotherapy gene expression profiling was carried out by oligonucleotide microarrays (U133A/U133 Plus 2.0), three independent cores were analyzed (192 microarrays). Analysis was carried out by JMP Genomics (SAS Institute, Cary, USA) and R/Bioconductor genefu package.At first step, the overall tumor profile was analysed by Principal Component Analysis. Based on first two principal components, 44 patients (68%) showed highly concordant profile in all three cores, whereas in 21 tumors (32%) larger scatter was observed. We analysed research versions of commercially available multigene predictors, PAM50 are presented in abstract. Prediction was done independently for each core. In 40% of patients all three cores provided identical predictions for all analysed signatures (mainly triple-negative tumors). In 17% of patients we observed minor discordances (in one core 1 or 2 signatures discordant), in 10% discordances in 2 cores. Profound differences were found in 33% of patients (similar to overall profile scatter seen by PCA), mainly in luminal and HER2-positive tumors. Subtypes predicted by genomic testing were - as expected - slightly different from immunohistochemistry prediction. The most often occurring was Basal subtype (87% of TNBC patients, but occurring also in HER2-positive tumors, 20-25% and luminal B tumors, 26.7%). The second molecular subtype was LumB. These tumors constituted 60% of clinically diagnosed luminal B patients, molecular LumB subtype was also frequent among clinically luminal B HER2-positive individuals (30%). Genomic LumA subtype was found in all clinical subgroups, in 10-25% of these patients. Her2 subtype by PAM50 classification was occurring less frequently, in 50% of HER2-nonluminal and 40% luminal B HER2-positive tumors. The concordance of results improved, when classification included both immunohistochemistry results as well as the results of genomic measurements. ER and HER2 showed excellent concordance between three tumor cores and showed bimodal expression, while MKI67 and PGR although concordant showed continuous pattern of expression rather than any visible subgroups. Conclusions. Significant heterogeneity is seen in genomic profile of at least 1/3 of tested breast cancers and shall be taken into account. The error of sampling was lowest in triple negative subtype Citation Format: Michal Jarzab. Heterogeneity of multigene signatures in breast cancer among multiple specimens taken by core needle biopsy [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P4-06-14.
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