Abstract 2896: Impact of intratumoral heterogeneity on gene expression profiles and known biomarkers in FFPE tumor biopsies from early stage breast cancer patients
Authors: Lucas Delmonico, Joan Chen, Trushna Desai, Lisa Barnett, Aladdin Shadyab, John Obenauer, Gilda Alves Brown, Mauricio Magalhaes Costa, Marcia Fournier
Journal: Cancer Research (2019)

Abstract Background: Cancer is a dynamic disease that becomes more heterogeneous during its course, with cellular subpopulations with distinct molecular profiles across different regions. Because this intratumoral heterogeneity may result in varying levels of gene expression patterns and sensitivity to treatment across different regions of the tumor, it is important to understand patterns of heterogeneity to develop effective biomarkers. We conducted multiregion sampling within single breast tumor biopsies to evaluate the effect of intratumoral heterogeneity on expression of known and novel biomarkers. Methods: We sampled three sequential regions of breast tumor biopsies to compare gene expression patterns determined by a novel biomarker panel (BA355), 5 known biomarkers (ERS1, ERBB2, PGR, AR, and MKi67) and a novel predictive classifier (BA100). RNA expression levels were measured using a proprietary custom designed nanoString nCounter assay. We investigated formalin-fixed paraffin-embedded (FFPE) breast tumor biopsies from a cohort of 40 early stage breast cancer patients (T1 N0 M0) collected prospectively. RNA was extracted from upper, middle, and lower regions of each biopsy, resulting in a total of 120 samples quantified and QC using standard procedures. Each layer consisted of 40 micrometers, with an interval of 50 micrometers of tissue. BA100 linear regression models were used to generate prediction scores. Analyses were done in R. Results: Eighteen of the 120 samples had poor data quality (sample median = 0 or inter quantile range &amp;gt; mean + 2*sd). Further analyses only included 102 good quality samples corresponding to 34 FFPE biopsies. Among 33 of 34 samples, gene expression patterns between the three regions of the biopsies were highly correlated, with correlation coefficients ranging from 0.90-0.99 (p-values ranged from 2.07e-19 to 8.45e-319). Among 31 of 34 samples, the three regions were clustered together in cluster analysis. The coefficient of variation (CV) for ESR1 ranged from 0.37%-15.5%, with a majority (32 of 34) of the samples having CV &amp;lt;10%. While the CVs of ERBB2, PGR, and AR were within the same range as ESR1, MKI67 had much larger variation (CV ranged from 0.99%-173%). BA100 scores yielded consistent predictions for the three regions in 33 of 34 samples. Conclusion: Examination of gene expression patterns across multiple regions of breast tumor biopsies did not reveal a significant impact of intratumoral heterogeneity on expression patterns using a novel gene signature panel. However, at the individual gene level, while a number of genes including ESR1, ERBB2, PGR, and ARdisplayed consistent gene expression, genes such as MKI67 showed significant variation, indicating that tumor heterogeneity may impact individual gene biomarkers. Further studies are ongoing to evaluate intratumoral heterogeneity. Citation Format: Lucas Delmonico, Joan Chen, Trushna Desai, Lisa Barnett, Aladdin Shadyab, John Obenauer, Gilda Alves Brown, Mauricio Magalhaes Costa, Marcia Fournier. Impact of intratumoral heterogeneity on gene expression profiles and known biomarkers in FFPE tumor biopsies from early stage breast cancer patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 2896.