Abstract PD4-07: PD4-07 Uncovering molecular heterogeneity of mixed ductal and lobular carcinoma using digital spatial profiling

Abstract

Abstract Background Mixed invasive ductal and lobular carcinoma (mDLC) is a rare special subtype (3-6%, ~10,000 cases/annually in US) of invasive breast cancer with elusive pathophysiology. This entity exhibits a mix of ductal-like and lobular-like tumor sub-components within the same tumor. With few seminal studies, mDLC remains poorly understood with little molecular understanding of its sub-components including their origin and implications on disease evolution, prognosis, and treatment response. With increasing recognition of no special type (NST) and invasive lobular carcinoma (ILC) as distinct diseases with unique biology, it is important to understand whether this mixed entity, and its sub-components are like NST and ILC subtypes or a distinct disease. Methods We identified mDLC cases from the UPMC cancer registry. These underwent comprehensive evaluation by a panel of expert pathologists. Three cases (each with a ductal and lobular sub-component on the same FFPE block) were shortlisted. These cases underwent digital spatial profiling (DSP) using Nanostring GeoMX Human Whole Transcriptome Atlas. Briefly, 5um slides were stained using RNAscope morphology marker probes (E-cadherin and PanCK) and GeoMX DSP oligo-conjugated RNA detection probes. Between 3-6 ductal and lobular regions of interest (ROI) per tumor were selected by pathologists. DSP barcodes were cleaved off using UV light and collected into 96-well plate. These underwent library preparation and sequencing. Raw reads were aligned to reference probes to quantify RNA counts. Q3 normalized counts were used in downstream analyses using R version 4.1. Linear modeling was used to assess differentially expressed genes (DEGs). Hypergeometric enrichment tests were used for geneset enrichment. T-tests was used to compare gene expression between two groups. Results In total 26 ROIs (14 ductal and 15 lobular) were profiled across the three mDLC FFPE slides. Overall data quality was excellent with > 90% sequencing saturation across profiled ROIs. Principle component analysis and consensus clustering showed that lobular and ductal ROIs clustered separately indicating distinct molecular profiles. Similarly, PAM50 analysis showed that ductal and lobular ROIs within each patient tumor had distinct PAM50 subtypes. To further investigate the molecular differences between ductal vs lobular ROIs, we performed differential gene expression analysis. We identified 38 up-regulated and 78 down-regulated genes in lobular compared to ductal ROIs. To assess whether mDLC sub-components share any molecular similarities to pure counterparts i.e., ILC and NST, we compared mDLC lobular vs ductal DEGs with those from TCGA ILC vs NST comparison. SHROOM1, KLK10 and KLK11 were up-regulated while CDH1, DCD, and CPB1 were down-regulated in both mDLC lobular ROIs and ILC vs mDLC ductal ROIs and NST, respectively. Pathway analysis revealed estrogen response, adhesion, and metabolism related differences between mDLC lobular vs ductal ROIs. Furthermore, key transcription factor signatures enriched in the up-regulated genes in lobular vs ductal ROIs included ESR1, FOXA2, GATA1/2 and AR signatures while those enriched in the down-regulated genes in lobular vs ductal ROIs included RCOR1, MYC, ZBTB7A, NELFE, and SPI1 signatures. Conclusion and Future Work Using DSP, we uncovered the molecular heterogeneity of mDLC. We revealed that lobular and ductal sub-components have distinct biology with differences in transcriptional signatures and hormone signaling, adhesion and metabolism related pathways. Our pilot study is the first to shed light on this elusive mixed entity using spatial profiling. Our future work will focus on DNA sequencing of mDLC sub-components to identify sub-component specific driver mutations. Our findings will need further investigation in larger mDLC cohorts to better understand their clinical implications in terms of evolution of this disease and its prognosis. Citation Format: Osama Shiraz Shah, Azadeh Nasrazadani, Jennifer M. Atkinson, Celina Kleer, Priscilla F. McAuliffe, Rohit Bhargava, Jorge Reis-Filho, Peter C. Lucas, ADRIAN V. LEE, Steffi Oesterreich. PD4-07 Uncovering molecular heterogeneity of mixed ductal and lobular carcinoma using digital spatial profiling [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr PD4-07.