Abstract P2-03-03: Profiling protein-protein interactions at single-molecule level as a novel biomarker-driven screening method for the detection of tumor recurrence in breast cancer patients
Authors: Hong Won Lee, Hee Jun Choi, Hyunwoo Kim, Seul Lee, Sangmin Kim, Tae-Young Yoon, Jeong Eun Lee
Journal: Cancer Research (2020)

Abstract Background: Protein-protein interactions (PPIs) modulate the vast majority of cellular processes. Therefore, profiling PPIs occurred in a clinical specimen may facilitate to understand molecular mechanisms involved in disease progression such as cancer. In breast cancer diagnosis, molecular subtyping is an important step for decision-making clinically. However, the molecular subtype is determined simply according to the expression level of receptors (hormone receptors and HER2). Here, we present the use of single-molecule analysis to visualize PPIs in a clinical specimen. We further assess the potential use of PPI-profiling to screen a subgroup of breast cancer patients who show aberrant PPIs. Methods: In total, 138 fresh-frozen breast tumor tissues were profiled. Specimens were selected based on IHC scores with an average follow-up of 7.5 years; ≥ 7 for hormone receptors (ER/PR+) and ≤ 1 for HER2 (HER2-) determined by IHC-scoring guidelines. We analyzed expression levels and strengths of PPIs for HER2, HER3 and EGFR from breast cancer specimens by applying single-molecule pull-down and co-immunoprecipitation techniques - a novel technology based on single-molecule fluorescence imaging (Proteina co., Ltd.). Tumor proteins were extracted from fresh-frozen tumor tissue via cryogenic grinding followed by the addition of tissue lysis buffer. Single-molecule PPI and expression level analysis were performed by using EGFR-PPI-Dx kit and proto-type HER2/HER3-PPI-Dx kit, respectively. Single-molecule analysis for the prepared kit was carried out using ProViewTM, an automated single-molecule fluorescence imaging equipment. Disease-free survival between groups were compared using Kaplan-Meier survival curve analysis and log-rank test was performed to determine the difference of survival distributions between groups. Results: 72 (discovery set) and 66 (validation set) patients were analyzed, respectively. Single-molecule measurement for HER2 level demonstrated that clinical specimens showed significant differences in HER2 level even though they had the same IHC score (up to 65-fold from 117 patients with ‘IHC-0’ and 33-fold from 21 patients with ‘IHC 1’, respectively). By combining HER2 PPI and expression data, we screened 12 patients (17%) as a high HER2-signal group, which showed positive HER2-PPI and enhanced HER2-level from a discovery set. Interestingly, this high HER2-signal group showed the enhanced tumor recurrence rate compared to that of low HER2-signal (58% for high HER2-signal vs. 17% for low HER2-signal, log-rank p=0.001). Using the same cutoff, we screened 17 patients from validation set and this screened group showed higher tumor recurrence risk rate than the low HER2-signal/group-prevalence (18% vs. 12%/13.6%, log-rank p=0.033). Conclusions: Defining a cancer patient by individual molecular features is a cornerstone of precision medicine. A comprehensive understanding of the molecular landscape may help a physician deciding a biomarker-driven treatment patient-by-patient. Molecular profiling (PPI and expression level) at single-molecule level enables to determine the strength of PPIs and the quantity of proteins quantitatively and precisely. In this study, we describe a novel concept of patient-classification by single-molecule PPI analysis. Our PPI analysis reveals a subgroup of HR+/HER2- patients who show an enhanced HER2-initiated signaling, which was hidden by conventional techniques. We further identified that this subgroup exhibited higher recurrence rate than the prevalence of whole group we tested. Our findings propose that adjuvant HER2-targeted therapies along with hormone-therapy may be a new opportunity to patients screened by PPI profiling for reduced risk of tumor recurrence. Citation Format: Hong Won Lee, Hee Jun Choi, Hyunwoo Kim, Seul Lee, Sangmin Kim, Tae-Young Yoon, Jeong Eun Lee. Profiling protein-protein interactions at single-molecule level as a novel biomarker-driven screening method for the detection of tumor recurrence in breast cancer patients [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 P2-03-03.