Scrutinizing ER Isoform Heterogeneity and Adverse Patient Outcomes in Triple-Negative Breast Cancer
Abstract
Just as no two people are exactly alike, no two breast cancers are exactly the same. This is especially true for triple-negative breast cancer (TNBC). In the clinic, TNBC lacks hormone receptor markers, yet the cancer is actually a heterogeneous collection of breast cancer subgroups. After diagnosis, the lack of markers limits efficacy of hormone and targeted therapies. Thus, TNBC is usually associated with poor prognosis and high risk of recurrence. The heterogeneity of TNBC raises little hope for an effective single-treatment approach. The clinical impact of new and refined TNBC classifications cannot be overstated. Measuring and then understanding the heterogeneity of TNBC is the only way to cure TNBC. Before trial and error in human subjects, researchers study archived breast tumor tissues to correlate biomarkers with patient outcomes. Analyses of archived tissues led to the discovery of the tumor HER2 protein which, in turn, led to the first Food and Drug Administration-approved targeted cancer therapy: the drug trastuzumab (Herceptin?). Retrospective studies of banked breast tissues can make TNBC cures possible. The status quo clinical test for breast cancer is immunohistochemistry (IHC). IHC relies on visual inspection of tissue samples using manual microscopy. Tissue sections are dyed with probes specific to protein biomarkers. While providing information on both cancer cell phenotype and relative protein expression, IHC provides only qualitative results (e.g., ER positive or negative), has serious reproducibility issues, and shows discordance with other clinical tests (like FISH). The advent of genomic analysis technologies useful for studying breast tissue samples raises the possibility of similar analysis of proteins. Technologies promote the breast cancer research forward; however, the methodology is not readily available in clinical practice. Importantly, proteins, instead of DNA or RNA, are the biomolecules targeted by new drugs and therapies. Consequently, understanding the function of key proteins, e.g., metastasis-related proteins, in TNBC would be a boon to development of new therapeutic strategies. Besides study of regular ER protein, researchers have found significant roles for ER isoforms -- a smaller version of the full-length protein -- in breast cancer progression and metastasis. For example, while ER is not found in TNBC, ER isoforms are found in TNBC and mediate metastasis related pathways. Intriguingly, localization of ER isoforms in cancer cells leads to different patient outcomes. Yet, no existing tools can discern ER versus ER isoforms, assess cell-to-cell variation, and provide objective, quantitative readouts. We propose to advance clinical TNBC classification by using our recently developed a high-functionality microsystem. We will use tiny microwells (i.e., one-half the diameter of a human hair) to measure protein in single cells to assess tumor heterogeneity. We will separate proteins by size using a method called electrophoresis prior to antibody probing, thus we will detect isoforms of different sizes. Accurate measurements and automated image processing will allow rapid, quantitative readout, and reduce the impact of lab-to-lab and pathologist-to-pathologist variability. Our tools will allow direct measurement of ER isoforms for further understanding mechanisms of metastasis in large patient tissue registries -- potentially opening new avenues of diagnosis, prognosis, and therapeutic of TNBC. We will apply this innovative technology to measure the expression, frequency, and cellular localization of ER isoforms in TNBC tissues. Establishing accurate TNBC subtypes will benefit TNBC patients not only by uncovering new druggable targets, but also by informing precise treatment selection. The approach is high-risk, yet offers an opportunity for a quantum advance in measurement tools available for the analysis of archived tissues. In essence, the propos
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Apr 04, 2016
- Source ID
- W81XWH1610003
Entities
People
- Mark D Pegram
Organizations
- Stanford University
- United States Army