In clinical breast cancer intervention, selection of the optimal treatment protocol based on predictive biomarkers remains an elusive goal. Here, we present a modeling tool to predict the likelihood of breast cancer response to neoadjuvant chemotherapy using patient-specific tumor vasculature biomarkers. A semiautomated analysis was implemented and performed on 3990 histological images from 48 patients, with 10–208 images analyzed for each patient. We applied a histology-based mathematical model to 30 resected primary breast cancer tumors and then evaluated a cohort of 18 patients undergoing neoadjuvant chemotherapy, collecting pre- and posttreatment pathology specimens and MRI data. We found that core biopsy samples can be used with acceptable accuracy to determine histological parameters representative of the whole tissue region. Analysis of model histology parameters obtained from tumor vasculature measurements, specifically diffusion distance divided by the radius of the drug-delivering blood vessel (L/rb) and blood volume fraction (BVF), provides a statistically significant separation of patients obtaining a pathologic complete response (pCR) from those who do not. With this model, it is feasible to evaluate primary breast tumor vasculature biomarkers in a patient-specific manner, thereby allowing a precision approach to breast cancer treatment.
Terisse A. Brocato, Ursa Brown-Glaberman, Zhihui Wang, Reed G. Selwyn, Colin M. Wilson, Edward F. Wyckoff, Lesley C. Lomo, Jennifer L. Saline, Anupama Hooda-Nehra, Renata Pasqualini, Wadih Arap, C. Jeffrey Brinker, Vittorio Cristini
Guidelines: The Editorial Board will only consider letters that we deem relevant and of interest to our readers. We will not post data that have not been subjected to peer review, nor will we post letters that are essentially a reiteration of another letter. We reserve the right to edit any letter for length, content, and clarity. Authors will be notified by e-mail if their letters were accepted. No appeals will be considered.
Specific requirements: All letters must be 400 words or fewer. You may enter the letter as plain text or HTML. The author's name and e-mail address are required, and will be posted with the letter. All possible conflicts of interest must be noted, even if they are not posted. If you wish to include a figure (keep in mind that non-peer-reviewed data will not be posted), please contact the editors directly at firstname.lastname@example.org.