Ensemble biomarkers for guiding anti‐angiogenesis therapy for ovarian cancer using deep learning

Dear Editor, The central contribution of this research is to present highly effective ensemble biomarkers for guiding therapies to ovarian cancer, which has become the major cause of death from gynecologic cancer in industrialized countries1 whereas 90% of all ovarian cancer types is epithelial ovarian cancer (EOC). The typical therapy for EOC is a combination of cytoreductive surgery, platinum and taxane chemotherapy.2,3 Bevacizumab (Avastin), which is the first FDA approved anti-angiogenic agent,4,5 leads to normalization of tumor vasculature and improved effectiveness of standard therapy with promising result, but unfortunately it is associated with high degree of adverse effects, including arterial thromboembolism, high blood pressure, presence of excess proteins in the urine, haemorrhage, poor wound healing and ruptured bowel.6 The goal of this study is to examine whether the angiogenesisrelated biomarkers, such as VEGF, Ang-2 and PKM2 could be used to build an effective therapeutic predictive system for patient selection, guiding ovarian cancer treatment. In this study, we investigate three angiogenesis-related potential biomarkers, including VEGF, Angiopoietin 2 (Ang-2) and Pyruvate kinase isoform M2 (PKM2), and develop an annotation-free instance boosting deep learning ensemble framework to forecast the treatment response to bevacizumab of patients with EOC or peritoneal serous papillary carcinoma (PSPC) using tissue microarrays. See Supporting Information (Section 1) for related works. To enable the development of therapeutic predictive AI systems, digitized whole slide images (WSIs) of tissue microarrays are collected from samples with EOC and PSPC, containing 720 female patient sample tissue cores in total. For the data inclusion and exclusion criteria, patients are eligible for the retrospective study if they are EOC or PSPC patients receiving 1) concurrent bevacizumab therapy, 2) second-line bevacizumab therapy post recurrence or 3) maintenance bevacizumab therapy. On the other hand, patients are ineligible if they are borderline