Background and Purpose: Advances in the treatment of triple-negative breast and ovarian cancer remain challenging. In particular, resistance to the available therapy, by restoring or overexpressing the DNA repair machinery, has often been reported. New strategies to improve the therapeutic outcomes of these cancers are needed.Herein, we disclose the dregamine 5-bromo-pyridin-2-ylhydrazone (BBIT20), a natural monoterpene indole alkaloid derivative, as an inhibitor of homologous DNA repair.Experimental Approach: To unveil BBIT20 antitumour activity and underlying molecular mechanism of action, two-dimensional (2D) and three-dimensional (3D) cell cultures, patient-derived cell lines and xenograft mouse models were used.Key Results: BBIT20 disrupted the BRCA1-BARD1 interaction, triggering nuclearto-cytoplasmic BRCA1 translocation, cell cycle arrest and downregulation of homologous DNA repair-related genes and proteins, with subsequent enhancement of DNA damage, reactive oxygen species generation and apoptosis, in triple-negative breast and ovarian cancer cells. BBIT20 also displayed pronounced antitumour activity in patient-derived cells and xenograft mouse models of ovarian cancer, with low toxicity in non-malignant cells and undetectable side effects

Purpose: Preclinical studies show that antiangiogenic therapy exacerbates tumor glycolysis and activates liver kinase B1/AMP kinase (AMPK), a pathway involved in the regulation of tumor metabolism. We investigated whether certain metabolism-related in situ biomarkers could predict benefit to regorafenib in the phase II randomized REGOMA trial.Patients and Methods: IHC and digital pathology analysis were used to investigate the expression in glioblastoma (GBM) sections of monocarboxylate transporter 1 and 4 (MCT1 and MCT4), associated with OXPHOS and glycolysis, respectively, phosphorylated AMPK (pAMPK), and phosphorylated acetyl-CoA carboxylase (pACC), a canonical target of AMPK activity. The status of each biomarker was associated with clinical endpoints, including overall survival (OS) and progression-free survival (PFS) in patients with relapsed GBM treated either with regorafenib or lomustine.Results: Between November 2015 and February 2017, 119 patients were enrolled (n ¼ 59 regorafenib and n ¼ 60 lomustine) and stratified for surgery at recurrence, and baseline characteristics were balanced. Biomarker analysis was performed in 84 patients (71%), including 42 patients of the regorafenib arm and 42 patients of the lomustine arm. Among all markers analyzed, only pACC showed predictive value in terms of OS. In fact, median OS was 9.3 months [95% confidence interval (CI), 5.6-13.2] for regorafenib and 5.5 months (95% CI, 4.2-6.6) for lomustine for pACC-positive patients, HR, 0.37 (95% CI, 0.20-0.70); log rank P ¼ 0.0013; test for interaction ¼ 0.0453. No statistically significant difference was demonstrated for PFS according to pACC status.Conclusions: We found that AMPK pathway activation is associated with clinical benefit from treatment with regorafenib in relapsed GBM.

Metabolic profiling of cancer is a rising interest in the field of biomarker development. One bottleneck of its clinical exploitation, however, is the lack of simple and quantitative techniques that enable to capture the key metabolic traits of tumor from archival samples. In fact, liquid chromatography associated with mass spectrometry is the gold-standard technique for the study of tumor metabolism because it has high levels of accuracy and precision. However, it requires freshly frozen samples, which are difficult to collect in large multi-centric clinical studies. For this reason, we propose here to investigate a set of established metabolism-associated protein markers by exploiting immunohistochemistry coupled with digital pathology. As case study, we quantified expression of MCT1, MCT4, GLS, PHGDH, FAS, and ACC in 17 patient-derived ovarian cancer xenografts and correlated it with survival. Among these markers, the glycolysis-associated marker MCT4 was negatively associated with survival of mice. The algorithm enabling a quantitative analysis of these metabolism-associated markers is an innovative research tool that can be exported to large sets of clinical samples and can remove the variability of individual interpretation of immunohistochemistry results.