# Dynamic BH3 Profiling with Patient Derived Organoids of Esophageal Cancer and Mesothelioma Enable Precision-Based Targeting of the Mitochondrial Apoptotic Pathway > **NIH NIH R03** · BAYLOR COLLEGE OF MEDICINE · 2022 · $80,000 ## Abstract SUMMARY / ABSTRACT Esophageal cancer and malignant pleural mesothelioma are difficult to treat because they typically harbor over 3000 somatic mutations from the repeated insults of reflux and asbestos. Identifying one mutation or pathway to target is circumvented by the tumor cell through new mutations and bypass pathways. For this reason, targeting the mitochondrial pathways represents a substantially improved approach because they are downstream of oncogenic driver proteins and pathway mutations. Recently, we have shown that chronic exposure of pre-neoplastic, Barrett’s esophageal cells to bile salt induced malignant transformation through a mechanism termed, ‘Minority MOMP (mitochondrial outer membrane permeabilization)’. MOMP is regulated by the B-cell lymphoma-2 (Bcl-2) family of proteins that are divided into pro- and anti-apoptotic proteins that interact at Bcl-2 homology-3 (BH3) domains. Minority MOMP partially activates the intrinsic pathway of the apoptotic machinery to a level not sufficient to result in cell death; rather, it promotes genomic instability, cellular transformation, and tumorigenesis. We noted that in ‘Minority MOMP’, Barrett’s cells resisted apoptosis through the upregulation of the anti-apoptotic protein, Mcl-1. When we targeted Mcl-1, Minority MOMP shifted from the sub-lethal mitochondrial activation to frank apoptosis and tumor cells died. Dynamic BH3 profiling (DBP) provides an assay to measure which anti-apoptotic proteins are responsible for the resistance for each tumor. By determining the relevant anti-apoptotic protein, a class of compounds, BH3 mimetics, target those specific protein. Recently, a biochemical ‘toolkit’ utilized DBP to identify the appropriate BH3 mimetic in murine cells that overexpressed bcl-2 proteins. Patient-derived organoids (PDO) can recapitulate tumor response to therapy. If a comprehensive biochemical toolkit utilizing DBP in PDOs identifies proteins that enable resistance directly from patient tumors, then precision-based targeting of the Bcl-2 proteins provides a therapeutic strategy to overcome treatment-refractory cancers. Our goal is to disrupt the mitochondrial balance that enables carcinogenesis but blocks apoptosis by directly targeting the proteins responsible for resistance. We will establish a biochemical toolkit to predict treatment response in esophageal cancer and mesothelioma by utilizing a DBP-PDO model. Targeting these proteins will shift Minority MOMP toward apoptosis by blocking the compensatory anti-apoptotic proteins. Our hypothesis is that the DBP-PDO model is a clinically actionable bioassay within seven days from tumor biopsy. This current research will allow us to circumvent intractable bypass mechanisms and mutations of cancer cells altogether by targeting the downstream mitochondrial resistance mechanism. This novel strategy is expected to shift Minority MOMP toward frank apoptosis and thus render these cells vulnerable to standard therapies. ## Key facts - **NIH application ID:** 10459596 - **Project number:** 5R03CA252685-02 - **Recipient organization:** BAYLOR COLLEGE OF MEDICINE - **Principal Investigator:** Robert Taylor Ripley - **Activity code:** R03 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2022 - **Award amount:** $80,000 - **Award type:** 5 - **Project period:** 2021-08-01 → 2023-07-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10459596 ## Citation > US National Institutes of Health, RePORTER application 10459596, Dynamic BH3 Profiling with Patient Derived Organoids of Esophageal Cancer and Mesothelioma Enable Precision-Based Targeting of the Mitochondrial Apoptotic Pathway (5R03CA252685-02). Retrieved via AI Analytics 2026-05-21 from https://api.ai-analytics.org/grant/nih/10459596. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*