Abstract 6502: Inhibition of VCP in an <i>in vivo</i> model of metastatic melanoma selected based on a predictive biomarker demonstrates tumor reduction

Abstract Valosin containing protein (VCP) is a member of the AAA-ATPase family. It is involved in multiple cellular processes, such as protein degradation, DNA damage response, protein quality control and clearance in the endoplasmic reticulum, all of which are important functions often dysregulated in cancer. VCP is a common essential gene and there have been reports of toxicity associated with its inhibition, therefore a predictive biomarker is needed to stratify patients who are selectively vulnerable. Turbine’s Simulated Cell model highlighted VCP from an in silico target identification screen where a subgroup of melanoma was found to be most sensitive to VCP inhibition (VCPi). These findings were confirmed in a cell line panel covering 12 indications, consisting of 64 cell lines. Next, a simulated drug modifier screen was run using patient relevant avatars with prevalent alterations, which identified MITF as a predictive biomarker of VCPi sensitivity. An in vitro melanoma model of MITF dependency, SKMEL5, was used to test our hypothesis. Hypotheses derived from in silico predictions were validated using various forms of VCP loss including pharmacological inhibition using a phase 1 VCPi, CB5083, as a reference compound, siRNA and by conditional knockout. The sensitivity of VCPi in melanoma was confirmed in vitro and a correlation (R= -0.86) was found between the protein levels of MITF and IC50 values of VCPi. In the SKMEL5 cells, we observed a dose dependent reduction in levels of MITF following VCPi. Next, we sought to test the efficacy of VCPi in the SKMEL5 in vivo CDX model. Four weeks of CB5083 dosing using 50 mg/kg 4on/3off schedule was tolerated, resulted in 46% tumor growth inhibition, and this was accompanied by a downregulation of MITF and one of MITFs targets, DCT, in tumor samples post treatment. These studies support the therapeutic potential of VCP inhibitors in the MITF High/MITF Amplification subgroup of patients with metastatic melanoma with a poor prognosis and a decreased 5-year survival. Targeting a common essential gene such as VCP is associated with a narrow therapeutic index, however, we have demonstrated efficacy using a relatively low dose of 50 mg/kg. Taken together, we are proposing a patient stratification strategy based on the identification of a predictive biomarker from an in silico screen. Citation Format: Aofie Campbell, Dóra Kállai, Boldizsár Elek, Csilla Hegedűs, Magdolna Djurec, Ivan Fekete, Péter Szikora, Csaba Szántai-Kis, Amrik Basran, Stephen Connolly, Daniel Veres. Inhibition of VCP in an in vivo model of metastatic melanoma selected based on a predictive biomarker demonstrates tumor reduction [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 6502.

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Cancer Research
Published
2025-04-21
DOI
https://doi.org/10.1158/1538-7445.am2025-6502
Primary Topic
Inflammatory mediators and NSAID effects
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article
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article

Abstract 6502: Inhibition of VCP in an in vivo model of metastatic melanoma selected based on a predictive biomarker demonstrates tumor reduction

Amrik Basran, Stephen Connolly, Csaba Szántai-Kis, Magdolna Djurec et al.
Cancer Research
Inflammatory mediators and NSAID effects
article

Abstract 6502: Inhibition of VCP in an in vivo model of metastatic melanoma selected based on a predictive biomarker demonstrates tumor reduction

Amrik Basran, Stephen Connolly, Csaba Szántai-Kis, Magdolna Djurec, Dániel V. Veres, Boldizsár Elek, Ailsa M. Campbell, Csilla Hegedüs, Ivan Fekete, Dóra Kállai, Péter Szikora
article en

Abstract

Abstract Valosin containing protein (VCP) is a member of the AAA-ATPase family. It is involved in multiple cellular processes, such as protein degradation, DNA damage response, protein quality control and clearance in the endoplasmic reticulum, all of which are important functions often dysregulated in cancer. VCP is a common essential gene and there have been reports of toxicity associated with its inhibition, therefore a predictive biomarker is needed to stratify patients who are selectively vulnerable. Turbine’s Simulated Cell model highlighted VCP from an in silico target identification screen where a subgroup of melanoma was found to be most sensitive to VCP inhibition (VCPi). These findings were confirmed in a cell line panel covering 12 indications, consisting of 64 cell lines. Next, a simulated drug modifier screen was run using patient relevant avatars with prevalent alterations, which identified MITF as a predictive biomarker of VCPi sensitivity. An in vitro melanoma model of MITF dependency, SKMEL5, was used to test our hypothesis. Hypotheses derived from in silico predictions were validated using various forms of VCP loss including pharmacological inhibition using a phase 1 VCPi, CB5083, as a reference compound, siRNA and by conditional knockout. The sensitivity of VCPi in melanoma was confirmed in vitro and a correlation (R= -0.86) was found between the protein levels of MITF and IC50 values of VCPi. In the SKMEL5 cells, we observed a dose dependent reduction in levels of MITF following VCPi. Next, we sought to test the efficacy of VCPi in the SKMEL5 in vivo CDX model. Four weeks of CB5083 dosing using 50 mg/kg 4on/3off schedule was tolerated, resulted in 46% tumor growth inhibition, and this was accompanied by a downregulation of MITF and one of MITFs targets, DCT, in tumor samples post treatment. These studies support the therapeutic potential of VCP inhibitors in the MITF High/MITF Amplification subgroup of patients with metastatic melanoma with a poor prognosis and a decreased 5-year survival. Targeting a common essential gene such as VCP is associated with a narrow therapeutic index, however, we have demonstrated efficacy using a relatively low dose of 50 mg/kg. Taken together, we are proposing a patient stratification strategy based on the identification of a predictive biomarker from an in silico screen. Citation Format: Aofie Campbell, Dóra Kállai, Boldizsár Elek, Csilla Hegedűs, Magdolna Djurec, Ivan Fekete, Péter Szikora, Csaba Szántai-Kis, Amrik Basran, Stephen Connolly, Daniel Veres. Inhibition of VCP in an in vivo model of metastatic melanoma selected based on a predictive biomarker demonstrates tumor reduction [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 6502.

Cancer ResearchVol. 85(8_Supplement_1)
Simula Research Laboratory (NO)
Openalex Percentile: Top 90%
Inflammatory mediators and NSAID effects
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