Exploring SDX-7320's Therapeutic Potential in Obesity and Cancer: Preclinical Insights

3 June 2024
Obese cancer patients have a higher mortality rate than their non-obese counterparts due to factors such as increased leptin levels, decreased adiponectin, estrogen production in fat tissue, and high insulin levels caused by resistance. The role of inflammatory cytokines also contributes to the spread and severity of cancer. MetAP2 inhibitors have shown potential in treating both cancer and obesity-related conditions, but some have faced challenges due to central nervous system (CNS) side effects.

SDX-7320 is a new type of MetAP2 inhibitor, a copolymer-drug conjugate that combines a fumagillin-derived inhibitor with a hydroxypropylmethacrylamide backbone through a cleavable linker. This design is aimed at reducing CNS penetration and toxicity. In vitro tests revealed that SDX-7320 requires cleavage to bind MetAP2 and become biologically active, while its constituent SDX-7539 is a strong binder with an IC50 of 0.13 nM. SDX-7539 also effectively inhibits the proliferation of HUVECs with an IC50 of 0.2 nM.

Preclinical studies of SDX-7320 were conducted using mice with obesity and insulin resistance induced by a high-fat diet. The compound was administered subcutaneously to these mice and a control group every four days for a month. Results showed that SDX-7320 significantly reduced body weight and fat mass in obese mice and improved insulin resistance. It was more effective in obese mice than in lean ones and also decreased leptin and insulin levels while increasing adiponectin levels.

In models where obesity accelerates tumor growth, SDX-7320 demonstrated greater efficacy in obese mice with melanoma or mammary gland tumors compared to lean mice. Importantly, these beneficial effects were observed without any neurotoxicity. SDX-7320 is currently in phase I clinical trials for solid tumors and is being developed for cancers that are exacerbated by obesity and metabolic dysfunction, an emerging field known as "metabo-oncology."

The study was presented by Peter Cornelius and colleagues at the American Association for Cancer Research Annual Meeting in 2018, with the abstract published in Cancer Research.

How to Use Synapse Database to Search and Analyze Translational Medicine Data?

The transational medicine section of the Synapse database supports searches based on fields such as drug, target, and indication, covering the T0-T3 stages of translation. Additionally, it offers a historical conference search function as well as filtering options, view modes, translation services, and highlights summaries, providing you with a unique search experience.

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Taking obesity as an example, select "obesity" under the indication category and click search to enter the Translational Medicine results list page. By clicking on the title, you can directly navigate to the original page.

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By clicking the analysis button, you can observe that GLP-1R treatment for obesity has gained significant attention over the past three years, with preclinical research still ongoing in 2023. Additionally, there are emerging potential targets, such as GDF15, among others.

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Click on the image below to go directly to the Translational Medicine search interface.

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