Discovery of Targets for Immune-Metabolic Antitumor Drugs Identifies Estrogen-Related Receptor Alpha

Area of Science:

• Computational biology
• Cancer research
• Immunology

Background:

• Drugs targeting multiple cancer mechanisms offer broad clinical potential.
• Identifying regulators that modulate both tumor immunity and oncogenic pathways is crucial for effective cancer therapies.

Purpose of the Study:

• To develop an in silico multiomics approach (BipotentR) for identifying cancer cell-specific regulators.
• To discover novel drug targets that simultaneously modulate tumor immunity and oncogenic pathways.
• To evaluate the utility of BipotentR in predicting patient response to immunotherapy and identifying new therapeutic strategies.

Main Methods:

• Developed BipotentR, an in silico multiomics approach.
• Identified 38 candidate immune-metabolic regulators.
• Utilized machine learning and deep neural networks to analyze regulator activity and patient response to anti-PD-1 therapy in melanoma.
• Applied BipotentR to angiogenesis and growth suppressor evasion pathways.

Main Results:

• BipotentR identified 38 candidate immune-metabolic regulators.
• Tumor activities of these regulators stratified melanoma patients by response to anti-PD-1 therapy, improving predictive power over current biomarkers.
• The top regulator, ESRRA, is activated in immunotherapy-resistant tumors; its inhibition suppressed tumor energy metabolism and activated immune mechanisms (cytokine induction, antigen presentation), leading to tumor cell death.
• BipotentR demonstrated utility in other cancer pathways.

Conclusions:

• BipotentR is a valuable resource for evaluating patient response and discovering drug targets with multi-mechanistic anti-tumor activity.
• Targeting ESRRA offers a potential therapeutic strategy by simultaneously suppressing tumor metabolism and enhancing anti-tumor immunity.
• The BipotentR approach can accelerate the discovery of novel cancer therapeutics.