Newly identified PET biomarker predicts success of immune checkpoint blockade therapy

Immunotherapies, such as ICB, have produced promising clinical outcomes in melanoma, non-small cell lung cancer, and several other types of tumors. However, only a subgroup of patients experiences positive outcomes with objective response rates spanning between five and 60 percent.

"Developing reliable approaches for assessing responses and selecting eligible patients for immunotherapy remains challenging," said Zhaofei Liu, PhD, Boya Distinguished Professor at Peking University in Beijing, China. "Current clinical criteria for monitoring solid tumor responses to immunotherapy are based on CT and MRI scans, but these methods result in a considerable delay between treatment commencement and response evaluation. Molecular imaging techniques, especially PET, have emerged as robust tools for predicting immunotherapy effectiveness through the real-time, quantitative, and noninvasive assessment of biomarkers in vivo."

In the study, a mouse model was utilized to identify new imaging biomarkers for tumor responses to ICB therapy. Through a proteomic analysis (separation, identification, and quantification of proteins in a tumor), researchers found that tumors exhibiting low Gal-1 expression responded positively to ICB therapy.

Next, Gal-1 was labeled with ¹²⁴I and the radiotracer (¹²⁴I-α-Gal-1) and small animal PET imaging and biodistribution studies were conducted to assess the specificity of the radiotracer. PET imaging with ¹²⁴I-αGal-1 showed the immunosuppressive status of the tumor microenvironment, thus enabling the prediction of ICB resistance in advance of treatment. For tumors that were not predicted to respond well to ICB therapy, researchers developed a rescue strategy that utilized a Gal-1 inhibitor that significantly improved the chance for success.

"Gal-1 PET opens avenues for the early prediction of ICB efficacy before treatment initiation and facilitates the precision design of combinational regimes," noted Liu. "This sensitive approach has the potential to achieve individualized precision treatment for patients in the future."

This research was published online in March 2024.