Lunit's 'Lunit Scope' Study on Nasopharyngeal Cancer Patients Published in Clinical Cancer Research

[Asia Economy Reporter Chunhee Lee] Medical artificial intelligence (AI) company Lunit announced on the 1st that the results of applying the AI biomarker 'Lunit SCOPE' to nasopharyngeal cancer patients treated with immuno-oncology drugs were published in the world-renowned cancer research journal 'Clinical Cancer Research.'

Nasopharyngeal cancer is a cancer commonly found in Asian patients, mainly in southern China, Taiwan, and other regions. Although the immune target substance 'PD-L1' is expressed in nasopharyngeal cancer, clinical trials on the effectiveness of immuno-oncology treatments have been limited, making research in this area urgently needed. Additionally, unlike other cancers, PD-L1 has not been predictive of the effectiveness of immuno-oncology drugs in nasopharyngeal cancer, posing challenges in finding predictive markers.

This study was conducted as a phase 2 clinical trial combining the immuno-oncology drug 'Opdivo' (generic name Nivolumab) and the conventional chemotherapy drug Gemcitabine, targeting 36 nasopharyngeal cancer patients from eight domestic hospitals in collaboration with the Korean Association for Cancer Chemotherapy, led by Professor Beomseok Kim of the Hematology-Oncology Department at Seoul National University Hospital and Professor Hyunae Jung of the Hematology-Oncology Department at Samsung Seoul Hospital.

As a result, the 'objective response rate (ORR),' which indicates the degree of tumor size reduction after drug administration, was recorded at 36.1%, and the 'median progression-free survival (mPFS),' which refers to the period during which the tumor does not grow beyond a certain size and the patient survives, was 13.8 months, meeting the primary endpoint of the study. The study also confirmed meaningful clinical results, including the efficacy of the combination therapy of Nivolumab and Gemcitabine in nasopharyngeal cancer.

During the analysis, the research team applied the AI biomarker platform 'Lunit SCOPE' to predict patients' treatment responses to the therapy. Using Lunit SCOPE, patients were classified into three immune phenotypes (IP) based on their immunological characteristics: Immune-Activated (Inflamed), Immune-Excluded, and Immune-Desert.

The results showed that the Immune-Activated group predicted a positive therapeutic effect of the immuno-oncology drug, whereas the Immune-Excluded group exhibited resistance to the combination therapy, resulting in shorter patient survival periods (mPFS). This demonstrated that in nasopharyngeal cancer, where PD-L1 expression has low predictive power, classifying immune phenotypes using Lunit SCOPE can predict the therapeutic effect of immuno-oncology drugs in advance.

Seobeomseok Seo, CEO of Lunit, stated, "This study will greatly aid in predicting the effectiveness of immuno-oncology treatments for nasopharyngeal cancer, which has had limited research so far, and in developing new therapies. It is also significant in showing the potential use of Lunit SCOPE not only in immuno-oncology monotherapy but also in actual clinical settings involving combination therapies with conventional chemotherapy."

This study was published online in Clinical Cancer Research, a leading international oncology journal issued by the American Association for Cancer Research (AACR).

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