Lunit (KRX:328130.KQ), a global leader of AI-powered cancer diagnostics and therapeutics solutions, is set to make a significant impact at the American Society of Clinical Oncology (ASCO) Annual Meeting in Chicago, Illinois. This year, Lunit will present 16 abstracts at the conference, showcasing the groundbreaking capabilities of its AI-biomarker platform, Lunit SCOPE. This comprehensive collection of studies includes 10 poster presentations and 6 online publications, covering a wide spectrum of topics. From predicting clinical outcomes to exploring the complex dynamics of tumor microenvironments, these advancements highlight Lunit's unwavering commitment to advancing AI pathology research and personalized cancer care.

A breakthrough joint study conducted with the Japan National Cancer Center East (NCCE), investigated microsatellite stable (MSS) locally advanced rectal cancer (LARC), using Lunit SCOPE IO, an AI-powered tumor-infiltrating lymphocyte (TIL) analyzer. The study measured TIL density in the tumor microenvironment (TME) of MSS LARC samples during chemoradiotherapy (CRT) and found a strong correlation between the change in TIL density and the pathologic complete response (pCR) rate. This finding indicates the potential of AI-powered spatial TIL analysis in predicting favorable clinical outcomes.

Another study using Lunit SCOPE IO in head and neck squamous cell carcinoma (HNSCC) patients undergoing immunotherapy demonstrated a shift towards an inflamed immune phenotype, leading to improved outcomes in patients treated with neoadjuvant durvalumab, with or without tremelimumab. Another clinical trial, evaluating the efficacy of neoadjuvant therapy in HPV-positive HNSCC patients, revealed treatment-induced immune changes are strongly associated with treatment outcomes.

Both studies observed a shift from non-inflamed to inflamed immune phenotype with immunotherapy, which was correlated with treatment effectiveness. Notably, patients treated with neoadjuvant durvalumab, with or without tremelimumab achieved a remarkable 93.1% 12-month disease-free survival rate. These results underscore Lunit SCOPE IO's potential in guiding personalized cancer care by revealing immune changes induced by treatment and their impact on clinical outcomes.

A comprehensive analysis of cancer images from The Cancer Genome Atlas (TCGA) using Lunit SCOPE IO unveiled the close correlation between fibroblast density and Transforming growth factor-beta (TGFβ) signaling, a factor associated with resistance to cancer immunotherapy. The finding emphasized that analyzing various cells within the tumor can be applied to the development of personalized therapies targeting specific tumor microenvironments. This study was proved by more than 1,800 real-world dataset consisting of multiple cancer types, treated with immune checkpoint inhibitors (ICI).

Another TCGA pan-cancer-based analysis with Lunit SCOPE IO investigated the association between spatial residue of macrophage and anti-tumor activity in the tumor microenvironment, revealing that intra-tumoral macrophage density was strongly correlated with immune phenotypes and genomic signatures.

Another study showcased the utility of Lunit SCOPE uIHC (Universal Immunohistochemistry) model in analyzing the expression of tumor-associated antigens (TAA) in various tumors. By accurately predicting responses to novel TAA-targeted agents, this AI-powered analyzer has the potential to guide personalized treatment decisions and facilitate the exploration of target cancer types.

The last study validated the Lunit SCOPE genotype analyzer's capability to enhance the accuracy and robustness of MET pathogenic mutation prediction model in non-small cell lung cancer (NSCLC), offering a cost-effective screening method for MET alterations in lung cancer. Area Under the Curve (AUC) of the predictive model recorded a significantly high level at 0.837.

"I am excited to present the groundbreaking results from our studies at ASCO, showcasing the immense impact of the Lunit SCOPE suite," said Brandon Suh, CEO of Lunit. "Through our AI-biomarker platform, we are paving the way to provide valuable insights into cancer progression, immune responses, and treatment efficacy. These findings exemplify our dedication to transforming cancer diagnostics and treatment, empowering healthcare professionals to make informed decisions and ultimately improve patient outcomes."