Lunit to Present Three Lung Cancer AI Biomarker Studies at WCLC 2026

Analysis of Tumor Microenvironment Differences by EGFR Subtype
Association of Preoperative Combination Therapy Response and TP53 Mutation Presented

Medical artificial intelligence (AI) company Lunit announced on September 8 that it will present three research abstracts on lung cancer using its AI biomarker platform 'Lunit Scope IO' at the World Conference on Lung Cancer (WCLC 2026), which will be held at COEX in Seoul from September 12 to 15.

This is the first time in 19 years that the WCLC is being held in Korea, following the previous conference in 2007. At this year’s event, Lunit will unveil research results analyzing the differences in the tumor microenvironment and treatment responses based on genetic mutations, as well as the associations between genetic mutations and histological features.

Promotional material for Lunit's participation in the World Conference on Lung Cancer (WCLC 2026). Lunit

The first study analyzed differences in the tumor microenvironment by subtype of EGFR mutations frequently found in non-small cell lung cancer (NSCLC). The research team analyzed the whole slide images (WSI) of 494 patients with confirmed EGFR subtypes using Lunit Scope IO.

The analysis showed that tumors with exon 19 deletion (Ex19del) exhibited a high density of tumor-infiltrating lymphocytes (TILs), which are immune cells, while L858R mutations were associated with increased infiltration of macrophages. Tumors with exon 20 insertion (Ex20ins) displayed relatively higher densities of endothelial cells that make up blood vessels.

The research team highlighted that even lung cancers with the same EGFR mutation can demonstrate distinct tumor microenvironment characteristics depending on the subtype. They suggested that these differences could be leveraged to better understand treatment responses by subtype and to establish tailored treatment strategies for individual patients.

The second study analyzed the association between treatment response and the tumor microenvironment in patients with NSCLC who underwent preoperative chemoimmunotherapy. In collaboration with Dr. Paola Nisticò’s research team at Regina Elena National Cancer Institute in Italy, Lunit analyzed tissue samples from 32 patients using Lunit Scope IO.

Among the group of patients who achieved pathological complete response (pCR), there was active immune cell infiltration and a pronounced presence of tertiary lymphoid structures (TLS) within the tumor microenvironment. In contrast, among those who did not achieve pCR, there was evidence of 'immune exclusion,' where immune cells failed to sufficiently infiltrate the tumor, accompanied by relatively heightened tumor cell proliferation.

The researchers explained that these findings help clarify tumor microenvironment characteristics related to preoperative immunotherapy responses, and suggested that they could be used in the future to develop biomarkers for determining adjuvant therapy after surgery.

The third study analyzed tissue samples from 462 patients with lung adenocarcinoma to compare tumor microenvironment characteristics according to the presence or absence of TP53 mutations. TP53 is a tumor suppressor gene that inhibits the abnormal proliferation of damaged cells.

The analysis revealed that tumors with TP53 mutations had a higher ratio of immune activity. Conversely, tumors without mutations exhibited immune exclusion along with higher densities of stromal fibroblasts and endothelial cells.

The research team confirmed that tumor microenvironment characteristics observed in tissue images may be associated with TP53 mutations, and proposed that these findings could serve as tissue-based biomarkers to help preselect patients or establish treatment strategies before genetic testing.

Beomseok Seo, CEO of Lunit, stated, "At this year’s World Conference on Lung Cancer, we have demonstrated that AI can help reveal clues connecting genetic mutations, the tumor microenvironment, and treatment responses. Moving forward, we will continue to contribute to providing more precise treatment strategies for cancer patients through the use of Lunit Scope."

This content was produced with the assistance of AI translation services.