Lunit’s SCOPE IO artificial intelligence (AI)-based pathology platform has demonstrated its ability to generate biomarkers that predict patients’ response to immunotherapy across cancer types.
Data from three studies are being debuted by the South Korean company in presentations at this year’s European Society for Medical Oncology (ESMO) congress, taking place from October 17–21 in Berlin, Germany.
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For the AtezoTRIBE and AVETRIC trials, conducted at the University of Pisa in Italy, SCOPE IO was applied to pre-treatment histology slides from enrolled patients with proficient mismatch repair (pMMR) metastatic colorectal cancer (mCRC). Lunit’s AI platform generated a biomarker that stratified patients into “biomarker-high” and “biomarker-low” groups in the respective trials.
In the AtezoTRIBE trial, biomarker-high patients treated with atezolizumab plus FOLFOXIRI/bevacizumab showed significantly improved progression-free survival (PFS) and overall survival (OS) compared to biomarker-low patients.
Among the AVETRIC trial cohort, SCOPE IO confirmed improved survival outcomes for biomarker-high patients receiving ICI-based therapy, with better PFS and OS compared to biomarker-low patients.
The results suggest that an AI-derived tumour microenvironment biomarker could help identify patients with pMMR mCRC who are most likely to benefit from immunotherapy combinations, according to Lunit.
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By GlobalDataA collaborative study between Lunit and Yonsei University College of Medicine, Korea, evaluated whether AI-defined immune phenotypes (IP) could predict outcomes in patients with advanced clear cell renal cell carcinoma (ccRCC), either treated with nivolumab plus ipilimumab (NIVO+IPI) or sunitinib (SUN).
SCOPE IO was applied in the study to classify tumours as inflamed or non-inflamed, based on the density and spatial distribution of tumour-infiltrating lymphocytes.
Patients with inflamed tumours treated with NIVO+IPI demonstrated significantly longer PFS, OS, and response rates of 60.5% versus 23.2% in patients with non-inflamed tumours.
Lunit stated that the results highlight that AI-based immune phenotyping is a promising biomarker to guide treatment selection between immunotherapy combinations and targeted therapies in first-line treatment for ccRCC.
The third presentation reveals data from Lunit’s collaboration with Japan’s National Cancer Center Hospital East (NCCHE) that evaluated the role of SCOPE IO for ICI treatment response in non-small cell lung cancer (NSCLC) patients.
In the study, tumours SCOPE IO classified as inflamed showed significantly better responses and longer survival with ICI therapy compared to non-inflamed tumours, Lunit said, with the difference not observed among patients treated with cytotoxic chemotherapy. The result strengthens the evidence supporting Lunit SCOPE IO as a predictive biomarker for immunotherapy benefit in NSCLC, Lunit added.
Lunit’s CEO, Brandon Suh, commented: “These findings show the potential of Lunit SCOPE IO to help identify patients who will truly benefit from immunotherapy – whether in colorectal or kidney cancer – and to guide treatment strategies that can make cancer care more precise and effective.”
SCOPE IO has previously demonstrated its ability in identifying specific patterns in rare tumour samples that correlate with better treatment outcomes, and in improving human epidermal growth factor receptor 2 (HER2) biomarker evaluation in metastatic colorectal cancer (mCRC) patients undergoing HER2-targeted therapy.
In June, Lunit forged a collaboration with Microsoft that aims to help bring its AI-powered diagnostics for cancer detection into clinical practice.
