"Will This Cancer Drug Work for Me?"... Predicting Treatment Response Before Administration [Reading Science]

GIST Enables Precise Diagnosis of Immuno-Oncology Drug Efficacy Through Single-Cell Analysis
Predicting Immune Response by Analyzing Genetic Errors in Individual Tumor Cells
Overcoming the Limitations of Conventional 'Average-Based' Testing Methods

The Gwangju Institute of Science and Technology (GIST) has developed a technology that analyzes cancer cells at the single-cell level to precisely predict the efficacy of immuno-oncology treatment. By reflecting the unique tumor characteristics of each patient, this technology is expected to improve the accuracy of personalized cancer therapy by allowing for a prior assessment of the likelihood of treatment success.

On May 6, GIST announced that the research team led by Professor Park Jihwan from the Department of Life Sciences has developed 'scMnT,' a technology for analyzing immuno-oncology treatment responses at the single-cell level.

A conceptual diagram of MSI, a biomarker predicting the response to immuno-oncology treatment. Currently, immuno-oncology treatment eligibility is determined solely based on the presence or absence of MSI; however, this study focused on the varying degrees of MSI within individual tumor cells and proposed a new approach to quantitatively analyze this as an 'intensity' concept. Provided by the research team

Immuno-oncology therapy works by inducing a patient's immune cells to attack cancer cells. However, even for the same type of cancer, treatment responses can vary significantly between patients, and some patients experience little to no benefit from the therapy.

The research team attributed these differences to the genetic characteristics within cancer cells. They focused in particular on 'microsatellite instability (MSI),' where replication errors accumulate in DNA repetitive sequences. Generally, cancer cells with high MSI produce more abnormal proteins, making them more easily recognized by immune cells, and thus tend to respond better to immuno-oncology drugs.

Conventional tests have relied on 'bulk analysis,' which examines the entire tumor as a whole and therefore cannot capture detailed variations between cells within the tumor. Because this method is centered on average values, it may overlook areas within the tumor that have a relatively low therapeutic response.

The scMnT technology developed by the research team quantitatively measures the MSI intensity of tens of thousands of individual cells within a tumor. Rather than simply classifying MSI as 'positive' or 'negative,' this method quantifies how strongly MSI is expressed in each cell.

When the team applied this technique to actual colorectal cancer patient data, they confirmed the presence of 'intra-tumoral heterogeneity,' where cells with high MSI levels and those with low MSI levels coexist within the same tumor.

Notably, in regions with high MSI intensity, immune cells known as T lymphocytes were found to be concentrated, resulting in more active attacks on cancer cells. In contrast, areas with low MSI showed relatively subdued immune responses. This indicates that subtle differences within the tumor can lead to significant differences in actual treatment outcomes.

The research team explained that tumors with higher MSI intensity generally tended to have better responses to immuno-oncology therapy. Accordingly, they expect the scMnT technology to be useful in formulating patient-specific treatment strategies and predicting responses to immuno-oncology drugs.

Professor Park Jihwan stated, "This study has laid the groundwork for understanding MSI as a quantitative indicator, rather than a simple binary marker," adding, "We expect it will contribute to the development of personalized treatment strategies for cancer patients and improve the success rate of immuno-oncology therapies in the future."

This research was supported by the Ministry of Science and ICT and the National Research Foundation of Korea (NRF) through the Mid-Career Researcher Program, as well as by the Ministry of SMEs and Startups and the Korea Technology and Information Promotion Agency for SMEs (TIPA). The results of the study were published online in the international journal Briefings in Bioinformatics on April 14.

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