KAIST Develops Antibodies With Cellular “Eyes” to Detect Cancer Mutations

KAIST researchers have reported a new class of T-cell-receptor-like antibodies designed to recognize an intracellular cancer mutation with high specificity. The work targets KRAS(G12D), a widely occurring oncogenic driver in pancreatic, colorectal, and lung cancers that has long been viewed as difficult to treat directly because it resides inside cells.

The central obstacle is access: conventional antibodies are generally unable to reach intracellular targets. To overcome this, the team exploited the way cells naturally process proteins. When mutated KRAS(G12D is broken down, it can generate short protein fragments—neoantigens—that act as molecular “clues” for the immune system.

In many cases, such neoantigen fragments are loaded onto the cell surface for immune surveillance. The researchers focused on designing an antibody that can “read” one of these KRAS(G12D)-derived neoantigen fragments. Using a computational-to-experimental workflow, they selected candidates that would bind only to cancer cells presenting the relevant mutation-derived trace.

Their antibody is described as TCR-like, borrowing design logic from T-cell receptors, which recognize peptide fragments displayed on the major histocompatibility complex. In effect, the antibody provides an immunotherapy molecule with an analog of the T cell’s sensing mechanism, enabling it to distinguish cancer-associated intracellular mutations from normal cellular proteins.

Experimental tests showed that the antibody selectively binds KRAS(G12D)-bearing cancer cells while exhibiting minimal reactivity to non-mutant targets. Functional assays further indicated that the antibody can eliminate mutation-positive cancer cells in immunotherapy settings, supporting the concept that intracellular driver mutations can be made therapeutically visible.

Importantly, the study presents its platform as more than a single-mutation achievement. Because neoantigen generation is a general feature of mutated proteins, the same design strategy could be adapted to other cancer mutations that generate distinct intracellular fragments.

The research, led by Professor Byung-Ha Oh of KAIST’s Department of Biological Sciences with collaboration from Therazyne, was conducted by KAIST-affiliated investigators including SangPhil Ahn at Therazyne. The paper was published online in Molecular Therapy, reflecting the journal’s focus on gene and cell therapy innovations.

Overall, the study positions computational protein design paired with targeted screening as a route to next-generation precision antibody therapies. By aiming specificity at mutation-derived neoantigen signatures, the approach seeks to improve therapeutic discrimination and reduce collateral effects on healthy cells.