IRP researchers develop AI tool with potential to more precisely match cancer drugs to patients

Thursday, April 18, 2024

Proof-of-concept study analyzed a newer technology known as single-cell RNA sequencing

In a proof-of-concept study, researchers at the National Institutes of Health (NIH) have developed an artificial intelligence (AI) tool that uses data from individual cells inside tumors to predict whether a person’s cancer will respond to a specific drug. Researchers at the National Cancer Institute (NCI), part of NIH, published their work on April 18, 2024, in Nature Cancer, and suggest that such single-cell RNA sequencing data could one day be used to help doctors more precisely match cancer patients with drugs that will be effective for their cancer.

Current approaches to matching patients to drugs rely on bulk sequencing of tumor DNA and RNA, which takes an average of all the cells in a tumor sample. However, tumors contain more than one type of cell and in fact can have many different types of subpopulations of cells. Individual cells in these subpopulations are known as clones. Researchers believe these subpopulations of cells may respond differently to specific drugs, which could explain why some patients do not respond to certain drugs or develop resistance to them.

In contrast to bulk sequencing, a newer technology known as single-cell RNA sequencing provides much higher resolution data, down to the single-cell level. Using this approach to identify and target individual clones may lead to more lasting drug responses. However, single-cell gene expression data are much more costly to generate than bulk gene expression data and not yet widely available in clinical settings.