NIH Researchers Develop AI Tool Toward More Targeted Cancer Treatment

NCI researchers 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. This model potentially could be used to help doctors more precisely match cancer patients with drugs that will be effective for their cancer. Findings from this pilot study were published in Nature Cancer.

Current approaches rely on bulk sequencing of tumor DNA and RNA. However, tumors contain more than one type of cell and often 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.

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. 

In the new study, researchers investigated whether they could use machine learning to predict drug responses using widely available data but fine-tuning it using single-cell RNA sequencing data. Using this approach on published cell-line data, researchers built AI models for 44 FDA-approved cancer drugs. The AI models accurately predicted how individual cells would respond to both single drugs and combinations of drugs. 

Researchers then tested their approach on published data for 41 patients with multiple myeloma treated with a combination of four drugs, and 33 patients with breast cancer treated with two drugs. Scientists discovered that if just one clone were resistant to a particular drug, the patient would not respond to that drug, even if all the other clones responded. 

In addition, the AI model successfully predicted the development of resistance in published data from 24 patients treated with targeted therapies for non-small cell lung cancer. 

Researchers developed a website and guide for how to use the AI model, called Personalized Single-Cell Expression-based Planning for Treatments In Oncology (PERCEPTION), with new datasets.