Our Discoveries

NIH scientists develop AI tool to predict how cancer patients will respond to immunotherapy

In a proof-of-concept study, CCR researchers developed an artificial intelligence (AI) tool that uses routine clinical data to predict whether someone’s cancer will respond to immune checkpoint inhibitors. The machine-learning model may help doctors determine if these immunotherapy drugs are effective for treating a patient’s cancer. The study, published June 3, 2024, in Nature Cancer, was led by Eytan Ruppin, M.D., Ph.D., Chief of the Cancer Data Science Laboratory, and collaborators at Memorial Sloan Kettering Cancer Center in New York.

Master regulators flip the switch on neuroblastoma’s developmental state

Waves of regulatory changes can transform self-renewing neuroblastoma cells into neurons.

Benign nail condition linked to rare syndrome that greatly increases cancer risk

Researchers from CCR and the National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS) discovered the presence of a benign nail abnormality may lead to the diagnosis of a rare inherited disorder that increases the risk of developing cancerous tumors. The study suggests conducting nail evaluation of affected patients and at-risk family members.

New AI tool classifies brain tumors using images of tumor slides

A new artificial intelligence model has been found to be highly effective at identifying brain tumor subtypes — with 95% accuracy — simply by analyzing a standard pathology image of the tumor tissue.

New research identifies a protein essential to maintaining chromosomal stability

Researchers discovered how overproduction of a protein called CENP-A can lead to chromosomal abnormalities, which are found in many types of cancer.

New database of sarcoma cell line data will drive rare cancer research

CCR researchers have developed the largest publicly accessible sarcoma cell line database called Sarcoma CellMinerCDB. The tool merges previously available and new sarcoma cell line data that can be used to identify new therapeutic targets for these cancers.

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

In a proof-of-concept study published on April 18, 2024, in Nature Cancer, CCR researchers 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. The team, led by Eytan Ruppin, M.D., Ph.D., Chief of the Cancer Data Science Laboratory, suggests 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 in treating their cancer.

Cellular processing reverses molecule’s effect on anticancer immunity

Immune cells convert an immunosuppressive lipid into an anticancer immunity enhancer.

New research on liver cell diversity could help scientists understand tumor complexity

Hepatocytes, the main cell type in the liver, differ in function according to their location in the liver. A new study shows that mitochondrial responses to nutrients drive this diversity — a finding that could help researchers better understand tumor cell heterogeneity.

New biomaterial enhances cancer vaccine effectiveness to help eliminate cancer in mice

Scientists have created a new type of cancer vaccine approach that uses a biomaterial that attracts immune cells and localizes the delivery of the vaccines. In mice, the biomaterial combined with a cancer vaccine was able to cure 50 to 75% of their tumors.

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