Help Fight Childhood Cancer

World Community Grid and scientists at Chiba Cancer Center Research Institute and Chiba University are working together to develop novel drugs to treat neuroblastoma, one of the most frequently occurring solid tumors in children.

Neuroblastoma is one of the most frequently occurring solid tumors in children, especially in the first two years of life, when it accounts for 50% of all tumors. Neuroblastoma comprises 6-10% of all childhood cancers, and 15% of cancer deaths in children. It is the most common cause of death in children with solid cancer tumors. The cause of neuroblastoma is unknown, though most physicians believe that it is an accidental cell growth that occurs during normal development of the adrenal glands and sympathetic ganglia.

The clinical hallmark of neuroblastoma is the prospect for cure varying widely depending on age at diagnosis, extent of disease, and tumor biology. A subset of tumors will undergo spontaneous regression while others show relentless progression. Around half of all cases are currently classified as high-risk for disease relapse, with overall survival rates less than 40% despite intensive multimodal therapy. Despite many advances in the past three decades, neuroblastoma has remained an enigmatic challenge to clinical and basic scientists.

The rapid advancement in genetic research on cancer holds great promise for treating neuroblastoma. Genes linked to various cancers have been found, and scientists are currently developing effective therapeutic drugs aimed at some of the important molecular targets.

World Community Grid and The Help Fight Childhood Cancer Project

World Community Grid, the Chiba Cancer Center Research Institute, and Chiba University are working together through the Help Fight Childhood Cancer project to develop novel drugs to treat this complex pediatric tumor.

It has been demonstrated repeatedly that the function of a protein molecule - a substance made up of many atoms – is related to its three-dimensional shape. Scientists are able to determine by experiment the shapes of a protein and of a drug separately, but not always for the two together. If scientists knew how a drug molecule interacts with a target protein, chemists could design even better drugs that would be more potent than existing drugs.

To that end, the project's researchers are using computational methods to identify new candidate drugs that have the right shape and chemical characteristics to block three proteins - TrkB, ALK and SCxx, which are expressed at high levels or abnormally mutated in aggressive neuroblastomas. If these proteins are disabled, scientists believe there should be a high cure rate using chemotherapy.

The researchers have prepared a library of three million compounds - or potential drug candidates (called ligands) - and will use World Community Grid to simulate laboratory experiments to test which of these compounds block these proteins. Simulations will be conducted using AutoDock (also used in World Community Grid's FightAIDS@Home and Discovering Dengue Druges – Together projects), a suite of tools that predict how large numbers of different small drug molecules might bind to TrkB, ALK and SCxx, so the best molecules can be found computationally, before they are selected and tested in the laboratory for efficacy against neuroblastoma.

In the absence of World Community Grid, researchers would have to undertake their investigation through individual docking simulations, which would take approximately 8,000 years to complete. With World Community Grid, analysis can be carried out for thousands of drug candidates in parallel, allowing high throughput screening to be conducted. Researchers estimate this will reduce the time required to about 2 years.

This added level of speed and sophistication could potentially enable researchers to identify new drug candidates for neuroblastoma, thereby facilitating discovery of prognostic clues, which are not apparent by human inspection or traditional analysis alone and could advance the fields of cancer biology, drug discovery and therapy planning.