Algorithm Matches Pediatric Patients with Cancer to Precision Medicines

Utilizing data from the INFORM registry, researchers were able to identify high level priority targets in pediatric patients with cancer utilizing an algorithm that matched them to targeted treatments extending their progression-free survival time and showing the feasibility of this program in a real-world setting.

A new algorithm designed to identify molecular targets in pediatric patients with cancer and match them to targeted therapies extended progression-free survival (PFS), according to findings presented at the virtual scientific program of the 2020 American Society of Clinical Oncology (ASCO) Annual Meeting.1-2

“For pediatric patients, if the cancer has relapsed, the prognosis is poor and there are few new innovative treatments,” said lead author Cornelis van Tilburg, MD, PhD, a pediatric oncologist at Hopp Children’s Cancer Center Heidelberg, in a press release. “Compare this to adult oncology, where there are many new trials, many new biomarkers, and many new drugs. Pediatric oncology is really lagging behind when it comes to precision medicine and the development of new drugs.” 

The study looked at the multicenter, multi-national, non-interventional INFORM registry that collected clinical and molecular data from pediatric patients with refractory, relapsed, or progressive malignant disease.

To date, 1300 patients were enrolled and 525 patients completed follow-up to be included in this analysis. Of those patients identified, 149 received a targeted treatment based on the identified markers.

Those who received precision medicine demonstrated a median PFS of 204.5 days compared to 114 days in patients who did not receive targeted treatment after biomarkers were identified.

The program aimed to identify the highest priority targets and match patients with the proper treatment. Biomarkers included molecular alterations and gene expressions in molecular pathways that impact the development of cancer. Moreover, the INFORM registry provided underlying cancer predisposition information and oncologists were given access to the data to make treatment decisions. 

Priority target levels consisted of very high (8.0%), high (14.8%), moderate (20.3%), intermediate (23.6%), borderline (14.4%), low (2.5%), and very low (1.0%). In total, 15.4% of patients with no actionable target. 

Patients with a very high priority level target demonstrated a higher progression ratio compared with the overall population (1.0 vs 0.7).

The researchers concluded that implementing this model in the real-world setting would be feasible and help patients find treatments that are previously approved or in a clinical trial setting. 

“This registry has opened up the genomic landscape in pediatric oncology,” said Cornelis van Tilburg. “It provides a unique source of information to help match new drugs or drug ideas with suitable biomarkers in certain pediatric patient populations,” he said. Tilburg also added that the study focused on high-risk targets as opposed to splitting up patients by cancer type as pediatric cancer is rare which would make the study group harder to analyze, he explained in a virtual press cast with media through ASCO.

Researchers are now planning to analyze the data in the registry with the algorithm developed and based on these results are launching a series of phase I/II trials driven by biomarkers identified in the program. 



1. Large Scale Precision Medicine Approach Successfully Applied to Pediatric Cancers With Poor Prognosis. Published May 28, 2020.  Accessed May 28, 2020.

2. Van Tilburg, Cornelis, Pfaff, Elke, et. Al. The pediatric precision oncology study INFORM: Clinical outcome and benefit for molecular subgroups. Presented at: 2020 American Society of Clinical Oncology (ASCO) Annual Meeting. Abstract LBA10503