Childhood cancers are rare and account for about one percent of U.S. cancer diagnoses. They differ from adult tumors in that they often arise from many more diverse kinds of cells, including embryonal tissues, sex-cord stromal cells of the ovary or testis, the brain’s neural and glial cells and more.
Yet although improved tumor detection and treatment have increased survival rates for many different cancer subtypes, more than 1,900 children across the U.S. still lose their battle each year.
A new dataset — comprising the genomic profiles of a huge array of pediatric tumors — could help change that.
Digging into the data
In recent years, pediatric oncologists have increasingly scrutinized tumors’ genomic signatures. This information helps them determine treatment for each child and design clinical trials for evaluating novel drugs and new uses of existing ones.
But ultimately improving precision treatment of childhood cancers, however, will require very robust patient-derived data analyses.
Fittingly, this extensive new dataset — reported in Cancer Research and developed by a multi-institutional team, including pediatric oncologist Katherine Janeway, MD, of the Dana-Farber/Boston Children’s Cancer and Blood Disorders Center — provides clinicians and researchers with a powerful new tool in the fight against cancer.
Not all tumors in a subtype are created equally
The dataset contains genomic profiles that represent known and previously-unknown gene mutations across six types and 49 subtypes of pediatric tumors. Gathered from 1,215 individuals aged 18 and under, it’s one of the largest such datasets ever created.
The data reveals that all tumors in a given subtype may not always result from the exact same genetic mutations. Therefore, treatment plans based upon a tumor subtype, as a rule, may not be personalized enough to treat all childhood cancers.
In fact, some children may have unprecedented genetic mutations that call for customized treatment plans.
“Currently, only a few children benefit from a precision medicine approach,” says Janeway. “However, when all the aspects of precision medicine align — from tumor profiling in the appropriate clinical setting to delivery of a targeted therapy — the effect can be transformative for the individual patient.”
That’s because, according to Janeway, individualized treatment plans can result in fewer long-term, toxic side effects than traditional chemotherapy.
A case-by-case look at childhood cancers
By mining the comprehensive dataset, Janeway and her collaborators discovered several instances of tumors with unique genomic profiles. For example, they found a gene mutation usually associated with lung tumors, EML4-ALK, in three children with other kinds of cancers.
The researchers also discovered similar instances in which well-documented gene mutations were linked to different types of tumors than observed before.
Furthermore, they found therapeutically-responsive gene mutations, like BRAF V600E, across a wider-than-expected variety of tumors. This hints that existing, FDA-approved therapies might be effective in fighting even more tumor types than originally indicated.
Unique tumors require unique treatments
All of these findings garner additional support for the well-established idea that genomic profiling can help guide treatment options. To boot, such information can better match individuals with leading-edge clinical trials.
“Targeted therapies may have a broader role in the treatment of some pediatric cancers than previously appreciated, and clinical trials investigating their efficacy outside of their approved indications are warranted,” the researchers remark in their paper.
The researchers have made the dataset publicly available so that it can be used right away to guide clinical management of pediatric cancers, aid in the discovery of novel genetic alterations and/or validate findings from other studies.
“As sequencing technologies advance, and access to sequencing data increases through efforts like this project, it will lead to increased clinical trial options,” says Janeway. “Subsequently, more children will benefit.”