California Initiative to Advance Precision Medicine California Kids Cancer Comparison
The California Kids Cancer Comparison project improved pediatric cancer care using novel, RNA-based approaches to treatment; and by using large data sets to compare tumors between patients. The team was led by David Haussler, PhD at University of California, Santa Cruz.
Compared to 50 years ago, standard treatment for childhood cancer has remained largely unchanged. In California, 500 of the 1,700 children annually diagnosed with cancer either do not respond to standard treatments or have no standard therapies available to treat their condition. Hard-to-treat cancers are categorized as "relapsed" or "refractory," meaning they have resisted available treatments. For most of these patients, hospice is the only remaining option.
Whereas adult cancers are often linked to genetic mutations that are acquired during an individual’s lifetime, such as through environmental exposures, pediatric cancers present with fewer mutations and are therefore more difficult to diagnose. Support for and advancement of adult cancer therapies continue to progress compared to pediatric cancers, due in large part to ample federal funding, the underlying biology of adult cancers, more established data sharing platforms, and the drug development pipeline. Childhood cancers are significantly less common, which ultimately limits clinical trials from recruiting sufficient numbers of patients and makes drug development a much slower process than for adult cancers. Pediatric cancers also tend to be more complex, which prevents a single therapy from benefitting large groups of patients. Of federal funding allocated to the National Cancer Institute, approximately 4% is annually designated for pediatric cancers.
Cancer cells are characterized by uncontrolled cell growth that causes tumors to form and grow. This occurs because the cancer cells' genome (complete blueprint of genetic material, or DNA) has acquired specific mutations (changes in basic DNA units).
Until 2017, cancer drugs were developed to target specific mutations based on where a tumor was located within the body (e.g., lung cancer). These targeted drugs work by interfering with the ability of cancer cells to grow or survive. They are effective as long as the patient's tumor has the most common mutation the drug is designed to target. Occasionally, a mutation known to occur in one tumor type is detected in a tumor in a different location of the body. For instance, a mutation typically found in lung cancer may be found in a brain tumor. Since the drug is targeted to prevent or reverse the negative effects of that mutation, it may help treat the brain cancer, even though it was originally developed for lung cancer. Advanced DNA sequencing allows clinicians to uncover a patient's specific cellular mutations and can help direct the treatment strategy.
Just as in healthy cells, each cancer cell contains the full genome but only uses a fraction of the total available genes to perform its specialized functions. Which genes are active or dormant distinguishes one cell type from another, like a muscle cell compared to a kidney cell. This on/off process is called gene expression, and RNA is a central part of it.
Consider the analogy of DNA as the full set of blueprints of a building site and RNA as the daily orders for a construction crew. Scientists can uncover which genes are active by identifying the collection of RNA molecules present in a cell. This set of RNA molecules is known as a cell's transcriptome, and the scientific study of it is called transcriptomics. By comparing RNA molecules that are detected in a patient's tumor to those found in thousands of other tumors (comparative RNA analysis), scientists can ascertain how the molecular pattern of a patient's tumor resembles or differs from other tumors. This information can help guide the best treatment strategy based on the underlying mechanisms of tumor growth.
For hard-to-treat cancers, recent clinical trials based on tumor genomics have had limited success, especially for children. On average, DNA analysis of pediatric cancers yields useful information for fewer than 10% of patients for whom standard treatment has been unsuccessful. The California Kids Cancer Comparison (CKCC) project sought to ameliorate cancer care for pediatric patients by leveraging two fundamental concepts: 1) instead of relying exclusively on genomic mutations in the tumor (DNA-based analysis), the research team employed an RNA-based approach; and 2) the team instituted large-scale computation to compare all RNA in a specific tumor with over 11,000 tumors from other patients ("Cancer Comparison"). Using these techniques, the team aimed to determine what is likely driving the uncontrolled growth of a patient’s specific tumor and therefore identify new potential targets for therapy.
As a step toward incorporating RNA analysis in the clinic, the research team collaborated with ongoing clinical trials for children with cancer. While the trials looked for new treatment options based on tumor DNA, CKCC obtained each tumor’s RNA data and analyzed it in several innovative ways. Using this data-driven comparative approach, the team identified new molecular information about the case, previously unavailable to the clinical team, in 100% of cases, exceeding their original goal of 20% for this initial study. Some of this information could be used for alternative treatment possibilities. The team then communicated its findings to the clinical trials and received feedback to develop effective communication strategies with clinicians.
To further test clinical efficacy of comparative cancer RNA analysis, the research team established a registry focused on clinical validation of the findings and optimization of patient/family engagement in medical decision-making. Supported by external funds, this work was completed at the end of 2019.
The team took steps to advance their data-driven tumor analysis toward clinical testing by evaluating the effectiveness of comparative RNA-sequencing analysis within the clinical process, including assessing: the impact on clinical decision making, the patient family understanding and engagement with genomic analysis, and patient outcomes. In line with UCSC’s commitment to providing open access to data, all software developed by UCSC genomic researchers for CKCC is open source. This means that all RNA-sequencing processed data and accompanying analysis will be made publicly available to benefit researchers. The hope is that by maintaining open access, CKCC can help advance the state of pediatric cancer research.
Research Team and Collaborators
- University of California, Santa Cruz
- David Haussler, PhD
- Olena Morozova Vaske, PhD
- Isabel Bjork, JD, MSc, MA
- Rob Currie, MBA
- Holly Beale, PhD
- Ted Goldstein, PhD
- Ann Durbin
- Katrina Learned
- Ellen Kephart
- Jacob Pfiel
- Lauren Sanders
- Katrina Slater
- Stanford University, Lucile Packard Children's Hospital
- Sheri L. SPunt, MD, MBA
- Norman J. Lacayo, MD
- Kara L. Davis, DO
- Alejandro Sweet-Cordero
- University of California, San Francisco
- Alejandro Sweet-Cordero (moved to UCSF during the project)
- Sabine Mueller
- University of British Columbia, BC Cancer Agency
- Marco Marra
- Children's Hospital Orange County
- Leonard Senders
- Ashley Plant
- Children's Mercy Hospital in Kansas City
- Sanford University of South Dakota Medical Center
- University of Michigan
- University of Pittsburg
- Alex's Lemonade Stand Foundation
- Amazon Services
- Jacob's Heart
- Key for a Cure
- Kids v Cancer
- Live For Others Foundation
- St. Baldrick's Foundation
- Team Finn
- Team G Foundation
- Unravel Pediatric Cancer
- Seven Bridges
- George Kraw