In a Cholangiocarcinoma (CCA) Foundation meeting session titled “Thinking Big: Transformative Approaches to Curing Cholangiocarcinoma,” Dr Zachariah H. Foda from the Johns Hopkins School of Medicine discussed the role of circulating tumor DNA (ctDNA) in early detection and disease monitoring for CCA.
Early detection of CCA is critical for use of curative approaches. However, this is challenging because of nonspecific symptoms and inadequacies in current methods of detection, including imaging techniques such as computed tomography and magnetic resonance imaging, as well as invasive procedures such as endoscopic retrograde cholangiopancreatography. Dr Foda noted, “Unfortunately, none of these procedures have great sensitivity or specificity. So overall, there is a need for new detection methods.”
Liquid biopsy is detection of DNA in the blood of a patient to diagnose or track disease. Cell-free DNA fragments (cfDNA) are released from cells and circulate in the blood. In patients with cancer, a small fraction of cfDNA originates from tumor cells and is known as ctDNA. Blood is drawn from the patient and cfDNA (including ctDNA) is extracted for molecular genomic analyses.
Advances in liquid biopsy analyses have allowed identification of cancer-related features in the cfDNA in circulating blood. Mutations in ctDNA can be directly detected in blood with or without knowledge of these alterations in tumor. However, only a small fraction of ctDNA contains mutations.
Therefore, assessing other characteristics such as fragment size may allow for greater detection of cfDNA change associated with cancer. Indeed, cfDNA profiles of healthy individuals were found to be uniform and reflected nucleosomal patterns of white blood cells, while patients with cancer had altered fragmentation profiles that were more heterogeneous.1
In particular, machine learning–based approaches incorporating genome-wide fragmentation features for analysis of cfDNA provide promise for noninvasive cancer detection.1 The DELFI (DNA Evaluation of Fragments for Early Interception) method has been used to detect a large number of abnormalities in cfDNA through genome-wide analysis of fragmentation patterns.1 The study applied the DELFI method to 236 patients with breast, colorectal, lung, ovarian, pancreatic, gastric, or bile duct cancer and 245 healthy individuals. This model achieved sensitivities of detection ranging from 57% to >99% among the 7 cancer types at 98% specificity. The fragmentation-based liquid biopsy approach with mutation-based cfDNA analyses detected 91% of cancer patients, including those with CCA.
As for future directions, Dr Foda stated, “These methods are always continually being refined. The methods need to be implemented in larger cohorts of CCA, so we could create perhaps a model specific for CCA. Once this is in place, then this could be used in actual screenings of high-risk cohorts such as people with PSA. Also, these methods are exportable to using for disease monitoring after treatment or surgery.”
To sign up for our newsletter or print publications, please enter your contact information below.
