Researchers led by Ludwig Stanford’s Ash Alizadeh and Maximilian Diehn described in Nature Biotechnology an epigenomic feature of cell-free (or cf) DNAs linked to their fragmentation patterns and predictive of how avidly individual genes they encode are expressed. Fragmentation patterns have previously been shown to be reliable indicators of the tissues or tumors from which cfDNA has been released. Those patterns can also be used to infer the expression levels of genes encoded by DNA, which can reveal the subtype and other biological features of the tumor the DNA came from—all of which could guide individualized therapy. Existing methods, however, require large amounts of DNA for such inference, and cfDNA is typically found at very low levels in blood. In their March publication, whose lead author is Ludwig Stanford scientist Mohammad Shahrokh Esfahani, Ash, Max and their colleagues described a new method, “epigenetic expression inference from cell-free DNA-sequencing” (EPIC-seq), that can predict the previous expression levels of genes encoded in cfDNA. Analyzing 329 blood samples from 201 cancer patients and 87 healthy adults, the researchers applied EPIC-seq to identify subtypes of lung carcinoma and diffuse large B cell lymphoma. They also showed that gene expression patterns predicted by EPIC-seq correlate with clinical responses in patients treated with anti-PD-1 checkpoint blockade. The researchers argue the method could be useful for both cancer diagnosis and the management of therapy.
This article appeared in the May 2022 issue of Ludwig Link. Click here to download a copy (PDF, 2MB).