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Biomarker Identifies Patients Who Don’t Respond to Precision Medicine
The new biomarker can identify which patients with lymphoma are unlikely to respond to precision medicine therapies, helping providers choose appropriate treatments.
Researchers from Penn Medicine have discovered a new biomarker that identifies which patients with aggressive lymphoma won’t respond to a precision medicine treatment called ibrutinib.
The findings could help providers make more appropriate treatment decisions for patients with activated B-cell diffuse large B-cell lymphoma (ABC-DLBCL) who have these newly discovered genetic mutations in the BCL10 gene.
“This is a mechanism of resistance that was previously underappreciated,” said Kojo S. J. Elenitoba-Johnson, MD, the Peter C. Nowell, MD, Professor in the Perelman School of Medicine at the University of Pennsylvania and Director of the Center for Personalized Diagnostics.
“Ibrutinib would have been a candidate for such patients, but if they have these BCL10 mutations, another route for treatment should be prioritized.”
Ibrutinib is a precision medicine therapy that blocks a protein known as Bruton’s tyrosine kinase (BTK), which is part of a pathway that helps B cells thrive. Blocking BTK causes cancerous B cells to die or keep from dividing. This makes the drug useful in the treatment of some relapsed and refractory forms of lymphomas and leukemias, but not all.
Researchers found that mutations in the BCL10 gene promote abnormal signaling pathways that enable cells to avoid the impact of ibrutinib. The normal BCL10 gene binds to two other proteins – CARD11 and MALT1 – to trigger NF-kB signaling, which is vital in order for B cells to function normally.
Mutations in BCL10 undermine this process, and researchers have a limited understanding of the ways in which this happens. Using innovative techniques, researchers have discovered that mutated BCL10 could be working alongside other cellular catalysts to accelerate lymphoma growth and resistance to treatment. However, it wasn’t clear what those cellular catalysts were.
Penn Medicine researchers used an advanced technology to analyze the nuances of protein complexes. The team identified new interactors that showed how cells are able to evade ibrutinib through auxiliary signaling.
Researchers compared the process to a relay race: In a patient without these mutations, ibrutinib would be able to knock the baton out of the first runner’s hand to stop cancer. In patients with these mutations, a runner from another team can step in with a new baton to help finish the race.
“Cutting off the signaling up top would be immaterial because this protein has now acquired a new capability that subverts the mechanism by which the drug could effectively act as an inhibitor in lymphomas harboring these mutations,” Elenitoba-Johnson said.
The biomarker adds to the list of genetic drivers of cancers that will help inform treatment plans for patients with lymphoma. DLBCL is the most common subtype of adult lymphomas, with more than 25,000 new cases each year in the US. ABC-DLBCL is one of its most aggressive forms.
Researchers expect that their findings will lead to the refinement and advancement of precision medicine for cancer.
“Precision medicine is the goal, where individualized therapy, based on genetics and other factors, lets us treats patients with the right drug for the right disease at the right dose and at the right time,” Elenitoba-Johnson said. “Identifying these new mechanisms strengthens that approach for patients with this type of lymphoma.”
Researchers are increasingly looking to biomarkers to learn more about disease development and treatment. A study recently published in Current Biology showed that high blood levels of RNA produced by the PHGDH gene could serve as a biomarker for early detection of Alzheimer’s disease.
Additionally, the discovery could lead to the development of a blood test to identify individuals who will develop Alzheimer’s years before they present symptoms.
“Several known changes associated with Alzheimer's disease usually show up around the time of clinical diagnosis, which is a little too late. We had a hunch that there is a molecular predictor that would show up years before, and that's what motivated this study,” said Sheng Zhong, a professor of bioengineering at the UC San Diego Jacobs School of Engineering.