Clinical Topics

Research News: RCC. Adrenal Tumors, Myeloma Therapy, Cancer Clusters, Hodgkin Lymphoma


 

Gene Assays Reveal Some Unknown Primary Cancers as RCC

Gene expression profiling and/or immunohistochemistry can identify occult renal cell carcinoma (RCC) in a subset of patients diagnosed with carcinoma of unknown primary (CUP), suggesting that these patients could benefit from RCC-specific targeted therapy or immunotherapy, investigators contend.

Of 539 with CUP patients presenting at a single center, a 92-gene reverse transcription polymerase chain reaction molecular cancer classifier assay (MCCA) performed on biopsy specimens identified 24 as having RCC. All patients had clinical characteristics typical of advanced RCC, but none had suspicious renal lesions on computed tomography scans, reported F. Anthony Greco, MD, and John D. Hainsworth, MD, of the Sarah Cannon Cancer Center and Research Institute in Nashville, Tennessee in Clinical Genitourinary Cancer. “Although further experience is necessary, these patients responded to RCC-specific therapy in a manner consistent with advanced RCC. These patients are unlikely to benefit from treatment with empiric chemotherapy. The reliable identification of RCC patients within the heterogeneous CUP population is possible using MCCA, and has potentially important therapeutic implications,” they wrote.

Neil Osterweil, Oncology Practice

Radioactive Agent for Adrenal Tumors

The Food and Drug Administration has approved iobenguane I 131 injection (Azedra) for IV use for the treatment of adults and adolescents aged |≥ 12 years with rare adrenal tumors (pheochromocytoma or paraganglioma) that are unresectable, have metastasized, and require systemic therapy. This is the first FDA-approved drug for this use.

Approval is based on a single-arm, open-label clinical trial that included 68 patients. The primary endpoint was the number or patients with a 50% or greater reduction of antihypertensive medications lasting at least 6 months; the secondary endpoint was overall tumor response according to traditional imaging criteria. The primary endpoint was met by 17 patients, and the secondary endpoint was achieved in 15.

The most common severe adverse effects were lymphopenia, neutropenia, thrombocytopenia, fatigue, anemia, increased international normalized ratio, nausea, dizziness, hypertension, and vomiting. Furthermore, because this is a radioactive therapeutic agent, there is a warning about radiation exposure for both patients and family members, a risk that is greatest in pediatric patients.Other warnings and precautions include a risk of myelosuppression, underactive thyroid, elevations in blood pressure, renal failure or kidney injury, and pneumonitis. Myelodysplastic syndrome and acute leukemias were observed in patients who received the radioactive agent, and the magnitude of this risk will continue to be studied, the FDA said.

Christopher Palmer, Oncology Practice

Treatment Simulation Could Help Personalize Myeloma Therapy

With the help of gene expression signatures, a simulated treatment learning model identified which patients with multiple myeloma (MM) would benefit most from treatment with bortezomib or lenalidomide, researchers reported in Nature Communications. The study included 910 participants across 3 phase 3 trials. In all, 20% had a 100% greater-than-average progression-free survival (PFS) benefit from bortezomib, while 31% had a 200% greater-than-average PFS benefit from lenalidomide, wrote Joske Ubels and colleagues of University Center Utrecht, the Netherlands.

The genetic heterogeneity of cancer and risk of treatment necessitate tools that “predict—at the moment of diagnosis—which patients will benefit most from a certain treatment,” the researchers wrote. While gene expression signatures can predict a favorable or adverse prognosis, they do not account for the effect of treatment on survival. “The key idea of simulated treatment learning is that a patient’s treatment benefit can be estimated by comparing [his or her] survival to a set of genetically similar patients [who] received the comparator treatment,” they noted.

The researchers applied an algorithm called GESTURE to combined data from the TT2 (Total Therapy 2 for Multiple Myeloma), TT3, and HOVON-65/GMMG-HD4 trials. These trials compared bortezomib or lenalidomide with conventional therapies for MM. The model identified 180 patients (20%) for whom bortezomib would produce a 100% greater PFS benefit than in the study population as a whole. Conversely, lenalidomide would produce a 200% greater PFS benefit in 31% of patients.

The simulated treatment learning model “can derive clinically actionable gene expression signatures that enable a more personalized approach to treatment,” the researchers concluded. The method requires a large dataset but could be useful for trials that have missed their primary endpoint. The next step is to see if the model makes useful treatment predictions for other cancers. The code needed to train and validate the model is available at github.com/jubels/GESTURE.

Amy Karon, Oncology Practice

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