Innovative Technique Identifies Peripheral T-Cell Lymphoma Types

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Findings could help direct patients to the most effective clinical trials and ultimately lead to new targeted therapies.

Catalina Amador, M.D., associate professor in the Division of Hematopathology, was first author on the paper.

A large international team, including researchers from Sylvester Comprehensive Cancer Center at the University of Miami Miller School of Medicine, the University of Nebraska, and several other institutions, has developed a new digital gene expression assay, using the nCounter platform (developed by NanoString Technologies) to precisely identify peripheral T-cell lymphoma (PTCL) types in formalin-fixed, paraffin-embedded (FFPE) tumor tissue. The study was published in the high-impact Journal of Clinical Oncology.

“Patients are treated based on their diagnoses,” said Catalina Amador, M.D., associate professor in the Division of Hematopathology and first author on the paper. “However, PTCL includes different types. You need an expert pathologist to distinguish between them, and those are not always available. Now, we have developed an automated way to determine the different type of PTCL a patient may have.”

Because PTCL includes different types, which can look quite similar under a microscope, precisely diagnosing the disease can be challenging. The results can be inconclusive or simply wrong.

To help solve this problem, the newly developed assay translates specific gene expression signatures into precise diagnoses. Most importantly, it can do this in FFPE tissue — the most common method to store biopsy samples. FFPE tissue is easy to work with and transport, and can be stored at room temperature. Previous efforts to create a PTCL diagnostic tool have only worked in frozen tissue, which is used exclusively in research and is not suitable for clinical applications.

“We translated these signatures that were only suitable for lab work into a platform that should be quite useful to characterize tumors as part of the diagnostic process,” said Dr. Amador.

More Accurate Classification

Using the newly described digital gene expression assay, the team assessed messenger RNA (mRNA) from 249 PTCL cases and found that this approach could delineate specific PTCL types with high sensitivity and specificity. In other words, the assay can accurately determine whether a biopsy can be classified as one of the most common forms of PTCL.

The team included scientists from the City of Hope, the National Cancer Institute, and other institutions on five continents, mainly from the Leukemia Lymphoma Molecular Profiling Project.

The study was led by Javeed Iqbal, Ph.D., a professor at the University of Nebraska Medical Center, where Dr. Amador was an associate professor before joining the Miller School. The team included scientists from the City of Hope, the National Cancer Institute, and other institutions on five continents. Sylvester Professor Jennifer Chapman, M.D., also contributed cases.

Though this work may eventually help clinicians provide more precise care for PTCL patients, the most important early benefits will be in clinical trials. The ability to consistently classify patients by their specific PTCL diagnosis will help researchers develop new therapies that target the genetics of each disease.

“Right now, this does not have a major impact on treatment, as most nodal PTCL are treated similarly,” said Dr. Amador. “But these are definitely different diseases, with different genetic variations. The treatments are not that different because they have not been well-studied. We hope that nCounter will help change that.”

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