Molecular Profiling Helps Classify Peripheral T-Cell Lymphomas

July 23, 2013

NEW YORK (Reuters Health) Jul 23 - Up to 30% of peripheral T-cell lymphomas are misdiagnosed, but molecular profiling can help address that problem, according to a new paper.

Molecular profiling can be used to differentiate angioimmunoblastic T-cell lymphoma (AITL) and anaplastic large-cell lymphoma (ALCL) from peripheral T-cell lymphoma (PTCL) not otherwise specified (NOS), say researchers from the T-Cell Lymphoma Study Group and the International Peripheral T-Cell Lymphoma Project.

These lymphomas may have different prognoses and need different therapies, the researchers point out.

To test the accuracy of gene expression profiling-based molecular classifiers for differentiating PTCO NOS from AITL and ALCL, and for evaluating the potential clinical implications, Dr. Pier Paolo Piccaluga from University of Bologna, Italy, and colleagues studied 244 nodal PTCLs.

Overall, 158 were PTCL NOS, 63 were AITL, and 21 were ALK-negative ALCL (i.e., anaplastic lymphoma kinase (ALK)-negative).

As reported July 15 online in the Journal of Clinical Oncology, genes that distinguished PTCL NOS from AITL were involved in lipid metabolism, DNA replication, and regulation of the cell cycle.

Genes differentially expressed in PTCL NOS versus ALK-negative ALCL were involved in regulation of apoptosis, protein kinase cascade, and immune response.

The AITL prediction models accurately classified 31 of 43 AITLs and 62 of 78 PTCL NOS, for an overall diagnostic accuracy of 77%. Similarly, the ALCL prediction model accurately classified 8 of 11 ALCLs and 75 of 78 PTCL NOS, for an overall diagnostic accuracy of 93%.

When conventional methods were used to classify patients, there was only a trend in favor of better median overall survival for ALK-negative ALCL vs PTCL NOS (1,484 vs 395 days; p=0.62). But when molecular profiling was used to reclassify the patients, the survival difference became statistically significant (1,570 vs 391 days; p=0.01).

On the other hand, neither method revealed a difference in survival between PTCL NOS and AITL.

"Our findings support the use of a molecular classifier as an additional tool in the diagnostic workup of nodal PTCLs," the authors say. "We were able to significantly limit the number of genes used for an efficient classification, thus making it possible to quickly define a custom assay specific to this issue, efficient in formalin-fixed paraffin-embedded (FFPE) samples."

"Our study identified gene signatures able to efficiently differentiate nodal PTCLs, starting from FFPE tissues, which may become useful tools in the diagnostic workup of these diseases," the researchers conclude. "Bologna University obtained a patent from the Italian Patent and Trademark Office for the molecular signatures used for the diagnostic classifier."

Dr. Piccaluga did not respond to a request for comments on this report.


J Clin Oncol 2013.


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