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Molecular Profiling Improves Classification of Nodal Peripheral T-cell Lymphomas

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Key Points

  • Overall accuracy of the molecular classifiers was 98% and 77% for angioimmunoblastic T-cell lymphoma and 98% and 93% for ALK-negative anaplastic large-cell lymphoma in test and validation sets, respectively.
  • The molecular classifiers significantly improved the prognostic stratification of patients with peripheral T-cell lymphoma.
  • The findings support the use of a molecular classifier as an additional tool in the diagnostic workup of nodal peripheral T-cell lymphoma.

The differential diagnosis of the most common peripheral T-cell lymphoma subtypes is difficult. In a phase III diagnostic accuracy study reported in Journal of Clinical Oncology, Pier Paolo Piccaluga, MD, PhD, of the University of Bologna, and colleagues in the European T-cell Lymphoma Study Group and International Peripheral T-cell Lymphoma Project assessed the ability of gene-expression profiles to identify peripheral T-cell lymphoma subtypes. They found that gene-expression profile–based molecular classifiers could distinguish angioimmunoblastic T-cell lymphoma and ALK-negative anaplastic large-cell lymphoma from peripheral T-cell lymphoma–not otherwise specified with a high degree of accuracy.

The study involved 244 peripheral T-cell lymphomas, including 158 peripheral T-cell lymphoma–not otherwise specified, 63 angioimmunoblastic T-cell lymphomas, and 23 ALK-negative anaplastic large-cell lymphomas. The gene-expression profile–based classification method was established on a support vector machine algorithm, and the reference standard was an expert pathologic diagnosis according to World Health Organization classification.

Predictive Accuracy

The investigators first identified gene-expression profile–based molecular classifiers discriminating angioimmunoblastic T-cell lymphoma and ALK-negative anaplastic large-cell lymphoma from peripheral T-cell lymphoma–not otherwise specified in a training set. The molecular classifiers were developed in formalin-fixed paraffin-embedded samples and validated in both formalin-fixed paraffin-embedded and frozen tissues.

In a training set, 208 genes distinguishing peripheral T-cell lymphoma–not otherwise specified from angioimmunoblastic T-cell lymphoma and 1,133 distinguishing peripheral T-cell lymphoma–not otherwise specified from ALK-negative anaplastic large-cell lymphoma were identified. Pathway analysis showed that genes discriminating peripheral T-cell lymphoma–not otherwise specified from angioimmunoblastic T-cell lymphoma were particularly involved in lipid metabolism, DNA replication, and regulation of cell cycle; genes differentially expressed in peripheral T-cell lymphoma–not otherwise specified vs ALK-negative anaplastic large-cell lymphoma were significantly involved in regulation of apoptosis, protein kinase cascade, and immune response. In an independent test set, the angioimmunoblastic T-cell lymphoma prediction model had overall accuracy of 98%, and the ALK-negative anaplastic large-cell lymphoma prediction model had accuracy of 98%. 

Molecular classifiers based on a smaller number of genes were identified, with discriminant analysis showing that molecular classifiers of 38 and 53 genes for predictive models of angioimmunoblastic T-cell lymphoma and ALK-negative anaplastic large-cell lymphoma, respectively, could maintain the same accuracy. In an independent validation set, the angioimmunoblastic T-cell lymphoma prediction model had overall accuracy of 77%, and the ALK-negative anaplastic large-cell lymphoma model had accuracy of 93%. 

Prognostic Performance

It was also found that the molecular classifier significantly improved the prognostic stratification of patients with peripheral T-cell lymphoma. In particular, it enhanced the distinction of ALK-negative anaplastic large-cell lymphoma from peripheral T-cell lymphoma–not otherwise specified—eg, when patients were classified using gene-expression profile, a significant difference in overall survival between the two subtypes was observed, whereas only a trend toward significance was observed according to classification by conventional histopathology.

The molecular classifier also classified as peripheral T-cell lymphoma–not otherwise specified all cases of peripheral T-cell lymphoma with strong CD30 expression but lack of typical anaplastic large-cell lymphoma morphology for which a consensus histopathologic diagnosis could not be reached. Overall survival in these patients was significantly worse than that of patients with ALK-negative anaplastic large-cell lymphoma.

In addition, the molecular classifier model identified as peripheral T-cell lymphoma–not otherwise specified several cases of peripheral T-cell lymphoma–not otherwise specified with a T-follicular helper phenotype but lacking a morphology consistent with either angioimmunoblastic T-cell lymphoma or peripheral T-cell lymphoma–not otherwise specified follicular variant. This finding supports other evidence that a subset of peripheral T-cell lymphoma–not otherwise specified shares a T-follicular helper derivation but is distinct from angioimmunoblastic T-cell lymphoma.

As stated by the investigators: “[T]hese results indicate a remarkable diagnostic accuracy for the [gene-expression profile]–based [molecular classifier] in discriminating [angioimmunoblastic T-cell lymphoma] and ALK-negative [anaplastic large-cell lymphoma] from [peripheral T-cell lymphoma–not otherwise specified]…. Our findings support the usage of a [molecular classifier] as an additional tool in the diagnostic workup of nodal [peripheral T-cell lymphoma].”

The content in this post has not been reviewed by the American Society of Clinical Oncology, Inc. (ASCO®) and does not necessarily reflect the ideas and opinions of ASCO®.


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