Molecular Profiling Improves Classification of Nodal Peripheral T-Cell Lymphomas 


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The differential diagnosis of the most common peripheral T-cell lymphoma subtypes is difficult. In a diagnostic accuracy study reported in the 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.1 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 lymphomas–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 WHO 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 genes 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 and that 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 a positive predictive value of 100% and negative predictive value of 98% for overall accuracy of 98%. The ALK-negative anaplastic large-cell lymphoma prediction model had a positive predictive value of 86% and negative predictive value of 100% for overall 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 a positive predictive value of 66% and negative predictive value of 84% for an overall diagnostic accuracy of 77% and the ALK-negative anaplastic large-cell lymphoma model had a positive predictive value of 73% and negative predictive value of 96% for overall accuracy of 93%.

In addition, the molecular classifier model identified as peripheral T-cell lymphoma–not otherwise specified several cases of the disease 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 indicating 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.

Prognostic Performance

It was also found that the molecular classifier improved the prognostic stratification of patients with peripheral T-cell lymphoma. Based on patients with complete information available, median follow-up of living patients was 1,088 days, median overall survival for the entire population was 469 days, and 3-year overall survival rates were 44% for patients with ALK-negative anaplastic large-cell lymphoma, 16% for those with angioimmunoblastic T-cell lymphoma, and 19% for those with peripheral T-cell lymphoma–not otherwise specified.

With conventional histopathology, the difference in median overall survival between ALK-negative anaplastic large-cell lymphoma and peripheral T-cell lymphoma–not otherwise specified showed only a trend toward significance (1,484 vs 395 days, P = .62); when cases were reclassified according to gene-expression profile, the difference became significant (1,570 vs 391 days, P = .011). No differences in survival were noted when peripheral T-cell lymphoma–not otherwise specified was compared with angioimmunoblastic T-cell lymphoma.

In addition, the molecular classifier categorized as peripheral T-cell lymphoma–not otherwise specified all 14 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 (median, 1,570 vs 333 days, P = .02).

The investigators stated, “[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].” ■

Disclosure: Dr. Piccaluga reported no potential conflicts of interest.

Reference

1. Piccaluga PP, Fuligni F, De Leo A, et al: Molecular profiling improves classification and prognostication of nodal peripheral T-cell lymphomas: Results of a phase III diagnostic accuracy study. J Clin Oncol. July 15, 2013.


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