A20 inactivation in ocular adnexal MALT lymphoma

Recent studies showed A20 inactivation by deletion, mutation and promoter methylation in ocular adnexal mucosa-associated lymphoid tissue lymphoma. However, the incidences of A20 abnormalities and their clinical impact remain for the most part unknown. It is also unknown whether ABIN-1 and ABIN-2, the components of the A20 NF-κB inhibitor complex, are inactivated by genetic changes in ocular adnexal mucosa-associated lymphoid tissue lymphoma. A total of 105 cases were investigated for A20 mutation/deletion, ABIN-1/2 mutation, MALT1 and IGH involved translocation. Somatic mutation was seen frequently in A20 (28.6%) but rarely in ABIN-1 (1%) and ABIN-2 (1%). A20 mutations were significantly associated with A20 heterozygous deletion, and both were mutually exclusive from the MALT1 or IGH involved translocations. A20 mutation/deletion was also significantly associated with increased expression of the NF-κB target genes CCR2, TLR6 and BCL2. The cases with A20 mutation/deletion required significantly higher radiation dosages to achieve complete remission than those without these abnormalities

Gene Expression Signatures for the Accurate Diagnosis of Peripheral T-Cell Lymphoma Entities in the Routine Clinical Practice

Peripheral T-cell lymphoma (PTCL) includes heterogeneous clinicopathologic entities with numerous diagnostic and treatment challenges. We previously defined robust transcriptomic signatures that distinguish common PTCL entities and identified two novel biologic and prognostic PTCL-not otherwise specified subtypes (PTCL-TBX21 and PTCL-GATA3). We aimed to consolidate a gene expression-based subclassification using formalin-fixed, paraffin-embedded (FFPE) tissues to improve the accuracy and precision in PTCL diagnosis. We assembled a well-characterized PTCL training cohort (n = 105) with gene expression profiling data to derive a diagnostic signature using fresh-frozen tissue on the HG-U133plus2.0 platform (Affymetrix, Inc, Santa Clara, CA) subsequently validated using matched FFPE tissues in a digital gene expression profiling platform (nCounter, NanoString Technologies, Inc, Seattle, WA). Statistical filtering approaches were applied to refine the transcriptomic signatures and then validated in another PTCL cohort (n = 140) with rigorous pathology review and ancillary assays. In the training cohort, the refined transcriptomic classifier in FFPE tissues showed high sensitivity (> 80%), specificity (> 95%), and accuracy (> 94%) for PTCL subclassification compared with the fresh-frozen-derived diagnostic model and showed high reproducibility between three independent laboratories. In the validation cohort, the transcriptional classifier matched the pathology diagnosis rendered by three expert hematopathologists in 85% (n = 119) of the cases, showed borderline association with the molecular signatures in 6% (n = 8), and disagreed in 8% (n = 11). The classifier improved the pathology diagnosis in two cases, validated by clinical findings. Of the 11 cases with disagreements, four had a molecular classification that may provide an improvement over pathology diagnosis on the basis of overall transcriptomic and morphological features. The molecular subclassification provided a comprehensive molecular characterization of PTCL subtypes, including viral etiologic factors and translocation partners. We developed a novel transcriptomic approach for PTCL subclassification that facilitates translation into clinical practice with higher precision and uniformity than conventional pathology diagnosis