Abstract
To further understand the molecular biology of mucosa-associated lymphoid tissue (MALT) lymphoma, we conducted a comprehensive gene expression study on the Affymetrix platform using total RNA extracted from biopsy specimen of 35 well-characterized pulmonary MALT lymphoma samples and compared them to gene expression profiles of a range of B and T cell lymphoma, such as Burkitt’s lymphoma, diffuse large B-cell lymphoma, Waldenstrom macroglobulinemia, chronic lymphocytic leukemia, multiple myeloma, and peripheral T-cell lymphoma, and normal cellular counterparts, such as different B-cell and T-cell populations, normal plasma cells and lung tussue. Analytical strategies were adopted to negate tissue specific effect such that our results can be generalized to MALT lymphoma from other anatomical sites. We further analyzed the data using functional tools such as gene-set enrichment analysis and gene ontology. Network/pathway analysis was performed using Metacore. Unsupervised clustering of whole dataset (including other lymphoid malignancies and normal cellular counterpart) using genes with variable expression, showed that compared to other B-cell lymphoid malignancies, MALT lymphoma have a prominent T-cell signature. Using established gene expression of different B-cell compartment, we confirmed that MALT has a marginal zone B-cell and memory B-cell cell-of-origin signature. Using ANOVA with post-hoc pair-wise comparison, we identified 4 novel transcripts over-expressed in MALT but not other B-cell tumors, and validated one of these using immunohistochemistry. MALT lymphoma with t(11;18) or t(14;18) over-expressed genes enriched for pathways other than the NFKB pathway such as JAK-STAT and SRC signaling pathways, which may represent novel therapeutic targets. We identified a number of genes with ‘outlier’ expression including RARA and RGS13. However, translocation involving RARA and the immunoglobulin heavy chain locus was not detected by FISH, suggesting other mechanisms of deregulating gene expression were involved. Using unsupervised clustering of only the MALT samples, we found that the molecular heterogeneity within MALT is composed of a group characterized by MALT1 translocations and another group with plasmacytic differentiation. Interestingly, further refinement of this grouping can be achieved by clustering the samples based on ‘outlier’ gene expression. Samples with MALT1 translocations have high expression of RARA, samples with plasmacytic differentiation have high FKBP11 expression and samples with high RGS13 expression tend to have trisomy 3 and reactive follicles. Our study therefore identified novel molecular markers, deregulated pathways and genetic defects in MALT. Furthermore, subgroups with distinct pathological features and anchored by unique pattern of ‘outlier’ gene expression were identified.
Author notes
Disclosure: No relevant conflicts of interest to declare.
