Global microRNA expression profiling uncovers molecular markers for classification and prognosis in aggressive B-cell lymphoma

Abstract

We studied the global microRNA (miRNA) expression in diffuse large B-cell lymphoma (DLBCL; n = 79), Burkitt lymphoma (BL; n = 36), primary mediastinal B-cell lymphoma (PMBL; n = 12), B-cell lines (n = 11), and normal subsets of naïve B cells, centroblasts (CBs), and peripheral blood B cells along with their corresponding gene expression profiles (GEPs). The normal B-cell subsets have well-defined miRNA signatures. The CB miRNA signature was significantly associated with germinal center B-cell (GCB)-DLBCL compared with activated B-cell (ABC)-DLBCL (P = .002). We identified a 27-miRNA signature that included v-myc avian myelomatosis viral oncogene homolog (MYC) targets and enabled the differentiation of BL from DLBCL, a distinction comparable with the "gold standard" GEP-defined diagnosis. Distinct miRNA signatures were identified for DLBCL subgroups, including GCB-DLBCL, activated B-cell (ABC)-DLBCL, and PMBL. Interestingly, most of the unclassifiable-DLBCL by GEP showed a strong similarity to the ABC-DLBCL by miRNA expression profiling. Consistent results for BL and DLBCL subgroup classification were observed in formalin-fixed, paraffin-embedded tissue, making such tests practical for clinical use. We also identified predictive miRNA biomarker signatures in DLBCL, including high expression of miR-155, which is significantly associated with rituximab plus cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP) treatment failure. This finding was further supported by the observation that high expression of miR-155 sensitizes cells to v-akt murine thymoma viral oncogene homolog-1 inhibitors in vitro, suggesting a novel treatment option for resistant DLBCL.

Figure 1

miRNA expression in normal B-cell subsets. Differential miRNA expression between naïve B-cells, CBs, and CCs (A). miRNAs were selected with C_T < 30 and P < .05 and at least fourfold difference of means. (B) Peripheral B-cell resting vs activated B cell. (C) Average expression of miRNA signatures associated with normal B-cell subsets compared in different lymphoma subtypes.

Figure 2

miRNA expression-based classification. An miRNA classifier derived using a Bayesian algorithm resulted in a 27-miRNA classifier (with 11 upregulated and 16 downregulated miRNAs) that can separate BL from DLBCL patients. The precision of the classifier was estimated by LOOCV, and a 90% probability threshold was used to differentiate the 2 entities. The expression of the miRNA classifier is compared in the DLBCL subgroups, mantle cell lymphoma (MCL), small lymphocytic lymphoma (SLL), HGL-UC, and normal B cells and cell lines. Orange boxes highlight the expression pattern in HGL-UC and BL cell lines.

Figure 3

miRNA signatures for DLBCL subgroups and comparative analysis in other subgroups, cell lines, and normal B-cell subsets. (A) ABC-DLBCL vs GCB-DLBCL. Eight miRNAs were able to distinguish ABC-DLBCL from GCB-DLBCL. GCB-DLBCL-related miRNAs are also expressed in CB and at least 1 GCB-DLBCL cell line, whereas only miRNA-155 from ABC-DLBCL shows association with activated B cells and ABC-DLBCL cell lines. Here, we chose an 80% probability threshold to distinguish the 2 DLBCL subgroups. (B) PMBL vs DLBCL. Five miRNAs were able to distinguish PMBL from DLBCL. (C) Differential miRNA expression between 3 subgroups of DLBCL.

Figure 4

miRNA expression in FFPE tissues. (A) Unsupervised HC on miRNA profiles from FFPE specimens showed distinct clusters of DLBCL and BL. (B) The miRNA classifier obtained from cryopreserved tissues showed a similar expression pattern in FFPE tissues of BL and DLBCL. (C) A similar pattern was observed in DLBCL subgroups; however, to retain high predictive power, additional miRNAs were required in FFPE tissues.

Figure 5

Association of miR-155 with rituximab resistance and target identification. (A) Association of miR-155 expression with EFS in DLBCL. (B) GEP analysis of miR-155-regulated genes and western blot detection of cyclin-dependent kinase inhibitor 1A (CDKN1A) (p21) (only downregulated genes are shown). (C) Cell-cycle analysis in miR-155 overexpressing DHL16 cells. (D) miR-155-expressing cells were more sensitive to AKT IV inhibition, compared with other inhibitors. (E) The 3-gene miR-155 signature was predictive of treatment failure in DLBCL in the entire cohort (upper) and in the ABC-DLBCL subgroup, but not in GCB-DLBCL (lower). EFS is shown using expression quartiles (Q) of the 3-gene signature in the entire cohort, but divided in halves in subgroup analysis.