PF511 DISSECTING THE MOLECULAR PROFILES IN DIFFUSE LARGE B‐CELL LYMPHOMA USING THE RNA‐ AND PROTEIN‐BARCODED NCOUNTER METHOD
Authors: Chen C.‐C. , Hsu C.‐C. , Huang C.‐E. , Chen Y.‐J. , Chen Y.‐Y. , Wu Y.‐Y. , Tsou H.‐Y. , Tsai P.‐W. , Li C.‐P. , Chuang W.‐H. , Lai Y.‐H. , Lin Y.‐H. 
Published: June 2019

Background:

Diffuse large B‐cell lymphoma (DLBCL), though highly curable with immunochemotherapy, is a heterogenous group of diseases that include subsets of tumors with different cells of origin (COO). Using gene‐expression profiling, DLBCLs can be categorized into 2 clinically distinct subgroups, namely activated B‐cell (ABC) and germinal center B‐cell (GCB). More recently, double‐expressor (DEL) or double‐hit lymphoma (DHL) was described as a new form of aggressive lymphoma based on the expression or re‐arrangement of 3 genes (MYC, BCL2, and BCL6), respectively. It is speculated that divergent signaling pathways are utilized among DLBCLs with different subtypes, and heterogeneity might even exist in the same subcategory.

Aims:

To improve our understanding in DLBCL biology, we aim to explore the signaling activities of tumor cells at the mRNA transcripts and protein levels in a cohort of patients with DLBCL.

Methods:

We enrolled 60 DLBCLs and 6 healthy adults in this study. The DLBCL samples were supplied in FFPE sections while the healthy samples were collected with fresh buffy coats followed by positive selection of pan‐B cells. RNA was extracted using the ReliaPrep™ FFPE kit, and digital GEP was performed to assess the expression of 240 genes using a barcoding profiling method (nCounter technology, NanoString). After data processing with nSolver4.0, the geometric mean expression of all house‐keeping genes was used as an inter‐sample normalization factor and the levels of expression in DLBCL cells were presented in log2(fold changes). The barcoded protein profiling was performed with nCounter® Vantage 3D™ Protein Panels which detected 35 proteins in one FFPE slide. The raw values of protein expression were subtracted with isotype background, normalized with house‐keeping proteins, and similarly presented in log2(fold change).

Results:

The nCounter technology successfully classified samples into ABC and GCB subtypes. Outcome analysis unequivocally demonstrated a worse overall survival in those with ABC. Activation of B‐cell receptor (BCR)‐AKT was a common theme in most GCBs, whereas ABC tumors could be further stratified into two groups, one with NF‐kB activation and the other with BCR‐AKT signaling, a phenomenon similar to that seen in GCBs. Patients with ABC tumors expressing activated BCR‐AKT exhibited a trend toward better progression‐free survival than those with NF‐kB activated ABC DLBCL. Compensated PTEN downregulation was found in samples with NF‐kB activation. We next employed nCounter method to identify DEL‐DLBCL, which constituted 35.1% and 28.1% of the whole cohort DLBCL using protein‐based and mRNA transcript‐based stratification, respectively. Although both groups of patients had significantly worse outcome, the poor prognosis of DEL‐DLBCL patients was better delineated in the stratification strategy determined by mRNA transcript levels. Lastly, we also unearthed prominent crosstalk between various signaling pathways including BCR, cell cycle, apoptosis, JAK‐STAT, NF‐kB, and RAS‐GEF/Gap in our patient samples.

Summary/Conclusion:

Barcode analysis expands our knowledge in the genetic complexity of DLBCLs. Importantly, this can be achieved even when only limited tumor tissue is available. Our data provide strong evidence that heterogeneity does exist, even among those within the same COO cluster. It also helps better sub‐categorize DEL‐DLBCL prognostically. The information on disparate signaling activities in different subtypes could lead to improved strategies in molecularly stratified targeted therapy.

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