Protocol for qRT-PCR analysis from formalin fixed paraffin embedded tissue sections from diffuse large b-cell lymphoma: Validation of the six-gene predictor score

Lymphoma Microenvironment in DLBCL and PTCL-NOS: the key to uncovering heterogeneity and the potential for stratification

Diffuse large B-cell lymphoma (DLBCL) and peripheral T-cell lymphoma, not otherwise specified (PTCL-NOS) are the most common subtypes of mature B cell neoplasm and T/NK cell lymphoma, respectively. They share a commonality in that they are, by definition, highly heterogeneous populations. Recent studies are revealing more about the heterogeneity of these diseases, and at the same time, there is an active debate on how to stratify these heterogeneous diseases and make them useful in clinical practice. The various immune cells and non-cellular components surrounding lymphoma cells, i.e., the lymphoma microenvironment, have been the subject of intense research since the late 2000s, and much knowledge has been accumulated over the past decade. As a result, it has become clear that the lymphoma microenvironment, despite its paucity in tissues, significantly impacts the lymphoma pathogenesis and clinical behavior, such as its prognosis and response to therapy. In this article, we review the role of the lymphoma microenvironment in DLBCL and PTCL-NOS, with particular attention given to its impact on the prognosis and stratification.

Prognostic molecular biomarkers in diffuse large B-cell lymphoma in the rituximab era and their therapeutic implications

Diffuse large B-cell lymphoma (DLBCL) represents a group of tumors characterized by substantial heterogeneity in terms of their pathological and biological features, a causal factor of their varied clinical outcome. This variation has persisted despite the implementation of rituximab in treatment regimens over the last 20 years. In this context, prognostic biomarkers are of great importance in order to identify high-risk patients that might benefit from treatment intensification or the introduction of novel therapeutic agents. Herein, we review current knowledge on specific immunohistochemical or genetic biomarkers that might be useful in clinical practice. Gene-expression profiling is a tool of special consideration in this effort, as it has enriched our understanding of DLBCL biology and has allowed for the classification of DLBCL by cell-of-origin as well as by more elaborate molecular signatures based on distinct gene-expression profiles. These subgroups might outperform individual biomarkers in terms of prognostication; however, their use in clinical practice is still limited. Moreover, the underappreciated role of the tumor microenvironment in DLBCL prognosis is discussed in terms of prognostic gene-expression signatures, as well as in terms of individual biomarkers of prognostic significance. Finally, the efficacy of novel therapeutic agents for the treatment of DLBCL patients are discussed and an evidence-based therapeutic approach by specific genetic subgroup is suggested.

Cell-of-Origin Subtyping of Diffuse Large B-Cell Lymphoma by Using a qPCR-based Gene Expression Assay on Formalin-Fixed Paraffin-Embedded Tissues

The well-established cell-of-origin (COO) algorithm categorizes diffuse large B-cell lymphoma (DLBCL) into activated B-cell-like (ABC) and germinal center B-cell-like (GCB) subgroups through gene expression profiling. We aimed to develop and validate a qPCR-based gene expression assay to determine the COO subgroups of DLBCL with formalin-fixed paraffin-embedded (FFPE) tissue. We first established a DLBCL transcriptome database of 1,016 samples retrieved from three published datasets (GSE10846, GSE22470, and GSE31312). With this database, we identified a qPCR-based 32-gene expression signature (DLBCL-COO assay) that is significantly associated with the COO subgroups. The DLBCL-COO assay was further validated in a cohort of 160 Chinese DLBCL patients. Biopsy samples from DLBCL patients with paired FFPE and fresh frozen tissue were collected to assign COO subtypes based on the immunohistochemistry (IHC) algorithm (Han's algorithm), DLBCL-COO assay, and global gene expression profiling with RNA-seq. For 111 paired FFPE and fresh DLBCL samples, the concordance between the IHC, qPCR, and RNA-seq methods was 77.5% and 91.9%, respectively. The DLBCL-COO assay demonstrated a significantly superior concordance of COO determination with the “gold standard” RNA-seq compared with the IHC assignment with Han's algorithm (P = 0.005). Furthermore, the overall survival of GCB patients defined by the DLBCL-COO assay was significantly superior to that of ABC patients (P = 0.023). This effect was not seen when the tumors were classified by the IHC algorithm. The DLBCL-COO assay provides flexibility and accuracy in DLBCL subtype characterization. These findings demonstrated that the DLBCL-COO assay might serve as a useful tool for guiding prognostic and therapeutic options for DLBCL patients.

Optimization of RNA extraction from laser captured microdissected glomeruli from formalin-fixed paraffin-embedded mouse kidney samples for Nanostring analysis

Optimized protocols for the microdissection of specific areas from archival tissues and the subsequent RNA analysis are needed but challenging due to RNA degradation and chemical modifications. The aim of this study was to present the most appropriate protocol for utilizing mouse FFPE kidney for laser capture microdissection and Nanostring gene expression analysis. We evaluated different section thicknesses (3, 5, 10 μm), 2 RNA extraction kits (Qiagen and Roche) and different H&E staining methods to optimize microdissection and RNA extraction from glomeruli and cortical tubules samples from FFPE mouse kidney. RNA quality and quantity were assessed via Nanodrop and Qubit. The protocol providing the best results consisted of 5 μm sections, a shorter protocol for H&E staining, and RNA extracted with the Roche kit. Higher Nanostring gene counts and lower qPCR cT significantly correlated with RNA concentrations measured with the Qubit, but not with measures obtained with the Nanodrop. The Nanostring data showed that none of the genes included in the panel was differentially expressed in the cortical tubule compartment compared to the whole kidney. However, 25 genes were differentially expressed in the glomerular compartment compared to the whole kidney. Our data showed that sufficient RNA can be extracted from small compartments like mouse renal glomeruli from archival FFPE tissue, and that whole kidney analysis does not accurately represent the transcriptome state of the glomeruli, which comprise only a small proportion of the overall kidney volume.

Cold Ischemia Score: An mRNA Assay for the Detection of Extended Cold Ischemia in Formalin-Fixed, Paraffin-Embedded Tissue

Although there are thousands of formalin-fixed paraffin-embedded (FFPE) tissue blocks potentially available for scientific research, many are of questionable quality, partly due to unknown preanalytical variables. We analyzed FFPE tissue biospecimens as part of the National Cancer Institute (NCI) Biospecimen Preanalytical Variables program to identify mRNA markers denoting cold ischemic time. The mRNA was extracted from colon, kidney, and ovary cancer FFPE blocks (40 patients, 10-12 hr fixation time) with 1, 2, 3, and 12 hr cold ischemic times, then analyzed using qRT-PCR for 23 genes selected following a literature search. No genes tested could determine short ischemic times (1-3 hr). However, a combination of three unstable genes normalized to a more stable gene could generate a "Cold Ischemia Score" that could distinguish 1 to 3 hr cold ischemia from 12 hr cold ischemia with 62% sensitivity and 84% specificity.

A Paradoxical Correlation of Cancer-Associated Fibroblasts With Survival Outcomes in B-Cell Lymphomas and Carcinomas

The tumor microenvironment is increasingly recognized as an active participant in tumor progression. A recent pan-cancer genomic profile analysis has revealed that gene signatures representing components of the tumor microenvironment are robust predictors of survival. A stromal gene signature representing fibroblasts and extracellular matrix components has been associated with good survival in diffuse large B-cell lymphoma (DLBCL). Paradoxically, a closely related gene signature has been shown to correlate with poor survival in carcinomas, including breast, ovarian, pancreatic, and colorectal cancer. To date, there has been no explanation for this paradoxical inverse correlation with survival outcomes in DLBCL and carcinomas. Using public gene data sets, we confirm that the DLBCL stromal gene signature is associated with good survival in DLBCL and several other B-cell lymphomas while it is associated with poor survival in ovarian cancer and several other solid tumors. We show that the DLBCL stromal gene signature is enriched in lymphoid fibroblasts in normal lymph nodes and in cancer-associated fibroblasts (CAFs) in ovarian cancer. Based on these findings, we propose several possible mechanisms by which CAFs may contribute to opposite survival outcomes in B-cell lymphomas and carcinomas.