Bone marrow expression of CD68/CD163 macrophages, IL-17 and FOXP3 cells in aplastic anemia and their relation to prognosis.

OBJECTIVES: The primary mechanism for bone marrow failure in aplastic anemia (AA) is autoimmune hematopoietic stem cell destruction. AA can be cured with antithymocyte globulin (ATG) treatment, and some smaller studies have indicated that the number of regulatory T cells (Tregs) may be predictive of response. Additionally, AA patients appear to have elevated numbers of Th17 cells and bone marrow macrophages, but outcome data are missing. METHODS: We performed immunohistochemistry on bone marrow biopsies from 121 ATG-treated AA patients and 14 healthy controls, using antibodies against FOXP3 (for Tregs), IL-17 (for Th17), CD68 (for pan-macrophages) and CD163 (for M2 type macrophages) to study their possible relation to ATG response and AA prognosis. RESULTS: AA patients had significantly fewer Tregs and Th17 cells but significantly more macrophages compared with controls. Treg, Th17 and pan-macrophage cell numbers were not associated with ATG response or differences in survival. Patients with higher levels of M2 macrophages had improved 5-year overall survival: 79.6% versus 57.4% (p = .017), and this benefit was primarily seen in AA patients with non-severe disease. CONCLUSIONS: We found that Treg and Th17 cell numbers did not predict ATG response or survival, whereas M2 macrophages may be associated with improved survival.

Transcriptome sequencing of archived lymphoma specimens is feasible and clinically relevant using exome capture technology.

Formalin-fixed, paraffin-embedded (FFPE) specimens are an underutilized resource in medical research, particularly in the setting of transcriptome sequencing, as RNA from these samples is often degraded. We took advantage of an exome capture-based RNA-sequencing protocol to explore global gene expression in paired fresh-frozen (FF) and FFPE samples from 16 diffuse large B-cell lymphoma (DLBCL) patients. While FFPE samples generated fewer mapped reads compared to their FF counterparts, these reads captured the same library complexity and had a similar number of genes expressed on average. Furthermore, gene expression demonstrated a high correlation when comparing housekeeping genes only or across the entire transcriptome (r = 0.99 for both comparisons). Differences in gene expression were primarily seen in lowly expressed genes and genes with small or large coding sequences. Using cell-of-origin classifiers and clinically relevant gene expression signatures for DLBCL, FF, and FFPE samples from the same biopsy paired nearly perfectly in clustering analysis. This was further confirmed in a validation cohort of 50 FFPE DLBCL samples. In summary, we found the biological differences between tumors to be far greater than artifacts created as a result of degraded RNA. We conclude that exome capture transcriptome sequencing data from archival samples can confidently be used for cell-of-origin classification of DLBCL samples.

TBLR1 and CREBBP as potential novel prognostic immunohistochemical biomarkers in diffuse large B-cell lymphoma.

Recent studies have identified prognostic mutational clusters for diffuse large B-cell lymphoma (DLBCL) patients, both within and outside the original cell-of-origin (COO) classification. For many of these mutations, there is limited information regarding the corresponding protein expression. With the aim to determine the relationship of protein expression and intensity to COO and prognosis, we used digital image analysis to quantitate immunohistochemical staining of CREBBP, IRF8, EZH2, and TBLR1 in 209 DLBCL patients. We found that patients with strong nuclear expression of TBLR1 had inferior progression-free survival (PFS) and overall survival (OS) in univariable analysis and inferior PFS in multivariable analysis. Patients with higher proportion of intermediate to strong nuclear CREBBP expression had a worse PFS and OS in univariable analysis. CREBBP was expressed with stronger intensity in non-GCB patients and the prognostic impact was restricted to this subgroup. These findings suggest that high nuclear protein expression of TBLR1 and CREBBP is negatively associated with prognosis in DLBCL.

Cell-of-origin determined by both gene expression profiling and immunohistochemistry is the strongest predictor of survival in patients with diffuse large B-cell lymphoma.

The tumor cells in diffuse large B-cell lymphomas (DLBCL) are considered to originate from germinal center derived B-cells (GCB) or activated B-cells (ABC). Gene expression profiling (GEP) is preferably used to determine the cell of origin (COO). However, GEP is not widely applied in clinical practice and consequently, several algorithms based on immunohistochemistry (IHC) have been developed. Our aim was to evaluate the concordance of COO assignment between the Lymph2Cx GEP assay and the IHC-based Hans algorithm, to decide which model is the best survival predictor. Both GEP and IHC were performed in 359 homogenously treated Swedish and Danish DLBCL patients, in a retrospective multicenter cohort. The overall concordance between GEP and IHC algorithm was 72%; GEP classified 85% of cases assigned as GCB by IHC, as GCB, while 58% classified as non-GCB by IHC, were categorized as ABC by GEP. There were significant survival differences (overall survival and progression-free survival) if cases were classified by GEP, whereas if cases were categorized by IHC only progression-free survival differed significantly. Importantly, patients assigned as non-GCB/ABC both by IHC and GEP had the worst prognosis, which was also significant in multivariate analyses. Double expression of MYC and BCL2 was more common in ABC cases and was associated with a dismal outcome. In conclusion, to determine COO both by IHC and GEP is the strongest outcome predictor to identify DLBCL patients with the worst outcome.