A multiple myeloma classification system that associates normal B-cell subset phenotypes with prognosis

Immune profiles to predict bortezomib-based treatment response for multiple myeloma patients

BACKGROUND

To evaluate the distribution of bone marrow immune cell subsets and their correlation with treatment efficacy in patients with multiple myeloma (MM).

METHODS

We analyzed the bone marrow lymphocyte subsets of 186 newly diagnosed MM patients at diagnosis and their correlation with clinical characteristics. In our study, eight-color flow cytometry, a method commonly used to detect plasma cell phenotypes, was used to analyze seven bone marrow immune cell groups by change gate-strategy.

RESULTS

First, for all the 7 immune cell groups, the percentage of immature B cells was significantly lower in stage III patients than in stage I patients, while the trend was reversed in memory B cells in both the International Staging System(p = 0.004) and Revised International Staging System(p = 0.018). Second, the percentage of naïve B cells were significantly lower in patients with severe anemia, while the percentage of memory B cells had reversed trend. The percentage of immature B cells were lower in patients with Cr ≥ 2 mg/dL than in patients with Cr < 2 mg/dL. Then we followed the treatment efficacy of 152 patients who received four cycles of induction therapy (bortezomib + dexamethasone or bortezomib + lenalidomide + dexamethasone) and analyzed the relationship between bone marrow lymphocyte subsets at the initial stage and treatment response datasets. We found that both the percentage of B cells(p＜0.001) and immature B(p = 0.002) were increased in patients who achieved very good partial remission(VGPR) after four cycles of induction therapy. The ROC results indicated the combination of the multiple immune subgroups had predictive values (AUC = 0.802, p<0.001) in the treatment effect after four cycles of induction therapy.

CONCLUSIONS

Overall, these results suggest that the analysis of lymphocyte subsets along with plasma cell immunophenotyping could be a potential index for determining the prognosis of MM patients.

The genomic and transcriptional landscape of primary central nervous system lymphoma

Primary lymphomas of the central nervous system (PCNSL) are mainly diffuse large B-cell lymphomas (DLBCLs) confined to the central nervous system (CNS). Molecular drivers of PCNSL have not been fully elucidated. Here, we profile and compare the whole-genome and transcriptome landscape of 51 CNS lymphomas (CNSL) to 39 follicular lymphoma and 36 DLBCL cases outside the CNS. We find recurrent mutations in JAK-STAT, NFkB, and B-cell receptor signaling pathways, including hallmark mutations in MYD88 L265P (67%) and CD79B (63%), and CDKN2A deletions (83%). PCNSLs exhibit significantly more focal deletions of HLA-D (6p21) locus as a potential mechanism of immune evasion. Mutational signatures correlating with DNA replication and mitosis are significantly enriched in PCNSL. TERT gene expression is significantly higher in PCNSL compared to activated B-cell (ABC)-DLBCL. Transcriptome analysis clearly distinguishes PCNSL and systemic DLBCL into distinct molecular subtypes. Epstein-Barr virus (EBV)+ CNSL cases lack recurrent mutational hotspots apart from IG and HLA-DRB loci. We show that PCNSL can be clearly distinguished from DLBCL, having distinct expression profiles, IG expression and translocation patterns, as well as specific combinations of genetic alterations.

Normal myeloid progenitor cell subset-associated gene signatures for acute myeloid leukaemia subtyping with prognostic impact

Acute myeloid leukaemia (AML) is characterised by phenotypic heterogeneity, which we hypothesise is a consequence of deregulated differentiation with transcriptional reminiscence of the normal compartment or cell-of-origin. Here, we propose a classification system based on normal myeloid progenitor cell subset-associated gene signatures (MAGS) for individual assignments of AML subtypes. We generated a MAGS classifier including the progenitor compartments CD34⁺/CD38^- for haematopoietic stem cells (HSCs), CD34⁺/CD38⁺/CD45RA^- for megakaryocyte-erythroid progenitors (MEPs), and CD34⁺/CD38⁺/CD45RA⁺ for granulocytic-monocytic progenitors (GMPs) using regularised multinomial regression with three discrete outcomes and an elastic net penalty. The regularisation parameters were chosen by cross-validation, and MAGS assignment accuracy was validated in an independent data set (N = 38; accuracy = 0.79) of sorted normal myeloid subpopulations. The prognostic value of MAGS assignment was studied in two clinical cohorts (TCGA: N = 171; GSE6891: N = 520) and had a significant prognostic impact. Furthermore, multivariate Cox regression analysis using the MAGS subtype, FAB subtype, cytogenetics, molecular genetics, and age as explanatory variables showed independent prognostic value. Molecular characterisation of subtypes by differential gene expression analysis, gene set enrichment analysis, and mutation patterns indicated reduced proliferation and overrepresentation of RUNX1 and IDH2 mutations in the HSC subtype; increased proliferation and overrepresentation of CEBPA mutations in the MEP subtype; and innate immune activation and overrepresentation of WT1 mutations in the GMP subtype. We present a differentiation-dependent classification system for AML subtypes with distinct pathogenetic and prognostic importance that can help identify candidates poorly responding to combination chemotherapy and potentially guide alternative treatments.