Germinal Center B-cell Subtype Research Articles

The genetic deletion and protein expression of PRDM1 and its clinical implications in diffuse large B cell lymphoma: A retrospective cohort study in China

ObjectTo investigate the clinical implications of the PRDM1 deletion and PRDM1 protein expression in Chinese diffuse large B cell lymphoma (DLBCL). Materials and methodsTumor samples of 199 patients with DLBCL were obtained from the Department of Pathology of Peking University First Hospital between 2008 and 2015. The PRDM1 expression was detected by immunohistochemistry (IHC) in all samples. Among them, the PRDM1 deletion was detected in 60 samples by fluorescence in situ hybridization (FISH). The correlations between PRDM1 protein expression and PRDM1 molecular status and clinicopathological features were analyzed. ResultsImmunohistochemically, 58 (29.1%) patients were classified as the germinal center B-cell (GCB) subtype, and 141 (70.9%) patients were non-GCB subtype. PRDM1 protein was strongly expressed in 15 (7.5%) patients, weakly expressed in 67 (33.7%) patients, and negative in 117 (26.6%) patients. Heterozygous and homozygous PRDM1 deletions were observed in 28.3% (17/60) and 8.3% (5/60) of cases, respectively. The PRDM1 deletion was not significantly correlated with PRDM1 protein expression. Neither the PRDM1 protein expression nor the PRDM1 deletion was significantly associated with most clinicopathological features, including their immunophenotypes according to the Han's algorithm. However, Kaplan-Meier survival analysis showed that heterozygous and/or homozygous PRDM1 deletion but not PRDM1 expression was a poor prognostic factor in the non-GCB group. In addition, there was a positive correlation between PRDM1 and c-Myc expression. ConclusionsOur results suggested that homozygous or heterozygous PRDM1 deletion is a poor prognostic factor for non-GCB DLBCL.

Cell of Origin Based on Hans’ Algorithm as Prognostic Factor in Diffuse Large B-Cell Lymphoma: A Clinicopathologic and Survival Study

Background: Diffuse Large B-Cell Lymphoma (DLBCL) has been classified based on Cell of Origin (COO) into Germinal Center B-cell (GCB) and Non-Germinal Center B-cell (Non-GCB). The practical application of this concept by immunohistochemistry (IHC)-based subtyping with Hans’ algorithm and its role as a prognostic factor has been widely investigated with conflicting results. Moreover, the recent deeper molecular characterizations of DLBCL have been another challenges for this approach to remain as a prognostic factor. Objective: To determine the prognostic value of COO by IHC-based subtyping with Hans’ algorithm for DLBCL. Materials and Methods: This was a single-center retrospective analysis including DLBCL cases diagnosed in 2014-2019 from Dr. Sardjito Hospital, Yogyakarta, Indonesia. Hans’ algorithm with CD10, BCL6, and MUM1 were used. The two subtypes were compared in terms of clinicopathological features and 3 years overall survival. Results: Seventy patients were included in this study. Non-GCB was predominant than GCB 74.3% vs 25.7%, with the ratio of 2.8:1. No statistical difference in the clinicopathological features from both subtypes in terms of age, gender, Ann Arbor stadium, ECOG performance status, extra-nodal involvement, and LDH level. Ann Arbor stadium and ECOG showed significant prognostic value for patients outcome with multivariate analysis (OR 3.64; 95%CI 0.18-0.61; p=0.001) and (OR 2.68; 95%CI 0.11-0.77; p=0.009). Survival analysis based on COO did not show significant difference between GCB and non-GCB subtypes (log rank=0.46). Further analysis based on COO and the use of rituximab showed better OS in the two subtypes than without rituximab although not significant (log rank=0.67). Conclusion: The role of COO with Hans’ algorithm as prognostic factor in DLBCL is not confirmed in this study. Some related factors may be the addition of rituximab and the recent molecular characterization of DLBCL which covered a more subtle classification of the disease beyond GCB and non-GCB subtypes.

MUM1 Expression versus Hans Algorithm to Predict Prognosis in Indonesian Diffuse Large B-Cell Lymphoma Patients Receiving R-CHOP.

BackgroundTreatment response in diffuse large B-cell lymphoma (DLBCL) is heterogenous. The Hans algorithm (using 30% cut-offs for CD10, BCL6, and MUM1 protein expression) has been the most favored method to categorize DLBCL into germinal center B-cell (GCB) and non-GCB subtypes in order to predict prognosis. However, the algorithm’s ability to prognosticate is not always consistent.MethodsThis retrospective cohort study was conducted on DLBCL patients receiving R-CHOP therapy at Dr. Cipto Mangunkusumo Hospital, Jakarta from 2014 to 2017. We aimed to compare the prognostic value of Hans algorithm as well as the protein levels of CD10, BCL6, MUM1, and Ki67 at different cut-offs. Ninety-two patients were classified based on Hans algorithm and various proteins at different cut-off values were analyzed with regard to event-free survival at 24 months using survival analysis. The cut-off values were then compared using receiver operating characteristic curves.ResultsA significant survival difference was observed with MUM1 expression cut-off of 50% or more (log rank p = 0.035). CD10, BCL6, Ki67, and Hans algorithm showed AUCs below or near 0.5 (0.405, 0.436, 0.498, and 0.413, respectively), whereas MUM1 showed an AUC of 0.835, in predicting events within 24 months. MUM-1 cut-off of 70.5% yielded an optimal trade-off for sensitivity and specificity.ConclusionMUM1 expression of 50% or more can help predict prognosis in DLBCL patients receiving R-CHOP therapy and can be considered as for use as a single marker to predict prognosis.

Clinicopathological features and prognosis of high-grade B-cell lymphoma with MYC and bcl-2 and/or bcl-6 rearrangements

Objective: To investigate the clinicopathological characteristics and prognosis of high-grade B-cell lymphoma (HGBL) involving combined rearrangements of MYC, bcl-2 and bcl-6. Methods: A total of 1 138 cases of large B cell lymphoma (LBL) that were treated at the Ruijin Hospital Affiliated to Shanghai Jiaotong University School of Medicine from January 2017 to September 2020 were analyzed using fluorescence in situ hybridization (FISH) with probes against MYC, bcl-2 and bcl-6. The clinical and pathological data of the 45 patients with HGBL that had rearrangements of MYC and bcl-2 and/or bcl-6 were collected and retrospectively analyzed. Results: Among the 1 138 LBL, 45 (4.0%) cases had combined rearrangements of MYC, bcl-2 and/or bcl-6 that included 6 HGBL cases with MYC, bcl-2 and bcl-6 rearrangements, 14 HGBL cases with MYC and bcl-2 rearrangements, and 25 HGBL cases with MYC and bcl-6 rearrangements. Of these 45 patients, 29 patients were male, and 16 patients were female, aged 29 to 83 years. HGBL with MYC, bcl-2 and bcl-6 rearrangements and HGBL with MYC and bcl-2 rearrangement were reclassified as the germinal center B-cell (GCB) subtype using the Hans algorithm. HGBL with MYC and bcl-6 rearrangement were reclassified as the GCB subtype (68.0%) and the non-GCB subtype (32.0%). The vast majority of HGBL cases had a high Ki-67 proliferation index. Most HGBL patients had advanced stage disease with a high IPI score and an increased LDH level. Also, some patients had clinical features including elevated plasma β2-microglobulin levels, B symptoms, and bone marrow involvement. The IPI scores and LDH levels were significantly different between the HGBL cases with MYC, bcl-2 and bcl-6 rearrangements and the HGBL cases with MYC and bcl-6 rearrangements (P<0.05). Compared with the HGBL cases with MYC, bcl-2 and bcl-6 rearrangements, the HGBL cases with MYC and bcl-2 or bcl-6 rearrangements had a lower incidence of bone marrow involvement (P<0.05). There were no significant differences in the prognosis among HGBL cases with MYC, bcl-2 and bcl-6 rearrangements, the cases with MYC and bcl-2 rearrangements, and the cases with MYC and bcl-6 rearrangements (P>0.05). Conclusions: HGBL with MYC, bcl-2 and/or bcl-6 rearrangements are rare types of B-cell lymphoma with high degree of malignancy and have a short overall survival. To reduce misdiagnosis and improve diagnostic accuracy, it is necessary to assess the patients' clinical features and conduct histopathological, immunohistochemical and FISH analyses.

SGK1 mutation status can further stratify patients with germinal center B-cell-like diffuse large B-cell lymphoma into different prognostic subgroups.

There are over a 100 driver gene mutations in patients with diffuse large B‐cell lymphoma (DLBCL), but their clinical significance remains unclear. Here, we first analyzed the DLBCL dataset from the UK‐based Haematological Malignancy Research Network. Patients were divided into high‐ and low‐risk groups based on whether lymphoma progressed within 24 months. Genes showing significantly different frequencies between groups were selected. Survival data for patients with the selected mutant genes were analyzed. The results were validated using two other large databases to evaluate the relationship between the selected mutant genes and prognosis. The mutation frequencies of 11 genes (MYD88[L265P], SGK1, MPEG1, TP53, SPEN, NOTCH1, ETV6, TNFRSF14, MGA, CIITA, and PIM1) significantly differed between the high‐ and low‐risk groups. The relationships between these mutant genes and patient survival were analyzed. Patients who harbored SGK1 (serum and glucocorticoid‐inducible kinase 1) mutations exhibited the best prognosis. Most patients with SGK1 mutation are germinal center B‐cell (GCB) subtype. Among patients with GCB DLBCL, those harboring SGK1 mutations exhibited better prognosis than those without SGK1 mutations. Most SGK1 mutations were single‐base substitutions, primarily scattered throughout the catalytic domain‐encoding region. Multiple SGK1 mutations were identified in a single patient. Thus, SGK1 mutations are a marker of good prognosis for DLBCL and occur predominantly in the GCB subtype of DLBCL. SGK1 mutation status can further stratify patients with GCB DLBCL into different prognostic subgroups.

Immunohistochemical Characterisation of Cell of Origin in Diffuse Large B-cell Lymphoma and its Association with the Double Expressor Phenotype: A Retrospective Study

Introduction: Diffuse Large B-cell Lymphoma (DLBCL) is the most common type of Non Hodgkin Lymphoma (NHL) and is categorised into the Germinal Centre B-cell (GCB) and Activated B-cell (ABC/Non GCB) subtypes as per the Cell Of Origin (COO) model with the help of gene expression profiling/ immunohistochemistry. The non GCB subtype has been found to associate with the Double Expressor (DE) phenotype (i.e., co-expression of BCL-2 and c-myc by IHC and this association was substantiated and proven to be statistically significant in the present study. Aim: To categorise all DLBCL cases into GCB and Non GCB and further into DE and Non-DE by using Hans and Choi IHC alogrithm. Materials and Methods: A retrospective study of 50 patients was carried out with the help of archival material filed in the Department of Anatomic Pathology at Dharamshila Narayana Superspeciality Hospital, New Delhi, India from 1st January 2019 to 30th June 2020. The study was approved by Instituitional Ethics Committee (IEC). Chi-square test and Yates correction were used for statistical analysis. Results: The study cohort was divided into two Groups- group-A with nodal presentation and group-B with extranodal presentation. By using the Hans and Choi IHC algorithms, the cases were categorised into the GCB and non GCB subtypes in both the groups. The DE phenotype was determined in each case by the co-expression of c-myc (&gt;40%) and BCL-2 (&gt;50%) by IHC. By using the statistical chi-square test analysis and Yates correction, the association of DE was found to be statistically significant with non GCB type lymphomas and non DE with GCB lymphomas with p-value being 0.0005 and 0.00168, respectively. Conclusion: Due to the heterogeneity inherent in DLBCL, prediction of the DE phenotype and the COO by IHC is a sensitive tool and helps in the prognostication and therapeutic triage of patients. Hence, in all the cases diagnosed as DLBCL, a detailed morphological and IHC work up is mandatory to determine prognosis and possibly tailor therapy according to COO and DE phenotype.

Artificial Neural Networks Predicted the Overall Survival and Molecular Subtypes of Diffuse Large B-Cell Lymphoma Using a Pancancer Immune-Oncology Panel.

Simple SummaryThis research predicted the overall survival of patients and cell-of-origin molecular subtypes of diffuse large B-cell lymphoma from Tokai University using gene expression data. A pancancer immune profiling panel was analyzed using artificial neural networks, and high accuracy of prediction was found. Additionally, the results were explained with other machine learning techniques and conventional bioinformatics analyses.Diffuse large B-cell lymphoma (DLBCL) is one of the most frequent subtypes of non-Hodgkin lymphomas. We used artificial neural networks (multilayer perceptron and radial basis function), machine learning, and conventional bioinformatics to predict the overall survival and molecular subtypes of DLBCL. The series included 106 cases and 730 genes of a pancancer immune-oncology panel (nCounter) as predictors. The multilayer perceptron predicted the outcome with high accuracy, with an area under the curve (AUC) of 0.98, and ranked all the genes according to their importance. In a multivariate analysis, ARG1, TNFSF12, REL, and NRP1 correlated with favorable survival (hazard risks: 0.3–0.5), and IFNA8, CASP1, and CTSG, with poor survival (hazard risks = 1.0–2.1). Gene set enrichment analysis (GSEA) showed enrichment toward poor prognosis. These high-risk genes were also associated with the gene expression of M2-like tumor-associated macrophages (CD163), and MYD88 expression. The prognostic relevance of this set of 7 genes was also confirmed within the IPI and MYC translocation strata, the EBER-negative cases, the DLBCL not-otherwise specified (NOS) (High-grade B-cell lymphoma with MYC and BCL2 and/or BCL6 rearrangements excluded), and an independent series of 414 cases of DLBCL in Europe and North America (GSE10846). The perceptron analysis also predicted molecular subtypes (based on the Lymph2Cx assay) with high accuracy (AUC = 1). STAT6, TREM2, and REL were associated with the germinal center B-cell (GCB) subtype, and CD37, GNLY, CD46, and IL17B were associated with the activated B-cell (ABC)/unspecified subtype. The GSEA had a sinusoidal-like plot with association to both molecular subtypes, and immunohistochemistry analysis confirmed the correlation of MAPK3 with the GCB subtype in another series of 96 cases (notably, MAPK3 also correlated with LMO2, but not with M2-like tumor-associated macrophage markers CD163, CSF1R, TNFAIP8, CASP8, PD-L1, PTX3, and IL-10). Finally, survival and molecular subtypes were successfully modeled using other machine learning techniques including logistic regression, discriminant analysis, SVM, CHAID, C5, C&R trees, KNN algorithm, and Bayesian network. In conclusion, prognoses and molecular subtypes were predicted with high accuracy using neural networks, and relevant genes were highlighted.

Obesity Is Associated with Increased Relapse Risk in Diffuse Large B-Cell Lymphoma

Introduction: Diffuse Large B-Cell Lymphoma (DLBCL) is an aggressive Non-Hodgkin's lymphoma (NHL) characterized by clinical, biological and genetic heterogeneity. Despite the tremendous advancement in anticancer therapy against DLBCL, up to 40% of patients are refractory and/or relapse after first-line chemo-immunotherapy. Mechanisms responsible for chemo-immunotherapy failure are largely uncharacterized; however, it is believed the microenvironment contributes to tumor adaptation and survival. Several studies have shown that high body mass index (BMI) is associated with increased risk of developing DLBCL and obesity is an independent prognostic indicator of worse outcome when compared to non-obese patients. Weight gain alters the metabolic landscape of tumor microenvironment to inhibit T cell function and promote cellular growth. Obesity induced proinflammatory mediators can activate numerous signaling pathways including nuclear factor (NF)-KB that result in anti-apoptotic and increased proliferative efficiency in B-cells Here, we report the results of our retrospective study from two hospital systems in Houston, Texas evaluating the impact of BMI on progression-free-survival (PFS) in DLBCL patients receiving standard induction chemotherapy.Methods: After Institutional Review Boards (IRB) approval, patients (pts) were identified by electronic medical record database query. Inclusion criteria included: (a) age>18 years old, (b) DLBCL diagnosis confirmed by pathology review at Ben Taub Medical Center and Baylor St. Luke's Medical Center. BMI was calculated using patient's height and weight at diagnosis. For all comparison, we selected DLBCL pts with World Health Organization (WHO) predefined overweight, class I, II, III obesity to better capture effect of extreme BMI on DLBCL PFS. Cell-of-origin (COO) was determined by Hans classification. R-CHOP/R-EPOCH were classified as intense therapy whereas R-CVP/R-CEOP as non-intense therapy. Descriptive statistics was used to evaluate differential expression of clinical and laboratory variables. PFS among pts with BMI <35 and BMI >35 was estimated with Kaplan Meier Method. Cox regression model evaluated effect of independent variables on PFS for pts with DLBCL exhibiting obesity. SAS was used for all analysis.Results: 123 pts were identified. Demographic, clinical and laboratory data was balanced among DLBCL pts with and without BMI >35 (Table 1). Median BMI was 25.9 for pts with BMI<35 v 37.3 in pts with BMI >35. In the pts with BMI <35, 36.9% were classified as germinal center b-cell (GCB) subtype and 63.1% were classified as non-GCB subtype (p= NS). Within the BMI >35, 46.2% were GCB subtype and 53.9% were non-GCB subtype. 45.9% of pts had low International Prognostic Index (IPI) score in BMI<35 compared to 56.52% in BMI>35, whereas 54% had high IPI in BMI<35 compared to 43.48% in BMI>35. PFS was 2,864 days vs 763 days in patients with BMI <35 and >35, respectively (p=0.02). (Fig 1). To address effect of “type of therapy administered” (low v high intensity), COO, and age as confounders for our observation that PFS is inferior in DLBCL pts with BMI >35, Cox regression model was performed confirming the independent predictive role for BMI >35 only on DLBCL PFS.Conclusions: Our study demonstrates that obesity (BMI >35) results in increased relapse risk in DLBCL patients. In our population, risk of relapse was enhanced by higher BMI independent of age, therapy administered and COO. Obesity, by itself, especially BMI>35 (Class II and Class III) may represent a unique factor for adverse outcome in DLBCL. The mechanism for which extreme obesity leads to inferior PFS in DLBCL is unclear. It is possible that obesity induces “high risk” mutations acquisition and/or adversely modifies tumor microenvironment resulting in chemotherapy cytotoxic attenuation. Larger studies are needed to externally validate our observation. [Display omitted] DisclosuresMims: Biogen: Current holder of individual stocks in a privately-held company; Incyte: Research Funding; IDEC: Current holder of individual stocks in a privately-held company; Celgene: Research Funding; Pfizer: Research Funding; AVEO: Research Funding.

Noninvasive Cell-of-Origin Classification of Diffuse Large B-Cell Lymphoma Using Inferred Gene Expression from Cell-Free DNA Sequencing

Noninvasive Cell-of-Origin Classification of Diffuse Large B-Cell Lymphoma Using Inferred Gene Expression from Cell-Free DNA Sequencing

Combination Benefit of Capivasertib and Venetoclax in Preclinical Models of Diffuse Large B-Cell Lymphoma

Diffuse large B-cell lymphoma (DLBCL) is the most common B-cell malignancy among adults and despite approximately 65% of patients with DLBCL being cured with RCHOP therapy, nonresponsive and relapsed patients have inadequate treatment options, highlighting the importance for innovative treatment regimens. Blockade of B-cell receptor (BCR) downstream signaling components with various targeted agents is emerging as a clinically tractable treatment strategy across multiple B-cell malignancies. Protein Kinase B (AKT) signaling downstream of the BCR complex has been shown to be a central node in germinal center B-cell (GCB) DLBCL and the potent, selective inhibitor of AKT1, AKT2, AKT3, capivasertib, currently being evaluated in multiple clinical trials by targeting AKT-driven solid cancers, has been shown to induce apoptosis in a subset of GCB-DLBCL cell lines and cause tumor stasis in xenograft mouse models (Erdman et al., 2017). Since the monotherapy capivasertib responses in GCB DLBCL models are partial and lack durability, we hypothesized a combination approach could deliver even greater therapeutic benefit. To identify optimal partners, we conducted a capivasertib centric in vitro combination screen with specific with BH3 family members across a panel of 15 DLBCL cell lines, which revealed a synergistically active combination with the BCL2 inhibitor, venetoclax which is currently being evaluated in DLBCL. The activity was specifically enhanced in cell lines of the GCB subtype, with 4 PTEN del and 2 PTEN wt cell line models showing combination benefit. To determine the ability of this combination to drive stronger and durable responses, we assessed capivasertib and ventoclax activity in xenograft mouse models using two GCB-DLBCL cell line lines, SUDHL4 (PTEN wt) and WSU-DLCL2 (PTEN del). Oral administration of either monotherapy capivasertib (130 mg/kg BID, 4-day on/3-day off) or venetoclax (100 mg/kg QD) provided partial tumor growth inhibition (capivasertib TGI = 74% in SUDHL4 and 29% in WSU-DLCL2, and venetoclax TGI = 46% in SUDHL4 and 0% in WSU-DLCL2), whereas the combination of capivasertib and venetoclax both on a 4-day on/3-day off schedule produced complete tumor regression (100% regression) in both xenograft GCB cell line models during the dosing period. Notably, in both xenograft models all mice (5/5 per model) remained tumor free for at least 30 days following dosing cessation demonstrating high durability of response for the combination. Additionally, this combination is currently being evaluated in clinically relevant GCB and non-GCB PDX mouse models. Taken together, our results provide preclinical evidence for the rational combination of AKT and BCL-2 blockade with capivasertib and venetoclax respectively in patients with relapsed/refractory GCB-DLBCL. DisclosuresWillis: AstraZeneca: Current Employment, Other: may hold equity, stock, or stock options. Neveras: AstraZeneca: Current Employment, Other: may hold equity, stock, or stock options. Dry: AstraZeneca: Current Employment, Other: may hold equity, stock, or stock options. Mongeon: AstraZeneca: Current Employment, Other: may hold equity, stock, or stock options. Rosen: AstraZeneca: Current Employment, Other: may hold equity, stock, or stock options. Mettetal: AstraZeneca: Current Employment, Other: may hold equity, stock, or stock options. Barry: AstraZeneca: Current Employment, Other: may hold equity, stock, or stock options.

Analysis of prognostic factors in diffuse large B-cell lymphoma associated with rheumatic diseases

ObjectiveThe risk of developing diffuse large B-cell lymphoma (DLBCL) is increased in many rheumatic diseases (RDs). It is possible that RD-associated DLBCL is a distinct subset within the category of...

Integrative analysis of hub genes and key pathway in two subtypes of diffuse large B-cell lymphoma by bioinformatics and basic experiments.

BackgroundThe germinal center B‐cell (GCB) and activated B‐cell (ABC) subtypes of diffuse large B‐cell lymphoma (DLBCL) have a significant difference in prognosis. This study aimed to identify potential hub genes, and key pathways involved in them.MethodsDatabases including Gene Expression Omnibus (GEO), Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and STRING were accessed to obtain potential crucial genes and key pathways associated with the GCB and ABC. Then qRT‐PCR and Western blot experiments were performed to verify the most clinically significant gene and pathway.ResultsThree cohort datasets from the GEO database were analyzed, including 195 GCB and 169 ABC samples. We identified 1113 differentially expressed genes (DEGs) between the GCB and ABC subtypes. The DEGs were mainly enriched in biological processes (BP). The KEGG analysis showed enrichment in cell cycle and Wnt signaling pathways. We selected the top 10 genes using the STRING database and Cytoscape software. We used 5 calculation methods of the cytoHubba plugin, and found 3 central genes (IL‐10, CD44, CCND2). CCND2 was significantly related to the prognosis of DLBCL patients. Besides, our experimental results demonstrated a significantly higher expression of CCND2 in the ABC‐type cell line than in the GCB‐type; it was proportional to the expression of key proteins in the Wnt signaling pathway.ConclusionCCND2 overexpression and Wnt pathway activation might be the main reasons for the poor prognosis of ABC‐DLBCL.

Application of CD54 in diagnosing bone marrow involvement by using flow cytometry in patients with diffuse large B-cell lymphoma

BackgroundFlow cytometry plays a key role in detecting bone marrow (BM) involvement in patients with diffuse large B-cell lymphoma (DLBCL). To improve its detection sensitivity, we need to explore novel markers. In this study, we detected the expression CD54 on lymphoma cells in BM specimens from DLBCL patients and clarified its diagnostic significance in BM involvement by DLBCL.MethodsWe collected BM specimens from 76 patients with DLBCL (germinal center B-cell (GCB) = 25, non-GCB = 51) and 10 control patients without lymphoma. We detected and compared the expression of CD54 on lymphoma cells and normal mature B cells by using 10-color panels.ResultsNormal plasma cells expressed a higher level of CD54 as compared with hematogones (p < 0.05) and normal mature B cells (p < 0.05). Among 76 patients, 23 of them (GCB = 12, non-GCB = 11) had BM involvement. Lymphoma B cells from 12 cases (GBC = 4, non-GCB = 8) expressed a higher level of CD54 compared to normal mature B cells (p < 0.05). Additionally, lymphoma cells of the non-GCB subtype frequently expressed a higher level of CD54 in comparison to the GCB subtype (p < 0.05). And the high expression of CD54 was not related to plasmacytoid differentiation.ConclusionAberrant expression of CD54 on lymphoma cells is frequently seen in patients’ BM specimens involved by DLBCL, especially in the non-GCB subtype. CD54 could be used as a new marker to gate on lymphoma cells and improve the detection sensitivity of BM involvement in patients with DLBCL.

A Phase II Study of Chidamide Plus R-CHOP in Elderly Patients with Newly Diagnosed Diffuse Large B-Cell Lymphoma: An Interim Analysis

Background: Diffuse large B-cell lymphoma (DLBCL) is the most common subtype of non-Hodgkin lymphoma, accounting for 30%-40% of all cases. Although rituximab in combination with cyclophosphamide, doxorubicin, vincristine and prednisone (R-CHOP) significantly improves the outcome of the patients, approximately 50% of the elderly patients eventually experience disease progression or relapse, particularly in the intermediate and high risk group (International prognostic index (IPI)>1). Therefore, novel agents along with R-CHOP have been applied to increase treatment efficacy and long-term outcome in this subset of DLBCL patients.Perturbation of the epigenome plays a crucial role in lymphoma progression. Mutations in histone modifier enzymes are frequently observed in DLBCL patients. Through targeting epigenetic lesions, HDAC inhibitors (HDACIs) are emerging as feasible therapeutic approaches to suppress lymphoma growth and to overcome resistance to immuno-chemotherapy. Chidamide, an orally active and subtype-selective HDACI, was developed in China. However, its anti-tumor activity has not yet been assessed in DLBCL. This prospective phase II study is to evaluate the efficacy and safety of chidamide in combination with R-CHOP (CR-CHOP) in elderly DLBCL (NCT02753647).Methods: Patients with newly diagnosed DLBCL, aged 61 to 75 years, Eastern Cooperative Oncology Group performance status of 0 to 2, IPI > 1 are enrolled. The doses and administration schedule are as follows: rituximab 375 mg/m2 on day 0, cyclophosphamide 750 mg/m2 on day 1, doxorubicin 50 mg/m2 on day 1, vincristine 1.4 mg/m2 on day 1, prednisone 60 mg/m2 from day 1 to day 5, chidamide 20 mg/d on days 1, 4, 8 and 11, every 21 days for 6 cycles. The primary endpoint is complete response (CR) rate assessed by PET-CT, and secondary endpoints include progression-free survival (PFS), overall survival (OS), overall response rate (ORR) and main adverse events (AEs).Results: To date, thirty-two patients have been enrolled, with median age of 67 years (range, 61-75). At diagnosis, twenty-two patients (68.8%) presented advanced Ann Arbor stage and 26 cases (81.3%) showed elevated serum LDH level. Twenty-one patients (65.6%) had multiple extra-nodal sites mainly involving bone, gastrointestinal, liver, and bone marrow, and 26 patients (81.2%) had IPI scores ≥ 3. By immunohistochemistry, eight (25.0%) patients were categorized as germinal center B-cell (GCB) subtype based on Hans algorithm, and 8 (25.0%) patients were defined as BCL-2 and MYC double expression (DE).For 16 patients available for response evaluation, the CR rate was 87.5% (14/16), and the ORR was 93.8% (15/16). No difference of the CR rate was observed between GCB and non-GCB subtype (75% and 90%, P=0.555), or DE and non-DE subtype (100% and 87.5%, P=1.0). Grade 3-4 neutropenia was found in 27 cases (84.4%), grade 3-4 thrombocytopenia in 11 cases (34.4%), and grade 3-4 anemia in 6 cases (18.8%). For non-hematological AEs, grade 3 liver dysfunction and prolonged QTc interval were observed in 3 cases (9.4%) and in 1 case (3.1%) respectively, while no grade 4 non-hematological AEs were observed.Conclusion: CR-CHOP as first-line therapy for elderly intermediate and high risk (IPI>1) patients with DLBCL showed encouraging response and good tolerability. DisclosuresNo relevant conflicts of interest to declare.

BCL2 Expression Identifies a Population with Unmet Medical Need in Previously Untreated (1L) Patients with DLBCL

▪Introduction.High BCL2 protein expression has been associated with inferior outcome in multiple studies in diffuse large B-cell lymphoma (DLBCL) (Gascoyne et al. 1997; Salles et al. 2011; Horn et al. 2013; Tsuyama et al. 2017). Patients with high levels of BCL2 expression may benefit from treatment with venetoclax, a first-in-class, highly selective BCL2 inhibitor with demonstrated activity in cell lines and xenograft models (Souers et al. 2013, Punnoose et al. 2016). The evaluation of BCL2 as a prognostic marker has been complicated by the variability in recognized immunohistochemistry (IHC) thresholds (de Jong et al. 2007; Tsuyama et al. 2017) and the impact of cell-of-origin (COO) (Iqbal et al. 2011). Using a BCL2 IHC scoring algorithm that was developed to identify cell lines that are sensitive to BCL2 inhibition, and that could potentially identify patients likely to benefit from venetoclax, we evaluated the prognostic capability of BCL2 IHC in three independent cohorts of 1L DLBCL patients. Cohorts included two Phase 3 studies (MAIN [NCT00486759] and GOYA [NCT01287741]), and a representative cohort from the British Columbia Cancer Agency (BCCA) registry-based population, in which subjects received chemoimmunotherapy (either rituximab or obinutuzumab, combined with cyclophosphamide, doxorubicin, vincristine and prednisone [CHOP]).Patients and Methods. Pretreatment tumor samples were tested for BCL2 IHC using an algorithm that assesses both the percent of tumor cells stained and the intensity of staining, similar to the BCL2 algorithm proposed by Tsuyama et al. (Table 1).Whole-tissue slides from184 patients from MAIN were tested at Genentech , whole tissue slides from 366 patients from GOYA were tested at Hematogenex (Ventana assay) and tissue microarray slides from 310 patients from BCCA were tested at Ventana (Ventana assay). The NanoString Lymphoma Subtyping gene expression assay was used for classification of COO into germinal center B-cell (GCB), activated B-cell (ABC) or unclassified subtypes in MAIN (n=159), GOYA (n=353) and BCCA (n=302). Multivariate Cox regression analysis of progression-free survival (PFS) was performed in each study with the International Prognostic Index (IPI; The International NHL Prognostic Factors Project 1993) and/or COO as covariates. Given the similar treatment effect, patient data from both treatment arms in each study were merged for this analysis.Results. Baseline characteristics were similar for the BCL2 IHC evaluable and intent-to-treat (ITT) populations of these three cohorts. Prevalence of BCL2 positive patients was 48% in MAIN, 49% in GOYA and 58% in the BCCA cohort. The prevalence of BCL2 positive samples within the ABC subtype was 64%, 75% and 60% in the MAIN, GOYA and BCCA cohorts, respectively, and 40%, 38% and 56% within the GCB subtype, respectively. In univariate analysis, BCL2 positivity was associated with shorter PFS in all three cohorts (Figure 1, A-C). In the MAIN study, the prognostic effect of BCL2 appeared to be in the GCB subgroup, not ABC, as previously reported (Punnoose et al. ASH 2015). In the two largest studies of GOYA and BCCA cohorts, the prognostic effect of BCL2 was similar in ABC and GCB (not shown), and was independent of IPI (Table 2).Conclusions. Using a newly developed BCL2 IHC scoring algorithm, we demonstrate that DLBCL patients positive for BCL2 have a consistently inferior prognosis compared with patients negative for BCL2. The prognostic value of BCL2 IHC is independent of IPI and COO in GOYA and BCCA. The Ventana assay is currently being used in a Phase 2 study of venetoclax in combination with R-CHOP to evaluate the correlation (if any) of BCL2 expression with venetoclax + R-CHOP treatment (CAVALLI - NCT02055820). [Display omitted] DisclosuresSzafer-Glusman:Genentech: Employment. Peale:Genentech / Roche: Employment, Equity Ownership. Lei:Roche: Employment. Ray:Genentech/Roche: Employment. Farazi:Genentech: Employment. Kornacker:Roche: Equity Ownership; F. Hoffmann-La Roche: Employment. Oestergaard:F. Hoffmann-La Roche Ltd: Employment. Liu:F. Hoffmann-La Roche: Employment. Punnoose:Genentech: Employment.

Utilizing Digital Pathology Informatics Algorithms for Diffuse Large B-Cell Lymphoma Subtyping

Introduction:Diffuse large B-cell lymphoma (DLBCL) is the most commonly occurring lymphoid malignancy in the United States. Through gene expression profiling (GEP), two biologically distinct molecular subgroups of DLBCL have been identified - germinal center B-cell (GCB) and activated B-cell - with disparate prognostic implications. Because GEP is not yet easily implemented in clinical practice, immunohistochemical (IHC) algorithms have been developed and validated to segment DLBCL into cell-of-origin subtypes. The most commonly employed algorithm uses CD10, BCL6 and MUM1 to distinguish GCB and non-GCB subtypes, but has been shown to misclassify up to 20% of cases. Advancements in digital pathology technology have led to the development of image analysis algorithms that allow for the extraction of quantitative descriptions of pathology image features such as level of IHC staining. We explore the feasibility of developing a precise, repeatable, and objective image analysis-based scoring algorithm for DLBCL whole slide images to replicate DLBCL subtype classification and prognostic assessment.Methods:Tissue slides of the immunostains included in the Hans algorithm (CD10, BCL6, MUM1) for 40 DLBCL patients were digitized at 40x objective resolution using Hamamatsu Nanozoomer 2.0 HT or Aperio AT2. We developed and trained an image analysis algorithm on the IHC whole slide images. The algorithm first masks the tissue area of the whole slide image, then performs superpixel segmentation, dividing tissue area into compact regions (60 microns square). Each region is normalized to a reference IHC image and has a color deconvolution algorithm applied to separate the hematoxylin and diaminobenzidine (DAB) stains. Features describing the distribution of both the hematoxylin and DAB stains are extracted using convolutional autoencoders. We then trained a classification algorithm using these features to classify the staining of these regions as positive or negative using machine learning techniques. Whereas pathologists examine specific regions in a high-power field and use visual estimation to determine if >30% of tumor cells are positive, our algorithm measures the percentage of positive regions over the entire DLBCL tissue. Receiver operating characteristics (ROC) curves were calculated to assess ability of image analysis-based measurements to predict pathologist classifications as positive or negative for CD10, BCL6, and MUM1. Pathologist classification of DLBCL subtype and positive or negative for each immunostain were obtained from pathology reports. Using thresholds for percent positive regions established by the ROC curves, patients were classified into GCB/non-GCB by the Hans algorithm using sequential application of the identified thresholds as shown in the Figure. The regions in the figure define the algorithm classification and the lines correspond to the pathologist classification displaying GCB in blue and non-GCB in red. Concordance with pathologist subtyping was calculated by agreement rate and Cohen's κ statistic.Results:Of the 40 patients included in our study, pathologists classified CD10, BCL6, and MUM1 as positive in 27.5%, 90%, and 84.9% respectively. Area under the ROC curve (AUC) for predicting pathologist classifications of positivity from image analysis measurements for CD10, BCL6, and MUM1 were 0.92, 1.0, and 0.95 respectively. Thresholds from the ROC curves for CD10, BCL6, and MUM1 were 13%, 15%, and 20% respectively. Using these thresholds, classification by image analysis algorithm was concordant with pathologist classification in 82.5% (κ = 0.65) of cases.Discussion:Pathologist IHC classification is limited by interobserver and interlaboratory variability, human error, difficulties with human eye distinguishing between low-intensity stains, and ordinal outputs. These limitations have led to inconsistent prognostic significance with IHC cell-of-origin subtyping. We developed a novel, objective image analysis scoring for predicting DLBCL subtype that uses whole slide images. Our image analysis algorithm may provide an effective decision-support tool for pathologist subtype classification and address known limitations. Future work will compare subtyping by the image analysis algorithm to gene expression profiling and inter-rater reliability of tissue microarrays and whole slide images performed by expert hematopathologists. [Display omitted] DisclosuresFlowers:National Institutes Of Health: Research Funding; Burroughs Welcome Fund: Research Funding; Celgene: Consultancy, Research Funding; Gilead: Consultancy; Research to Practice: Research Funding; Infinity: Research Funding; Onyx: Research Funding; Seattle Genetics: Consultancy; V Foundation: Research Funding; Genentech/Roche: Consultancy, Research Funding; OptumRx: Consultancy; Bayer: Consultancy; Millennium/Takeda: Research Funding; Eastern Cooperative Oncology Group: Research Funding; Clinical Care Options: Research Funding; National Cancer Institute: Research Funding; TG Therapeutics: Research Funding; Acerta: Research Funding; Prime Oncology: Research Funding; Educational Concepts: Research Funding; Spectrum: Consultancy; Pharmacyclics LLC, an AbbVie Company: Research Funding; Janssen Pharmaceutical: Research Funding; Abbvie: Consultancy, Research Funding. Cooper:Varian Medical Systems: Honoraria.

Combination of IRAK4 Inhibitor CA-4948 with BCL2 Inhibitor Venetoclax Induces Tumor Regression in an ABC-DLBCL Xenograft Model

IRAK4 kinase activity is required for toll-like receptor (TLR) and interleukin-1 receptor (IL-1R) signaling in a variety of myeloid and lymphoid cell types. Recruitment of IRAK4 to these receptors and its subsequent activation is facilitated by the MYD88 adaptor protein, which is mutated in ~22% of diffuse large B-cell lymphoma (DLBCL) cases. The MYD88- L265P activating mutation is found in ~30% of the activated B-cell (ABC) and ~6% of germinal center B-cell (GCB) subtypes of DLBCL and leads to constitutive activation of NF-κB signaling that is associated with worse prognosis. In Waldenstrom macroglobulinemia (WM), the MYD88- L265P activating mutation is present in >90% of cases. Thus, the development of small molecule inhibitors targeting IRAK4 is an attractive anticancer strategy for MYD88 mutation-containing cancers such as DLBCL and WM.We are developing a novel IRAK4 inhibitor, CA-4948, as a therapeutic agent for non-Hodgkin lymphoma (NHL) and hematological cancers with dysregulated TLR/MYD88/IRAK4 signaling. CA-4948 is a reversible kinase inhibitor that modulates IRAK4 function in both the toll-like receptor (TLR) and interleukin 1 receptor (IL-1R) signaling cascades, and demonstrates pharmacodynamic and antitumor activity in in vitro and in vivo nonclinical models. CA-4948 exhibits favorable DMPK properties, oral bioavailability, and is well tolerated in mice. Furthermore, CA-4948 was previously shown to exhibit dose-dependent efficacy in ABC-DLBCL MYD88 -L265P xenograft tumor models using cell lines OCI-LY3 and OCI-Ly10 and patient-derived tumors.Activating mutations in the B-cell receptor (BCR) signaling pathway are frequently present in various NHL subtypes, leading to activation of NF-kB signaling, and growth and survival pathways. Dysregulation of both TLR and BCR pathways suggest that targeting both pathways will be required for improved therapeutic responses in NHL. Here, we report efficacy results from combined treatment of CA-4948 and the BCL2 inhibitor venetoclax in an ABC-DLBCL xenograft tumor model.We performed an in vivo study in female SCID Beige mice implanted with the ABC-DLBCL cell line OCI-Ly10, which harbors TLR (MYD88 -L265P) and BCR (CD79A ITAM) pathway activating mutations. OCI-Ly10 tumor-bearing mice were treated with CA-4948 (50 mg/kg, qd, po), venetoclax (75 mg/kg, qd, po) or the combination for 21 continuous days. Single agent treatment of CA-4948 and venetoclax exhibited moderate tumor growth inhibition (TGI) of 63% and 71%, respectively, and the combination demonstrated tumor regression. The combination was tolerated at the end of treatment without body weight loss relative to predose weight. After the 21-day drug treatment period, the mice were given a 19-day dosing holiday. Within 5 days of the holiday rapid tumor growth occurred in the previously treated single drug-treated mice and this rapid growth continued for the remainder of the dosing holiday. In contrast, tumors from the combination drug-treated mice did not commence detectable regrowth until the 10th day of the drug holiday and proceeded with a slow growth rate for the subsequent 9 days.After the 19-day drug holiday, dosing of the respective drug treatments was reinstated to each cohort. After 7 days of re-dosing, the tumors in each cohort exhibited antitumor responses to respective drug treatments with the CA-4948 plus venetoclax combination again driving the tumors into regression. In summary, CA-4948 plus venetoclax was a well-tolerated drug combination that exhibited a much greater in vivo antitumor response as compared to the single agent treatments. These results underscore the therapeutic potential of targeted IRAK4 kinase inhibition by CA-4948 in combination with other targeted agents for the treatment of NHL. DisclosuresBooher:Curis, Inc: Employment, Equity Ownership. Dellarocca:Curis, Inc: Employment, Equity Ownership. Atoyan:Curis, Inc: Employment, Equity Ownership. Borek:Curis, Inc: Employment, Equity Ownership. Samson:Curis, Inc: Employment, Equity Ownership. Tuck:Curis, Inc: Employment, Equity Ownership.

High Expression of Programmed Death-Ligand 1 (PD-L1) Correlates with Macrophage Gene Expression and Is Associated with Prolonged Progression-Free Survival (PFS) in Patients (pts) with First-Line (1L) Diffuse Large B-Cell Lymphoma (DLBCL)

▪Introduction PD-L1 and its receptor PD-1 are both expressed on multiple cell types, including antigen-presenting cells, T cells and tumor cells. In DLBCL, PD-L1 expression on non-malignant immune cells is common, whereas tumor-cell PD-L1 expression is restricted to a small percentage of pts. Because PD-L1/PD-1 are expressed on macrophages after in vitro activation, and activated macrophages contribute to antibody-dependent cellular phagocytosis (ADCP), high PD-L1 expression may identify tumors enriched with activated tumor-infiltrating macrophages primed for ADCP. Considering the role of ADCP in clinical responses to anti-CD20 (rituximab/obinutuzumab), we hypothesized that PD-L1 expression could reflect abundance of activated tumor-infiltrating macrophages and may be associated with prolonged PFS in 1L DLBCL. We leveraged 2 large Phase 3 trials and cell-line immune gene expression to better understand the biological and clinical relevance of PD-L1 expression in 1L DLBCL.Methods We used clinical, genomic and pre-treatment immunohistochemistry (IHC) data from 1L DLBCL pts treated in the MAIN (NCT00486759) and GOYA (NCT01287741) trials. Pre-treatment tissue microarray cores from 201 MAIN pts were stained for PD-L1 (clone SP263), with 21 uninvolved lymph node FFPE sections used as controls. PD-L1+ samples were defined as IHC > 1+ (> 1% tissue area occupied by PD-L1+ cells). Tumor cells were identified based on morphological/cytological features, and PD-L1 tumor expression was scored as a percentage. Activated B-cell (ABC), germinal center B-cell (GCB) and unclassified DLBCL prognostic subtypes were determined by the NanoString Lymph2Cx cell-of-origin (COO) assay. We quantified mRNA expression of PD-L1, macrophage and B-cell genes using TruSeq (Illumina) RNAseq among 702 DLBCL pts (GOYA, n = 552; MAIN, n = 150), with 28 DLBCL cell lines and 15 purified normal B-cell samples as comparators. High/low expression of each gene signature was determined by median cutoffs. Median follow-up durations were 24 and 29 mo in MAIN and GOYA, respectively (≈ 30% of PFS events in both cohorts). We used Cox regression to examine associations between these markers and PFS, adjusting for IPI, age, COO, sex and treatment arm.Results Among 201 DLBCL pts in MAIN, PD-L1 was primarily detected on inter-follicular cells with myeloid/dendritic morphology, similar to the PD-L1 staining pattern of normal lymph nodes. In samples with evaluable germinal centers (GCs), a subset of GC cells expressed PD-L1 with a punctate and granular pattern consistent with a myeloid origin. Overall, there were significantly more pts with high PD-L1 expression by IHC (IHC 3+) and mRNA among ABC vs GCB DLBCL pts. A minority of DLBCL pts (10%) had PD-L1+ tumor cells, consistent with low/undetectable CD274 (PD-L1) mRNA in the majority of DLBCL cell lines and purified normal B-cell samples tested. Additionally, among the 702 evaluable pts in both studies, CD274 mRNA inversely correlated with a B-cell gene signature (MAIN, r= −0.55; GOYA, r= −0.32). High PD-L1 expression (IHC 2+/3+) correlated with prolonged PFS (HR, 0.44 [0.24, 0.80]; P < 0.01) among the 201 evaluable pts in MAIN. Among 552 evaluable pts in GOYA, CD274 expression was higher in pts with a PET-CR (P= 0.02), particularly in pts with ABC DLBCL (P= 0.0001), with a trend toward prolonged PFS in the ABC subtype (HR, 0.80 [0.63, 1.0]; P= 0.054). CD274 mRNA positively correlated with macrophage gene expression in both cohorts (MAIN, r= 0.61; GOYA, r= 0.57); pts with high PD-L1 expression (IHC 2+/3+) also demonstrated high mRNA expression of the macrophage marker CD68. Consistent with PD-L1 reflecting abundance of activated tumor-infiltrating macrophages relevant to anti-CD20 response, high expression of a macrophage signature correlated with prolonged PFS (HR, 0.63 [0.45, 0.87]; P= 0.003) in GOYA and a trend toward prolonged PFS among DLBCL pts treated in MAIN (HR, 0.64 [0.35, 1.16]; P= 0.10), although statistical significance was not reached.Conclusions In 1L DLBCL, most pts expressed PD-L1 on immune cells with myeloid/dendritic morphology, potentially reflecting activated macrophages primed for ADCP and supportive of the correlation between high PD-L1 expression and improved clinical outcomes among pts treated with immunochemotherapy. In the context of anti-CD20, the biology of PD-L1 expression on macrophages and the impact of PD-L1/PD-1 blockade on ADCP merit further study. DisclosuresMcCord:Genentech, Inc.: Employment. Bolen:Genentech: Employment, Equity Ownership. Koeppen:Genentech, Inc.: Employment. Kadel:Genentech, Inc.: Employment. Fingerle-Rowson:F. Hoffmann-La Roche Ltd: Employment, Equity Ownership. Oestergaard:F. Hoffmann-La Roche Ltd: Employment. Venstrom:Genentech, Inc.: Employment.

Phase 1 Clinical Safety, Pharmacokinetics (PK), and Activity of Apilimod Dimesylate (LAM-002A), a First-in-Class Inhibitor of Phosphatidylinositol-3-Phosphate 5-Kinase (PIKfyve), in Patients with Relapsed or Refractory B-Cell Malignancies

Phase 1 Clinical Safety, Pharmacokinetics (PK), and Activity of Apilimod Dimesylate (LAM-002A), a First-in-Class Inhibitor of Phosphatidylinositol-3-Phosphate 5-Kinase (PIKfyve), in Patients with Relapsed or Refractory B-Cell Malignancies

The Positivity of Phosphorylated STAT3 Is a Novel Marker for Favorable Prognosis in Germinal Center B-Cell Type of Diffuse Large B-Cell Lymphoma.

On the basis of immunohistochemistry, diffuse large B-cell lymphoma (DLBCL) is categorized as a germinal center B-cell (GCB) or non-GCB subtype. Recent integrated genomic analyses have highlighted the importance of the JAK-STAT3 pathway in the molecular pathogenesis of DLBCL. However, its relevance to clinical outcomes remains controversial. Therefore, we evaluated the extent of the nuclear expression of phosphorylated STAT3 (pSTAT3), a surrogate marker of signal transducer and activator of transcription 3 (STAT3) activation, by immunohistochemistry. We also analyzed the potential relationship between pSTAT3 positivity (defined as ≥40% positive neoplastic cells) and clinicopathologic characteristics in 294 patients with DLBCL. pSTAT3 was detected in 122 patients (42%), with a higher rate in the non-GCB subtype than in the GCB subtype (57% vs. 28%, P<0.001). Factors potentially activating STAT3, MYD88L265P, and Epstein-Barr virus-encoded small RNA were identified in the pSTAT3-positive non-GCB subtype, whereas the pSTAT3-positive GCB subtype often showed STAT3 mutations and lacked EZH2 mutations and the rearrangements of BCL2 and MYC. Multivariate analyses revealed that the pSTAT3-positive GCB subtype showed a favorable prognosis (HR: 0.17; 95% confidence interval, 0.04-0.7; P=0.014). These findings suggest that pSTAT3 positivity may have a unique impact on the clinicopathologic characteristics of DLBCL, making it a promising novel marker for the favorable prognosis of patients with the GCB subtype.