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Purpose:Atezolizumab [anti–programmed death-ligand 1 (PD-L1)] selectively targets PD-L1 to block its interaction with receptors programmed death 1 and B7.1, thereby reinvigorating antitumor T-cell activity. We evaluated the long-term safety and activity of atezolizumab, along with biological correlates of clinical activity endpoints, in a cohort of patients with melanoma in an ongoing phase Ia study (NCT01375842).Patients and Methods:Patients with unresectable or metastatic melanoma were enrolled to receive atezolizumab 0.1 to 20 mg/kg or ≥10 mg/kg every 3 weeks. Primary study objectives were safety and tolerability. Secondary objectives included investigator-assessed efficacy measures; pharmacodynamic and predictive biomarkers of antitumor activity were explored.Results:Forty-five patients were enrolled and were evaluable for safety. Most treatment-related adverse events (AE) were grade 1/2 (60%). Fatigue (44%), pruritus (20%), pyrexia (18%), and rash (18%) were the most common treatment-related AEs of any grade. No treatment-related deaths occurred. Overall response rate was 30% among 43 efficacy- evaluable patients, with a median duration of response of 62 months [95% CI, 35–not estimable (NE)]. Clinically meaningful long-term survival was observed, with a median overall survival of 23 months (95% CI, 9–66). Baseline biomarkers of tumor immunity [PD-L1 expression on immune cells, T effector (Teff), and antigen presentation gene signatures) and tumor mutational burden (TMB) were associated with improved response, progression-free survival, and overall survival.Conclusions:Atezolizumab was well tolerated, with durable responses and survival in patients with melanoma. PD-L1 expression, TMB, and Teff signatures may indicate improved benefit with atezolizumab in these patients.

Figures S1-S4

Purpose:Natural killer (NK) cells are key effector cells for anti-CD20 monoclonal antibodies (mAb), such as obinutuzumab and rituximab. We assessed whether low pretreatment NK-cell count (NKCC) in peripheral blood or tumor tissue was associated with worse outcome in patients receiving antibody-based therapy.Patients and Methods:Baseline peripheral blood NKCC was assessed by flow cytometry (CD3−CD56+ and/or CD16+ cells) in 1,064 of 1,202 patients with follicular lymphoma treated with obinutuzumab or rituximab plus chemotherapy in the phase III GALLIUM trial (NCT01332968) and 1,287 of 1,418 patients with diffuse large B-cell lymphoma (DLBCL) treated with obinutuzumab or rituximab plus cyclophosphamide, doxorubicin, vincristine, and prednisone (G-CHOP or R-CHOP) in the phase III GOYA trial (NCT01287741). The prognostic value of tumor NK-cell gene expression, as assessed by whole-transcriptome gene expression using TruSeq RNA sequencing, was also analyzed. The association of baseline variables, such as treatment arm, was evaluated using multivariate Cox regression models using a stepwise approach.Results:In this exploratory analysis, low baseline peripheral blood NKCC was associated with shorter progression-free survival (PFS) in both follicular lymphoma [hazard ratio (HR), 1.48; 95% confidence interval (CI), 1.02–2.14; P = 0.04] and DLBCL (HR, 1.36; 95% CI, 1.01–1.83; P = 0.04), and overall survival in follicular lymphoma (HR, 2.20; 95% CI, 1.26–3.86; P = 0.0058). Low tumor NK-cell gene expression was associated with shorter PFS in G-CHOP–treated patients with DLBCL (HR, 1.95; 95% CI, 1.22–3.15; P < 0.01).Conclusions:These findings indicate that the number of NK cells in peripheral blood may affect the outcome of patients with B-cell non-Hodgkin lymphoma receiving anti-CD20–based immunochemotherapy.

Baseline patient and disease characteristics in FL and DLBCL patients with NKCCs available (analysis population) and in the GALLIUM and GOYA ITT populations.

Association between baseline peripheral blood NKCC and tumor NK cell gene expression in FL (A) and DLBCL (B)

Tables S1-S4

Glofitamab, a novel CD20xCD3, T-cell–engaging bispecific antibody, exhibited single-agent activity in Study NP30179, a first-in-human, phase 1 trial in relapsed/refractory B-cell non-Hodgkin lymphoma. Preclinical studies showed that glofitamab leads to T-cell activation, proliferation, and tumor cell killing upon binding to CD20 on malignant cells. Here, we provide evidence of glofitamab’s clinical activity, including pharmacodynamic profile, mode of action, and factors associated with clinical response, by evaluating biomarkers in patient samples from the dose-escalation part of this trial. Patients enrolled in Study NP30179 received single-dose obinutuzumab pretreatment (1000 mg) 7 days before IV glofitamab (5 µg-25 mg). Glofitamab treatment lasted ≤12 cycles once every 2 or 3 weeks. Blood samples were collected at predefined time points per the clinical protocol; T-cell populations were evaluated centrally by flow cytometry, and cytokine profiles were analyzed. Immunohistochemical and genomic biomarker analyses were performed on tumor biopsy samples. Pharmacodynamic modulation was observed with glofitamab treatment, including dose-dependent induction of cytokines, and T-cell margination, proliferation, and activation in peripheral blood. Gene expression analysis of pretreatment tumor biopsy samples indicated that tumor cell intrinsic factors such as TP53 signaling are associated with resistance to glofitamab, but they may also be interlinked with a diminished effector T-cell profile in resistant tumors and thus represent a poor prognostic factor per se. This integrative biomarker data analysis provides clinical evidence regarding glofitamab’s mode of action, supports optimal biological dose selection, and will further guide clinical development. This trial was registered at www.clinicaltrials.gov as #NCT03075696.

Fc γ receptor IIB (FcγRIIB) is an inhibitory molecule capable of reducing antibody immunotherapy efficacy. We hypothesized its expression could confer resistance in patients with diffuse large B-cell lymphoma (DLBCL) treated with anti-CD20 monoclonal antibody (mAb) chemoimmunotherapy, with outcomes varying depending on mAb (rituximab [R]/obinutuzumab [G]) because of different mechanisms of action. We evaluated correlates between FCGR2B messenger RNA and/or FcγRIIB protein expression and outcomes in 3 de novo DLBCL discovery cohorts treated with R plus cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP) reported by Arthur, Schmitz, and Reddy, and R-CHOP/G-CHOP-treated patients in the GOYA trial (NCT01287741). In the discovery cohorts, higher FCGR2B expression was associated with significantly shorter progression-free survival (PFS; Arthur: hazard ratio [HR], 1.09; 95% confidence interval [CI], 1.01-1.19; P = .0360; Schmitz: HR, 1.13; 95% CI, 1.02-1.26; P = .0243). Similar results were observed in GOYA with R-CHOP (HR, 1.26; 95% CI, 1.00-1.58; P = .0455), but not G-CHOP (HR, 0.91; 95% CI, 0.69-1.20; P = .50). A nonsignificant trend that high FCGR2B expression favored G-CHOP over R-CHOP was observed (HR, 0.67; 95% CI, 0.44-1.02; P = .0622); however, low FCGR2B expression favored R-CHOP (HR, 1.58; 95% CI, 1.00-2.50; P = .0503). In Arthur and GOYA, FCGR2B expression was associated with tumor FcγRIIB expression; correlating with shorter PFS for R-CHOP (HR, 2.17; 95% CI, 1.04-4.50; P = .0378), but not G-CHOP (HR, 1.37; 95% CI, 0.66-2.87; P = .3997). This effect was independent of established prognostic biomarkers. High FcγRIIB/FCGR2B expression has prognostic value in R-treated patients with DLBCL and may confer differential responsiveness to R-CHOP/G-CHOP.

Image texture analysis (radiomics) uses radiographic images to quantify characteristics that may identify tumour heterogeneity and associated patient outcomes. Using fluoro-deoxy-glucose positron emission tomography/computed tomography (FDG-PET/CT)-derived data, including quantitative metrics, image texture analysis and other clinical risk factors, we aimed to develop a prognostic model that predicts survival in patients with previously untreated diffuse large B-cell lymphoma (DLBCL) from GOYA (NCT01287741). Image texture features and clinical risk factors were combined into a random forest model and compared with the international prognostic index (IPI) for DLBCL based on progression-free survival (PFS) and overall survival (OS) predictions. Baseline FDG-PET scans were available for 1263 patients, 832 patients of these were cell-of-origin (COO)-evaluable. Patients were stratified by IPI or radiomics features plus clinical risk factors into low-, intermediate- and high-risk groups. The random forest model with COO subgroups identified a clearer high-risk population (45% 2-year PFS [95% confidence interval (CI) 40%-52%]; 65% 2-year OS [95% CI 59%-71%]) than the IPI (58% 2-year PFS [95% CI 50%-67%]; 69% 2-year OS [95% CI 62%-77%]). This study confirms that standard clinical risk factors can be combined with PET-derived image texture features to provide an improved prognostic model predicting survival in untreated DLBCL.

Acute myeloid leukemia (AML) is a heterogeneous disease with variable responses to therapy. Cytogenetic and genomic features are used to classify AML patients into prognostic and treatment groups. However, these molecular characteristics harbor significant patient-to-patient variability and do not fully account for AML heterogeneity. RNA-based classifications have also been applied in AML as an alternative approach, but transcriptomic grouping is strongly associated with AML morphologic lineages. We used a training cohort of newly diagnosed AML patients and conducted unsupervised RNA-based classification after excluding lineage-associated genes. We identified three AML patient groups that have distinct biological pathways associated with outcomes. Enrichment of inflammatory pathways and downregulation of HOX pathways were associated with improved outcomes, and this was validated in 2 independent cohorts. We also identified a group of AML patients who harbored high metabolic and mTOR pathway activity, and this was associated with worse clinical outcomes. Using a comprehensive reverse phase protein array, we identified higher mTOR protein expression in the highly metabolic group. We also identified a positive correlation between degree of resistance to venetoclax and mTOR activation in myeloid and lymphoid cell lines. Our approach of integrating RNA, protein, and genomic data uncovered lineage-independent AML patient groups that share biologic mechanisms and can inform outcomes independent of commonly used clinical and demographic variables; these groups could be used to guide therapeutic strategies.

The aim of the present study was to determine cell of origin (COO) from a platform using a DNA-based method, COO DNA classifier (COODC). A targeted exome-sequencing platform that applies the mutational profile of a sample was used to classify COO subtype. Two major mutational signatures associated with COO were identified: Catalogue of Somatic Mutations in Cancer (COSMIC) signature 23 enriched in activated B cell (ABC) and COSMIC signature 3, which suggested increased frequency in germinal center B cell (GCB). Differential mutation signatures linked oncogenesis to mutational processes during B-cell activation, confirming the putative origin of GCB and ABC subtypes. Integrating COO with comprehensive genomic profiling enabled identification of features associated with COO and demonstrated the feasibility of determining COO without RNA.Lay abstract To determine subtypes of diffuse large B-cell lymphoma (DLBCL), a cancer with poor survival, we aimed to identify DLBCL subtypes using DNA mutation-based tools. A targeted gene-sequencing platform, which measures the number and types of DNA mutations in a sample, was used to categorize DLBCL subtypes. Two major patterns of mutations associated with subtypes were identified: Catalogue of Somatic Mutations in Cancer (COSMIC) signature 23 and COSMIC signature 3. Differences in how the subtypes developed suggest a link between tumor developments and B cells being activated normally, confirming where the DLBCL subtypes came from. Combining this information with comprehensive genomic profiling, which determines all of the genes that a person has, allowed identification of features that are associated with DLBCL subtypes and showed that a DLBCL subtype can be determined without using RNA.

7526 Background: Mosunetuzumab (M) is a bispecific antibody targeting CD20 and CD3 that redirects T cells to engage and eliminate malignant B cells being developed for relapsed or refractory (R/R) B-cell non-Hodgkin lymphomas (B-NHL). CD20 is an optimal target, with uniform expression across B-NHL histologies and minimal receptor turnover. We characterized CD20 loss as a potential mechanism of resistance to M in patients (pts) on a Phase I/II trial (NCT02500407) receiving M monotherapy for the treatment (tx) of R/R B-NHL. Methods: Pts with R/R B-NHL received M intravenously in 3-week cycles, for eight to 17 cycles depending on tumor response. At baseline (BL), biomarker-evaluable (archival or fresh) biopsies were collected from 293 pts. Biopsies from 62 pts were collected at additional time points during tx with M and/or at disease progression (PD). The proportion of CD20+ and PAX5+ tumor cells was determined by immunohistochemistry (IHC) using dual-staining with anti-CD20 (clone L26, VENTANA) and anti-PAX5 (clone DAK-PAX5, DAKO) antibodies. Expression of MS4A1, the gene encoding CD20 , was measured by RNA-sequencing (RNA-seq); MS4A1 mutation profiling was performed by whole exome sequencing (WES). Levels of CD20 expression were assessed relative to response rates. Correlative analyses were performed and assessed centrally (IHC, RNA-seq, and WES) and locally (IHC). Results: CD20 levels were consistently high ( > 75% CD20+PAX5+ cells) in the majority of BL biopsies and generally comparable across histologies (FL, DLBCL, tFL, MCL, and RT). BL CD20 loss (≤5% CD20+PAX5+ cells) was seen in 16/293 pts (5.5%), more commonly in aggressive NHL, and responses to M were not seen in these pts. Among 62 pts with BL and on-tx/at-PD biopsies, BL CD20 levels were ≤5% in 7/62 pts (11%) (6/7 pts [86%] progressed before completing Cycle 2). CD20 levels were maintained in on-tx biopsies from 23/24 pts (96%). At PD, biopsies showed CD20 loss in 7/26 pts (27%). For five pts with BL, on-tx and at-PD biopsies, all pts maintained CD20 while on-tx and 1/5 pts (20%) had CD20 loss at PD. There was no clear association between CD20 reduction and histology. Data from 185 BL biopsies showed generally concordant levels of CD20 gene and protein expression (r = 0.72). In 10/185 pts (5%), MS4A1 was expressed without detectable CD20 protein expression; DNA sequencing revealed novel mutations in MS4A1, including mutations leading to truncation of the protein. CD20 transmembrane and extra-cellular domain mutations were also observed but do not block CD20 expression. Conclusions: In pts with R/R B-NHL treated with M, low BL CD20 expression is associated with lack of response to M. During M tx, loss of tumor cell expression of CD20 is one mechanism of acquired resistance; however, CD20 expression is maintained in most pts with PD, implying alternative mechanisms for acquired M resistance. Clinical trial information: NCT02500407.

Diffuse large B-cell lymphoma represents a biologically and clinically heterogeneous diagnostic category with well-defined cell-of-origin subtypes. Using data from the GOYA study (NCT01287741), we characterized the mutational profile of diffuse large B-cell lymphoma and evaluated the prognostic impact of somatic mutations in relation to cell-of-origin. Targeted DNA next-generation sequencing was performed in 499 formalin-fixed paraffin-embedded tissue biopsies from previously untreated patients. Prevalence of genetic alterations/mutations was examined. Multivariate Cox regression was used to evaluate the prognostic effect of individual genomic alterations. Of 465 genes analyzed, 59 were identified with mutations occurring in at least 10 of 499 patients (≥2% prevalence); 334 additional genes had mutations occurring in ≥1 patient. Single nucleotide variants were the most common mutation type. On multivariate analysis, BCL2 alterations were most strongly associated with shorter progression-free survival (multivariate hazard ratio: 2.6; 95% confidence interval: 1.6 to 4.2). BCL2 alterations were detected in 102 of 499 patients; 92 had BCL2 translocations, 90% of whom had germinal center B-cell-like diffuse large B-cell lymphoma. BCL2 alterations were also significantly correlated with BCL2 gene and protein expression levels. Validation of published mutational subsets revealed consistent patterns of co-occurrence, but no consistent prognostic differences between subsets. Our data confirm the molecular heterogeneity of diffuse large B-cell lymphoma, with potential treatment targets occurring in distinct cell-of-origin subtypes. clinicaltrials.gov identifier: NCT01287741.

Patients with advanced‐stage follicular lymphoma (FL) who progress early after receiving first‐line therapy have poor overall survival (OS). Currently applied clinical prognostic models such as FL International Prognostic Index [FLIPI], FLIPI‐2 and PRIMA‐Prognostic Index [PRIMA‐PI] have suboptimal sensitivity and specificity to predict this poor prognosis subgroup. The primary objective was to develop a novel prognostic model, the FL Evaluation Index (FLEX) score, to identify high‐risk patients and compare its performance with FLIPI, FLIPI‐2 and PRIMA‐PI. Progression‐free survival (PFS) after first‐line immunochemotherapy was the key endpoint, while OS and progression of disease within 24 months (POD24) were also assessed. The model, which includes nine clinical variables, was developed using a cohort of patients with previously untreated advanced‐stage FL from the phase 3 GALLIUM trial ({"type":"clinical-trial","attrs":{"text":"NCT01332968","term_id":"NCT01332968"}}NCT01332968). The performance of the model was validated using data from the SABRINA trial ({"type":"clinical-trial","attrs":{"text":"NCT01200758","term_id":"NCT01200758"}}NCT01200758). In GALLIUM (n = 1004; 127 with and 877 without POD24), FLEX increased the intergroup (low‐risk/high‐risk) difference in 2‐year and 3‐year PFS rates and demonstrated superior intergroup differences in 2‐year and 3‐year OS rates compared with FLIPI, FLIPI‐2 and PRIMA‐PI. Sensitivity for a high‐risk score to predict POD24 was 60% using FLEX compared with 53% for FLIPI and FLIPI‐2, and 69% for PRIMA‐PI, while specificity was 68% for FLEX compared with 58% for FLIPI, 59% for FLIPI‐2 and 48% for PRIMA‐PI. The prognostic value of FLEX in SABRINA was similar to FLIPI. Therefore, FLEX appears to perform better than existing prognostic models in previously untreated FL, in particular for the newer treatment regimens.

Systemic lupus erythematosus (SLE) is a complex autoimmune disease that follows an unpredictable disease course and affects multiple organs and tissues. We performed an integrated, multicohort analysis of 7,471 transcriptomic profiles from 40 independent studies to identify robust gene expression changes associated with SLE. We identified a 93-gene signature (SLE MetaSignature) that is differentially expressed in the blood of patients with SLE compared with healthy volunteers; distinguishes SLE from other autoimmune, inflammatory, and infectious diseases; and persists across diverse tissues and cell types. The SLE MetaSignature correlated significantly with disease activity and other clinical measures of inflammation. We prospectively validated the SLE MetaSignature in an independent cohort of pediatric patients with SLE using a microfluidic quantitative PCR (qPCR) array. We found that 14 of the 93 genes in the SLE MetaSignature were independent of IFN-induced and neutrophil-related transcriptional profiles that have previously been associated with SLE. Pathway analysis revealed dysregulation associated with nucleic acid biosynthesis and immunometabolism in SLE. We further refined a neutropoiesis signature and identified underappreciated transcripts related to immune cells and oxidative stress. In our multicohort, transcriptomic analysis has uncovered underappreciated genes and pathways associated with SLE pathogenesis, with the potential to advance clinical diagnosis, biomarker development, and targeted therapeutics for SLE.

Background Rituximab (R) plus cyclophosphamide, doxorubicin, vincristine, and prednisone (CHOP) is the current standard therapy for diffuse large B cell lymphoma (DLBCL). Obinutuzumab (G), a glycoengineered, type II anti-CD20 monoclonal antibody, has shown activity and an acceptable safety profile when combined with CHOP (G-CHOP) in patients with advanced DLBCL. We present the final analysis results of the Phase III GOYA study (NCT01287741), which compared the efficacy and safety of G-CHOP versus R-CHOP in patients with previously untreated DLBCL. Methods Patients aged ≥ 18 years with previously untreated advanced DLBCL were randomly assigned to receive eight 21-day cycles of R or G, plus six or eight cycles of CHOP. The primary endpoint was investigator-assessed progression-free survival (PFS). Secondary endpoints included overall survival, other time-to-event endpoints, and safety; investigator-assessed PFS by cell of origin subgroup was an exploratory endpoint. Results A total of 1418 patients were randomized, with 1414 included in this final analysis (G-CHOP, N = 704; R-CHOP, N = 710). Five-year PFS rates were 63.8% and 62.6% for G-CHOP and R-CHOP, respectively (stratified hazard ratio 0.94, 95% CI 0.78–1.12; p = 0.48). The results of the secondary efficacy endpoints did not show a benefit of G-CHOP over R-CHOP. In the exploratory analysis, a trend towards benefit with G-CHOP over R-CHOP was apparent in the patients with germinal center B cell DLBCL. The safety profile of G-CHOP was as expected, and no new safety signals were observed. More grade 3–5 (75.1% vs 65.8%), serious (44.4% vs 38.4%), and fatal (6.1% vs 4.4%) adverse events (AEs) were observed in the G-CHOP arm compared with the R-CHOP arm, respectively, with the most common fatal AEs being infections. A higher incidence of late-onset neutropenia occurred in the G-CHOP arm (8.7%) versus the R-CHOP arm (4.9%). Conclusions The final analysis, similar to the primary analysis, did not show a PFS benefit of G-CHOP over R-CHOP in previously untreated patients with DLBCL. The results of the secondary endpoints were consistent with the primary endpoint. Further exploratory analyses and investigation of biomarkers are ongoing.

Background: Chemotherapy combined with anti-CD20 antibodies is the current standard treatment for patients with symptomatic advanced stage follicular lymphoma (FL). We have previously shown that the EZH2 gene mutation status was predictive of differential efficacy of the chemotherapy backbone within the GALLIUM trial. Specifically, EZH2 mutations, found in 22% of cases (93/418), were associated with longer progression-free survival (PFS) in patients who received CHOP/CVP regimens (with either Rituximab (R) or Obinutuzumab (G)), but were not predictive in patients who received Bendamustine-based regimens (Jurinovic, ASH 2019). In an earlier study, we defined a gene expression profile (GEP) signature which was significantly associated with EZH2 gene mutation status (Pastore, Lancet Oncol 2015). Here, we wanted to explore the predictive utility of this EZH2 GEP signature within the GALLIUM trial. Methods: GALLIUM (NCT01332968) enrolled 1202 patients with FL randomized to either receive R- or G-based therapy (Marcus, NEJM 2017). The chemotherapy consisted either of CHOP, CVP or Bendamustine according to a center-level decision. Inclusion criteria comprised previously untreated FL, advanced stage or stage II with bulky disease, and ECOG performance status 0-2. All patients required treatment according to the GELF criteria. Here, we analyzed all 134 cases with available DNA and transcriptome sequencing data. Results: Of the 129 genes from the original EZH2 GEP signature, 96 (74%) were evaluable in our transcriptome data. We used the unsupervised k-means algorithm to identify 2 GEP clusters, EZH2_mut and EZH2_WT, comprising 67 patients each (Fig A). Patients in the EZH2_mut cluster had significantly longer PFS with CHOP/CVP-based regimens (HR = 4.99, P = 0.002), while the EZH2 GEP signature was not predictive in patients receiving Bendamustine-based treatment (Fig B). As expected, EZH2 mutations were significantly enriched in the EZH2_mut cluster (30% vs 13%; P = 0.034). Of note, 47 cases in the EZH2_mut cluster had no detectable EZH2 mutation. We wanted to test, whether the predictive utility of the EZH2 GEP signature was maintained in cases without EZH2 mutations. Indeed, patients without EZH2 mutations grouped into the EZH2_mut cluster also had longer PFS with CHOP/CVP-based regimens (HR = 4.74, P = 0.007), whereas the ones grouped into the EZH2_WT cluster had longer PFS with Bendamustine-based regimens (HR = 0.36, P = 0. 03) (Fig. C). To explore the genetic determinants of the EZH2 GEP signature in cases without EZH2 mutations, we analyzed the available DNA sequencing data, considering recurrent non-silent gene mutations and copy-number alterations (CNA) with frequencies of 10% in either cluster. As expected, gain of chromosome 7 (chr7), which contains the EZH2 gene, was enriched in the EZH2_mut cluster (21% vs 7%, P = 0.04). Cases with chr7 gain had significantly increased EZH2 mRNA expression levels as compared to cases without EZH2 CNA or mutations (P < 0.0001). Furthermore, univariate analysis revealed enrichment of mutations in TNFRSF14 (49% vs 24%), BCL7A (28% vs 8%), GNA13 (15 vs 7%), SOCS1(19 vs 8%), and HVCN1 (13 vs 7%) in the EZH2_mut cluster, but none of these associations were significant after correction for multiple testing. Finally, we wanted to better delineate the transcriptional phenotype of the EZH2 GEP signature in cases that lack EZH2 mutations. GSEA analysis revealed that the EZH2_mut cluster was strongly enriched for the hallmark signatures mTORC1 signaling, MYC and E2F target genes. Furthermore, we used CIBERSORT to estimate the immune cell composition of the tumor microenvironment (TME). The TME compositions of FL in the EZH2_mut cluster lacking EZH2 mutations more closely resembled FL with EZH2 mutations, most notably for higher T follicular helper (TFH) cell (P = 0.003) and macrophage M0 scores (P < 0.001) as compared to FL in the EZH2_WT cluster lacking EZH2 mutations. In conclusion we show that an EZH2 GEP signature is (i) significantly associated with EZH2 gene mutation status, (ii) also observed in a subset (47/105, 45%) of cases that lack EZH2 mutations but harbor other genetic alterations (including chr7 gain/EZH2 overexpression), (iii) associated with a distinct TME composition enriched for TFH cells and M0 macrophages, and (iv) predictive of differential efficacy of chemotherapy-backbones in combination with Rituximab or Obinutuzumab. Figure 1 Figure 1. Disclosures Bolen: F. Hoffmann-La Roche: Current equity holder in publicly-traded company; Genentech: Current Employment. Knapp: F. Hoffmann-La Roche Ltd: Current Employment. Bottos: F. Hoffmann-La Roche Ltd: Current Employment, Current equity holder in publicly-traded company. Richter: HTG Molecular Diagnostics, Inc.: Current Employment, Research Funding. Fitzgibbon: Epizyme: Research Funding. Klapper: Takeda: Consultancy, Research Funding; Amgen: Research Funding; Regeneron: Consultancy, Research Funding; Roche: Consultancy, Research Funding. Davies: Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: travel to scientific conferences, Research Funding; Roche: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: travel to scientific conferences, Research Funding; Kite: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Honoraria, Research Funding; Karyopharm Therapeutics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Acerta Pharma/AstraZeneca: Honoraria, Research Funding; ADC Therapeutics: Honoraria, Research Funding; BioInvent: Research Funding; Incyte: Membership on an entity's Board of Directors or advisory committees. von Bergwelt: MSD Sharpe & Dohme: Honoraria, Research Funding, Speakers Bureau; Mologen: Honoraria, Research Funding, Speakers Bureau; Kite/Gilead: Honoraria, Research Funding, Speakers Bureau; Astellas: Honoraria, Research Funding, Speakers Bureau; BMS: Honoraria, Research Funding, Speakers Bureau; Roche: Honoraria, Research Funding, Speakers Bureau; Novartis: Honoraria, Research Funding, Speakers Bureau; Miltenyi: Honoraria, Research Funding, Speakers Bureau. Nielsen: F. Hoffmann-La Roche Ltd: Current Employment, Current equity holder in publicly-traded company. Dreyling: Bayer HealthCare Pharmaceuticals: Consultancy, Research Funding, Speakers Bureau; Celgene: Consultancy, Research Funding, Speakers Bureau; Astra Zeneca: Consultancy, Speakers Bureau; BeiGene: Consultancy; Novartis: Consultancy, Speakers Bureau; Genmab: Consultancy; Amgen: Speakers Bureau; Gilead/Kite: Consultancy, Research Funding, Speakers Bureau; Incyte: Consultancy, Speakers Bureau; Janssen: Consultancy, Research Funding, Speakers Bureau; Roche: Consultancy, Research Funding, Speakers Bureau; Abbvie: Research Funding. Hiddemann: Janssen: Research Funding; F. Hoffmann-La Roche: Membership on an entity's Board of Directors or advisory committees, Research Funding. Unterhalt: Roche: Research Funding. Weigert: Janssen: Speakers Bureau; Epizyme: Membership on an entity's Board of Directors or advisory committees; Roche: Research Funding.

Introduction: AML is a heterogeneous disease with a wide array of common genetic aberrations. Traditional classification of AML leverages both classical cytogenetics and mutational profiling to stratify patients into four distinct risk groups (ELN). However, tumor gene expression profiles can play an important role in response to therapy, and are potentially useful for unravelling the heterogeneity of AML. In this study, we hypothesized that clinical outcomes and variable responses to therapeutic modalities in AML may be driven by patterns of gene expression, and sought to identify clinically actionable molecular subtypes using the available RNAseq data from the BEAT AML functional genomics study. Methods: Unsupervised machine learning approach based on consensus non-negative matrix factorization (cNMF) was applied to VOOM normalized BEAT-AML RNAseq data from patient samples with ≥50% blasts (N=389) to identify transcriptomic-based molecular subtypes. The subtypes were then compared to the genomic based subtypes for their association with clinical outcome (log-rank test) and ex-vivo drug sensitivity (Kruskal Wallis test). Subtypes were also biologically characterized by gene signature scoring using well curated pathway signatures (GSVA analysis using Hallmark pathways), cell type enrichment (xCell enrichment) and AML differentiation state (scRNAseq signature based on Van Galen et. al). Finally, a random forest classifier was defined based on samples from BEAT AML to predict the NMF subtypes in an independent data set (TCGA AML cohort). Results: Our cNMF based analysis identified six clusters of patients based on the 5,060 (top 10%) most variable genes. These novel subtypes were strongly prognostic (Figure 1A, log rank p=2.79e-08), and were independent of ELN genomic based subtypes (anova p=4.45e-07). Comparison to other genomic based classification is ongoing. The prognostic value of the transcriptomic subtypes was further validated by predicting the subtypes in an independent cohort (TCGA LAML, N=200). We observed a significant association with outcome (Figure 1B, p=0.00013), with clusters 5 and 1 showing markedly better prognosis, similar to BEATAML. These subtypes also displayed unique biological profiles, including significant association with scRNAseq-derived AML differentiation state cell types, Hallmark pathways and cellularity signatures. Notably, clusters 1 and 3 showed a mature phenotype, while clusters 2, 4, and 5 were more progenitor-like (table 1). Importantly, the transcriptomic subtypes were highly predictive of ex-vivo drug sensitivity, with sensitivity to 70 compounds significantly associated with cNMF subtype (Kruskal Wallis p>0.01), compared with 4 in the ELN subtypes.Of the tested molecules, single agent Venetoclax was the most strongly associated with subtype (p=1.7e-13); two subtypes were strongly resistant (median IC50 of 10uM) and four were sensitive, with IC50s in the sub-micromolar range (Table 1). No association was seen between the ELN subtypes and venetoclax sensitivity (p=.35). Conclusions: Unsupervised machine learning-based clustering analysis of transcriptomic data identified six novel subtypes which are similarly prognostic as the ELN genomic based subtype and provide a novel avenue for identifying clinically actionable subsets of AML. Figure 1 Figure 1. Disclosures Hamidi: Genentech: Current Employment, Current equity holder in publicly-traded company. Bolen: Genentech: Current Employment; F. Hoffmann-La Roche: Current equity holder in publicly-traded company. Lasater: Genentech: Current Employment, Current equity holder in publicly-traded company. Dunshee: Genentech/Roche: Current Employment, Current equity holder in publicly-traded company. Punnoose: Genentech: Current Employment, Current equity holder in publicly-traded company. Dail: Genentech/Roche: Current Employment, Current equity holder in publicly-traded company.

Systemic Lupus Erythematosus (SLE) is a heterogeneous autoimmune disease with heightened disease severity in children. The incomplete understanding of the precise cellular and molecular events that drive disease activity pose a significant hurdle to the development of targeted therapeutic agents. Here, we performed single-cell phenotypic and functional characterization of pediatric SLE patients and healthy controls blood via mass cytometry. We identified a distinct CD14hi monocyte cytokine signature, with increased levels of monocyte chemoattractant protein-1 (MCP1), macrophage inflammatory protein-1β (Mip1β), and interleukin-1 receptor antagonist (IL-1RA). This signature was shared by every clinically heterogeneous patient, and reproduced in healthy donors' blood upon ex-vivo exposure to plasma from clinically active patients only. This SLE-plasma induced signature was abrogated by JAK1/JAK2 selective inhibition. This study demonstrates the utility of mass cytometry to evaluate immune dysregulation in pediatric autoimmunity, by identification of a multi-parametric immune signature that can be further dissected to delineate the events that drive disease pathogenesis.

The canonical Wnt/β-catenin signalling pathway governs diverse developmental, homeostatic and pathological processes. Palmitoylated Wnt ligands engage cell-surface frizzled (FZD) receptors and LRP5 and LRP6 co-receptors, enabling β-catenin nuclear translocation and TCF/LEF-dependent gene transactivation. Mutations in Wnt downstream signalling components have revealed diverse functions thought to be carried out by Wnt ligands themselves. However, redundancy between the 19 mammalian Wnt proteins and 10 FZD receptors and Wnt hydrophobicity have made it difficult to attribute these functions directly to Wnt ligands. For example, individual mutations in Wnt ligands have not revealed homeostatic phenotypes in the intestinal epithelium-an archetypal canonical, Wnt pathway-dependent, rapidly self-renewing tissue, the regeneration of which is fueled by proliferative crypt Lgr5+ intestinal stem cells (ISCs). R-spondin ligands (RSPO1-RSPO4) engage distinct LGR4-LGR6, RNF43 and ZNRF3 receptor classes, markedly potentiate canonical Wnt/β-catenin signalling, and induce intestinal organoid growth in vitro and Lgr5+ ISCs in vivo. However, the interchangeability, functional cooperation and relative contributions of Wnt versus RSPO ligands to in vivo canonical Wnt signalling and ISC biology remain unknown. Here we identify the functional roles of Wnt and RSPO ligands in the intestinal crypt stem-cell niche. We show that the default fate of Lgr5+ ISCs is to differentiate, unless both RSPO and Wnt ligands are present. However, gain-of-function studies using RSPO ligands and a new non-lipidated Wnt analogue reveal that these ligands have qualitatively distinct, non-interchangeable roles in ISCs. Wnt proteins are unable to induce Lgr5+ ISC self-renewal, but instead confer a basal competency by maintaining RSPO receptor expression that enables RSPO ligands to actively drive and specify the extent of stem-cell expansion. This functionally non-equivalent yet cooperative interaction between Wnt and RSPO ligands establishes a molecular precedent for regulation of mammalian stem cells by distinct priming and self-renewal factors, with broad implications for precise control of tissue regeneration.

Despite clear differences in immune system responses and in the prevalence of autoimmune diseases between males and females, there is little understanding of the processes involved. In this study, we identified a gene signature of immature-like neutrophils, characterized by the overexpression of genes encoding for several granule-containing proteins, which was found at higher levels (up to 3-fold) in young (20–30 y old) but not older (60 to >89 y old) males compared with females. Functional and phenotypic characterization of peripheral blood neutrophils revealed more mature and responsive neutrophils in young females, which also exhibited an elevated capacity in neutrophil extracellular trap formation at baseline and upon microbial or sterile autoimmune stimuli. The expression levels of the immature-like neutrophil signature increased linearly with pregnancy, an immune state of increased susceptibility to certain infections. Using mass cytometry, we also find increased frequencies of immature forms of neutrophils in the blood of women during late pregnancy. Thus, our findings show novel sex differences in innate immunity and identify a common neutrophil signature in males and in pregnant women.

Systemic lupus erythematosus (SLE) is a complex autoimmune disease that follows an unpredictable disease course and affects multiple organs and tissues. We performed an integrated, multi-cohort analysis of 7,471 transcriptomic profiles from 40 independent studies to identify robust gene expression changes associated with SLE. We identified a 93-gene signature (SLE MetaSignature) that is differentially expressed in the blood of SLE patients compared to healthy volunteers; distinguishes SLE from other autoimmune, inflammatory, and infectious diseases; and persists across diverse tissues and cell types. The SLE MetaSignature correlated significantly with disease activity and other clinical measures of inflammation. We prospectively validated the SLE MetaSignature in an independent cohort of pediatric SLE patients using a microfluidic RT-qPCR array. We found that 14 of the 93 genes in the SLE MetaSignature were independent of interferon-induced and neutrophil-related transcriptional profiles that have previously been associated with SLE. Pathway analysis revealed dysregulation associated with nucleic acid biosynthesis and immunometabolism in SLE. We further refined a neutropoeisis signature and identified under-appreciated transcripts related to immune cells and oxidative stress. Our multi-cohort, transcriptomic analysis has uncovered under-appreciated genes and pathways associated with SLE pathogenesis, with the potential to advance clinical diagnosis, biomarker development, and targeted therapeutics for SLE.

Dimensionality reduction using the t-Distributed Stochastic Neighbor Embedding (t-SNE) algorithm has emerged as a popular tool for visualizing high-parameter single-cell data. While this approach has obvious potential for data visualization it remains unclear how t-SNE analysis compares to conventional manual hand-gating in stratifying and quantitating the frequency of diverse immune cell populations. We applied a comprehensive 38-parameter mass cytometry panel to human blood and compared the frequencies of 28 immune cell subsets using both conventional bivariate and t-SNE-guided manual gating. t-SNE analysis was capable of stratifying every general cellular lineage and most sub-lineages with high correlation between conventional and t-SNE-guided cell frequency calculations. However, specific immune cell subsets delineated by the manual gating of continuous variables were not fully separated in t-SNE space thus causing discrepancies in subset identification and quantification between these analytical approaches. Overall, these studies highlight the consistency between t-SNE and conventional hand-gating in stratifying general immune cell lineages while demonstrating that particular cell subsets defined by conventional manual gating may be intermingled in t-SNE space.

Small sample sizes combined with high person-to-person variability can make it difficult to detect significant gene expression changes from transcriptional profiling studies. Subtle, but coordinated, gene expression changes may be detected using gene set analysis approaches. Meta-analysis is another approach to increase the power to detect biologically relevant changes by integrating information from multiple studies. Here, we present a framework that combines both approaches and allows for meta-analysis of gene sets. QuSAGE meta-analysis extends our previously published QuSAGE framework, which offers several advantages for gene set analysis, including fully accounting for gene-gene correlations and quantifying gene set activity as a full probability density function. Application of QuSAGE meta-analysis to influenza vaccination response shows it can detect significant activity that is not apparent in individual studies.

Central nervous system (CNS) relapse carries a poor prognosis in diffuse large B-cell lymphoma (DLBCL). Integrating biomarkers into the CNS–International Prognostic Index (CNS-IPI) risk model may improve identification of patients at high risk for developing secondary CNS disease. CNS relapse was analyzed in 1418 DLBCL patients treated with obinutuzumab or rituximab plus cyclophosphamide, doxorubicin, vincristine, prednisone chemotherapy in the phase 3 GOYA study. Cell of origin (COO) was assessed using gene-expression profiling. BCL2 and MYC protein expression was analyzed by immunohistochemistry. The impact of CNS-IPI, COO, and BCL2/MYC dual-expression status on CNS relapse was assessed using a multivariate Cox regression model (data available in n = 1418, n = 933, and n = 688, respectively). High CNS-IPI score (hazard ratio [HR], 4.0; 95% confidence interval [CI], 1.3-12.3; P = .02) and activated B-cell‒like (ABC) (HR, 5.2; 95% CI, 2.1-12.9; P = .0004) or unclassified COO subtypes (HR, 4.2; 95% CI, 1.5-11.7; P = .006) were independently associated with CNS relapse. BCL2/MYC dual-expression status did not impact CNS relapse risk. Three risk subgroups were identified based on the presence of high CNS-IPI score and/or ABC/unclassified COO (CNS-IPI-C model): low risk (no risk factors, n = 450 [48.2%]), intermediate risk (1 factor, n = 408 [43.7%]), and high risk (both factors, n = 75 [8.0%]). Two-year CNS relapse rates were 0.5%, 4.4%, and 15.2% in the respective risk subgroups. Combining high CNS-IPI and ABC/unclassified COO improved CNS relapse prediction and identified a patient subgroup at high risk for developing CNS relapse. The study was registered at www.clinicaltrials.gov as #{"type":"clinical-trial","attrs":{"text":"NCT01287741","term_id":"NCT01287741"}}NCT01287741.

Purpose: Atezolizumab [anti–programmed death-ligand 1 (PD-L1)] selectively targets PD-L1 to block its interaction with receptors programmed death 1 and B7.1, thereby reinvigorating antitumor T-cell activity. We evaluated the long-term safety and activity of atezolizumab, along with biological correlates of clinical activity endpoints, in a cohort of patients with melanoma in an ongoing phase Ia study (NCT01375842). Patients and Methods: Patients with unresectable or metastatic melanoma were enrolled to receive atezolizumab 0.1 to 20 mg/kg or ≥10 mg/kg every 3 weeks. Primary study objectives were safety and tolerability. Secondary objectives included investigator-assessed efficacy measures; pharmacodynamic and predictive biomarkers of antitumor activity were explored. Results: Forty-five patients were enrolled and were evaluable for safety. Most treatment-related adverse events (AE) were grade 1/2 (60%). Fatigue (44%), pruritus (20%), pyrexia (18%), and rash (18%) were the most common treatment-related AEs of any grade. No treatment-related deaths occurred. Overall response rate was 30% among 43 efficacy- evaluable patients, with a median duration of response of 62 months [95% CI, 35–not estimable (NE)]. Clinically meaningful long-term survival was observed, with a median overall survival of 23 months (95% CI, 9–66). Baseline biomarkers of tumor immunity [PD-L1 expression on immune cells, T effector (Teff), and antigen presentation gene signatures) and tumor mutational burden (TMB) were associated with improved response, progression-free survival, and overall survival. Conclusions: Atezolizumab was well tolerated, with durable responses and survival in patients with melanoma. PD-L1 expression, TMB, and Teff signatures may indicate improved benefit with atezolizumab in these patients.

Mass cytometry is capable of measuring more than 40 distinct proteins on individual cells making it a promising technology for innovating biomarker discovery. However, in order for this potential to be fully realized, best practices in panel design need to be further defined in order to achieve consistency and reproducibility in data analysis. Of particular importance are controls that reveal, and panel design principles that mitigate the effects of signal interference or overlap. We observed a disparity between the staining profiles of two noncompeting anti- integrin β7 mAbs and hypothesized that signal interference was responsible. A mass-minus-one (MMO) control was applied and demonstrated that signal overlap caused the perceived interclonal discrepancy in β7 expression. Panel redesign in consideration of mass-cytometry specific interference dynamics dramatically improved concordance between both mAbs by redistributing background signals caused by overlap. These studies visualize how signal overlap can complicate mass cytometry data interpretation and demonstrate how the rational distribution of interference can greatly improve panel design and data quality. © 2016 International Society for Advancement of Cytometry.

The adaptive immune system's capability to protect the body requires a highly diverse lymphocyte antigen receptor repertoire. However, the influence of individual genetic and epigenetic differences on these repertoires is not typically measured. By leveraging the unique characteristics of B, CD4+ T and CD8+ T-lymphocyte subsets from monozygotic twins, we quantify the impact of heritable factors on both the V(D)J recombination process and on thymic selection. We show that the resulting biases in both V(D)J usage and N/P addition lengths, which are found in naïve and antigen experienced cells, contribute to significant variation in the CDR3 region. Moreover, we show that the relative usage of V and J gene segments is chromosomally biased, with ∼1.5 times as many rearrangements originating from a single chromosome. These data refine our understanding of the heritable mechanisms affecting the repertoire, and show that biases are evident on a chromosome-wide level., The diversity of antigen receptor specificities is largely generated by random recombination of its segments. Here the authors show, by genetic comparison of monozygotic twin lymphocyte subsets, that individual genetic and epigenetic biases also contribute to the shape of the B and T cell repertoires.

Background: The anti-CD20 monoclonal antibody (mAb), obinutuzumab (G), has shown improved outcomes versus rituximab (R) in indolent lymphomas; however, no improvement was seen in diffuse large B-cell lymphoma (DLBCL), and the molecular basis is unclear. The inhibitory Fc gamma receptor IIB (Fc γRIIB), expressed on lymphoma cells, can impair the effects of direct targeting mAbs, such as R, by binding and internalizing them, reducing opsonization and limiting FcγR-mediated killing. We hypothesized that FcγRIIB expression on cellular effectors and/or the lymphoma confers treatment resistance in some patients (pts) and evaluated if outcomes differ for therapies involving a non-internalized mAb (G). Methods: We evaluated correlates between FCGR2B mRNA and/or FcγRIIB protein expression and pt outcomes in two discovery cohorts of de novo DLBCL treated with R-CHOP (Arthur et al. 2018, n=372; Schmitz et al. 2018, n=234), and the phase III GOYA trial (NCT01287741; n=552), which compared R-CHOP with G-CHOP in pts with previously untreated DLBCL. FCGR2B mRNA expression was assessed by RNA-Seq, and protein expression was assessed in evaluable cohorts by immunohistochemistry, using tissue microarrays with macrophages identified by CD68. FCGR2B expression was also measured by a NanoString assay (Arthur cohort). Cox regression analyzed the impact of FcγRIIB/FCGR2B expression on progression-free survival (PFS), with univariate and multivariate models adjusted for International Prognostic Index (IPI), cell of origin (COO), and BCL2 protein expression. Results: In the discovery cohorts, a higher FCGR2B expression was significantly associated with shorter PFS (Arthur: HR 1.09 [95% CI: 1.01–1.19], P=0.036; Schmitz: HR 1.13 [95% CI: 1.02–1.26], P=0.0243). Expression by NanoString strongly correlated with RNA-Seq, confirming the association with shorter PFS (HR 1.13 [95% CI: 1.04–1.23], P=0.0048). In GOYA, a significant association between PFS and FCGR2B was observed in the R arm (HR 1.26 [95% CI: 1.00–1.58], P=0.0455), with no prognostic effect observed for G (HR 0.91 [95% CI: 0.69–1.20], P=0.5). Pts with high FCGR2B expression appeared to benefit more from G than R (HR 0.67 [95% CI: 0.44–1.02], P=0.0622), in contrast to pts with low FCGR2B expression (HR 1.58 [95% CI: 1.00–2.50], P=0.0503). In both Arthur and GOYA cohorts, FCGR2B expression by RNA-Seq was associated with FcγRIIB on the tumor, which correlated with a shorter PFS for R (HR 2.17 [95% CI: 1.04–4.50], P=0.03), but not G (HR 1.37 [95% CI: 0.66–2.87], P=0.4). This prognostic effect on PFS was independent of established prognostic biomarkers, IPI, COO and BCL2. Conclusion: High FcγRIIB/FCGR2B expression in pts with DLBCL has prognostic value in those treated with R and may confer differential responsiveness to R or G. Citation Format: Laura K. Hilton, Malgorzata Nowicka, Margaret Ashton-Key, Chantal E. Hargreaves, Chern Lee, Russell Foxall, Matthew J. Carter, Stephen A. Beers, Kathleen N. Potter, Christopher R. Bolen, Christian Klein, Andrea Knapp, Farheen Mir, Matthew Rose-Zerilli, Cathy Burton, Wolfram Klapper, David W. Scott, Laurie H. Sehn, Umberto Vitolo, Maurizio Martelli, Marek Trneny, Graham W. Slack, Pedro Farinha, Jonathan C. Strefford, Mikkel Z. Oestergaard, Ryan D. Morin, Mark S. Cragg. Prognostic significance of Fc gamma receptor IIB expression in the response of previously untreated diffuse large B-cell lymphomas to anti-CD20 monoclonal antibodies: Differing impact of rituximab and obinutuzumab [abstract]. In: Proceedings of the AACR Virtual Meeting: Advances in Malignant Lymphoma; 2020 Aug 17-19. Philadelphia (PA): AACR; Blood Cancer Discov 2020;1(3_Suppl):Abstract nr PO-26.

Purpose: Natural killer (NK) cells are key effector cells for anti-CD20 monoclonal antibodies (mAb), such as obinutuzumab and rituximab. We assessed whether low pretreatment NK-cell count (NKCC) in peripheral blood or tumor tissue was associated with worse outcome in patients receiving antibody-based therapy. Patients and Methods: Baseline peripheral blood NKCC was assessed by flow cytometry (CD3−CD56+ and/or CD16+ cells) in 1,064 of 1,202 patients with follicular lymphoma treated with obinutuzumab or rituximab plus chemotherapy in the phase III GALLIUM trial (NCT01332968) and 1,287 of 1,418 patients with diffuse large B-cell lymphoma (DLBCL) treated with obinutuzumab or rituximab plus cyclophosphamide, doxorubicin, vincristine, and prednisone (G-CHOP or R-CHOP) in the phase III GOYA trial (NCT01287741). The prognostic value of tumor NK-cell gene expression, as assessed by whole-transcriptome gene expression using TruSeq RNA sequencing, was also analyzed. The association of baseline variables, such as treatment arm, was evaluated using multivariate Cox regression models using a stepwise approach. Results: In this exploratory analysis, low baseline peripheral blood NKCC was associated with shorter progression-free survival (PFS) in both follicular lymphoma [hazard ratio (HR), 1.48; 95% confidence interval (CI), 1.02–2.14; P = 0.04] and DLBCL (HR, 1.36; 95% CI, 1.01–1.83; P = 0.04), and overall survival in follicular lymphoma (HR, 2.20; 95% CI, 1.26–3.86; P = 0.0058). Low tumor NK-cell gene expression was associated with shorter PFS in G-CHOP–treated patients with DLBCL (HR, 1.95; 95% CI, 1.22–3.15; P < 0.01). Conclusions: These findings indicate that the number of NK cells in peripheral blood may affect the outcome of patients with B-cell non-Hodgkin lymphoma receiving anti-CD20–based immunochemotherapy.

Background The B and T cells of the human adaptive immune system leverage a highly diverse repertoire of antigen-specific receptors to protect the human body from pathogens. The sequencing and analysis of immune repertoires is emerging as an important tool to understand immune responses, whether beneficial or harmful (in the case of autoimmunity). However, methods for studying these repertoires, and for directly comparing different immune repertoires, are lacking. Results In this paper, we present a non-parametric method for directly comparing sequencing repertoires, with the goal of rigorously quantifying differences in V, D, and J gene segment utilization. This method, referred to as the Repertoire Dissimilarity Index (RDI), uses a bootstrapped subsampling approach to account for variance in sequencing depth, and, coupled with a data simulation approach, allows for direct quantification of the average variation between repertoires. We use the RDI method to recapitulate known differences in the formation of the CD4+ and CD8+ T cell repertoires, and further show that antigen-driven activation of naïve CD8+ T cells is more selective than in the CD4+ repertoire, resulting in a more specialized CD8+ memory repertoire. Conclusions We prove that the RDI method is an accurate and versatile method for comparisons of immune repertoires. The RDI method has been implemented as an R package, and is available for download through Bitbucket. Electronic supplementary material The online version of this article (doi:10.1186/s12859-017-1556-5) contains supplementary material, which is available to authorized users.

International audience; Previous immunohistochemical (IHC) studies showed controversial data about the prognostic value of tumor-infiltrating lymphocytes (TILs) in follicular lymphoma (FL). To clarify this issue, a large series of FL samples from rituximab-treated patients enrolled in the randomized PRIMA trial was examined. IHC was quantified using automated image analysis in 417, 287, 418, 406, 379, and 369 patients for CD3, CD4, CD8, PD1, ICOS, and FOXP3, respectively. RNAseq analysis was used to quantify TIL-related mRNA transcripts from 148 patients. When each IHC marker was used as a continuous variable in the whole cohort, high CD3 counts were associated with better progression-free survival (PFS) (P = .025). When an optimal IHC cut point was applied to the whole patient population, high CD3 counts and high PD1 counts were associated with better PFS (P = .011 and P = .044, respectively), whereas none of the other TIL markers had any significant correlation with outcome. When a stringent analysis was performed by dividing the whole cohort into a training set and a validation set, none of the TIL markers showed a prognostic significance in both groups. RNAseq analysis showed a significant correlation between high levels of CD3 and CD8 transcripts and better PFS (P = .001 and P = .037, respectively). No prognostic correlation was found as to the level of other immune gene transcripts. These results suggest that the IHC prognostic value of TILs is circumvented by rituximab treatment, although there is a trend for high numbers of CD3+ TILs to correlate with better PFS.

International audience; BCL2 mutations have been suggested to confer an adverse prognosis to follicular lymphoma (FL) patients, but their prognostic value has not been assessed in patients treated with a rituximab-containing regimen. Here we evaluated the prognostic value of BCL2 mutations in a large prospective cohort of 252 patients with FL treated with immunochemotherapy in the PRIMA randomized trial. Using a DNA-targeted sequencing approach, we detected amino acid altering mutations in 135 patients (54%) and showed that these mutations were probably mediated by the over-activation of AICDA (activation-induced cytidine deaminase) in the context of the t(14;18) translocation. The BCL2 variants identified in PRIMA patients affected the BH1, BH2, and BH3 functional motifs at a lower frequency than the N-terminus and flexible loop domain, with mostly conservative aminoacid changes. With a median follow-up of 6.7 years, we did not observe any impact of BCL2 mutations either on overall survival or progression-free survival.

West Nile virus (WNV) infection is usually asymptomatic but can cause severe neurological disease and death, particularly in older patients, and how individual variations in immunity contribute to disease severity is not yet defined. Animal studies identified a role for several immunity-related genes that determine the severity of infection. We have integrated systems-level transcriptional and functional data sets from stratified cohorts of subjects with a history of WNV infection to define whether these markers can distinguish susceptibility in a human population. Transcriptional profiles combined with immunophenotyping of primary cells identified a predictive signature of susceptibility that was detectable years after acute infection (67% accuracy), with the most prominent alteration being decreased IL1B induction followingex vivoinfection of macrophages with WNV. Deconvolution analysis also determined a significant role for CXCL10 expression in myeloid dendritic cells. This systems analysis identified markers of pathogenic mechanisms and offers insights into potential therapeutic strategies.

The first two authors contributed equally. Introduction: VenR (2 years of Ven, plus R during the first 6 months) improved progression-free/overall survival (PFS/OS) vs bendamustine + R (BR) in patients (pts) in with R/R CLL in MURANO (Seymour et al. N Eng J Med 2018). MURANO also showed early, sustained and durable undetectable minimal residual disease (uMRD) status with VenR, which is associated with prolonged survival in CLL (Kater et al. J Clin Oncol 2019). Here we explore associations between baseline molecular characteristics and VenR-induced MRD responses and PFS based on the 4-year follow-up of MURANO. Methods: DNA specimens from CD19-enriched baseline samples (313/389 enrolled pts) were analyzed with whole-exome sequencing (WES). Genetic complexity (GC) was assessed by array comparative-genomic hybridization. Gene expression data were generated by RNA sequencing from matched RNA samples (209 pts). Univariate analysis determined the impact of gene mutations, GC, and BCL-2 (family) expression on MRD and PFS at end of combination therapy (EOCT) and end of treatment (EOT). MRD (peripheral blood only) was categorized as uMRD Results: Mutation frequencies/GC status at baseline were equally distributed between arms. All 313 pts had CLL cells with non-silent, deleterious mutations by WES (mean 47/pt; 0.97±0.3 mutations/megabase). Of 44 frequently mutated genes, 202/313 (65%) pts had ≥1 frequent mutation; 69/313 (22%) pts had ≥2. Frequencies (%) of deleterious mutations were TP53 21.7, ATM 18.8, NOTCH1 17.9, SF3B1 12.5, XPO1 9.9, BIRC3/POT1/BRAF/EGR2 5.1-5.4, rest WES data: BIRC3 mut and BRAF mut tended to be enriched in pts with detectable MRD at EOCT (% MRD+ in mutation vs wild type: 62.5% vs 23.7% [p=0.146] and 55.6% vs 21.4% [p=0.027] respectively) (Table 1). At EOT, NOTCH1 mut and TP53 mut were negatively associated with uMRD (35.3% vs 63.5% [p=0.10]; 41.7% vs 63.9% [p=0.028]) (Table 1). These observations were concordant with observed PFS outcomes (Figure 1). Array data: Negative effects on MRD status were seen in pts with either del17p at EOCT (p=0.055) and at EOT (p=0.054) or del13q14bi at EOCT (p=0.018) (Table 1). Trends were seen for gain 2p, loss 18p/4q/trisomy 12 at EOCT and gain 2p/8q, loss 14q/18p/4q and trisomy 12 at EOT. High MRD+ at EOT was also associated with low and high GC vs non-complex GC (p=0.042) (Figure 2). PFS was shorter in high but not low GC pts at 36-mo follow-up (HR 3.2, p=0.0055; HR 1.1, p=0.77). Conversely, after 4-years follow-up, low GC pts had reduced PFS benefit vs non-complex GC (HR 2.0, p=0.025; Figure 3), differing from previously reported findings (Lugano, 3-year follow-up). The delayed deterioration in PFS benefit in low GC pts was unprecedented, and warrants further investigation into prognostic risks associated with this subgroup. RNA expression data: Gene-specific and pathway-level enrichment analyses are ongoing to explore associations between RNA sequencing data and MRD status. Preliminary gene expression analyses showed that pts with MRD+ at EOCT expressed higher BCL-2 than those with uMRD (p=0.028), but not at EOT (Table 1). There was a trend towards increased MCL-1 expression from high MRD to low MRD and uMRD at EOT. Conclusions: We identified genomic alterations having impact on MRD response at EOCT and EOT (i.e. BIRC3, BRAF, NOTCH1, TP53): mutations mostly were associated with increased MRD and del17p tended to lead to increase in high and low clones of MRD+. Low/high GC negatively impacted long-term PFS with VenR and may represent high-risk pt subgroups. High BCL-2 may associate with MRD+ at EOCT but not at EOT. Given the small size of the genomic alteration cohort, further validation of these findings are needed. Studying the large CLL clinicogenomic data in MURANO helped determine whether VenR combinations overcome challenges posed by CLL/SLL with unfavorable clinical characteristics, and further identify biomarkers that may predict clinical benefits in these pts. Disclosures Kater: AbbVie: Consultancy, Honoraria, Research Funding; Roche: Other: Travel funding, Research Funding; Genentech: Research Funding. Wu:Genentech, Inc.: Employment, Equity Ownership. Bolen:F. Hoffmann-La Roche: Equity Ownership; Genentech, Inc.: Employment. Assaf:Genentech, Inc.: Employment, Equity Ownership. Hillmen:AbbVie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel Expenses, Research Funding; Acerta: Membership on an entity's Board of Directors or advisory committees; Apellis: Research Funding; Gilead: Research Funding; Roche: Research Funding; Pharmacyclics LLC, an AbbVie Company: Consultancy, Honoraria, Research Funding; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel Expenses, Research Funding. Eichhorst:AbbVie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; ArQule: Membership on an entity's Board of Directors or advisory committees; Roche: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; BeiGene: Research Funding; Gilead Sciences, Inc.: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau. Eldering:Genetech, Roche, AbbVie: Research Funding. Kipps:AstraZeneca, Inc.: Membership on an entity's Board of Directors or advisory committees; Verastem: Membership on an entity's Board of Directors or advisory committees; Abbvie: Membership on an entity's Board of Directors or advisory committees, Research Funding; Pharmacyclics: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Jannsen Pharmaceutical Companies of Johnson & Johnson: Honoraria, Membership on an entity's Board of Directors or advisory committees; Genentech, Inc.: Membership on an entity's Board of Directors or advisory committees, Research Funding; Velos-Bio: Equity Ownership, Membership on an entity's Board of Directors or advisory committees, Research Funding. Langerak:Gilead: Research Funding, Speakers Bureau; Janssen: Speakers Bureau; F. Hoffmann-La Roche Ltd: Research Funding; Genentech, Inc.: Research Funding. Mellink:Roche/Genentech: Research Funding. Van Der Kevie-Kersemaekers:Array analysis is financed by Roche/Genentech: Research Funding. Owen:AstraZeneca: Consultancy, Honoraria, Research Funding; AbbVie: Consultancy, Honoraria, Research Funding; Janssen: Honoraria, Research Funding; Roche: Honoraria, Research Funding; Gilead: Honoraria, Research Funding; Teva: Honoraria; Merck: Honoraria; Acerta: Research Funding. Chyla:Abbvie, Inc: Employment, Other: Stock or options. Punnoose:Roche: Other: Stock/stock options; Genentech, Inc.: Employment. Wang:Roche: Equity Ownership; Genentech, Inc.: Employment. Lefebure:F. Hoffmann-La Roche Ltd: Employment, Equity Ownership. Boyer:F. Hoffmann-La Roche Ltd: Employment. Humphrey:F. Hoffmann-La Roche Ltd: Employment. Jiang:Genentech: Employment, Equity Ownership; F. Hoffman-La Roche: Equity Ownership. Seymour:Roche: Consultancy, Research Funding, Speakers Bureau; Janssen: Consultancy, Research Funding; Acerta: Consultancy; AbbVie: Consultancy, Honoraria, Research Funding, Speakers Bureau; Celgene: Consultancy, Research Funding, Speakers Bureau; Takeda: Consultancy.