Loss of CD20 expression as a mechanism of resistance to mosunetuzumab in relapsed/refractory B-cell lymphomas

ABSTRACT

CD20 is an established therapeutic target in B-cell malignancies. The CD20 × CD3 bispecific antibody mosunetuzumab has significant efficacy in B-cell non-Hodgkin lymphomas (NHLs). Because target antigen loss is a recognized mechanism of resistance, we evaluated CD20 expression relative to clinical response in patients with relapsed and/or refractory NHL in the phase 1/2 GO29781 trial investigating mosunetuzumab monotherapy. CD20 was studied using immunohistochemistry (IHC), RNA sequencing, and whole-exome sequencing performed centrally in biopsy specimens collected before treatment at predose, during treatment, or upon progression. Before treatment, most patients exhibited a high proportion of tumor cells expressing CD20; however, in 16 of 293 patients (5.5%) the proportion was <10%. Analyses of paired biopsy specimens from patients on treatment revealed that CD20 levels were maintained in 29 of 30 patients (97%) vs at progression, where CD20 loss was observed in 11 of 32 patients (34%). Reduced transcription or acquisition of truncating mutations explained most but not all cases of CD20 loss. In vitro modeling confirmed the effects of CD20 variants identified in clinical samples on reduction of CD20 expression and missense mutations in the extracellular domain that could block mosunetuzumab binding. This study expands the knowledge about the occurrence of target antigen loss after anti-CD20 therapeutics to include CD20-targeting bispecific antibodies and elucidates mechanisms of reduced CD20 expression at disease progression that may be generalizable to other anti-CD20 targeting agents. These results also confirm the utility of readily available IHC staining for CD20 as a tool to inform clinical decisions. This trial was registered at www.ClinicalTrials.gov as #NCT02500407.

NGS-determined molecular markers and disease burden metrics from ctDNA correlate with PFS in previously untreated DLBCL

Personalized risk stratification and treatment may help improve outcomes among patients with diffuse large B-cell lymphoma (DLBCL). We developed a next-generation sequencing (NGS)-based method to assess a range of potential prognostic indicators, and evaluated it using pretreatment plasma samples from 310 patients with previously untreated DLBCL from the GOYA trial (NCT01287741). Variant calls and DLBCL subtyping with the plasma-based method were concordant with corresponding tissue-based methods. Patients with a tumor burden greater than the median (p = .003) and non-germinal center B-cell-like (non-GCB) DLBCL (p = .049) had worse progression-free survival than patients with a tumor burden less than the median or GCB DLBCL. Multi-factor assessment combining orthogonal features from a single pretreatment plasma sample has promise as a prognostic indicator in this setting (p = .085). This minimally invasive plasma-based NGS assay could enable comprehensive prognostic assessment of patients in a clinical setting, with greater accessibility than current methods.

Characterization of CD20 expression loss as a mechanism of resistance to mosunetuzumab in patients with relapsed/refractory B-cell non-Hodgkin lymphomas

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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.

A prognostic model integrating PET‐derived metrics and image texture analyses with clinical risk factors from GOYA

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.

Prognostic mutational subtyping in de novo diffuse large B-cell lymphoma

BACKGROUND

Diffuse large B-cell lymphoma (DLBCL) is a heterogeneous disease defined using a number of well-established molecular subsets. Application of non-negative matrix factorization (NMF) to whole exome sequence data has previously been used to identify six distinct molecular clusters in DLBCL with potential clinical relevance. In this study, we applied NMF-clustering to targeted sequencing data utilizing the FoundationOne Heme® panel from the Phase III GOYA (NCT01287741) and Phase Ib/II CAVALLI studies (NCT02055820) in de novo DLBCL. Biopsy samples, survival outcomes, RNA-Seq and targeted exome-sequencing data were available for 423 patients in GOYA (obinutuzumab [G]-cyclophosphamide, doxorubicin, vincristine, and prednisone [CHOP] vs rituximab [R]-CHOP) and 86 patients in CAVALLI (venetoclax+[G/R]-CHOP).

RESULTS

When the NMF algorithm was applied to samples from the GOYA study analyzed using a comprehensive genomic profiling platform, four of the six groups previously reported were observed: MYD88/CD79B, BCL2/EZH2, NOTCH2/TNFAIP3, and no mutations. Mutation profiles, cell-of-origin subset distributions and clinical associations of MYD88/CD79B and BCL2/EZH2 groups were similar to those described in previous NMF studies. In contrast, application of NMF to the CAVALLI study yielded only three; MYD88/CD79B-, BCL2/EZH2-like clusters, and a no mutations group, and there was a trend towards improved outcomes for BCL2/EZH2 over MYD88/CD79B.

CONCLUSIONS

This analysis supports the utility of NMF used in conjunction with targeted sequencing platforms for identifying patients with different prognostic subsets. The observed trend for improved overall survival in the BCL2/EZH2 group is consistent with the mechanism of action of venetoclax, suggesting that targeting sequencing and NMF has potential for identifying patients who are more likely to gain benefit from venetoclax therapy.

Decoupling Lineage-Associated Genes in Acute Myeloid Leukemia Reveals Inflammatory and Metabolic Signatures Associated With Outcomes

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.

Prognostic significance of FCGR2B expression for the response of DLBCL patients to rituximab or obinutuzumab treatment

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.

Single-nucleotide Fcγ receptor polymorphisms do not impact obinutuzumab/rituximab outcome in patients with lymphoma

Single-nucleotide polymorphisms (SNPs) have been shown to influence Fcγ receptor (FcγR) affinity and activity, but their effect on treatment response is unclear. We assessed their importance in the efficacy of obinutuzumab or rituximab combined with chemotherapy in untreated advanced follicular lymphoma (FL) and diffuse large B-cell lymphoma (DLBCL) in the GALLIUM (www.clinicaltrials.gov #NCT01332968) and GOYA (#NCT01287741) trials, respectively. Genomic DNA was extracted from patients enrolled in GALLIUM (n = 1202) and GOYA (n = 1418). Key germline SNPs, FCGR2A R131H (rs1801274), FCGR3A F158V (rs396991), and FCGR2B I232T (rs1050501), were genotyped and assessed for their impact on investigator-assessed progression-free survival (PFS). In both cohorts there was no prognostic effect of FCGR2A or FCGR3A. In FL, FCGR2B was associated with favorable PFS in univariate and multivariate analyses comparing I232T with I232I, with a more modest association for rituximab-treated (univariate: hazard ratio [HR], 0.78; 95% confidence interval [CI], 0.54-1.14; P = .21) vs obinutuzumab-treated patients (HR, 0.56; 95% CI, 0.34-0.91; P = .02). Comparing T232T with I232I, an association was found for obinutuzumab (univariate: HR, 2.76; 95% CI, 1.02-7.5; P = .0459). Neither observation retained significance after multiple-test adjustment. FCGR2B was associated with poorer PFS in multivariate analyses comparing T232T with I232I in rituximab- but not obinutuzumab-treated patients with DLBCL (HR, 4.40; 95% CI, 1.71-11.32; P = .002; multiple-test-adjusted P = .03); however, this genotype was rare (n = 13). This study shows that FcγR genotype is not associated with response to rituximab/obinutuzumab plus chemotherapy in treatment-naive patients with advanced FL or DLBCL.

Prediction and characterization of diffuse large B-cell lymphoma cell-of-origin subtypes using targeted sequencing

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.

Follicular Lymphoma Evaluation Index (FLEX): A new clinical prognostic model that is superior to existing risk scores for predicting progression-free survival and early treatment failure after frontline immunochemotherapy

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 (NCT01332968). The performance of the model was validated using data from the SABRINA trial (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.

Venetoclax Plus Rituximab in Relapsed Chronic Lymphocytic Leukemia: 4-Year Results and Evaluation of Impact of Genomic Complexity and Gene Mutations From the MURANO Phase III Study

PURPOSE

In previous analyses of the MURANO study, fixed-duration venetoclax plus rituximab (VenR) resulted in improved progression-free survival (PFS) compared with bendamustine plus rituximab (BR) in patients with relapsed or refractory chronic lymphocytic leukemia (CLL). At the 4-year follow-up, we report long-term outcomes, response to subsequent therapies, and the predictive value of molecular and genetic characteristics.

PATIENTS AND METHODS

Patients with CLL were randomly assigned to 2 years of venetoclax (VenR for the first six cycles) or six cycles of BR. PFS, overall survival (OS), peripheral-blood minimal residual disease (MRD) status, genomic complexity (GC), and gene mutations were assessed.

RESULTS

Of 389 patients, 194 were assigned to VenR and 195 to BR. Four-year PFS and OS rates were higher with VenR than BR, at 57.3% and 4.6% (hazard ratio [HR], 0.19; 95% CI, 0.14 to 0.25), and 85.3% and 66.8% (HR, 0.41; 95% CI, 0.26 to 0.65), respectively. Undetectable MRD (uMRD) at end of combination therapy (EOCT) was associated with superior PFS compared with low MRD positivity (HR, 0.50) and high MRD positivity (HR, 0.15). Patients in the VenR arm who received ibrutinib as their first therapy after progression (n = 12) had a reported response rate of 100% (10 of 10 evaluable patients); patients subsequently treated with a venetoclax-based regimen (n = 14) had a reported response rate of 55% (six of 11 evaluable patients). With VenR, the uMRD rate at end of treatment (EOT) was lower in patients with GC than in those without GC (P = .042); higher GC was associated with shorter PFS. Higher MRD positivity rates were seen with BIRC3 and BRAF mutations at EOCT and with TP53, NOTCH1, XPO1, and BRAF mutations at EOT.

CONCLUSION

Efficacy benefits with fixed-duration VenR are sustained and particularly durable in patients who achieve uMRD. Salvage therapy with ibrutinib after VenR achieved high response rates. Genetic mutations and GC affected MRD rates and PFS.

Abstract PO-26: 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

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.

Prognostic impact of somatic mutations in diffuse large B-cell lymphoma and relationship to cell-of-origin: data from the phase III GOYA study

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.

A randomized, open-label, Phase III study of obinutuzumab or rituximab plus CHOP in patients with previously untreated diffuse large B-Cell lymphoma: final analysis of GOYA

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.

Integrated, multicohort analysis reveals unified signature of systemic lupus erythematosus

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.

Increased T Cell Differentiation and Cytolytic Function in Bangladeshi Compared to American Children

During the first 5 years of life, children are especially vulnerable to infection-related morbidity and mortality. Conversely, the Hygiene Hypothesis suggests that a lack of exposure to infectious agents early in life could explain the increasing incidence of allergies and autoimmunity in high-income countries. Understanding these phenomena, however, is hampered by a lack of comprehensive, direct immune monitoring in children with differing degrees of microbial exposure. Using mass cytometry, we provide an in-depth profile of the peripheral blood mononuclear cells (PBMCs) of children in regions at the extremes of exposure: the San Francisco Bay Area, USA and an economically poor district of Dhaka, Bangladesh. Despite variability in clinical health, functional characteristics of PBMCs were similar in Bangladeshi and American children at 1 year of age. However, by 2–3 years of age, Bangladeshi children's immune cells often demonstrated altered activation and cytokine production profiles upon stimulation with PMA-ionomycin, with an overall immune trajectory more in line with American adults. Conversely, immune responses in children from the US remained steady. Using principal component analysis, donor location, ethnic background, and cytomegalovirus infection status were found to account for some of the variation identified among samples. Within Bangladeshi 1-year-olds, stunting (as measured by height-for-age z-scores) was found to be associated with IL-8 and TGFβ expression in PMA-ionomycin stimulated samples. Combined, these findings provide important insights into the immune systems of children in high vs. low microbial exposure environments and suggest an important role for IL-8 and TGFβ in mitigating the microbial challenges faced by the Bangladeshi children.

Quantitative Comparison of Conventional and t-SNE-guided Gating Analyses

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.

Prognostic Impact of Natural Killer Cell Count in Follicular Lymphoma and Diffuse Large B-cell Lymphoma Patients Treated with Immunochemotherapy

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.

Gene set meta-analysis with Quantitative Set Analysis for Gene Expression (QuSAGE)

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.

Rituximab treatment circumvents the prognostic impact of tumor-infiltrating T-cells in follicular lymphoma patients

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.

Mass cytometry identifies a distinct monocyte cytokine signature shared by clinically heterogeneous pediatric SLE patients

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.

Multicenter Systems Analysis of Human Blood Reveals Immature Neutrophils in Males and During Pregnancy

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.

The Repertoire Dissimilarity Index as a method to compare lymphocyte receptor repertoires

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.

Expression of specific inflammasome gene modules stratifies older individuals into two extreme clinical and immunological states

Low-grade, chronic inflammation has been associated with many diseases of aging, but the mechanisms responsible for producing this inflammation remain unclear. Inflammasomes can drive chronic inflammation in the context of an infectious disease or cellular stress, and they trigger the maturation of interleukin-1β (IL-1β). Here we find that the expression of specific inflammasome gene modules stratifies older individuals into two extremes: those with constitutive expression of IL-1β, nucleotide metabolism dysfunction, elevated oxidative stress, high rates of hypertension and arterial stiffness; and those without constitutive expression of IL-1β, who lack these characteristics. Adenine and N⁴-acetylcytidine, nucleotide-derived metabolites that are detectable in the blood of the former group, prime and activate the NLRC4 inflammasome, induce the production of IL-1β, activate platelets and neutrophils and elevate blood pressure in mice. In individuals over 85 years of age, the elevated expression of inflammasome gene modules was associated with all-cause mortality. Thus, targeting inflammasome components may ameliorate chronic inflammation and various other age-associated conditions.

Dysregulation of B Cell Repertoire Formation in Myasthenia Gravis Patients Revealed through Deep Sequencing

Myasthenia gravis (MG) is a prototypical B cell-mediated autoimmune disease affecting 20-50 people per 100,000. The majority of patients fall into two clinically distinguishable types based on whether they produce autoantibodies targeting the acetylcholine receptor (AChR-MG) or muscle specific kinase (MuSK-MG). The autoantibodies are pathogenic, but whether their generation is associated with broader defects in the B cell repertoire is unknown. To address this question, we performed deep sequencing of the BCR repertoire of AChR-MG, MuSK-MG, and healthy subjects to generate ∼518,000 unique V_H and V_L sequences from sorted naive and memory B cell populations. AChR-MG and MuSK-MG subjects displayed distinct gene segment usage biases in both V_H and V_L sequences within the naive and memory compartments. The memory compartment of AChR-MG was further characterized by reduced positive selection of somatic mutations in the V_H CDR and altered V_H CDR3 physicochemical properties. The V_L repertoire of MuSK-MG was specifically characterized by reduced V-J segment distance in recombined sequences, suggesting diminished V_L receptor editing during B cell development. Our results identify large-scale abnormalities in both the naive and memory B cell repertoires. Particular abnormalities were unique to either AChR-MG or MuSK-MG, indicating that the repertoires reflect the distinct properties of the subtypes. These repertoire abnormalities are consistent with previously observed defects in B cell tolerance checkpoints in MG, thereby offering additional insight regarding the impact of tolerance defects on peripheral autoimmune repertoires. These collective findings point toward a deformed B cell repertoire as a fundamental component of MG.

Individual heritable differences result in unique cell lymphocyte receptor repertoires of naïve and antigen-experienced cells

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.

Quantitative gene set analysis generalized for repeated measures, confounder adjustment, and continuous covariates

Background

Gene set analysis (GSA) of gene expression data can be highly powerful when the biological signal is weak compared to other sources of variability in the data. However, many gene set analysis approaches utilize permutation tests which are not appropriate for complex study designs. For example, the correlation of subjects is broken when comparing time points within a longitudinal study. Linear mixed models provide a method to analyze longitudinal studies as well as adjust for potential confounding factors and account for sources of variability that are not of primary interest. Currently, there are no known gene set analysis approaches that fully account for these study design and analysis aspects. In order to do so, we generalize the QuSAGE gene set analysis algorithm, denoted Q-Gen, and provide the necessary estimation adjustments to incorporate linear mixed model analyses.

Results

We assessed the performance of our generalized method in comparison to the original QuSAGE method in settings such as longitudinal repeated measures analysis and accounting for potential confounders. We demonstrate that the original QuSAGE method can not control for type-I error when these complexities exist. In addition to statistical appropriateness, analysis of a longitudinal influenza study suggests Q-Gen can allow for greater sensitivity when exploring a large number of gene sets.

Conclusions

Q-Gen is an extension to the gene set analysis method of QuSAGE, and allows for linear mixed models to be applied appropriately within a gene set analysis framework. It provides GSA an added layer of flexibility that was not currently available. This flexibility allows for more appropriate statistical modeling of complex data structures that are inherent to many microarray study designs and can provide more sensitivity.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-015-0707-9) contains supplementary material, which is available to authorized users.

Dynamic expression profiling of type I and type III interferon-stimulated hepatocytes reveals a stable hierarchy of gene expression

Despite activating similar signaling cascades, the type I and type III interferons (IFNs) differ in their ability to antagonize virus replication. However, it is not clear whether these cytokines induce unique antiviral states, particularly in the liver, where the clinically important hepatitis B and C viruses cause persistent infection. Here, clustering and promoter analyses of microarray-based gene expression profiling were combined with mechanistic studies of signaling pathways to dynamically characterize the transcriptional responses induced by these cytokines in Huh7 hepatoma cells and primary human hepatocytes. Type I and III IFNs differed greatly in their level of interferon-stimulated gene (ISG) induction with a clearly detectable hierarchy (IFN-β > IFN-α > IFN-λ3 > IFN-λ1 > IFN-λ2). Notably, although the hierarchy identified varying numbers of differentially expressed genes when quantified using common statistical thresholds, further analysis of gene expression over multiple timepoints indicated that the individual IFNs do not in fact regulate unique sets of genes. The kinetic profiles of IFN-induced gene expression were also qualitatively similar with the important exception of IFN-α. While stimulation with either IFN-β or IFN-λs resulted in a similar long-lasting ISG induction, IFN-α signaling peaked early after stimulation then declined due to a negative feedback mechanism. The quantitative expression hierarchy and unique kinetics of IFN-α reveal potential specific roles for individual IFNs in the immune response, and elucidate the mechanism behind previously observed differences in IFN antiviral activity. While current clinical trials are focused on IFN-λ1 as a potential antiviral therapy, the finding that IFN-λ3 invariably possesses the highest activity among type III IFNs suggests that this cytokine may have superior clinical activity.

Quantitative set analysis for gene expression: a method to quantify gene set differential expression including gene-gene correlations

Enrichment analysis of gene sets is a popular approach that provides a functional interpretation of genome-wide expression data. Existing tests are affected by inter-gene correlations, resulting in a high Type I error. The most widely used test, Gene Set Enrichment Analysis, relies on computationally intensive permutations of sample labels to generate a null distribution that preserves gene–gene correlations. A more recent approach, CAMERA, attempts to correct for these correlations by estimating a variance inflation factor directly from the data. Although these methods generate P-values for detecting gene set activity, they are unable to produce confidence intervals or allow for post hoc comparisons. We have developed a new computational framework for Quantitative Set Analysis of Gene Expression (QuSAGE). QuSAGE accounts for inter-gene correlations, improves the estimation of the variance inflation factor and, rather than evaluating the deviation from a null hypothesis with a P-value, it quantifies gene-set activity with a complete probability density function. From this probability density function, P-values and confidence intervals can be extracted and post hoc analysis can be carried out while maintaining statistical traceability. Compared with Gene Set Enrichment Analysis and CAMERA, QuSAGE exhibits better sensitivity and specificity on real data profiling the response to interferon therapy (in chronic Hepatitis C virus patients) and Influenza A virus infection. QuSAGE is available as an R package, which includes the core functions for the method as well as functions to plot and visualize the results.

Impaired toll-like receptor 3-mediated immune responses from macrophages of patients chronically infected with hepatitis C virus

Hepatitis C virus (HCV) is the most common chronic blood-borne infection in the United States, with the majority of patients becoming chronically infected and a subset (20%) progressing to cirrhosis and hepatocellular carcinoma. Individual variations in immune responses may help define successful resistance to infection with HCV. We have compared the immune response in primary macrophages from patients who have spontaneously cleared HCV (viral load negative [VL-], n = 37) to that of primary macrophages from HCV genotype 1 chronically infected (VL+) subjects (n = 32) and found that macrophages from VL- subjects have an elevated baseline expression of Toll-like receptor 3 (TLR3). Macrophages from HCV patients were stimulated ex vivo through the TLR3 pathway and assessed using gene expression arrays and pathway analysis. We found elevated TLR3 response genes and pathway activity from VL- subjects. Furthermore, macrophages from VL- subjects showed higher production of beta interferon (IFN-β) and related IFN response genes by quantitative PCR (Q-PCR) and increased phosphorylation of STAT-1 by immunoblotting. Analysis of polymorphisms in TLR3 revealed a significant association of intronic TLR3 polymorphism (rs13126816) with the clearance of HCV and the expression of TLR3. Of note, peripheral blood mononuclear cells (PBMCs) from the same donors showed opposite changes in gene expression, suggesting ongoing inflammatory responses in PBMCs from VL+ HCV patients. Our results suggest that an elevated innate immune response enhances HCV clearance mechanisms and may offer a potential therapeutic approach to increase viral clearance.

The blood transcriptional signature of chronic hepatitis C virus is consistent with an ongoing interferon-mediated antiviral response

Blood transcriptional profiling is a powerful tool for understanding global changes after infection, and may be useful for prognosis and prediction of drug treatment responses. This study characterizes the effects of chronic hepatitis C virus (HCV) infection on gene expression by analyzing blood samples from 10 treatment-naïve HCV patients and 6 healthy volunteers. Differential expression analysis of microarray data from peripheral blood mononuclear cells (PBMCs) identified a 136-gene signature, including 66 genes elevated in infected individuals. Most of the upregulated genes were associated with interferon (IFN) activity (including members of the OAS and MX families, ISG15, and IRF7), suggesting an ongoing immune response. This HCV signature was also found to be consistently enriched in many other viral infection and vaccination datasets. These genes were validated using a second cohort composed of 5 HCV patients and 5 healthy volunteers, confirming the upregulation of the IFN signature. In summary, this is the first study to directly compare blood transcriptional profiles from HCV patients with healthy controls. The results show that chronic HCV infection has a pronounced effect on gene expression in PBMCs of infected individuals, and significantly elevates the expression of a subset of IFN-stimulated genes.

Cell subset prediction for blood genomic studies

BACKGROUND

Genome-wide transcriptional profiling of patient blood samples offers a powerful tool to investigate underlying disease mechanisms and personalized treatment decisions. Most studies are based on analysis of total peripheral blood mononuclear cells (PBMCs), a mixed population. In this case, accuracy is inherently limited since cell subset-specific differential expression of gene signatures will be diluted by RNA from other cells. While using specific PBMC subsets for transcriptional profiling would improve our ability to extract knowledge from these data, it is rarely obvious which cell subset(s) will be the most informative.

RESULTS

We have developed a computational method (Subset Prediction from Enrichment Correlation, SPEC) to predict the cellular source for a pre-defined list of genes (i.e. a gene signature) using only data from total PBMCs. SPEC does not rely on the occurrence of cell subset-specific genes in the signature, but rather takes advantage of correlations with subset-specific genes across a set of samples. Validation using multiple experimental datasets demonstrates that SPEC can accurately identify the source of a gene signature as myeloid or lymphoid, as well as differentiate between B cells, T cells, NK cells and monocytes. Using SPEC, we predict that myeloid cells are the source of the interferon-therapy response gene signature associated with HCV patients who are non-responsive to standard therapy.

CONCLUSIONS

SPEC is a powerful technique for blood genomic studies. It can help identify specific cell subsets that are important for understanding disease and therapy response. SPEC is widely applicable since only gene expression profiles from total PBMCs are required, and thus it can easily be used to mine the massive amount of existing microarray or RNA-seq data.

Lambda and alpha interferons inhibit hepatitis B virus replication through a common molecular mechanism but with different in vivo activities

The type III interferons (IFN-lambda1, 2, and 3) induce an antiviral response similar to IFN-alpha/beta, but mediate their activity through a unique receptor. We found that like IFN-alpha/beta, IFN-lambda prevents the assembly of HBV capsids, demonstrating convergence of the two signaling pathways through a single antiviral mechanism. In contrast to IFN-lambda, the structurally related cytokine interleukin (IL)-22 only minimally reduced HBV replication. The transcriptional program activated by IL-22 displayed little similarity to that induced by IFN-lambda, but instead resembled the response elicited by IL-6. We also found that murine IFN-lambda2 had only weak antiviral activity against HBV in the liver of transgenic mice, and that human IFN-lambda2 activity in serum correlated with the sensitivity of the cytokine to proteases. These results demonstrate that the IFN-alpha/beta and IFN-lambda anti-HBV responses operate through a single molecular mechanism, and support the notion that IFN-lambda plays a local, rather than systemic, role in antiviral immunity.