Citations

Key Points Elevated IL-2R, IL-1RA, and CXCL9 are associated with shorter event-free survival in newly diagnosed FL, treated with chemoimmunotherapy. Increased serum IL-12 and IL-1RA is associated with shorter event-free survival in patients who were observed or treated with rituximab alone.

Abstract Motivation: RNA-seq has become the method of choice to quantify genes and exons, discover novel transcripts and detect fusion genes. However, reliable variant identification from RNA-seq data remains challenging because of the complexities of the transcriptome, the challenges of accurately mapping exon boundary spanning reads and the bias introduced during the sequencing library preparation. Method: We developed RVboost, a novel method specific for RNA variant prioritization. RVboost uses several attributes unique in the process of RNA library preparation, sequencing and RNA-seq data analyses. It uses a boosting method to train a model of ‘good quality’ variants using common variants from HapMap, and prioritizes and calls the RNA variants based on the trained model. We packaged RVboost in a comprehensive workflow, which integrates tools of variant calling, annotation and filtering. Results: RVboost consistently outperforms the variant quality score recalibration from the Genome Analysis Tool Kit and the RNA-seq variant-calling pipeline SNPiR in 12 RNA-seq samples using ground-truth variants from paired exome sequencing data. Several RNA-seq–specific attributes were identified as critical to differentiate true and false variants, including the distance of the variant positions to exon boundaries, and the percent of the reads supporting the variant in the first six base pairs. The latter identifies false variants introduced by the random hexamer priming during the library construction. Availability and implementation: The RVboost package is implemented to readily run in Mac or Linux environments. The software and user manual are available at http://bioinformaticstools.mayo.edu/research/rvboost/. Supplementary information: Supplementary data are available at Bioinformatics online.

Abstract Motivation: Exome sequencing (exome-seq) data, which are typically used for calling exonic mutations, have also been utilized in detecting DNA copy number variations (CNVs). Despite the existence of several CNV detection tools, there is still a great need for a sensitive and an accurate CNV-calling algorithm with built-in QC steps, and does not require a paired reference for each sample. Results: We developed a novel method named PatternCNV, which (i) accounts for the read coverage variations between exons while leveraging the consistencies of this variability across different samples; (ii) reduces alignment BAM files to WIG format and therefore greatly accelerates computation; (iii) incorporates multiple QC measures designed to identify outlier samples and batch effects; and (iv) provides a variety of visualization options including chromosome, gene and exon-level views of CNVs, along with a tabular summarization of the exon-level CNVs. Compared with other CNV-calling algorithms using data from a lymphoma exome-seq study, PatternCNV has higher sensitivity and specificity. Availability and implementation: The software for PatternCNV is implemented using Perl and R, and can be used in Mac or Linux environments. Software and user manual are available at http://bioinformaticstools.mayo.edu/research/patterncnv/ , and R package at https://github.com/topsoil/patternCNV/ . Contact: Asmann.Yan@mayo.edu Supplementary information: Supplementary data are available at Bioinformatics online.

Abstract Purpose: Transformation of follicular lymphoma is a critical event associated with a poor prognosis. The role of the tumor microenvironment in previous transformation studies has yielded conflicting results. Experimental Design: To define cell subtypes associated with transformation, we examined tissue specimens at diagnosis from patients with follicular lymphoma that later transformed and, using immunohistochemistry (IHC), stained for CD68, CD11c, CD21, CXCL13, FOXP3, PD1, and CD14. Cell content and the pattern of expression were evaluated. Those identified as significantly associated with time to transformation (TTT) and overall survival (OS) were further characterized by flow cytometry and multicolor IHC. Results: Of note, 58 patients were analyzed with median TTT of 4.7 years. The pattern of PD1+ and CD14+ cells rather than the quantity of cells was predictive of clinical outcomes. On multivariate analysis, including the follicular lymphoma international prognostic index score, CD14+ cells localized in the follicle were associated with a shorter TTT (HR, 3.0; P = 0.004). PD1+ cells with diffuse staining were associated with a shorter TTT (HR, 1.9; P = 0.045) and inferior OS (HR, 2.5; P = 0.012). Multicolor IHC and flow cytometry identified CD14+ cells as follicular dendritic cells (FDC), whereas PD1+ cells represented two separate populations, TFH and exhausted T cells. Conclusion: These results identify the presence of PD1+ T cells and CD14+ FDC as independent predictors of transformation in follicular lymphoma. Clin Cancer Res; 20(11); 2862–72. ©2014 AACR.

Key Points STAT5 is constitutively phosphorylated in malignant B cells obtained from patients with Waldenström's macroglobulinemia. Inhibition of STAT5 signaling significantly decreases IgM production and may be useful therapeutically for patients with high IgM levels.

Abstract Purpose: Although the International Prognostic Score (IPS) is the gold standard for risk-stratifying patients with classical Hodgkin lymphoma (cHL), these criteria do not accurately predict outcome. As cytokines are critically involved in driving cHL, we tested whether pretreatment serum cytokine levels could provide additional prognostic information. Experimental Design: Thirty cytokines were measured in pretreatment serum from 140 patients with cHL and compared with 50 nonlymphoma controls. Patients were followed for event-free survival (EFS) and overall survival (OS), and Cox proportional hazards regression models were used to assess the association of individual cytokines and the cytokine profiles with outcome via unadjusted and IPS-adjusted HR. Results: Twelve cytokines (EGF, bFGF, G-CSF, HGF, IL-6, IL-8, IL-12, IL-2R, IP-10, MIG, TNF-α, and VEGF) were significantly (P < 0.05) higher in patients with cHL than controls; elevated levels of HGF, IL-6, IL-2R, IP-10, and MIG were all associated with poorer EFS. Only interleukin-2 receptor (IL-2R; P = 0.002) and interleukin (IL)-6 (P < 0.001) were independently prognostic. Patients with increased IL-6 and IL-2R had a significantly higher risk of early relapse and death, a finding that remained significant even after IPS-based risk stratification. Although elevated IL-6 and IL-2R correlated with the IPS, soluble CD30 (sCD30), and thymus and activation-related chemokine (TARC) levels, the two-cytokine model remained independently predictive of prognosis. Conclusions: Elevated pretreatment serum cytokines are associated with increased disease relapse and inferior survival in cHL. Thus, the pretreatment cytokine profile, particularly serum levels of IL-6 and IL-2R, may be used to identify patients with cHL at high risk for early-disease relapse. Clin Cancer Res; 19(24); 6812–9. ©2013 AACR.

Abstract Background: Our genome-wide association study (GWAS) of chronic lymphocytic leukemia (CLL) identified 4 highly correlated intronic variants within the IRF8 gene that were associated with CLL. These results were further supported by a recent meta-analysis of our GWAS with two other GWAS of CLL, supporting the IRF8 gene as a strong candidate for CLL risk. Methods: To refine the genetic association of CLL risk, we conducted Sanger sequencing of IRF8 in 94 CLL cases and 96 controls. We then conducted fine mapping by genotyping 39 variants (of which 10 were identified from sequencing) in 745 CLL cases and 1,521 controls. We also assessed these associations with risk of other non-Hodgkin lymphoma (NHL) subtypes. Results: The strongest association with CLL risk was observed with a common single-nucleotide polymorphism (SNP) located within the 3′ untranslated region (UTR) of IRF8 (rs1044873, log additive OR = 0.7, P = 1.81 × 10−6). This SNP was not associated with the other NHL subtypes (all P > 0.05). Conclusions: We provide evidence that rs1044873 in the IRF8 gene accounts for the initial GWAS signal for CLL risk. This association appears to be unique to CLL with little support for association with other common NHL subtypes. Future work is needed to assess functional role of IRF8 in CLL etiology. Impact: These data provide support that a functional variant within the 3′UTR of IRF8 may be driving the GWAS signal seen on 16q24.1 for CLL risk. Cancer Epidemiol Biomarkers Prev; 22(3); 461–6. ©2013 AACR.

AbstractMany common genetic variants have been associated with non-Hodgkin lymphoma (NHL), but individual study results are often conflicting. To confirm the role of putative risk alleles in B-cell NHL etiology, we performed a validation genotyping study of 67 candidate single nucleotide polymorphisms within InterLymph, a large international consortium of NHL case-control studies. A meta-analysis was performed on data from 5633 B-cell NHL cases and 7034 controls from 8 InterLymph studies. rs3789068 in the proapoptotic BCL2L11 gene was associated with an increased risk for B-cell NHL (odds ratio = 1.21, P random = 2.21 × 10−11), with similar risk estimates for common B-cell subtypes. PRRC2A rs3132453 in the HLA complex class III region conferred a reduced risk of B-cell NHL (odds ratio = 0.68, P random = 1.07 × 10−9) and was likewise evident for common B-cell subtypes. These results are consistent with the known biology of NHL and provide insights into shared pathogenic components, including apoptosis and immune regulation, for the major B-cell lymphoma subtypes.

Abstract Background: Non-Hodgkin lymphoma (NHL) is a malignancy of lymphocytes, and there is growing evidence for a role of germline genetic variation in immune genes in NHL etiology. Methods: To identify susceptibility immune genes, we conducted a 2-stage analysis of single-nucleotide polymorphisms (SNP) from 1,253 genes using the Immune and Inflammation Panel. In Stage 1, we genotyped 7,670 SNPs in 425 NHL cases and 465 controls, and in Stage 2 we genotyped the top 768 SNPs on an additional 584 cases and 768 controls. The association of individual SNPs with NHL risk from a log-additive model was assessed using the OR and 95% confidence intervals (CI). Results: In the pooled analysis, only the TAP2 coding SNP rs241447 (minor allele frequency = 0.26; Thr655Ala) at 6p21.3 (OR = 1.34, 95% CI 1.17–1.53) achieved statistical significance after accounting for multiple testing (P = 3.1 × 10−5). The TAP2 SNP was strongly associated with follicular lymphoma (FL, OR = 1.82, 95%CI 1.46–2.26; p = 6.9 × 10−8), and was independent of other known loci (rs10484561 and rs2647012) from this region. The TAP2 SNP was also associated with diffuse large B-cell lymphoma (DLBCL, OR = 1.38, 95% CI 1.08–1.77; P = 0.011), but not chronic lymphocytic leukemia (OR = 1.08; 95% CI 0.88–1.32). Higher TAP2 expression was associated with the risk allele in both FL and DLBCL tumors. Conclusion: Genetic variation in TAP2 was associated with NHL risk overall, and FL risk in particular, and this was independent of other established loci from 6p21.3. Impact: Genetic variation in antigen presentation of HLA class I molecules may play a role in lymphomagenesis. Cancer Epidemiol Biomarkers Prev; 21(10); 1799–806. ©2012 AACR.