Citations

Objective Determinants of the increased risk of diffuse large B-cell lymphoma (DLBCL) in SLE are unclear. Using data from a recent lymphoma genome-wide association study (GWAS), we assessed whether certain lupus-related single nucleotide polymorphisms (SNPs) were also associated with DLBCL. Methods GWAS data on European Caucasians from the International Lymphoma Epidemiology Consortium (InterLymph) provided a total of 3857 DLBCL cases and 7666 general-population controls. Data were pooled in a random-effects meta-analysis. Results Among the 28 SLE-related SNPs investigated, the two most convincingly associated with risk of DLBCL included the CD40 SLE risk allele rs4810485 on chromosome 20q13 (OR per risk allele=1.09, 95% CI 1.02 to 1.16, p=0.0134), and the HLA SLE risk allele rs1270942 on chromosome 6p21.33 (OR per risk allele=1.17, 95% CI 1.01 to 1.36, p=0.0362). Of additional possible interest were rs2205960 and rs12537284. The rs2205960 SNP, related to a cytokine of the tumour necrosis factor superfamily TNFSF4, was associated with an OR per risk allele of 1.07, 95% CI 1.00 to 1.16, p=0.0549. The OR for the rs12537284 (chromosome 7q32, IRF5 gene) risk allele was 1.08, 95% CI 0.99 to 1.18, p=0.0765. Conclusions These data suggest several plausible genetic links between DLBCL and SLE.

The Institute of Medicine and US Food and Drug Administration (FDA) recognize that activating clinical trials in the United States is lengthy and inefficient. Downstream consequences include increased expense, suboptimal accrual, move of clinical trials overseas, and delayed availability of treatments for patients. An in‐tandem processing initiative is here highlighted that transformed the activation of clinical trials (TACT), reduced the activation time by 70%, and offers a paradigm for enhanced translational readiness.

AbstractWaldenström macroglobulinemia (WM) is an immunoglobulin M‐associated lymphoma, with majority of cases demonstrating MYD88 locus alteration, most commonly, MYD88L265P. Owing to low prevalence of the wild‐type (WT) MYD88 genotype in WM, clinically relevant data in this patient population are sparse, with one study showing nearly a 10‐fold increased risk of mortality in this subgroup compared to patients with MYD88L265P mutation. We studied a large cohort of patients with MYD88L265P and MYD88WT WM, evaluated at Mayo Clinic, Rochester, between 1995 and 2016, to specifically assess the impact of these genotypes on clinical course. Of 557 patients, MYD88L265P mutation status, as determined by allele‐specific polymerase chain reaction, was known in 219, and 174 (79%) of those exhibited MYD88L265P, 157 of 174 patients had active disease. Of 45 (21%) patients with MYD88WT genotype, 44 had active disease. The estimated median follow‐up was 7.0 years; median overall survival was 10.2 years (95% CI: 8.4‐16.5) for MYD88L265P versus 13.9 years (95% CI: 6.4‐29.3) for the MYD88WT (P = 0.86). The time‐to‐next therapy from frontline treatment and the presenting features were similar in the two patient populations. For patients with smoldering WM at diagnosis, the median time‐to‐progression to active disease was 2.8 years (95% CI: 2.2‐3.8) in the MYD88L265P cohort and 1.9 years (95% CI: 0.7‐3.1) in the MYD88WT cohort (P = 0.21). The frequency of transformation to high‐grade lymphoma, or the development of therapy‐elated myelodysplastic syndrome was higher in the MYD88WT cohort (16% versus 4% in the MYD88L265P, P = 0.009). In conclusion, MYD88L265P mutation does not appear to be a determinant of outcome, and its presence may not be a disease‐defining feature in WM. Our findings warrant external validation, preferably through prospective studies.

Abstract Purpose: Glioblastoma is an aggressive and molecularly heterogeneous cancer with few effective treatment options. We hypothesized that next-generation sequencing can be used to guide treatment recommendations within a clinically acceptable time frame following surgery for patients with recurrent glioblastoma. Experimental Design: We conducted a prospective genomics-informed feasibility trial in adults with recurrent and progressive glioblastoma. Following surgical resection, genome-wide tumor/normal exome sequencing and tumor RNA sequencing were performed to identify molecular targets for potential matched therapy. A multidisciplinary molecular tumor board issued treatment recommendations based on the genomic results, blood–brain barrier penetration of the indicated therapies, drug–drug interactions, and drug safety profiles. Feasibility of generating genomics-informed treatment recommendations within 35 days of surgery was assessed. Results: Of the 20 patients enrolled in the study, 16 patients had sufficient tumor tissue for analysis. Exome sequencing was completed for all patients, and RNA sequencing was completed for 14 patients. Treatment recommendations were provided within the study's feasibility time frame for 15 of 16 (94%) patients. Seven patients received treatment based on the tumor board recommendations. Two patients reached 12-month progression-free survival, both adhering to treatments based on the molecular profiling results. One patient remained on treatment and progression free 21 months after surgery, 3 times longer than the patient's previous time to progression. Analysis of matched nonenhancing tissue from 12 patients revealed overlapping as well as novel putatively actionable genomic alterations. Conclusions: Use of genome-wide molecular profiling is feasible and can be informative for guiding real-time, central nervous system–penetrant, genomics-informed treatment recommendations for patients with recurrent glioblastoma. Clin Cancer Res; 24(2); 295–305. ©2017 AACR. See related commentary by Wick and Kessler, p. 256

ObjectivesTo identify any anatomic barriers to local anesthetic spread between the sciatic nerve (SN) and the posterior femoral cutaneous nerve (PFCN) at the level of the infragluteal crease and to describe a potential technique for an ultrasound (US)‐guided subgluteal PFCN block in a cadaveric model.MethodsBilateral US‐guided subgluteal injections of a colored latex solution were performed around the SN (15 mL) and PFCN (10 mL) in 4 unembalmed cadavers, for a total of 8 cadaver thighs. The specimens were dissected after latex polymerization to observe the spread of the latex solutions.ResultsWith US guidance, the PFCN was visualized deep to the gluteus maximus and slightly superficial or lateral to the SN at the level of the infragluteal crease. The SN and PFCN were found on dissection to be coated with their respective colored latex in all 8 thighs. The SN and PFCN were consistently separated by the deep investing muscular fascia of the thigh, with only 2 thighs showing substantial mixing of latex injectates.ConclusionsThe deep investing muscular fascia of the thigh appears to impede the spread of injectate between the SN and PFCN in a most unembalmed cadaver specimens. A US‐guided subgluteal PFCN blockade may be a feasible technique to complement an SN block when complete anesthesia of the posterior thigh is required.

AbstractMotivationOne objective of human microbiome studies is to identify differentially abundant microbes across biological conditions. Previous statistical methods focus on detecting the shift in the abundance and/or prevalence of the microbes and treat the dispersion (spread of the data) as a nuisance. These methods also assume that the dispersion is the same across conditions, an assumption which may not hold in presence of sample heterogeneity. Moreover, the widespread outliers in the microbiome sequencing data make existing parametric models not overly robust. Therefore, a robust and powerful method that allows covariate-dependent dispersion and addresses outliers is still needed for differential abundance analysis.ResultsWe introduce a novel test for differential distribution analysis of microbiome sequencing data by jointly testing the abundance, prevalence and dispersion. The test is built on a zero-inflated negative binomial regression model and winsorized count data to account for zero-inflation and outliers. Using simulated data and real microbiome sequencing datasets, we show that our test is robust across various biological conditions and overall more powerful than previous methods.Availability and implementationR package is available at https://github.com/jchen1981/MicrobiomeDDA.Supplementary informationSupplementary data are available at Bioinformatics online.