Citations

Telomeres cap chromosome ends, protecting them from degradation, double‐strand breaks, and end‐to‐end fusions. Telomeres are maintained by telomerase, a reverse transcriptase encoded by TERT, and an RNA template encoded by TERC. Loci in the TERT and adjoining CLPTM1L region are associated with risk of multiple cancers. We therefore investigated associations between variants in 22 telomere structure and maintenance gene regions and colorectal, breast, prostate, ovarian, and lung cancer risk. We performed subset‐based meta‐analyses of 204,993 directly‐measured and imputed SNPs among 61,851 cancer cases and 74,457 controls of European descent. Independent associations for SNP minor alleles were identified using sequential conditional analysis (with gene‐level p value cutoffs ≤3.08 × 10−5). Of the thirteen independent SNPs observed to be associated with cancer risk, novel findings were observed for seven loci. Across the DCLRE1B region, rs974494 and rs12144215 were inversely associated with prostate and lung cancers, and colorectal, breast, and prostate cancers, respectively. Across the TERC region, rs75316749 was positively associated with colorectal, breast, ovarian, and lung cancers. Across the DCLRE1B region, rs974404 and rs12144215 were inversely associated with prostate and lung cancers, and colorectal, breast, and prostate cancers, respectively. Near POT1, rs116895242 was inversely associated with colorectal, ovarian, and lung cancers, and RTEL1 rs34978822 was inversely associated with prostate and lung cancers. The complex association patterns in telomere‐related genes across cancer types may provide insight into mechanisms through which telomere dysfunction in different tissues influences cancer risk.

Abstract Breast, ovarian, and prostate cancers are hormone-related and may have a shared genetic basis, but this has not been investigated systematically by genome-wide association (GWA) studies. Meta-analyses combining the largest GWA meta-analysis data sets for these cancers totaling 112,349 cases and 116,421 controls of European ancestry, all together and in pairs, identified at P < 10−8 seven new cross-cancer loci: three associated with susceptibility to all three cancers (rs17041869/2q13/BCL2L11; rs7937840/11q12/INCENP; rs1469713/19p13/GATAD2A), two breast and ovarian cancer risk loci (rs200182588/9q31/SMC2; rs8037137/15q26/RCCD1), and two breast and prostate cancer risk loci (rs5013329/1p34/NSUN4; rs9375701/6q23/L3MBTL3). Index variants in five additional regions previously associated with only one cancer also showed clear association with a second cancer type. Cell-type–specific expression quantitative trait locus and enhancer–gene interaction annotations suggested target genes with potential cross-cancer roles at the new loci. Pathway analysis revealed significant enrichment of death receptor signaling genes near loci with P < 10−5 in the three-cancer meta-analysis. Significance: We demonstrate that combining large-scale GWA meta-analysis findings across cancer types can identify completely new risk loci common to breast, ovarian, and prostate cancers. We show that the identification of such cross-cancer risk loci has the potential to shed new light on the shared biology underlying these hormone-related cancers. Cancer Discov; 6(9); 1052–67. ©2016 AACR. This article is highlighted in the In This Issue feature, p. 932

Background Intracranial aneurysms ( IAs ), abdominal aortic aneurysms ( AAAs ), and thoracic aortic aneurysms ( TAAs ) all have a familial predisposition. Given that aneurysm types are known to co‐occur, we hypothesized that there may be shared genetic risk factors for IAs , AAAs, and TAAs . Methods and Results We performed a mega‐analysis of 1000 Genomes Project‐imputed genome‐wide association study ( GWAS ) data of 4 previously published aneurysm cohorts: 2 IA cohorts (in total 1516 cases, 4305 controls), 1 AAA cohort (818 cases, 3004 controls), and 1 TAA cohort (760 cases, 2212 controls), and observed associations of 4 known IA , AAA , and/or TAA risk loci (9p21, 18q11, 15q21, and 2q33) with consistent effect directions in all 4 cohorts. We calculated polygenic scores based on IA ‐, AAA ‐, and TAA ‐associated SNP s and tested these scores for association to case‐control status in the other aneurysm cohorts; this revealed no shared polygenic effects. Similarly, linkage disequilibrium–score regression analyses did not show significant correlations between any pair of aneurysm subtypes. Last, we evaluated the evidence for 14 previously published aneurysm risk single‐nucleotide polymorphisms through collaboration in extended aneurysm cohorts, with a total of 6548 cases and 16 843 controls ( IA ) and 4391 cases and 37 904 controls ( AAA ), and found nominally significant associations for IA risk locus 18q11 near RBBP 8 to AAA (odds ratio [ OR ]=1.11; P =4.1×10 −5 ) and for TAA risk locus 15q21 near FBN 1 to AAA ( OR =1.07; P =1.1×10 −3 ). Conclusions Although there was no evidence for polygenic overlap between IAs , AAAs , and TAAs , we found nominally significant effects of two established risk loci for IAs and TAAs in AAAs . These two loci will require further replication.

Objective: To evaluate the quality of available evidence of drug class combinations and their association with the development of acute kidney injury (AKI). Data Sources: A search of MEDLINE and Embase databases was completed using the following terms: “risk factor AND (acute kidney injury or acute kidney failure) AND (drug or medication).” Study Selection and Data Extraction: Inclusion criteria were the following: English language, full-text availability, and at least 1 drug-combination. Each citation was evaluated using the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) criteria. The literature was evaluated using the quality of evidence component of GRADE. No standardized definition of AKI was applied throughout.. Data Synthesis: Out of 2139 total citations, 151 were assessed for full-text review, with 121 citations (6%) meeting inclusion criteria, producing76 unique drug class combinations. Overall, 56 combinations (73.7%) were considered very low quality; 12 (15.8%) were considered low quality. There were 8 (10.5%) of moderate quality, and no combination was considered high quality. 58 (76%) combinations that had a single citation,with a mean of 1.6 citations per drug class combination. The combination of nonsteroidal anti-inflammatory drugs (NSAIDs) and diuretics was reported in 10 citations, the largest number of citations. Conclusions: Our study demonstrates a lack of well-designed studies addressing drug class combination–associated AKI. The combination of NSAIDs and diuretics with or without additional renin-angiotensin aldosterone agents had the strongest level of evidence. Despite limitations, the information included in this review may result in additional scrutiny about combining certain individual nephrotoxic drugs.

Background: Needle biopsy has proven to be a potentially adequate method for initial biopsy of many soft-tissue and bone lesions. To help optimize this procedure, this study sought to test the characteristics of several needles, including a steerable needle. Materials and Methods: Five needle types were tested, including a steerable needle. Animal muscle tissue was used for all testing. The following experiments were performed: (1) sample collection with different needle types, (2) histological analysis of needle track, (3) observation of steerable needle characteristics using CT-guidance. Results: Sample collection: The Menghini 21 g and Chiba 22 g needles were graded as excellent for ease of use and integrity of sample. Histologic evaluation showed good specimen preservation with all needle types. Histological analysis of needle track: tracks created by the Menghini 21 g and Spinal 20 g needles both showed no histologically detectable damage to surrounding tissue. Observation of steerable Menghini needle under CT-guidance: needle advanced easily through tissue, even when maximally curved. Small, large, and double curves were feasible to avoid obstacles and reach targets. There was no deflection or change in position of the needle tip when the stylet was removed. Needle withdrawal did not damage surrounding tissue. Conclusions: Compared to the other needles, the steerable needle was found to be durable and easy to use, allowing for precise navigation around vital structures yielding superior integrity of sample tissue.

Background This study used machine-learning techniques to develop discriminative brain-connectivity biomarkers from resting-state functional magnetic resonance neuroimaging ( rs-fMRI) data that distinguish between individual migraine patients and healthy controls. Methods This study included 58 migraine patients (mean age = 36.3 years; SD = 11.5) and 50 healthy controls (mean age = 35.9 years; SD = 11.0). The functional connections of 33 seeded pain-related regions were used as input for a brain classification algorithm that tested the accuracy of determining whether an individual brain MRI belongs to someone with migraine or to a healthy control. Results The best classification accuracy using a 10-fold cross-validation method was 86.1%. Resting functional connectivity of the right middle temporal, posterior insula, middle cingulate, left ventromedial prefrontal and bilateral amygdala regions best discriminated the migraine brain from that of a healthy control. Migraineurs with longer disease durations were classified more accurately (>14 years; 96.7% accuracy) compared to migraineurs with shorter disease durations (≤14 years; 82.1% accuracy). Conclusions Classification of migraine using rs-fMRI provides insights into pain circuits that are altered in migraine and could potentially contribute to the development of a new, noninvasive migraine biomarker. Migraineurs with longer disease burden were classified more accurately than migraineurs with shorter disease burden, potentially indicating that disease duration leads to reorganization of brain circuitry.

BACKGROUND. Variable response to chemotherapy in acute myeloid leukemia (AML) represents a major treatment challenge. Clinical and genetic features incompletely predict outcome. The value of clinical epigenetic assays for risk classification has not been extensively explored. We assess the prognostic implications of a clinical assay for multilocus DNA methylation on adult patients with de novo AML. METHODS. We performed multilocus DNA methylation assessment using xMELP on samples and calculated a methylation statistic (M-score) for 166 patients from UPENN with de novo AML who received induction chemotherapy. The association of M-score with complete remission (CR) and overall survival (OS) was evaluated. The optimal M-score cut-point for identifying groups with differing survival was used to define a binary M-score classifier. This classifier was validated in an independent cohort of 383 patients from the Eastern Cooperative Oncology Group Trial 1900 (E1900; NCT00049517). RESULTS. A higher mean M-score was associated with death and failure to achieve CR. Multivariable analysis confirmed that a higher M-score was associated with death ( P = 0.011) and failure to achieve CR ( P = 0.034). Median survival was 26.6 months versus 10.6 months for low and high M-score groups. The ability of the M-score to perform as a classifier was confirmed in patients ≤ 60 years with intermediate cytogenetics and patients who achieved CR, as well as in the E1900 validation cohort. CONCLUSION. The M-score represents a valid binary prognostic classifier for patients with de novo AML. The xMELP assay and associated M-score can be used for prognosis and should be further investigated for clinical decision making in AML patients.