Specific binding of HIV-1 viral protein NCp7 to a unique 35-base RNA stem-loop SL1 is critical for formation and packaging of the genomic RNA dimer found within HIV-1 virions. NCp7 binding stimulates refolding of SL1 from a metastable kissing dimer (KD) into thermodynamically stable linear dimer (LD). Using UV melting, gel electrophoresis and heteronuclear NMR, we investigated effects of various site-specific mutations within the full-length SL1 on temperature- or NCp7-induced refolding in vitro. Refolding involved intramolecular melting of SL1 stems but not dissociation of the intermolecular KD interface. Refolding required only two NCp7 molecules per KD but was limited by the amount of NCp7 present, implying that the protein does not catalytically promote refolding. Efficient refolding depended strictly on the presence and, to a lesser degree, on sequence of a highly conserved G-rich internal loop that normally limits thermal stability of the SL1 stem. Adding two base pairs to the lower stem created a hyperstable SL1 mutant that failed to refold, even when bound by NCp7 at high stoichiometries. NMR analysis of these kinetically trapped mutant RNA-protein complexes indicated that NCp7 initiates refolding by dissociating base pairs in the upper stem of SL1. This study illuminates structural transitions critical for HIV-1 assembly and replication.

Activity of GFR/PI3K/AKT pathway inhibitors in glioblastoma clinical trials has not been robust. We hypothesized variations in the pathway between tumors contribute to poor response. We clustered GBM based on AKT pathway genes and discovered new subtypes then characterized their clinical and molecular features. There are at least 5 GBM AKT subtypes having distinct DNA copy number alterations, enrichment in oncogenes and tumor suppressor genes and patterns of expression for PI3K/AKT/mTOR signaling components. Gene Ontology terms indicate a different cell of origin or dominant phenotype for each subgroup. Evidence suggests one subtype is very sensitive to BCNU or CCNU (median survival 5.8 vs. 1.5 years; BCNU/CCNU vs other treatments; respectively). AKT subtyping advances previous approaches by revealing additional subgroups with unique clinical and molecular features. Evidence indicates it is a predictive marker for response to BCNU or CCNU and PI3K/AKT/mTOR pathway inhibitors. We anticipate Akt subtyping may help stratify patients for clinical trials and augment discovery of class-specific therapeutic targets.

Glioblastoma (GBM) is a highly malignant brain tumor with a dismal prognosis. Gene expression profiling of GBM has revealed clinically relevant tumor subtypes, and this provides exciting opportunities to better understand disease pathogenesis. Results from an increasing number of studies demonstrate a role for the immune response in cancer progression, yet it is unclear how the immune response differs across tumor subtypes and how it affects outcome. Utilizing gene expression data from The Cancer Genome Atlas Project and the Gene Expression Omnibus database, we demonstrate an enrichment of immune response-related gene expression in the mesenchymal subtype of adult GBM (n = 173) and pediatric high-grade gliomas (n = 53). In an independent cohort of pediatric astrocytomas (n = 24) from UCSF, we stratified tumors into subtypes and confirmed these findings. Using novel immune cell-specific gene signatures we demonstrate selective enrichment of microglia/macrophage-related genes in adult and pediatric GBM tumors of the mesenchymal subtype. Furthermore, immunostaining of adult GBM tumors showed significantly higher cell numbers of microglia/macrophages in mesenchymal versus non-mesenchymal tumors (p = 0.04). Interestingly, adult GBM tumors with the shortest survival had significant enrichment of microglia/macrophage-related genes but this was not true for pediatric GBMs. Consistent with an association with poor outcome, immune response-related genes were highly represented in an adult poor prognosis gene signature, with the expression of genes related to macrophage recruitment and activation being most strongly associated with survival (p<0.05) using CoxBoost multivariate modeling. Using a microglia/macrophage high gene signature derived from quantification of tumor-infiltrating cells in adult GBM, we identified enrichment of genes characteristic of CD4 T cells, granulocytes, and microglia/macrophages (n = 573). These studies support a role for the immune response, particularly the microglia/macrophage response, in the biology of an important subset of GBM. Identification of this subset may be important for future therapeutic stratification.

The growth factor receptor/PI3K/AKT pathway is an important drug target in many cancers including Glioblastoma. AKT, a key node in the pathway, has 3 isoforms, AKT1, AKT2 and AKT3. Here we investigate their role in GBM. We find each activated, ser473 phosphorylated isoform is present in some GBMs but expression patterns vary. There is a direct relationship between human GBM patient outcome and both AKT1 and AKT2 mRNA levels, but an inverse relationship with AKT3 mRNA. Furthermore, AKT3 mRNA levels were high in a less aggressive GBM subtype. Overexpressing AKT3 improves survival in a rodent model of GBM and decreases colony forming efficiency, but not growth rate, in glioma cells. Silencing AKT3 slows cell cycle progression in one cell line and increases apoptosis in another. Our studies of AKT3 substrates indicate (1) silencing both AKT2 and AKT3 reduces GSK3 phosphorylation (2) only AKT2 silencing reduces S6 phosphorylation. Since S6 phosphorylation is a marker of mTORC1 activity this indicates that AKT2 activates mTORC1, but AKT3 does not. Our results indicate AKT isoforms have different roles and downstream substrates in GBM. Unexpectedly, they indicate AKT3 delays tumor progression. Therefore strategies that inhibit AKT3 may be unhelpful in some GBM patients.

Purpose

Telomere length-associated SNPs have been associated with incidence and survival rates for malignant brain tumors such as glioma. Here, we study the influence of genetically determined lymphocyte telomere length (LTL) by comparing telomerase associated SNPs between the most common non-malignant brain tumor, i.e. meningioma, and healthy controls.

Methods/patients

One thousand fifty-three (1053) surgically treated meningioma patients and 4437 controls of Western European ancestry were included. Germline DNA was genotyped for 8 SNPs previously significantly associated with LTL. Genotypically-estimated LTL was then calculated by summing each SNP's genotypically-specified telomere length increase in base pairs (bp) for each person. Odds ratios for genotypically-estimated LTL in meningioma cases and controls were evaluated using logistic regression with the first two ancestral principal components and sex as covariates.

Results

Three out of the eight evaluated LTL SNPs were significantly associated with increased meningioma risk (rs10936599: OR 1.14, 95% CI 1.01-1.28, rs2736100: OR 1.13, 95% CI 1.03-1.25, rs9420907: OR 1.22, 95% CI 1.07-1.39). Only rs9420907 remained significant after correction for multiple testing. Average genotypically-estimated LTL was significantly longer for those with meningioma compared to controls [mean cases: 560.2 bp (standard error (SE): 4.05 bp), mean controls: 541.5 bp (SE: 2.02 bp), logistic regression p value = 2.13 × 10^-5].

Conclusion

Increased genotypically-estimated LTL was significantly associated with increased meningioma risk. A role for telomere length in the pathophysiology of meningioma is novel, and could lead to new insights on the etiology of meningioma.

Although genome-wide association studies have identified several susceptibility loci for adult glioma, little is known regarding the potential contribution of genetic variation in the human leukocyte antigen (HLA) region to glioma risk. HLA associations have been reported for various malignancies, with many studies investigating selected candidate HLA polymorphisms. However, no systematic analysis has been conducted in glioma patients, and no investigation into potential non-additive effects has been described. We conducted comprehensive genetic analyses of HLA variants among 1746 adult glioma patients and 2312 controls of European-ancestry from the GliomaScan Consortium. Genotype data were generated with the Illumina 660-Quad array, and we imputed HLA alleles using a reference panel of 5225 individuals in the Type 1 Diabetes Genetics Consortium who underwent high-resolution HLA typing via next-generation sequencing. Case-control comparisons were adjusted for population stratification using ancestry-informative principal components. Because alleles in different loci across the HLA region are linked, we created multigene haplotypes consisting of the genes DRB1, DQA1, and DQB1. Although none of the haplotypes were associated with glioma in additive models, inclusion of a dominance term significantly improved the model for multigene haplotype HLA-DRB1*1501-DQA1*0102-DQB1*0602 (P = 0.002). Heterozygous carriers of the haplotype had an increased risk of glioma [odds ratio (OR) 1.23; 95% confidence interval (CI) 1.01-1.49], while homozygous carriers were at decreased risk compared with non-carriers (OR 0.64; 95% CI 0.40-1.01). Our results suggest that the DRB1*1501-DQA1*0102-DQB1*0602 haplotype may contribute to the risk of glioma in a non-additive manner, with the positive dominance effect partly explained by an epistatic interaction with HLA-DRB1*0401-DQA1*0301-DQB1*0301.

SNPLogic (http://www.snplogic.org) brings together single nucleotide polymorphism (SNP) information from numerous sources to provide a comprehensive SNP selection, annotation and prioritization system for design and analysis of genotyping projects. SNPLogic integrates information about the genetic context of SNPs (gene, chromosomal region, functional location, haplotypes tags and overlap with transcription factor binding sites, splicing sites, miRNAs and evolutionarily conserved regions), genotypic data (allele frequencies per population and validation method), coverage of commercial arrays (ParAllele, Affymetrix and Illumina), functional predictions (modeled on structure and sequence) and connections or established associations (biological pathways, gene ontology terms and OMIM disease terms). The SNPLogic web interface facilitates construction and annotation of user-defined SNP lists that can be saved, shared and exported. Thus, SNPLogic can be used to identify and prioritize candidate SNPs, assess custom and commercial arrays panels and annotate new SNP data with publicly available information. We have found integration of SNP annotation in the context of pathway information and functional prediction scores to be a powerful approach to the analysis and interpretation of SNP-disease association data.

Background

Although increased height has been associated with osteosarcoma risk in previous epidemiologic studies, to the authors' knowledge the relative contribution of stature during different developmental timepoints remains unclear. Furthermore, the question of how genetic determinants of height impact osteosarcoma etiology remains unexplored. Genetic variants associated with stature in previous genome-wide association studies may be biomarkers of osteosarcoma risk.

Methods

The authors tested the associations between osteosarcoma risk and polygenic scores for adult height (416 variants), childhood height (6 variants), and birth length (5 variants) in 864 osteosarcoma cases and 1879 controls of European ancestry.

Results

Each standard deviation increase in the polygenic score for adult height, corresponding to a 1.7-cm increase in stature, was found to be associated with a 1.10-fold increase in the risk of osteosarcoma (95% confidence interval [95% CI], 1.01-1.19; P =.027). Each standard deviation increase in the polygenic score for childhood height, corresponding to a 0.5-cm increase in stature, was associated with a 1.10-fold increase in the risk of osteosarcoma (95% CI, 1.01-1.20; P =.023). The polygenic score for birth length was not found to be associated with osteosarcoma risk (P =.11). When adult and childhood height scores were modeled together, they were found to be independently associated with osteosarcoma risk (P =.037 and P = .043, respectively). An expression quantitative trait locus for cartilage intermediate layer protein 2 (CILP2), rs8103992, was significantly associated with osteosarcoma risk after adjustment for multiple comparisons (odds ratio, 1.35; 95% CI, 1.16-1.56 [P = 7.93×10^-5 and P_adjusted =.034]).

Conclusions

A genetic propensity for taller adult and childhood height attainments contributed independently to osteosarcoma risk in the current study data. These results suggest that the biological pathways affecting normal bone growth may be involved in osteosarcoma etiology.

Background

Chronic lymphocytic leukemia (CLL) is the most common leukemia in the Western world. Shorter mean telomere length in leukemic cells has been associated with more aggressive disease. Germline polymorphisms in telomere maintenance genes affect telomere length and may contribute to CLL susceptibility.

Methods

We collected genome-wide data from two groups of patients with CLL (N = 273) and two control populations (N = 5,725). In ancestry-adjusted case-control comparisons, we analyzed eight SNPs in genes definitively associated with inter-individual variation in leukocyte telomere length (LTL) in prior genome-wide association studies: ACYP2, TERC, NAF1, TERT, OBFC1, CTC1, ZNF208, and RTEL1 RESULTS: Three of the eight LTL-associated SNPs were associated with CLL risk at P < 0.05, including those near: TERC [OR, 1.46; 95% confidence interval (CI), 1.15-1.86; P = 1.8 × 10(-3)], TERT (OR = 1.23; 95% CI, 1.02-1.48; P = 0.030), and OBFC1 (OR, 1.36; 95% CI, 1.08-1.71; P = 9.6 × 10(-3)). Using a weighted linear combination of the eight LTL-associated SNPs, we observed that CLL patients were predisposed to longer LTL than controls in both case-control sets (P = 9.4 × 10(-4) and 0.032, respectively). CLL risk increased monotonically with increasing quintiles of the weighted linear combination.

Conclusions

Genetic variants in TERC, TERT, and OBFC1 are associated with both longer LTL and increased CLL risk. Because the human CST complex competes with shelterin for telomeric DNA, future work should explore the role of OBFC1 and other CST complex genes in leukemogenesis.

Impact

A genetic predisposition to longer telomere length is associated with an increased risk of CLL, suggesting that the role of telomere length in CLL etiology may be distinct from its role in disease progression. Cancer Epidemiol Biomarkers Prev; 25(7); 1043-9. ©2016 AACR.

Background: The genetic etiology of osteosarcoma remains poorly understood despite the publication of a genome-wide association study. Association between HLA genetic variants and risk of several cancers has been observed, but HLA variation is not well captured by standard SNP arrays.Methods: We genotyped 207 Californian pediatric osteosarcoma cases and 696 controls of European ancestry using a custom genome-wide array supplemented with approximately 6,000 additional probes across the MHC region. We subsequently imputed 4-digit classical HLA alleles using a reference panel of 5,225 individuals who underwent high-resolution HLA typing via next-generation sequencing. Case-control comparisons were adjusted for ancestry-informative principal components, and top associations from the discovery analysis underwent replication in an independent dataset of 657 cases and 1,183 controls.Results: Three highly correlated HLA class II variants (r ² = 0.33-0.98) were associated with osteosarcoma risk in discovery analyses, including HLA-DRB1*0301 (OR = 0.52; P = 3.2 × 10^-3), HLA-DQA1*0501 (OR = 0.74; P = 0.031), and HLA-DQB1*0201 (OR = 0.51; P = 2.7 × 10^-3). Similar associations were observed in the replication data (P _range = 0.011-0.037). Meta-analysis of the two datasets identified HLA-DRB1*0301 as the most significantly associated variant (OR_meta = 0.62; P _meta = 1.5 × 10^-4), reaching Bonferroni-corrected statistical significance. The meta-analysis also revealed a second significant independent signal at HLA-DQA1*01:01 (OR_meta = 1.33, P _meta = 1.2 × 10^-3), and a third suggestive association at HLA-DQB1*0302 (OR_meta = 0.73, P _meta = 6.4 × 10^-3).Conclusions: Multiple independent HLA class II alleles may influence osteosarcoma risk.Impact: Additional work is needed to extend our observations to other patient populations and to clarify the potential causal mechanisms underlying these associations. Understanding immunologic contributions to the etiology of osteosarcoma may inform rational therapeutic targets. Cancer Epidemiol Biomarkers Prev; 27(10); 1151-8. ©2018 AACR.