OBJECTIVE.—: To validate Anyplex II HPV HR Detection (Anyplex II, Seegene) using FFPE samples.

DESIGN.—: We used 248 stored DNA extracts from cervical cancer FFPE samples collected during 2005-2015 that tested HPV positive using the RHA kit HPV SPF10-LiPA25, v1 (SPF10, Labo Biomedical Products) HPV genotyping assay, manufacturer-validated for FFPE samples.

RESULTS.—: Of the selected 248 samples, 243 were used in our analysis. Consistent with SPF10 genotyping results, Anyplex II detected all 12 oncogenic types and had an overall HPV detection rate of 86.4% (210 of 243 samples). Anyplex II and SPF10 showed very high agreement for the detection of the 2 most important oncogenic genotypes: HPV 16 (219 of 226; 96.9%; 95% CI, 93.7-98.75) and HPV 18 (221 of 226; 97.8%; 95% CI, 94.9-99.3).

METHODS: We performed a genome-wide survival analysis of cause-specific death in 24,023 prostate cancer patients (3,513 disease-specific deaths) from the PRACTICAL and BPC3 consortia. Top findings were assessed for replication in a Norwegian cohort (CONOR).

RESULTS: We observed no significant association between genetic variants and prostate cancer survival.

CONCLUSIONS: Common genetic variants with large impact on prostate cancer survival were not observed in this study.

METHODS: Experimental infections, morphological and molecular characterizations were used for discrimination of a new Sarcocystis species isolated from colubrid snakes and small mammals collected in Thailand, Borneo and China.

RESULTS: We identified a new species, Sarcocystis muricoelognathis sp. nov., that features a relatively wide geographic distribution and infects both commensal and forest-inhabiting intermediate hosts. Sarcocystis sporocysts collected from rat snakes (Coelognathus radiatus, C. flavolineatus) in Thailand induced development of sarcocysts in experimental SD rats showing a type 10a cyst wall ultrastructure that was identical with those found in Rattus norvegicus from China and the forest rat Maxomys whiteheadi in Borneo. Its cystozoites had equal sizes in all intermediate hosts and locations, while sporocysts and cystozoites were distinct from other Sarcocystis species. Partial 28S rRNA sequences of S. muricoelognathis from M. whiteheadi were largely identical to those from R. norvegicus in China but distinct from newly sequenced Sarcocystis zuoi. The phylogeny of the nuclear 18S rRNA gene placed S. muricoelognathis within the so-called S. zuoi complex, including Sarcocystis attenuati, S. kani, S. scandentiborneensis and S. zuoi, while the latter clustered with the new species. However, the phylogeny of the ITS1-region confirmed the distinction between S. muricoelognathis and S. zuoi. Moreover, all three gene trees suggested that an isolate previously addressed as S. zuoi from Thailand (KU341120) is conspecific with S. muricoelognathis. Partial mitochondrial cox1 sequences of S. muricoelognathis were almost identical with those from other members of the group suggesting a shared, recent ancestry. Additionally, we isolated two partial 28S rRNA Sarcocystis sequences from Low's squirrel Sundasciurus lowii that clustered with those of S. scandentiborneensis from treeshews.

RESULTS: We found three distinct matrilineal groups of red muntjacs: Sri Lankan red muntjacs (including the Western Ghats) diverged first from other muntjacs about 1.5 Mya; later northern red muntjacs (including North India and Indochina) and southern red muntjacs (Sundaland) split around 1.12 Mya. The diversification of red muntjacs into these three main lineages was likely promoted by two Pleistocene barriers: one through the Indian subcontinent and one separating the Indochinese and Sundaic red muntjacs. Interestingly, we found a high level of gene flow within the populations of northern and southern red muntjacs, indicating gene flow between populations in Indochina and dispersal of red muntjacs over the exposed Sunda Shelf during the Last Glacial Maximum.

METHODS: We conducted a gene-environment interaction (GxE) analysis including 8,255 cases and 11,900 controls from four pancreatic cancer genome-wide association study (GWAS) datasets (Pancreatic Cancer Cohort Consortium I-III and Pancreatic Cancer Case Control Consortium). Obesity (body mass index ≥30 kg/m2) and diabetes (duration ≥3 years) were the environmental variables of interest. Approximately 870,000 SNPs (minor allele frequency ≥0.005, genotyped in at least one dataset) were analyzed. Case-control (CC), case-only (CO), and joint-effect test methods were used for SNP-level GxE analysis. As a complementary approach, gene-based GxE analysis was also performed. Age, sex, study site, and principal components accounting for population substructure were included as covariates. Meta-analysis was applied to combine individual GWAS summary statistics.

RESULTS: No genome-wide significant interactions (departures from a log-additive odds model) with diabetes or obesity were detected at the SNP level by the CC or CO approaches. The joint-effect test detected numerous genome-wide significant GxE signals in the GWAS main effects top hit regions, but the significance diminished after adjusting for the GWAS top hits. In the gene-based analysis, a significant interaction of diabetes with variants in the FAM63A (family with sequence similarity 63 member A) gene (significance threshold P < 1.25 × 10-6) was observed in the meta-analysis (P GxE = 1.2 ×10-6, P Joint = 4.2 ×10-7).

CONCLUSIONS: This analysis did not find significant GxE interactions at the SNP level but found one significant interaction with diabetes at the gene level. A larger sample size might unveil additional genetic factors via GxE scans.

METHODS: Freshly isolated mouse BM cells were initially exposed to 1,4-BQ at 1.25 to 5 µM for 24 h, followed by miRNAs and TF studies in BM cells. Then, the miRNAs expression was further evaluated in HSPCs of different lineages comprised of myeloid, erythroid and pre-B lymphoid progenitors following 7-14 days of colony forming unit (CFU) assay.