Identification of methylation markers for the prediction of nodal metastasis in oral and oropharyngeal squamous cell carcinoma

Hypermethylation is an important mechanism for the dynamic regulation of gene expression, necessary for metastasizing tumour cells. Our aim is to identify methylation tumour markers that have a predictive value for the presence of regional lymph node metastases in patients with oral and oropharyngeal squamous cell carcinoma (OOSCC). Significantly differentially expressed genes were retrieved from four reported microarray expression profiles comparing pN0 and pN+ head-neck tumours, and one expression array identifying functionally hypermethylated genes. Additional metastasis-associated genes were included from the literature. Thus genes were selected that influence the development of nodal metastases and might be regulated by methylation. Methylation-specific PCR (MSP) primers were designed and tested on 8 head-neck squamous cell carcinoma cell lines and technically validated on 10 formalin-fixed paraffin-embedded (FFPE) OOSCC cases. Predictive value was assessed in a clinical series of 70 FFPE OOSCC with pathologically determined nodal status. Five out of 28 methylation markers (OCLN, CDKN2A, MGMT, MLH1 and DAPK1) were frequently differentially methylated in OOSCC. Of these, MGMT methylation was associated with pN0 status (P = 0.02) and with lower immunoexpression (P = 0.02). DAPK1 methylation was associated with pN+ status (P = 0.008) but did not associate with protein expression. In conclusion, out of 28 candidate genes, two (7%) showed a predictive value for the pN status. Both genes, DAPK1 and MGMT, have predictive value for nodal metastasis in a clinical group of OOSCC. Therefore DNA methylation markers are capable of contributing to diagnosis and treatment selection in OOSCC. To efficiently identify additional new methylation markers, genome-wide methods are needed.     

Physiological and biochemical characterization of NERICA‐L‐44: a novel source of heat tolerance at the vegetative and reproductive stages in rice

The predicted increase in the frequency and magnitude of extreme heat spikes under future climate can reduce rice yields significantly. Rice sensitivity to high temperatures during the reproductive stage is well documented while the same during the vegetative stage is more speculative. Hence, to identify and characterize novel heat‐tolerant donors for both the vegetative and reproductive stages, 71 rice accessions, including approximately 75% New Rice for Africa (NERICAs), were phenotyped across field experiments during summer seasons in Delhi, India, and in a controlled environment study at International Rice Research Institute , Philippines. NERICA‐L‐44 (NL‐44) recorded high seedling survival (52%) and superior growth and greater reproductive success exposed to 42.2°C (sd ± 2.3) under field conditions. NL‐44 and the heat‐tolerant check N22 consistently displayed lower membrane damage and higher antioxidant enzymes activity across leaves and spikelets. NL‐44 recorded 50–60% spikelet fertility, while N22 recorded 67–79% under controlled environment temperature of 38°C (sd ±1.17), although both had about 87% fertility under extremely hot field conditions. N22 and NL‐44, exposed to heat stress (38°C), had similar pollen germination percent and number of pollen tubes reaching the ovary. NL‐44 maintained low hydrogen peroxide production and non‐photochemical quenching (NPQ) with high photosynthesis while N22 avoided photosystem II damage through high NPQ under high‐temperature stress. NL‐44 with its reproductive stage resilience to extreme heat stress, better antioxidant scavenging ability in both vegetative tissue and spikelets and superior yield and grain quality is identified as a novel donor for increasing heat tolerance at both the vegetative and reproductive stages in rice.     

Oncostatin-M inhibits luteinizing hormone stimulated Leydig cell progenitor formation in vitro

Background  

The initial steps of stem Leydig cell differentiation into steroid producing progenitor cells are thought to take place independent of luteinizing hormone (LH), under the influence of locally produced factors such as leukaemia inhibitory factor (LIF), platelet derived growth factor A and stem cell factor. For the formation of a normal sized Leydig cell population in the adult testis, the presence of LH appears to be essential.     

Comparison of novel and existing methods for detecting differentially methylated regions

Background

Single-probe analyses in epigenome-wide association studies (EWAS) have identified associations between DNA methylation and many phenotypes, but do not take into account information from neighboring probes. Methods to detect differentially methylated regions (DMRs) (clusters of neighboring probes associated with a phenotype) may provide more power to detect associations between DNA methylation and diseases or phenotypes of interest.

Results

We proposed a novel approach, GlobalP, and perform comparisons with 3 methods—DMRcate, Bumphunter, and comb-p—to identify DMRs associated with log triglycerides (TGs) in real GAW20 data before and after fenofibrate treatment. We applied these methods to the summary statistics from an EWAS performed on the methylation data. Comb-p, DMRcate, and GlobalP detected very similar DMRs near the gene CPT1A on chromosome 11 in both the pre- and posttreatment data. In addition, GlobalP detected 2 DMRs before fenofibrate treatment in the genes ETV6 and ABCG1. Bumphunter identified several DMRs on chromosomes 1 and 20, which did not overlap with DMRs detected by other methods.

Conclusions

Our novel method detected the same DMR identified by two existing methods and detected two additional DMRs not identified by any of the existing methods we compared.

     

Gene action,genetic variation,and GWAS: A user-friendly web tool

Fisher’s partitioning of genotypic values and genetic variance is highly relevant in the current era of genome-wide association studies (GWASs). However, despite being more than a century old, a number of persistent misconceptions related to nonadditive genetic effects remain. We developed a user-friendly web tool, the Falconer ShinyApp, to show how the combination of gene action and allele frequencies at causal loci translate to genetic variance and genetic variance components for a complex trait. The app can be used to demonstrate the relationship between a SNP effect size estimated from GWAS and the variation the SNP generates in the population, i.e., how locus-specific effects lead to individual differences in traits. In addition, it can also be used to demonstrate how within and between locus interactions (dominance and epistasis, respectively) usually do not lead to a large amount of nonadditive variance relative to additive variance, and therefore, that these interactions usually do not explain individual differences in a population.