The long noncoding RNA KCNQ1DN suppresses the survival of renal cell carcinoma cells through downregulating c-Myc

Green space exposure and blood DNA methylation at birth and in childhood - A multi-cohort study

Green space exposure has been associated with improved mental, physical and general health. However, the underlying biological mechanisms remain largely unknown. The aim of this study was to investigate the association between green space exposure and cord and child blood DNA methylation. Data from eight European birth cohorts with a total of 2,988 newborns and 1,849 children were used. Two indicators of residential green space exposure were assessed: (i) surrounding greenness (satellite-based Normalized Difference Vegetation Index (NDVI) in buffers of 100 m and 300 m) and (ii) proximity to green space (having a green space ≥ 5,000 m2 within a distance of 300 m). For these indicators we assessed two exposure windows: (i) pregnancy, and (ii) the period from pregnancy to child blood DNA methylation assessment, named as cumulative exposure. DNA methylation was measured with the Illumina 450K or EPIC arrays. To identify differentially methylated positions (DMPs) we fitted robust linear regression models between pregnancy green space exposure and cord blood DNA methylation and between cumulative green space exposure and child blood DNA methylation. Two sensitivity analyses were conducted: (i) without adjusting for cellular composition, and (ii) adjusting for air pollution. Cohort results were combined through fixed-effect inverse variance weighted meta-analyses. Differentially methylated regions (DMRs) were identified from meta-analysed results using the Enmix-combp and DMRcate methods. There was no statistical evidence of pregnancy or cumulative exposures associating with any DMP (False Discovery Rate, FDR, p-value < 0.05). However, surrounding greenness exposure was inversely associated with four DMRs (three in cord blood and one in child blood) annotated to ADAMTS2, KCNQ1DN, SLC6A12 and SDK1 genes. Results did not change substantially in the sensitivity analyses. Overall, we found little evidence of the association between green space exposure and blood DNA methylation. Although we identified associations between surrounding greenness exposure with four DMRs, these findings require replication.

LDA-VGHB: identifying potential lncRNA-disease associations with singular value decomposition, variational graph auto-encoder and heterogeneous Newton boosting machine

Long noncoding RNAs (lncRNAs) participate in various biological processes and have close linkages with diseases. In vivo and in vitro experiments have validated many associations between lncRNAs and diseases. However, biological experiments are time-consuming and expensive. Here, we introduce LDA-VGHB, an lncRNA-disease association (LDA) identification framework, by incorporating feature extraction based on singular value decomposition and variational graph autoencoder and LDA classification based on heterogeneous Newton boosting machine. LDA-VGHB was compared with four classical LDA prediction methods (i.e. SDLDA, LDNFSGB, IPCARF and LDASR) and four popular boosting models (XGBoost, AdaBoost, CatBoost and LightGBM) under 5-fold cross-validations on lncRNAs, diseases, lncRNA-disease pairs and independent lncRNAs and independent diseases, respectively. It greatly outperformed the other methods with its prominent performance under four different cross-validations on the lncRNADisease and MNDR databases. We further investigated potential lncRNAs for lung cancer, breast cancer, colorectal cancer and kidney neoplasms and inferred the top 20 lncRNAs associated with them among all their unobserved lncRNAs. The results showed that most of the predicted top 20 lncRNAs have been verified by biomedical experiments provided by the Lnc2Cancer 3.0, lncRNADisease v2.0 and RNADisease databases as well as publications. We found that HAR1A, KCNQ1DN, ZFAT-AS1 and HAR1B could associate with lung cancer, breast cancer, colorectal cancer and kidney neoplasms, respectively. The results need further biological experimental validation. We foresee that LDA-VGHB was capable of identifying possible lncRNAs for complex diseases. LDA-VGHB is publicly available at https://github.com/plhhnu/LDA-VGHB.

Epigenome-wide analysis of maternal exposure to green space during gestation and cord blood DNA methylation in the ENVIRONAGE cohort

BACKGROUND

DNA methylation programming is sensitive to prenatal life environmental influences, but the impact of maternal exposure to green space on newborns DNA methylation has not been studied yet.

METHODS

We conducted a meta-epigenome-wide association study (EWAS) of maternal exposure to green space during gestation with cord blood DNA methylation in two subsets of the ENVIRONAGE cohort (N = 538). Cord blood DNA methylation was measured by Illumina HumanMethylation 450K in one subset (N = 189) and EPICarray in another (N = 349). High (vegetation height>3 m (m)), low (vegetation height<3 m) and total (including both) high-resolution green space exposures during pregnancy were estimated within 100 m and 1000 m distance around maternal residence. In each subset, we sought cytosine-phosphate-guanine (CpG) sites via linear mixed models adjusted on newborns' sex, ethnicity, gestational age, season at delivery, sampling day, maternal parity, age, smoking, education, and estimated blood cell proportions. EWASs results were meta-analysed via fixed-effects meta-analyses. Differentially methylated regions (DMRs) were identified via ENmix-combp and DMRcate algorithms. Sensitivity analyses were additionally adjusted on PM_2.5, distance to major roads, urbanicity and neighborhood income. In the 450K subset, cord blood expression of differentially methylated genes was measured by Agilent microarrays and associated with green space.

RESULTS

147 DMRs were identified, 85 of which were still significant upon adjustment for PM_2.5, distance to major roads, urbanicity and neighborhood income, including HLA-DRB5, RPTOR, KCNQ1DN, A1BG-AS1, HTR2A, ZNF274, COL11A1 and PRSS36 DMRs. One CpG reached genome-wide significance, while 54 CpGs were suggestive significant (p-values<1e-05). Among them, a CpG, hypermethylated with 100 m buffer total green space, was annotated to PAQR9, whose expression decreased with 1000 m buffer low green space (p-value = 1.45e-05).

CONCLUSIONS

Our results demonstrate that maternal exposure to green space during pregnancy is associated with cord blood DNA methylation, mainly at loci organized in regions, in genes playing important roles in neurological development (e.g., HTR2A).

lncRNAs: Key Regulators of Signaling Pathways in Tumor Glycolysis

In response to overstimulation of growth factor signaling, tumor cells can reprogram their metabolism to preferentially utilize and metabolize glucose to lactate even in the presence of abundant oxygen, which is termed the “Warburg effect” or aerobic glycolysis. Long noncoding RNAs (lncRNAs) are a group of transcripts longer than 200 nucleotides and do not encode proteins. Accumulating evidence suggests that lncRNAs can affect aerobic glycolysis through multiple mechanisms, including the regulation of glycolytic transporters and key rate-limiting enzymes. In addition, maladjusted signaling pathways are critical for glycolysis. Therefore, this article mainly reviews the lncRNAs involved in the regulation of tumor glycolysis key signal pathways in recent years and provides an in-depth understanding of the role of differentially expressed lncRNAs in the key signal pathways of glucose metabolism, which may help to provide new therapeutic targets and new diagnostic and prognostic markers for human cancer.

Global expression profiling of CD10 + /CD19 + pre-B lymphoblasts from Hispanic B-ALL patients correlates with comparative TARGET database analysis

Mexico City has one of the highest incidences of acute lymphoblastic leukemia (ALL) globally, with patients showing low survival, and high relapse rates. To gain more insight into the molecular features of B-ALL in Mexican children, we isolated CD10 + /CD19 + precursor B lymphoblasts from four bone marrow and nine peripheral blood samples of B-ALL patients using a fluorescence-activated cell sorting protocol. The global gene expression profile (BM vs PB) revealed 136 differentially expressed genes; 62 were upregulated (45.6%) and 74 were downregulated (54.4%). Pearson's correlation coefficient was calculated to determine the similarity between pre-B lymphoblast populations. We selected 26 highly significant genes and validated 21 by RT-qPCR (CNN3, STON2, CALN1, RUNX2, GADD45A, CDC45, CDC20, PLK1, AIDA, HCK, LY86, GPR65, PIK3CG, LILRB2, IL7R, TCL1A, DOCK1, HIST1H3G, PTPN14, CD72, and NT5E). The gene set enrichment analysis of the total expression matrix and the ingenuity pathway analysis of the 136 differentially expressed genes showed that the cell cycle was altered in the bone marrow with four overexpressed genes (PLK1, CDC20, CDC45, and GADD45A) and a low expression of IL7R and PIK3CG, which are involved in B cell differentiation. A comparative bioinformatics analysis of 15 bone marrow and 10 peripheral blood samples from Hispanic B-ALL patients collected by the TARGET program, corroborated the genes observed, except for PIK3CG. We conclude the Mexican and the Hispanic B-ALL patients studied present common driver alterations and histotype-specific mutations that could facilitate risk stratification and diagnostic accuracy and serve as potential therapeutic targets.

Long noncoding RNAs as tumorigenic factors and therapeutic targets for renal cell carcinoma

Approximately 338,000 patients are diagnosed with kidney cancer worldwide each year, and renal cell carcinoma (RCC), which is derived from renal epithelium, accounts for more than ninety percent of the malignancy. Next generation RNA sequencing has enabled the identification of novel long noncoding RNAs (lncRNAs) in the past 10 years. Recent studies have provided extensive evidence that lncRNAs bind to chromatin modification proteins, transcription factors, RNA-binding proteins and microRNAs, and thereby modulate gene expression through regulating chromatin status, gene transcription, pre-mRNA splicing, mRNA decay and stability, protein translation and stability. In vitro and in vivo studies have demonstrated that over-expression of oncogenic lncRNAs and silencing of tumor suppressive lncRNAs are a common feature of human RCC, and that aberrant lncRNA expression is a marker for poor patient prognosis, and is essential for the initiation and progression of RCC. Because lncRNAs, compared with mRNAs, are expressed in a tissue-specific manner, aberrantly expressed lncRNAs can be better targeted for the treatment of RCC through screening small molecule compounds which block the interaction between lncRNAs and their binding proteins or microRNAs.

lncRNA SNHG3 acts as a novel Tumor Suppressor and regulates Tumor Proliferation and Metastasis via AKT/mTOR/ERK pathway in Papillary Thyroid Carcinoma

The incidence of papillary thyroid carcinoma (PTC) has been increased rapidly in recent decades. Long noncoding RNAs (lncRNA) are a class of non-protein-coding transcripts and play critical roles in regulating gene expression and influence biological behaviors of multiple cancers, including PTC. Here, we discovered that lncRNA SNHG3 was significantly downregulated in PTC tissues and cell lines, the expression of SNHG3 was negatively correlated with the TNM stage and poor prognosis of PTC patients. Functional studies illustrated that the depletion of SNHG3 via CRISPR/Cas9 technology promoted the proliferation, migration and invasion abilities of PTC cells. Tumor xenograft models confirmed the tumor-promoting role of silenced SNHG3 in vivo. Further mechanistic analyses revealed that knockout of SNHG3 activated the AKT/mTOR/ERK pathway in PTC cell lines and the mTOR inhibitor AZD8055 abrogated the tumor-promoting effect induced by SNHG3 inhibition. Taken together, our findings identified a lncRNA SNHG3 that functions its tumor-suppressor role during PTC development and SNHG3 might serve as a promising candidate for target therapy of PTC.