Comprehensive multi-omics analysis identified core molecular processes in esophageal cancer and revealed GNGT2 as a potential prognostic marker

BACKGROUND Esophageal cancer is one of the most poorly diagnosed and fatal cancers in the world.Although a series of studies on esophageal cancer have been reported,the molecular pathogenesis of the disease remains elusive.AIM To investigate comprehensively the molecular process of esophageal cancer.METHODS Differential expression analysis was performed to identify differentially expressed genes(DEGs)in different stages of esophageal cancer from The Cancer Genome Atlas data.Exacting gene interaction modules were generated,and hub genes in the module interaction network were found.Further,through survival analysis,methylation analysis,pivot analysis,and enrichment analysis,some important molecules and related functions/pathways were identified to elucidate potential mechanisms in esophageal cancer.RESULTS A total of 7457 DEGs and 14 gene interaction modules were identified.These module genes were significantly involved in the positive regulation of protein transport,gastric acid secretion,insulin-like growth factor receptor binding,and other biological processes as well as p53 signaling pathway,epidermal growth factor signaling pathway,and epidermal growth factor receptor signaling pathway.Transcription factors(including hypoxia inducible factor 1A)and noncoding RNAs(including colorectal differentially expressed and hsa-miR-330-3p)that significantly regulate dysfunction modules were identified.Survival analysis showed that G protein subunit gamma transducin 2(GNGT2)was closely related to survival of esophageal cancer.DEGs with strong methylation regulation ability were identified,including SST and SH3GL2.Furthermore,the expression of GNGT2 was evaluated by quantitative real time polymerase chain reaction,and the results showed that GNGT2 expression was significantly upregulated in esophageal cancer patient samples and cell lines.Moreover,cell counting kit-8 assay revealed that GNGT2 could promote the proliferation of esophageal cancer cell lines.CONCLUSION This study not only revealed the potential regulatory factors involved in the development of esophageal cancer but also deepens our understanding of its underlying mechanism.

Repair mechanism of astrocytes and non-astrocytes in spinal cord injury

BACKGROUND Spinal cord injury(SCI)is a destructive disease that incurs huge personal and social costs,and there is no effective treatment.Although the pathogenesis and treatment mechanism of SCI has always been a strong scientific focus,the pathogenesis of SCI is still under investigation.AIM To determine the key genes based on the modularization of in-depth analysis,in order to identify the repair mechanism of astrocytes and non-astrocytes in SCI.METHODS Firstly,the differences between injured and non-injured spinal cord of astrocyte(HA),injured and non-injured spinal cord of non-astrocyte(FLOW),injured spinal cord of non-injured astrocyte(HA)and non-injured spinal cord of nonastrocyte(FLOW),and non-injured spinal cord of astrocyte(HA)and nonastrocyte(FLOW)were analyzed.The total number of differentially expressed genes was obtained by merging the four groups of differential results.Secondly,the genes were co-expressed and clustered.Then,the enrichment of GO function and KEGG pathway of module genes was analyzed.Finally,non-coding RNA,transcription factors and drugs that regulate module genes were predicted using hypergeometric tests.RESULTS In summary,we obtained 19 expression modules involving 5216 differentially expressed genes.Among them,miR-494,XIST and other genes were differentially expressed in SCI patients,and played an active regulatory role in dysfunction module,and these genes were recognized as the driving genes of SCI.Enrichment results showed that module genes were significantly involved in the biological processes of inflammation,oxidation and apoptosis.Signal pathways such as NF-kappa B/A20,AMPK and MAPK were significantly regulated.In addition,non-coding RNA pivot(including miR-136-5p and let-7d-5p,etc.)and transcription factor pivot(including NFKB1,MYC,etc.)were identified as significant regulatory dysfunction modules.CONCLUSION Overall,this study uncovered a co-expression network of key genes involved in astrocyte and non-astrocyte regulation in SCI.These findings helped to reveal the core dysfunction modules,potential regulatory factors and driving genes of the disease,and to improve our understanding of its pathogenesis.

Decoding transcriptional regulation via a human gene expression predictor

Transcription factors(TFs)regulate cellular activities by controlling gene expression,but a predictive model describing how TFs quantitatively modulate human transcriptomes is lacking.We construct a universal human gene expression predictor named EXPLICIT-Human and utilize it to decode transcriptional regulation.Using the expression of 1613 TFs,the predictor reconstitutes highly accurate transcriptomes for samples derived from a wide range of tissues and conditions.The broad applicability of the predictor indicates that it recapitulates the quantitative relationships between TFs and target genes ubiquitous across tissues.Significant interacting TF-target gene pairs are extracted from the predictor and enable downstream inference of TF regulators for diverse pathways involved in development,immunity,metabolism,and stress response.A detailed analysis of the hematopoiesis process reveals an atlas of key TFs regulating the development of different hematopoietic cell lineages,and a portion of these TFs are conserved between humans and mice.The results demonstrate that our method is capable of delineating the TFs responsible for fate determination.Compared to other existing tools,EXPLICIT-Human shows a better performance in recovering the correct TF regulators.

Genome-and transcriptome-wide association studies provide insights into the genetic basis of natural variation of seed oil content in Brassica napus

Seed oil content(SOC)is a highly important and complex trait in oil crops.Here,we decipher the genetic basis of natural variation in SOC of Brassica napus by genome-and transcriptome-wide association studies using 505 inbred lines.We mapped reliable quantitative trait loci(QTLs)that control SOC in eight environments,evaluated the effect of each QTL on SOC,and analyzed selection in QTL regions during breeding.Six-hundred and ninety-two genes and four gene modules significantly associated with SOC were identified by analyzing population transcriptomes from seeds.A gene prioritization framework,POCKET(prioritizing the candidate genes by incorporating information on knowledge-based gene sets,effects of variants,genome-wide association studies,and transcriptome-wide association studies),was implemented to determine the causal genes in the QTL regions based on multi-omic datasets.A pair of homologous genes,BnPMT6s,in two QTLs were identified and experimentally demonstrated to negatively regulate SOC.This study provides rich genetic resources for improving SOC and valuable insights toward understanding the complex machinery that directs oil accumulation in the seeds of B.napus and other oil crops.