Stoichioproteomics study of differentially expressed proteins and pathways in head and neck cancer

Hypoxia is a prominent feature of head and neck cancer. However, the oxygen element characteristics of proteins and how they adapt to hypoxia microenvironments of head and neck cancer are still unknown. Human genome sequences and proteins expressed data of head and neck cancer were retrieved from pathology atlas of Human Protein Atlas project. Then compared the oxygen and carbon element contents between proteomes of head and neck cancer and normal oral mucosa-squamous epithelial cells, genome locations, pathways, and functional dissection associated with head and neck cancer were also studied. A total of 902 differentially expressed proteins were observed where the average oxygen content is higher than that of the lowly expressed proteins in head and neck cancer proteins. Further, the average oxygen content of the up regulated proteins was 2.54% higher than other. None of their coding genes were distributed on the Y chromosome. The up regulated proteins were enriched in endocytosis, apoptosis and regulation of actin cytoskeleton. The increased oxygen contents of the highly expressed and the up regulated proteins might be caused by frequent activity of cytoskeleton and adapted to the rapid growth and fast division of the head and neck cancer cells. The oxygen usage bias and key proteins may help us to understand the mechanisms behind head and neck cancer in targeted therapy, which lays a foundation for the application of stoichioproteomics in targeted therapy and provides promise for potential treatments for head and neck cancer.

The Role of miR-4256/HOXC8 Signaling Axis in the Gastric Cancer Progression: Evidence From lncRNA-miRNA-mRNA Network Analysis

Gastric cancer is a deadly human malignancy and the molecular mechanisms underlying gastric cancer pathophysiology are very complicated. Thus, further investigations are warranted to decipher the underlying molecular mechanisms. With the development of high-throughput screening and bioinformatics, gene expression profiles with large scale have been performed in gastric cancer. In the present study, we mined The Cancer Genome Atlas (TCGA) database and analyzed the gene expression profiles between gastric cancer tissues and normal gastric tissues. A series of differentially expressed lncRNAs, miRNAs and mRNAs between gastric cancer tissues and normal gastric tissues were identified. Based on the differentially expressed genes, we constructed miRNA-mRNA network, lncRNA-mRNA network and transcriptional factors-mRNA-miRNA-lncRNA network. Furthermore, the Kaplan survival analysis showed that high expression levels of EVX1, GBX2, GCM1, HOXC8, HOXC9, HOXC10, HOXC11, HOXC12 and HOXC13 were all significantly correlated with shorter overall survival of the patients with gastric cancer. On the other hand, low expression level of HOXA13 was associated with shorter overall survival of patients with gastric cancer. Among these hub genes, we performed the in vitro functional studies of HOXC8 in the gastric cancer cells. Knockdown of HOXC8 and overexpression of miR-4256 both significantly repressed the gastric cancer cell proliferation and migration, and miR-4256 repressed the expression of HOXC8 via targeting its 3’ untranslated region in gastric cancer cells. Collectively, our results revealed that a complex interaction networks of differentially expressed genes in gastric cancer, and further functional studies indicated that miR-4256/HOXC8 may be an important axis in regulating gastric cancer progression.

Identification of Novel Diagnostic Biomarkers in Prostate Adenocarcinoma Based on the Stromal-Immune Score and Analysis of the WGCNA and ceRNA Network

Prostate cancer is still a significant global health burden in the coming decade. Novel biomarkers for detection and prognosis are needed to improve the survival of distant and advanced stage prostate cancer patients. The tumor microenvironment is an important driving factor for tumor biological functions. To investigate RNA prognostic biomarkers for prostate cancer in the tumor microenvironment, we obtained relevant data from The Cancer Genome Atlas (TCGA) database. We used the bioinformatics tools Estimation of Stromal and Immune cells in Malignant Tumor tissues using Expression data (ESTIMATE) algorithm and weighted coexpression network analysis (WGCNA) to construct tumor microenvironment stromal-immune score-based competitive endogenous RNA (ceRNA) networks. Then, the Cox regression model was performed to screen RNAs associated with prostate cancer survival. The differentially expressed gene profile in tumor stroma was significantly enriched in microenvironment functions, like immune response, cancer-related pathways, and cell adhesion-related pathways. Based on these differentially expressed genes, we constructed three ceRNA networks with 152 RNAs associated with the prostate cancer tumor microenvironment. Cox regression analysis screened 31 RNAs as the potential prognostic biomarkers for prostate cancer. The most interesting 8 prognostic biomarkers for prostate cancer included lncRNA LINC01082, miRNA hsa-miR-133a-3p, and genes TTLL12, PTGDS, GAS6, CYP27A1, PKP3, and ZG16B. In this systematic study for ceRNA networks in the tumor environment, we screened out potential biomarkers to predict prognosis for prostate cancer. Our findings might apply a valuable tool to improve prostate cancer clinical management and the new target for mechanism study and therapy.

Common and Distinctive Intercellular Communication Patterns in Human Obstructive and Nonobstructive Hypertrophic Cardiomyopathy

Hypertrophic Cardiomyopathy (HCM) is a common inherited disorder characterized by unexplained left ventricular hypertrophy with or without left ventricular outflow tract (LVOT) obstruction. Single-nuclei RNA-sequencing (snRNA-seq) of both obstructive and nonobstructive HCM patient samples has revealed alterations in communication between various cell types, but no direct and integrated comparison between the two HCM phenotypes has been reported. We performed a bioinformatic analysis of HCM snRNA-seq datasets from obstructive and nonobstructive patient samples to identify differentially expressed genes and distinctive patterns of intercellular communication. Differential gene expression analysis revealed 37 differentially expressed genes, predominantly in cardiomyocytes but also in other cell types, relevant to aging, muscle contraction, cell motility, and the extracellular matrix. Intercellular communication was generally reduced in HCM, affecting the extracellular matrix, growth factor binding, integrin binding, PDGF binding, and SMAD binding, but with increases in adenylate cyclase binding, calcium channel inhibitor activity, and serine-threonine kinase activity in nonobstructive HCM. Increases in neuron to leukocyte and dendritic cell communication, in fibroblast to leukocyte and dendritic cell communication, and in endothelial cell communication to other cell types, largely through changes in the expression of integrin-β1 and its cognate ligands, were also noted. These findings indicate both common and distinct physiological mechanisms affecting the pathogenesis of obstructive and nonobstructive HCM and provide opportunities for the personalized management of different HCM phenotypes.

Integrative Multi−Omics Analysis Reveals Candidate Biomarkers for Oral Squamous Cell Carcinoma

Oral squamous cell carcinoma (OSCC) is one of the most common types of cancer worldwide. Due to the lack of early detection and treatment, the survival rate of OSCC remains poor and the incidence of OSCC has not decreased during the past decades. To explore potential biomarkers and therapeutic targets for OSCC, we analyzed differentially expressed genes (DEGs) associated with OSCC using RNA sequencing technology. Methylation−regulated and differentially expressed genes (MeDEGs) of OSCC were further identified via an integrative approach by examining publicly available methylomic datasets together with our transcriptomic data. Protein−protein interaction (PPI) networks of MeDEGs were constructed and highly connected hub MeDEGs were identified from these PPI networks. Subsequently, expression and survival analyses of hub genes were performed using The Cancer Genome Atlas (TCGA) database and the Gene Expression Profiling Interactive Analysis (GEPIA) online tool. A total of 56 upregulated MeDEGs and 170 downregulated MeDEGs were identified in OSCC. Eleven hub genes with high degree of connectivity were picked out from the PPI networks constructed by those MeDEGs. Among them, the expression level of four hub genes (CTLA4, CDSN, ACTN2, and MYH11) were found to be significantly changed in the head and neck squamous carcinoma (HNSC) patients. Three hypomethylated hub genes (CTLA4, GPR29, and TNFSF11) and one hypermethylated hub gene (ISL1) were found to be significantly associated with overall survival (OS) of HNSC patients. Therefore, these hub genes may serve as potential DNA methylation biomarkers and therapeutic targets of OSCC.

Parallel molecular mechanisms underlie convergent evolution of the exaggerated snout phenotype in East African cichlids

Studying instances of convergent evolution of novel phenotypes can shed light on the evolutionary constraints that shape morphological diversity. Cichlid fishes from the East African Great Lakes are a prime model to investigate convergent adaptations. However, most studies on cichlid craniofacial morphologies have primarily considered bony structures, while soft tissue adaptations have been less intensely scrutinised. A rare example of an exaggerated soft tissue phenotype is the formation of a snout flap. This tissue flap develops from the upper lip and has evolved in only one cichlid genus from Lake Malawi and one genus from Lake Tanganyika. To investigate the molecular basis of snout flap convergence, we used mRNA sequencing to compare two species with snout flap (Labeotropheus trewavasae and Ophthalmotilapia nasuta) to their close relatives without snout flaps (Tropheops tropheops and Ophthalmotilapia ventralis) from Lake Tanganyika and Malawi. Our analysis revealed a greater complexity of differential gene expression patterns underlying the snout flap in the younger adaptive radiation of Lake Malawi than in the older Lake Tanganyika radiation. We identified 201 genes that were repeatedly differentially expressed between species with and without the snout flap in both lakes, suggesting that the pathway that gives rise to snout flaps is evolutionarily constrained, even though the flaps play very different functions in each species. The convergently expressed genes are involved in proline and hydroxyproline metabolism, which have been linked to human skin and facial deformities. Additionally, we also found enrichment for transcription factor binding sites upstream of differentially expressed genes such as members of the FOX transcription factor family, especially foxf1 and foxa2, which also showed an increased expression in the flapped snout and are linked to nose morphogenesis in mammals, as well as ap4 (tfap4), a transcription factor showing reduced expression in the flapped snout with an unknown role in the development of craniofacial soft tissues. As genes involved in cichlids snout flap development are associated with many human mid-line facial dysmorphologies, our findings imply a conservation of genes involved in mid-line patterning across vastly distant evolutionary lineages of vertebrates.

Uncovering of Key Pathways and miRNAs for Intracranial Aneurysm Based on Weighted Gene Co-Expression Network Analysis

<b><i>Background:</i></b> Intracranial aneurysm (IA) is a serious cerebrovascular disease. The identification of key regulatory genes can provide research directions for early diagnosis and treatment of IA. <b><i>Methods:</i></b> Initially, the miRNA and mRNA data were downloaded from the Gene Expression Omnibus database. Subsequently, the limma package in R was used to screen for differentially expressed genes. In order to investigate the function of the differentially expressed genes, a functional enrichment analysis was performed. Moreover, weighted gene co-expression network analysis (WGCNA) was performed to identify the hub module and hub miRNAs. The correlations between miRNAs and mRNAs were assessed by constructing miRNA-mRNA regulatory networks. In addition, in vitro validation was performed. Finally, diagnostic analysis and electronic expression verification were performed on the GSE122897 dataset. <b><i>Results:</i></b> In the present study, 955 differentially expressed mRNAs (DEmRNAs, 480 with increased and 475 with decreased expression) and 46 differentially expressed miRNAs (DEmiRNAs, 36 with increased and 10 with decreased expression) were identified. WGCNA demonstrated that the yellow module was the hub module. Moreover, 16 hub miRNAs were identified. A total of 1,124 negatively regulated miRNA-mRNA relationship pairs were identified. Functional analysis demonstrated that DEmRNAs in the targeted network were enriched in vascular smooth muscle contraction and focal adhesion pathways. In addition, the area under the curve of 16 hub miRNAs was &#x3e;0.8. It is implied that 16 hub miRNAs may be used as potential diagnostic biomarkers of IA. <b><i>Conclusion:</i></b> Hub miRNAs and key signaling pathways were identified by bioinformatics analysis. This evidence lays the foundation for understanding the underlying molecular mechanisms of IA and provided potential therapeutic targets for the treatment of this disease.

Whole Blood Transcriptome Analysis in Children with Sickle Cell Anemia

Whole transcriptome RNA-sequencing was performed to quantify RNA expression changes in whole blood samples collected from steady state sickle cell anemia (SCA) and control subjects. Pediatric SCA and control subjects were recruited from Atlanta (GA)—based hospital(s) systems and consented for RNA sequencing. RNA sequencing was performed on an Ion Torrent S5 sequencer, using the Ion Total RNA-seq v2 protocol. Data were aligned to the hg19 reference genome and analyzed in the Partek Genomics studio package (v7.0). 223 genes were differentially expressed between SCA and controls (± 1.5 fold change FDR p &lt; 0.001) and 441 genes show differential transcript expression (± 1.5 fold FDR p &lt; 0.001). Differentially expressed RNA are enriched for hemoglobin associated genes and ubiquitin-proteasome pathway genes. Further analysis shows higher gamma globin gene expression in SCA (33-fold HBG1 and 49-fold HBG2, both FDR p &lt; 0.05), which did not correlate with hemoglobin F protein levels. eQTL analysis identified SNPs in novel non-coding RNA RYR2 gene as having a potential regulatory role in HBG1 and HBG2 expression levels. Gene expression correlation identified JHDM1D-AS1(KDM7A-DT), a non-coding RNA associated with angiogenesis, enhanced GATA1 and decreased JAK-STAT signaling to correlate with HBG1 and HBG2 mRNA levels. These data suggest novel regulatory mechanisms for fetal hemoglobin regulation, which may offer innovative therapeutic approaches for SCA.