Elevated GAPDH expression is associated with the proliferation and invasion of lung and esophageal squamous cell carcinomas

Construction and analysis of protein-protein interaction network for esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC) is a prevalent malignant tumor of the digestive tract. Clinical findings reveal that the five-year survival rate for mid-to late-stage ESCC patients is merely around 20 %, whereas those diagnosed at an early stage can achieve up to a 95 % survival rate. Consequently, early detection is paramount to improving ESCC patient survival. Protein markers are essential for diagnosing diseases, and the identification of new candidate proteins associated with ESCC through the protein-protein interaction (PPI) network is aimed for in this paper. The PPI network related to ESCC was constructed using protein data, comprising 2094 nodes and 19,660 edges. To assess the nodes' importance in the network, three metrics-degree centrality, betweenness centrality, and closeness centrality-were employed, leading to the identification of 81 key proteins. Subsequently, the biological significance of these proteins in the network was explored, combining biomedical knowledge from three perspectives: network, node, and cluster. The results demonstrated that 52 out of 81 key proteins were confirmed to be linked to ESCC. Among the remaining 29 unreported proteins, 18 displayed significant biological significance, indicating their potential as protein markers related to ESCC.

The clinical significance of endoplasmic reticulum stress related genes in non-small cell lung cancer and analysis of single nucleotide polymorphism for CAV1

In recent years, protein homeostasis imbalance caused by endoplasmic reticulum stress has become a major hallmark of cancer. Studies have shown that endoplasmic reticulum stress is closely related to the occurrence, development, and drug resistance of non-small cell lung cancer, however, the role of various endoplasmic reticulum stress-related genes in non-small cell lung cancer is still unclear. In this study, we established an endoplasmic reticulum stress scores based on the Cancer Genome Atlas for non-small cell lung cancer to reflect patient features and predict prognosis. Survival analysis showed significant differences in overall survival among non-small cell lung cancer patients with different endoplasmic reticulum stress scores. In addition, endoplasmic reticulum stress scores was significantly correlated with the clinical features of non-small cell lung cancer patients, and can be served as an independent prognostic indicator. A nomogram based on endoplasmic reticulum stress scores indicated a certain clinical net benefit, while ssGSEA analysis demonstrated that there was a certain immunosuppressive microenvironment in high endoplasmic reticulum stress scores. Gene Set Enrichment Analysis showed that scores was associated with cancer pathways and metabolism. Finally, weighted gene co-expression network analysis displayed that CAV1 was closely related to the occurrence of non-small cell lung cancer. Therefore, in order to further analyze the role of this gene, Chinese non-smoking females were selected as the research subjects to investigate the relationship between CAV1 rs3779514 and susceptibility and prognosis of non-small cell lung cancer. The results showed that the mutation of rs3779514 significantly reduced the risk of non-small cell lung cancer in Chinese non-smoking females, but no prognostic effect was found. In summary, we proposed an endoplasmic reticulum stress scores, which was an independent prognostic factor and indicated immune characteristics in the microenvironment of non-small cell lung cancer. We also validated the relationship between single nucleotide polymorphism locus of core genes and susceptibility to non-small cell lung cancer.

Edge-based relative entropy as a sensitive indicator of critical transitions in biological systems

BACKGROUND

Disease progression in biosystems is not always a steady process but is occasionally abrupt. It is important but challenging to signal critical transitions in complex biosystems.

METHODS

In this study, based on the theoretical framework of dynamic network biomarkers (DNBs), we propose a model-free method, edge-based relative entropy (ERE), to identify temporal key biomolecular associations/networks that may serve as DNBs and detect early-warning signals of the drastic state transition during disease progression in complex biological systems. Specifically, by combining gene‒gene interaction (edge) information with the relative entropy, the ERE method converts gene expression values into network entropy values, quantifying the dynamic change in a biomolecular network and indicating the qualitative shift in the system state.

RESULTS

The proposed method was validated using simulated data and real biological datasets of complex diseases. The applications show that for certain diseases, the ERE method helps to reveal so-called "dark genes" that are non-differentially expressed but with high ERE values and of essential importance in both gene regulation and prognosis.

CONCLUSIONS

The proposed method effectively identified the critical transition states of complex diseases at the network level. Our study not only identified the critical transition states of various cancers but also provided two types of new prognostic biomarkers, positive and negative edge biomarkers, for further practical application. The method in this study therefore has great potential in personalized disease diagnosis.

Construction and Validation of a Prognostic Model Based on Novel Senescence-Related Genes in Non-Small Cell Lung Cancer Patients with Drug Sensitivity and Tumor Microenvironment

Cellular senescence contributes to cancer pathogenesis and immune regulation. Using the LASSO Cox regression, we developed a 12-gene prognostic signature for lung adenocarcinoma (LUAD) from The Cancer Genome Atlas (TCGA) and a Gene Expression Omnibus (GEO) dataset. We assessed gene expression, drug sensitivity, immune infiltration, and conducted cell line experiments. High-risk LUAD patients showed increased mortality risk and shorter survival (P < 0.001). Senescence-related gene analysis indicated differences in protein phosphorylation and DNA methylation between normal individuals and LUAD patients. The high-risk group showed a positive association with PD-L1 expression (P = 0.003). Single-cell sequencing data suggested PEBP1 might significantly impact T cell infiltration. We predicted potential sensitive compounds for 12 senescence genes and found GAPDH promoted cell line proliferation. We established a novel prognostic system based on a newly identified senescence gene. High-risk patients had elevated immunosuppressive markers, and PEBP1 might influence T cell infiltration significantly. GAPDH, expressed at higher levels in tumors, could affect cancer progression. Our drug prediction model may guide treatment selection.

Exogenous succinate impacts mouse brown adipose tissue mitochondrial proteome and potentiates body mass reduction induced by liraglutide

Obesity is one of the leading noncommunicable diseases in the world. Despite intense efforts to develop strategies to prevent and treat obesity, its prevalence continues to rise worldwide. A recent study has shown that the tricarboxylic acid intermediate succinate increases body energy expenditure by promoting brown adipose tissue thermogenesis through the activation of uncoupling protein-1; this has generated interest surrounding its potential usefulness as an approach to treat obesity. It is currently unknown how succinate impacts brown adipose tissue protein expression, and how exogenous succinate impacts body mass reduction promoted by a drug approved to treat human obesity, the glucagon-like-1 receptor agonist, liraglutide. In the first part of this study, we used bottom-up shotgun proteomics to determine the acute impact of exogenous succinate on the brown adipose tissue. We show that succinate rapidly affects the expression of 177 brown adipose tissue proteins, which are mostly associated with mitochondrial structure and function. In the second part of this study, we performed a short-term preclinical pharmacological intervention, treating diet-induced obese mice with a combination of exogenous succinate and liraglutide. We show that the combination was more efficient than liraglutide alone in promoting body mass reduction, food energy efficiency reduction, food intake reduction, and an increase in body temperature. Using serum metabolomics analysis, we showed that succinate, but not liraglutide, promoted a significant increase in the blood levels of several medium and long-chain fatty acids. In conclusion, exogenous succinate promotes rapid changes in brown adipose tissue mitochondrial proteins, and when used in association with liraglutide, increases body mass reduction.NEW & NOTEWORTHY Exogenous succinate induces major changes in brown adipose tissue protein expression affecting particularly mitochondrial respiration and structural proteins. When given exogenously in drinking water, succinate mitigates body mass gain in a rodent model of diet-induced obesity; in addition, when given in association with the glucagon-like peptide-1 receptor agonist, liraglutide, succinate increases body mass reduction promoted by liraglutide alone.

Exploration of the breast ductal carcinoma in situ signature and its prognostic implications

Following the implementation of breast screening programs, the occurrence of ductal carcinoma in situ (DCIS) as an early type of neoplasia has increased. Although the prognosis is promising, 20%-50% of DCIS patients will progress to invasive ductal carcinoma (IDC) if not treated. It is essential to look for promising biomarkers for predicting DCIS prognosis. The Gene Expression Omnibus (GEO) database was used to explore the expression of genes that differed between DCIS and normal tissue in this investigation. Enrichment analysis was performed to characterize the biological role and intrinsic process pathway. The Cancer Genome Atlas Breast Cancer Dataset was used to categorize the hub genes, and the results were confirmed using the Cytoscape plugin CytoHubba and MCODE. The prognostic ability of the core gene signature was determined through time-dependent receiver operating characteristic (ROC), Kaplan-Meier survival curve, Oncomine databases, and UALCAN databases. In addition, the prognostic value of core genes was verified in proliferation assays. We identified 217 common differentially expressed genes (DEGs) in the present study, with 101 upregulated and 138 downregulated genes. The top genes were obtained from the PPI network (protein-protein interaction). A unique six-gene signature (containing GAPDH, CDH2, BIRC5, NEK2, IDH2, and MELK) was developed for DCIS prognostic prediction. Centered on the Cancer Genome Atlas (TCGA) cohort, the ROC curve showed strong results in prognosis prediction. The six core gene signatures is often overexpressed in DCIS, with a weak prognosis. Furthermore, when breast cancer cells are transfected with small interfering RNAs, downregulation of core gene expression substantially inhibits cell proliferation, revealing a high potential for employing core genes in DCIS prognosis. In conclusion, the current investigation verified the six core genes signatures for prospective DCIS biomarkers, which may aid clinical decision-making for individual care.

A Network Pharmacological Elucidation of the Systematic Treatment Activities and Mechanisms of the Herbal Drug FDY003 Against Esophageal Cancer

Despite accumulating evidence for the value of herbal drugs for cancer treatment, the mechanisms underlying their effects have not been fully elucidated in a systematic manner. In this study, we performed a network pharmacological analysis to elucidate the anti-esophageal cancer (EC) properties of the herbal drug FDY003, a mixture of Artemisia capillaris Thunberg (AcT), Cordyceps militaris (Linnaeus) Link (Cm), and Lonicera japonica Thunberg (LjT). FDY003 reduced human EC cell viability and increased the pharmacological effects of chemotherapeutic drugs. There were 15 active pharmacological chemicals targeting 61 EC-associated genes and proteins in FDY003. The FDY003 targets were key regulators of major oncogenic EC-associated signaling pathways, such as phosphoinositide 3-kinase (PI3K)-Akt, hypoxia-inducible factor (HIF)-1, mitogen-activated protein kinase (MAPK), tumor necrosis factor (TNF), p53, Janus kinase (JAK)-signal transducer and activator of transcription (STAT), erythroblastic leukemia viral oncogene homolog (ErbB), nuclear factor kappa-light-chain-enhancer of activated B cells (NF-kappa B), and vascular endothelial growth factor (VEGF) cascades. These EC-associated genes, proteins, and pathways targeted by FDY003 determine the malignant behaviors of EC cells, including cell death, survival, division, proliferation, and growth. This network pharmacological analysis provides an integrative view of the mechanisms by which FDY003 contributes to EC treatment.

Mechanism of Synsepalum dulcificum Daniell. Inhibiting Lung Adenocarcinoma

Objective: Synsepalum dulcificum Daniell. (SD) is a natural plant fruit and is famous for containing miraculin. It has been reported that SD can be used as an adjuvant treatment to correct patients' loss of taste during the antitumor process, but the effect of SD itself as an antitumor is not clear. In this study, we investigated the mechanism of action of SD on lung adenocarcinoma using network pharmacology. Materials and Methods. The components of SD were identified by liquid chromatography-mass spectrometry, and then the compounds that affect tumor immunity of SD were screened and the related targets were predicted by TCMIO database. At the same time, the results were associated with lung adenocarcinoma targets included in the MalaCards and CTD databases, so as to construct a compound-target action network diagram and explore the mechanism of SD in the treatment of lung adenocarcinoma. In in vitro experiments, cell viability was determined and western blotting was used to detect the related expression of action targets to determine the therapeutic effect of SD. Results. In this experiment, 335 chemical components were identified in SD, and 107 components were related to tumor immunity. After screening by ADME, it was found that 11 compounds might be inhaled into the human body and affect the growth of lung adenocarcinoma. In vitro experiments showed that SD could inhibit the growth of lung adenocarcinoma A549 cells. SD could reduce the expression of PCNA (P < 0.05) and significantly increase the expression of Caspase-3 (P < 0.05). The results of further experiments showed that SD could significantly reduce the phosphorylation of EGFR (P < 0.05), and SD could also effectively inhibit the expression of JAK and STAT3 phosphorylation (P < 0.01) and inhibit the expression of PI3K and AKT phosphorylation (P < 0.01). Conclusion. SD can inhibit the growth of lung adenocarcinoma A549 cells and the potential mechanism was found to be the inhibition of EGFR/JAK/STAT3 and EGFR/PI3K/AKT signaling pathway, and the substance basis for SD to exert antitumor effect may be catechin, taxifolin, betaine, epigallocatechin gallate, erucamide, guanosine, kaempferol, lanosterol, morin, oleanolic acid, and quercetin.

A Five Autophagy-Related Long Non-Coding RNA Prognostic Model for Patients with Lung Adenocarcinoma

Purpose

Lung adenocarcinoma is the most common pathological type among non-small cell lung cancer. Although huge progress has been made in terms of early diagnosis and precision treatment in recent years, the overall 5-year survival rate of a patient remains low. In our study, we try to construct an autophagy-related lncRNA prognostic signature that may guide clinical practice.

Methods

The mRNA and lncRNA expression matrix of lung adenocarcinoma patients were retrieved from the TCGA database. Next, we constructed a co-expression network of lncRNAs and autophagy-related genes. Lasso regression and multivariate Cox regression were then applied to establish a prognostic risk model. Subsequently, a risk score was generated to differentiate the high and low risk groups and a ROC curve and nomogram to visualize the predictive ability of the current signature. Finally, gene ontology and pathway enrichment analysis were executed via GSEA.

Results

A total of 1,703 autophagy-related lncRNAs were screened and five autophagy-related lncRNAs (LINC01137, AL691432.2, LINC01116, AL606489.1, and HLA-DQB1-AS1) were finally included in our signature. Judging from univariate (HR=1.075, 95% CI=1.046–1.104) and multivariate (HR=1.088, 95% CI=1.057−1.120) Cox regression analysis, the risk score is an independent factor for LUAD patients. Further, the AUC value based on the risk score for 1-year, 3-years, and 5-years, was 0.735, 0.672, and 0.662, respectively, indicating a reliable model. Drug sensitivity analysis revealed low risk patients were more sensitive to Gemcitabine and Gefitinib, while high risk patients had a better response to Paclitaxel and Erlotinib. Moreover, the lncRNAs included in our signature were primarily enriched in the autophagy process, metabolism, p53 pathway, and JAK/STAT pathway. Finally, a multi-omics analysis of correlated genes showed CFLAR overexpressed in the tumor sample, while GAPDH and MLST8 had a slightly higher expression in the normal sample.

Conclusion

Overall, our study indicated that the prognostic model we generated had certain predictability for LUAD patients’ prognosis and the related genes might be potential biomarkers and therapeutic targets.

Identification of Key Genes Related to CD8+ T-Cell Infiltration as Prognostic Biomarkers for Lung Adenocarcinoma

Background

CD8+ T cells are one of the central effector cells in the immune microenvironment. CD8+ T cells play a vital role in the development and progression of lung adenocarcinoma (LUAD). This study aimed to explore the key genes related to CD8+ T-cell infiltration in LUAD and to develop a novel prognosis model based on these genes.

Methods

With the use of the LUAD dataset from The Cancer Genome Atlas (TCGA), the differentially expressed genes (DEGs) were analyzed, and a co-expression network was constructed by weighted gene co-expression network analysis (WGCNA). Combined with the CIBERSORT algorithm, the gene module in WGCNA, which was the most significantly correlated with CD8+ T cells, was selected for the subsequent analyses. Key genes were then identified by co-expression network analysis, protein–protein interactions network analysis, and least absolute shrinkage and selection operator (Lasso)-penalized Cox regression analysis. A risk assessment model was built based on these key genes and then validated by the dataset from the Gene Expression Omnibus (GEO) database and multiple fluorescence in situ hybridization experiments of a tissue microarray.

Results

Five key genes (MZT2A, ALG3, ATIC, GPI, and GAPDH) related to prognosis and CD8+ T-cell infiltration were identified, and a risk assessment model was established based on them. We found that the risk score could well predict the prognosis of LUAD, and the risk score was negatively related to CD8+ T-cell infiltration and correlated with the advanced tumor stage. The results of the GEO database and tissue microarray were consistent with those of TCGA. Furthermore, the risk score was higher significantly in tumor tissues than in adjacent lung tissues and was correlated with the advanced tumor stage.

Conclusions

This study may provide a novel risk assessment model for prognosis prediction and a new perspective to explore the mechanism of tumor immune microenvironment related to CD8+ T-cell infiltration in LUAD.

Inverse molecular docking reveals a novel function of thymol: Inhibition of fat deposition induced by high-dose glucose in Caenorhabditis elegans

As a natural product isolated from thyme oil in thyme, thymol (2-isopropyl-5-methylphenol) harbors antiviral, antioxidant, and other properties, and thus could be potentially used for the treatment of various diseases. However, the function of thymol has not been comprehensively studied. Here, we applied an inverse molecular docking approach to identify unappreciated functions of thymol. Potential targets of thymol in humans were identified by the server of DRAR-CPI, and targets of interest were then assessed by GO and KEGG pathway analysis. Subsequently, homologous proteins of these targets in Caenorhabditis elegans were identified by Blast tool, and their three-dimensional structures were achieved using Swiss-Model workspace. Interaction between thymol and the targeted proteins in worms was verified using AutoDock 4.0. Analyses of the targets revealed that thymol could be potentially involved in the glycolysis/gluconeogenesis and fatty acid degradation pathways. To verify the activity of thymol on lipid deposition in vivo, the C. elegans model was established. The lipid content of nematodes induced by high-dose glucose was determined by Oil Red O and Nile Red staining, and gene expression was assessed by qRT-PCR. The results showed that thymol might lead to the acceleration of β-oxidation by upregulating cpt-1, aco, fabp, and tph-1, causing the descent of lipid content in nematodes. Our findings indicated that thymol could be potentially used for the treatment of chronic metabolic diseases associated with increased fatty acid deposition.

Development of a gene signature associated with iron metabolism in lung adenocarcinoma

There are few studies on the role of iron metabolism genes in predicting the prognosis of lung adenocarcinoma (LUAD). Therefore, our research aims to screen key genes and to establish a prognostic signature that can predict the overall survival rate of lung adenocarcinoma patients. RNA-Seq data and corresponding clinical materials of 594 adenocarcinoma patients from The Cancer Genome Atlas(TCGA) were downloaded. GSE42127 of Gene Expression Omnibus (GEO) database was further verified. The multi-gene prognostic signature was constructed by the Cox regression model of the Least Absolute Shrinkage and Selection Operator (LASSO). We constructed a prediction signature with 12 genes (HAVCR1, SPN, GAPDH, ANGPTL4, PRSS3, KRT8, LDHA, HMMR, SLC2A1, CYP24A1, LOXL2, TIMP1), and patients were split into high and low-risk groups. The survival graph results revealed that the survival prognosis between the high and low-risk groups was significantly different (TCGA: P < 0.001, GEO: P = 0.001). Univariate and multivariate Cox regression analysis confirmed that the risk value is a predictor of patient OS (P < 0.001). The area under the time-dependent ROC curve (AUC) indicated that our signature had a relatively high true positive rate when predicting the 1-year, 3-year, and 5-year OS of the TCGA cohort, which was 0.735, 0.711, and 0.601, respectively. In addition, immune-related pathways were highlighted in the functional enrichment analysis. In conclusion, we developed and verified a 12-gene prognostic signature, which may be help predict the prognosis of lung adenocarcinoma and offer a variety of targeted options for the precise treatment of lung cancer.

Transcriptomic analysis identifies differences in gene expression in actinic keratoses after treatment with imiquimod and between responders and non responders

The presence of actinic keratoses (AKs) increases a patient’s risk of developing squamous cell carcinoma by greater than six-fold. We evaluated the effect of topical treatment with imiquimod on the tumor microenvironment by measuring transcriptomic differences in AKs before and after treatment with imiquimod 3.75%. Biopsies were collected prospectively from 21 patients and examined histologically. RNA was extracted and transcriptomic analyses of 788 genes were performed using the nanoString assay. Imiquimod decreased number of AKs by study endpoint at week 14 (p < 0.0001). Post-imiquimod therapy, levels of CDK1, CXCL13, IL1B, GADPH, TTK, ILF3, EWSR1, BIRC5, PLAUR, ISG20, and C1QBP were significantly lower (adjusted p < 0.05). Complete responders (CR) exhibited a distinct pattern of inflammatory gene expression pre-treatment relative to incomplete responders (IR), with alterations in 15 inflammatory pathways (p < 0.05) reflecting differential expression of 103 genes (p < 0.05). Presence of adverse effects was associated with improved treatment response. Differences in gene expression were found between pre-treatment samples in CR versus IR, suggesting that higher levels of inflammation pre-treament may play a part in regression of AKs. Further characterization of the immune micro-environment in AKs may help develop biomarkers predictive of response to topical immune modulators and may guide therapy.

Quantitative Acetylomics Revealed Acetylation-Mediated Molecular Pathway Network Changes in Human Nonfunctional Pituitary Neuroendocrine Tumors

Acetylation at lysine residue in a protein mediates multiple cellular biological processes, including tumorigenesis. This study aimed to investigate the acetylated protein profile alterations and acetylation-mediated molecular pathway changes in human nonfunctional pituitary neuroendocrine tumors (NF-PitNETs). The anti-acetyl antibody-based label-free quantitative proteomics was used to analyze the acetylomes between NF-PitNETs (n = 4) and control pituitaries (n = 4). A total of 296 acetylated proteins with 517 acetylation sites was identified, and the majority of which were significantly down-acetylated in NF-PitNETs (p<0.05 or only be quantified in NF-PitNETs/controls). These acetylated proteins widely functioned in cellular biological processes and signaling pathways, including metabolism, translation, cell adhesion, and oxidative stress. The randomly selected acetylated phosphoglycerate kinase 1 (PGK1), which is involved in glycolysis and amino acid biosynthesis, was further confirmed with immunoprecipitation and western blot in NF-PitNETs and control pituitaries. Among these acetylated proteins, 15 lysine residues within 14 proteins were down-acetylated and simultaneously up-ubiquitinated in NF-PitNETs to demonstrate a direct competition relationship between acetylation and ubiquitination. Moreover, the potential effect of protein acetylation alterations on NF-PitNETs invasiveness was investigated. Overlapping analysis between acetylomics data in NF-PitNETs and transcriptomics data in invasive NF-PitNETs identified 26 overlapped molecules. These overlapped molecules were mainly involved in metabolism-associated pathways, which means that acetylation-mediated metabolic reprogramming might be the molecular mechanism to affect NF-PitNET invasiveness. This study provided the first acetylomic profiling and acetylation-mediated molecular pathways in human NF-PitNETs, and offered new clues to elucidate the biological functions of protein acetylation in NF-PitNETs and discover novel biomarkers for early diagnosis and targeted therapy of NF-PitNETs.

Aberrant Methylation and Differential Expression of SLC2A1, TNS4, GAPDH, ATP8A2, and CASZ1 Are Associated with the Prognosis of Lung Adenocarcinoma

Lung cancer is one of the leading triggers for cancer death worldwide. In this study, the relationship of the aberrantly methylated and differentially expressed genes in lung adenocarcinoma (LUAD) with cancer prognosis was investigated, and 5 feature genes were identified eventually. Specifically, we firstly downloaded the LUAD-related mRNA expression profile (including 57 normal tissue samples and 464 LUAD tissue samples) and Methy450 expression data (including 32 normal tissue samples and 373 LUAD tissue samples) from the TCGA database. The package "limma" was used to screen differentially expressed genes and aberrantly methylated genes, which were intersected for identifying the hypermethylated downregulated genes (DGs Hyper) and the hypomethylated upregulated genes (UGs Hypo). GO annotation and KEGG pathway enrichment analysis were further performed, and it was found that these DGs Hyper and UGs Hypo were predominantly activated in the biological processes and signaling pathways such as the regulation of vasculature development, DNA-binding transcription activator activity, and Ras signaling pathway, indicating that these genes play a vital role in the initiation and progression of LUAD. Additionally, univariate and multivariate Cox regression analyses were conducted to find the genes significantly associated with LUAD prognosis. Five genes including SLC2A1, TNS4, GAPDH, ATP8A2, and CASZ1 were identified, with the former three highly expressed and the latter two poorly expressed in LUAD, indicating poor prognosis of LUAD patients as judged by survival analysis.

Investigating the Role of Telomere and Telomerase Associated Genes and Proteins in Endometrial Cancer

Endometrial cancer (EC) is the commonest gynaecological malignancy. Current prognostic markers are inadequate to accurately predict patient survival, necessitating novel prognostic markers, to improve treatment strategies. Telomerase has a unique role within the endometrium, whilst aberrant telomerase activity is a hallmark of many cancers. The aim of the current in silico study is to investigate the role of telomere and telomerase associated genes and proteins (TTAGPs) in EC to identify potential prognostic markers and therapeutic targets. Analysis of RNA-seq data from The Cancer Genome Atlas identified differentially expressed genes (DEGs) in EC (568 TTAGPs out of 3467) and ascertained DEGs associated with histological subtypes, higher grade endometrioid tumours and late stage EC. Functional analysis demonstrated that DEGs were predominantly involved in cell cycle regulation, while the survival analysis identified 69 DEGs associated with prognosis. The protein-protein interaction network constructed facilitated the identification of hub genes, enriched transcription factor binding sites and drugs that may target the network. Thus, our in silico methods distinguished many critical genes associated with telomere maintenance that were previously unknown to contribute to EC carcinogenesis and prognosis, including NOP56, WFS1, ANAPC4 and TUBB4A. Probing the prognostic and therapeutic utility of these novel TTAGP markers will form an exciting basis for future research.

Glycolytic biomarkers predict transformation in patients with follicular lymphoma

Follicular lymphoma (FL) is an indolent neoplasia comprising approximately 20% of lymphomas. FL is generally considered incurable, with a median survival exceeding 10 years. A subset of FL patients experiences histological transformation (HT) to a more aggressive lymphoma, resulting in markedly poorer clinical outcome, with a reduced median survival after transformation of 1–2 years. Early, reliable prediction of HT would be valuable in the clinical setting, allowing pre-emptive therapeutic intervention. We previously used proteomics to identify the glycolytic enzymes fructose-bisphosphate aldolase A (aldolase A) and glyceraldehyde-3-phosphate dehydrogenase (GAPDH) as candidate predictors of FL transformation. Now, we use immunohistochemistry to evaluate expression of these enzymes in paired primary FLs from patients with (n = 41) or without subsequent HT (n = 49), to test their value as predictive biomarkers. At initial FL diagnosis, patients with subsequent HT had significantly higher expression of aldolase A and GAPDH (p<0.001 and p<0.01) compared with patients without HT. Furthermore, high expression of aldolase A and GAPDH was associated with significantly shorter transformation free survival (p = 0.018, p = 0.001). These data suggest that high expression of aldolase A and GAPDH, may indicate increased metabolic turnover, and that these enzymes may be useful biomarkers in primary FL for predicting the risk of subsequent lymphoma transformation.

Glyceraldehyde-3-phosphate Dehydrogenase is a Multifaceted Therapeutic Target

Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) is a glycolytic enzyme whose role in cell metabolism and homeostasis is well defined, while its function in pathologic processes needs further elucidation. Depending on the cell context, GAPDH may bind a number of physiologically important proteins, control their function and correspondingly affect the cell’s fate. These interprotein interactions and post-translational modifications of GAPDH mediate its cytotoxic or cytoprotective functions in the manner of a Janus-like molecule. In this review, we discuss the functional features of the enzyme in cellular physiology and its possible involvement in human pathologies. In the last part of the article, we describe drugs that can be employed to modulate this enzyme’s function in some pathologic states.

Screening and identification of key biomarkers in lung squamous cell carcinoma by bioinformatics analysis

The high mortality rate of lung squamous cell carcinoma (LUSC) is in part due to the lack of early detection of its biomarkers. The identification of key molecules involved in LUSC is therefore required to improve clinical diagnosis and treatment outcomes. The present study used the microarray datasets GSE31552, GSE6044 and GSE12428 from the Gene Expression Omnibus database to identify differentially expressed genes (DEGs). Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analyses were conducted to construct the protein-protein interaction network of DEGs and hub genes module using STRING and Cytoscape. The 67 DEGs identified consisted of 42 upregulated genes and 25 downregulated genes. The pathways predicted by KEGG and GO enrichment analyses of DEGs mainly included cell cycle, cell proliferation, glycolysis or gluconeogenesis, and tetrahydrofolate metabolic process. Further analysis of the University of California Santa Cruz and ONCOMINE databases identified 17 hub genes. Overall, the present study demonstrated hub genes that were closely associated with clinical tissue samples of LUSC, and identified TYMS, CCNB2 and RFC4 as potential novel biomarkers of LUSC. The findings of the present study contribute to an improved understanding of the molecular mechanisms of carcinogenesis and progression of LUSC, and assist with the identification of potential diagnostic and therapeutic targets of LUSC.

Serum anti-GAPDH autoantibody levels reflect the severity of cervical lesions: A potential serum biomarker for cervical cancer screening

Recent studies have indicated that a certain level of autoantibodies may be essential for maintaining good health as well as preventing cancer development, and that the levels of serum autoantibodies can decline during malignant progression. The aim of the present study was to identify such an autoantibody-based biomarker for screening cervical lesions. An autoantigen reactive with healthy female sera was detected in the cytosolic fraction of HeLa cells, a cervical cancer cell line, and identified. Serum immunoglobulin (Ig)-G and IgM levels against the purified autoantigen in normal, cervical intraepithelial neoplasias (CINs) I, II and III, and cervical cancer were compared using ELISAs. The autoantigen in HeLa cells was identified to be GAPDH. The serum levels of anti-HeLa-GAPDH IgG decreased with increasing severity of cervical lesions, and similar decreases in IgM levels were revealed. Notably, the anti-HeLa-GAPDH IgG level was discovered to discriminate cervical cancer from normal samples with 80.0% sensitivity and 96.6% specificity. The serum anti-HeLa-GAPDH autoantibody level, as a single parameter, is a promising serum biomarker for screening cervical lesions.

The CIMP-high phenotype is associated with energy metabolism alterations in colon adenocarcinoma

BACKGROUND

CpG island methylator phenotype (CIMP) is found in 15-20% of malignant colorectal tumors and is characterized by strong CpG hypermethylation over the genome. The molecular mechanisms of this phenomenon are not still fully understood. The development of CIMP is followed by global gene expression alterations and metabolic changes. In particular, CIMP-low colon adenocarcinoma (COAD), predominantly corresponded to consensus molecular subtype 3 (CMS3, "Metabolic") subgroup according to COAD molecular classification, is associated with elevated expression of genes participating in metabolic pathways.

METHODS

We performed bioinformatics analysis of RNA-Seq data from The Cancer Genome Atlas (TCGA) project for CIMP-high and non-CIMP COAD samples with DESeq2, clusterProfiler, and topGO R packages. Obtained results were validated on a set of fourteen COAD samples with matched morphologically normal tissues using quantitative PCR (qPCR).

RESULTS

Upregulation of multiple genes involved in glycolysis and related processes (ENO2, PFKP, HK3, PKM, ENO1, HK2, PGAM1, GAPDH, ALDOA, GPI, TPI1, and HK1) was revealed in CIMP-high tumors compared to non-CIMP ones. Most remarkably, the expression of the PKLR gene, encoding for pyruvate kinase participating in gluconeogenesis, was decreased approximately 20-fold. Up to 8-fold decrease in the expression of OGDHL gene involved in tricarboxylic acid (TCA) cycle was observed in CIMP-high tumors. Using qPCR, we confirmed the increase (4-fold) in the ENO2 expression and decrease (2-fold) in the OGDHL mRNA level on a set of COAD samples.

CONCLUSIONS

We demonstrated the association between CIMP-high status and the energy metabolism changes at the transcriptomic level in colorectal adenocarcinoma against the background of immune pathway activation. Differential methylation of at least nine CpG sites in OGDHL promoter region as well as decreased OGDHL mRNA level can potentially serve as an additional biomarker of the CIMP-high status in COAD.

Effect of Derris scandens extract on a human hepatocellular carcinoma cell line

The incidence rate of hepatocellular carcinoma (HCC) remains high in numerous countries, including Thailand. There are numerous different lines of HCC treatment; however, various side effects and the resistance of cancer cells during treatment remain issues. At present, traditionally used herb plants have been widely used as alternatives to cancer therapy. Derris scandens is a Thai traditional herb which is commonly found in Thailand and widely used as a traditional medicine for numerous different diseases. The cytotoxicity of D. scandens ethanolic extract on a HCC cell line (HCC-S102) was determined using an MTT assay. Following treatment with D. scandens ethanolic extract, the induction of apoptosis was determined by Annexin V and dead cell assays, and then confirmed by the upregulation of cleaved poly(ADP-ribose) polymerase. Furthermore, a proteomic approach was used in order to study protein alteration upon treatment with D. scandens ethanolic extract coupled with liquid chromatography-tandem mass spectrometry analysis for protein identification. The results suggested that D. scandens ethanolic extract resulted in cytotoxicity against HCC-S102 cells, as the half-maximal inhibitory concentration values were 36.0±1.0, 29.6±0.6, and 22.6±1.5 µg/ml at 24, 48 and 72 h, respectively. Apoptotic cells were induced following treatment with D. scandens. The comparative proteomic profiles of D. scandens ethanolic extract-treated and untreated cells revealed various protein targets for anticancer activity including heterogeneous nuclear ribonucleoprotein (hnRNP) K, hnRNP A2/B1, stomatin-like 2 and GAPDH. In the present study, the anticancer activity of D. scandens ethanolic extract was demonstrated to affect the cell proliferation of HCC-S102 via an apoptotic pathway. The alteration in these proteins provides a better understanding of the mechanism of action of D. scandens, which may be a promising anticancer agent for the treatment of patients with HCC in the future.

Cancer Characteristic Gene Selection via Sample Learning Based on Deep Sparse Filtering

Identification of characteristic genes associated with specific biological processes of different cancers could provide insights into the underlying cancer genetics and cancer prognostic assessment. It is of critical importance to select such characteristic genes effectively. In this paper, a novel unsupervised characteristic gene selection method based on sample learning and sparse filtering, Sample Learning based on Deep Sparse Filtering (SLDSF), is proposed. With sample learning, the proposed SLDSF can better represent the gene expression level by the transformed sample space. Most unsupervised characteristic gene selection methods did not consider deep structures, while a multilayer structure may learn more meaningful representations than a single layer, therefore deep sparse filtering is investigated here to implement sample learning in the proposed SLDSF. Experimental studies on several microarray and RNA-Seq datasets demonstrate that the proposed SLDSF is more effective than several representative characteristic gene selection methods (e.g., RGNMF, GNMF, RPCA and PMD) for selecting cancer characteristic genes.

Glyceraldehyde-3-phosphate dehydrogenase promotes liver tumorigenesis by modulating phosphoglycerate dehydrogenase

Up-regulated glyceraldehyde-3-phosphate dehydrogenase (GAPDH) is observed in multiple cancers with unclear mechanism. Using GAPDH transgenic mouse and a mouse model of diethylnitrosamine-induced hepatocellular carcinoma (HCC), here we show that GAPDH overexpression aggravated tumor development by activating cell proliferation and inflammation. In cultured hepatic cells, overexpression of GAPDH or a catalytic domain-deleted GAPDH (GAPDH^ΔCD ) affected metabolism, up-regulated phosphoglycerate dehydrogenase (PHGDH), increased histone methylation levels, and promoted proliferation. Consistently, inhibition of GAPDH by short hairpin RNA reprogrammed metabolism down-regulated PHGDH and histone methylation, and inhibited proliferation. The xenograft study suggested that HepG2 cells overexpressing GAPDH or GAPDH^ΔCD similarly promoted tumor development, whereas knockdown PHGDH in GAPDH overexpressing cells significantly inhibited tumor development. In liver sections of HCC patients, increased GAPDH staining was found to be positively correlated with PHGDH and histone methylation staining.

CONCLUSION

GAPDH increases histone methylation levels by up-regulating PHGDH, promoting diversion from glycolysis to serine biosynthesis, and consequently accelerating HCC development. (Hepatology 2017;66:631-645).

Temporal and spatial expression of glyceraldehyde 3-phosphate dehydrogenase (Gapdh) in the mouse placenta

Glucose metabolism in trophoblast cells is essential to provide the required energy for the development and function of the placenta. Glyceraldehyde 3-phosphate dehydrogenase (Gapdh), a key enzyme in the glycolysis pathway has been considered ubiquitously expressed in cells. There is, however, a growing body of evidence suggesting that Gapdh has many functions in pathways unrelated to glucose metabolism. In the present study, we show that GAPDH expression and sub-cellular localization changes through gestation in the mouse placenta. Our findings raise the possibility that GAPDH has multiple functions in trophoblast cells and the developing placenta, while also cautioning against its use as an endogenous reference or standard for gene expression in the placenta.

Recent mass spectrometry-based proteomics for biomarker discovery in lung cancer, COPD, and asthma

INTRODUCTION

Lung cancer and related diseases have been one of the most common causes of deaths worldwide. Genomic-based biomarkers may hardly reflect the underlying dynamic molecular mechanism of functional protein interactions, which is the center of a disease. Recent developments in mass spectrometry (MS) have made it possible to analyze disease-relevant proteins expressed in clinical specimens by proteomic challenges. Areas covered: To understand the molecular mechanisms of lung cancer and its subtypes, chronic obstructive pulmonary disease (COPD), asthma and others, great efforts have been taken to identify numerous relevant proteins by MS-based clinical proteomic approaches. Since lung cancer is a multifactorial disease that is biologically associated with asthma and COPD among various lung diseases, this study focused on proteomic studies on biomarker discovery using various clinical specimens for lung cancer, COPD, and asthma. Expert commentary: MS-based exploratory proteomics utilizing clinical specimens, which can incorporate both experimental and bioinformatic analysis of protein-protein interaction and also can adopt proteogenomic approaches, makes it possible to reveal molecular networks that are relevant to a disease subgroup and that could differentiate between drug responders and non-responders, good and poor prognoses, drug resistance, and so on.

Identification of reference genes and miRNAs for qRT-PCR in human esophageal squamous cell carcinoma

It is important to select an appropriate reference gene and miRNA when using quantitative real-time polymerase chain reaction (qRT-PCR) to analyze gene and miRNA expression. However, many commonly used reference genes and miRNAs are not stably expressed and therefore not suitable for normalization or quantification of qRT-PCR data. This study aims to identify appropriate reference genes and miRNAs for use in human esophageal squamous carcinoma qRT-PCR analysis. Using data provided by The Cancer Genome Atlas, we identified DDX5, LAPTM4A, P4HB, RHOA, miR-28-5p, miR-34a-5p, and miR-186-5p as candidate reference genes and miRNAs. We used qRT-PCR to verify the expression levels of these candidates and another seven commonly used reference genes and miRNAs. A set of 50 paired human normal esophageal tissues and squamous cell carcinoma samples were used in the analysis. We then used geNorm and NormFinder to analyze the results. DDX5, LAPTM4A, RHOA, ACTB, RNU48, miR-28-5p, miR-34a-5p, and miR-186-5p were stably expressed, indicating they are suitable for used as references in qRT-PCR analysis of esophageal squamous cell carcinoma. However, expression levels of 18s rRNA, GAPDH, P4HB, 5s rRNA, U6, and RNU6B varied greatly between esophageal normal and squamous cell carcinoma samples, indicating that they are not suitable for use as references in the qRT-PCR analysis of esophageal squamous cell carcinoma.

H2A/K pseudogene mutation may promote cell proliferation

Little attention has been paid to the histone H2A/K pseudogene. Results from our laboratory showed that 7 of 10 kidney cancer patients carried a mutant H2A/K pseudogene; therefore, we were interested in determining the relationship between mutant H2A/K and cell proliferation. We used shotgun and label-free proteomics methods to study whether mutant H2A/K lncRNAs affected cell proliferation. Quantitative proteomic analysis indicated that the expression of mutant H2A/K lncRNAs resulted in the upregulation of many oncogenes, which promoted cell proliferation. Further interaction analyses revealed that a proliferating cell nuclear antigen (PCNA)-protein interaction network, with PCNA in the center, contributes to cell proliferation in cells expressing the mutant H2A/K lncRNAs. Western blotting confirmed the critical upregulation of PCNA by mutant H2A/K lncRNA expression. Finally, the promotion of cell proliferation by mutant H2A/K lncRNAs (C290T, C228A and A45G) was confirmed using cell proliferation assays. Although we did not determine the exact mechanism by which the oncogenes were upregulated by the mutant H2A/K lncRNAs, we confirmed that the mutant H2A/K lncRNAs promoted cell proliferation by upregulating PCNA and other oncogenes. The hypothesis that cell proliferation is promoted by the mutant H2A/K lncRNAs was supported by the protein expression and cell proliferation assay results. Therefore, mutant H2A/K lncRNAs may be a new factor in renal carcinogenesis.