Systems biology approach to stage-wise characterization of epigenetic genes in lung adenocarcinoma

Serum Carbohydrate Antigen 19-9 and Metabolite Hypotaurine Are Predictive Markers for Early Recurrence of Pancreatic Ductal Adenocarcinoma

OBJECTIVE

A significant number of patients experience early recurrence after surgical resection for pancreatic ductal adenocarcinoma (PDAC), negating the benefit of surgery. The present study conducted clinicopathologic and metabolomic analyses to explore the factors associated with the early recurrence of PDAC.

MATERIALS AND METHODS

Patients who underwent pancreatectomy for PDAC at Kagawa University Hospital between 2011 and 2020 were enrolled. Tissue samples of PDAC and nonneoplastic pancreas were collected and frozen immediately after resection. Charged metabolites were quantified by capillary electrophoresis-mass spectrometry. Patients who relapsed within 1 year were defined as the early recurrence group.

RESULTS

Frozen tumor tissue and nonneoplastic pancreas were collected from 79 patients. The clinicopathologic analysis identified 11 predictive factors, including preoperative carbohydrate antigen 19-9 levels. The metabolomic analysis revealed that only hypotaurine was a significant risk factor for early recurrence. A multivariate analysis, including clinical and metabolic factors, showed that carbohydrate antigen 19-9 and hypotaurine were independent risk factors for early recurrence ( P = 0.045 and P = 0.049, respectively). The recurrence-free survival rate 1 year after surgery with both risk factors was only 25%.

CONCLUSIONS

Our results suggested that tumor hypotaurine is a potential metabolite associated with early recurrence. Carbohydrate antigen 19-9 and hypotaurine showed a vital utility for predicting early recurrence.

DNA Methylation Analysis Reveals Potential Mechanism in Takifugu rubripes Against Cryptocaryon irritans Infection

Takifugu rubripes (T. rubripes) is a valuable commercial fish, and Cryptocaryon irritans (C. irritans) has a significant impact on its aquaculture productivity. DNA methylation is one of the earliest discovered ways of gene epigenetic modification and also an important form of modification, as well as an essential type of alteration that regulates gene expression, including immune response. To further explore the anti-infection mechanism of T. rubripes in inhibiting this disease, we determined genome-wide DNA methylation profiles in the gill of T. rubripes using whole-genome bisulfite sequencing (WGBS) and combined with RNA sequence (RNA-seq). A total of 4659 differentially methylated genes (DMGs) in the gene body and 1546 DMGs in the promoter between the infection and control group were identified. And we identified 2501 differentially expressed genes (DEGs), including 1100 upregulated and 1401 downregulated genes. After enrichment analysis, we identified DMGs and DEGs of immune-related pathways including MAPK, Wnt, ErbB, and VEGF signaling pathways, as well as node genes prkcb, myca, tp53, and map2k2a. Based on the RNA-Seq results, we plotted a network graph to demonstrate the relationship between immune pathways and functional related genes, in addition to gene methylation and expression levels. At the same time, we predicted the CpG island and transcription factor of four immune-related key genes prkcb and mapped the gene structure. These unique discoveries could be helpful in the understanding of C. irritans pathogenesis, and the candidate genes screened may serve as optimum methylation-based biomarkers that can be utilized for the correct diagnosis and therapy T. rubripes in the development of the ability to resist C. irritans infection.

Stage-specific coexpression network analysis of Myc in cohorts of renal cancer

The present study investigates the molecular dynamics of Myc in normal precursors and in different stages (I/II/III/IV) of cohorts of renal cancer using two distinct yet complementary approaches: gene expression and gene coexpression. We also analysed the variation of coexpression networks of Myc through the stage-wise progression of renal cancer cohorts. Myc expression is significantly higher in stage I compared to normal tissue but changed inconsistently across stages of renal cancer. We identified that Myc consistently coexpressed with fourteen genes in the KIPAN [Pan-kidney cohort (KICH + KIRC + KIRP)] and eight in the KIRC (Kidney renal clear cell carcinoma) across all stages, providing potential prognostic and diagnostic biomarkers. Coexpression network complexity decreased from normal precursor tissues to associated tumour stage I in KIPAN and KIRC but was inconsistent after that. In the process of cancer development, there is generally lower cross-tissue cancer network homology observed among coexpressed genes with Myc during the normal to the stage I compared to the stage-wise progression of cancer. Overall, this research provides novel perceptions of the molecular causes of kidney cancer. It also highlights potential genes and pathways crucial for diagnosing and treating this disease.

Comparison of Plasma Metabolites From Patients With Non-Small Cell Lung Cancer by Erlotinib Treatment and Skin Rash

Erlotinib is a necessary anticancer treatment for non-small cell lung cancer (NSCLC) patients yet it causes severe side effects such as skin rash. In this study, researchers compared the untargeted compound profiles before and after erlotinib administration to observe changes in blood metabolites in NSCLC patients. The levels of 1005 substances changed after taking erlotinib. The levels of 306 and 699 metabolites were found to have increased and decreased, respectively. We found 5539 substances with peak area differences based on the presence of skin rash. Carbohydrate, amino acid, and vitamin metabolic pathways were altered in response to the onset of erlotinib-induced skin rash. Finally, this study proposed using plasma metabolites to identify biomarker(s) induced by erlotinib, as well as target molecule(s), for the treatment of dermatological toxic effects.

Identification of a Novel Renal Metastasis Associated CpG-Based DNA Methylation Signature (RMAMS)

Approximately 21% of patients with renal cell cancer (RCC) present with synchronous metastatic disease at the time of diagnosis, and metachronous metastatic disease occurs in 20–50% of cases within 5 years. Recent advances in adjuvant treatment of aggressive RCC following surgery suggest that biomarker-based prediction of risk for distant metastasis could improve patient selection. Biometrical analysis of TCGA-KIRC data identified candidate loci in the NK6 homeobox 2 gene (NKX6-2) that are hypermethylated in primary metastatic RCC. Analyses of NKX6-2 DNA methylation in three gene regions including a total of 16 CpG sites in 154 tumor-adjacent normal tissue, 189 RCC, and 194 metastatic tissue samples from 95 metastasized RCC patients revealed highly significant tumor-specific, primary metastatic-specific, and metastatic tissue-specific hypermethylation of NKX6-2. Combined CpG site methylation data for NKX6-2 and metastasis-associated genes (INA, NHLH2, and THBS4) demonstrated similarity between metastatic tissues and metastatic primary RCC tissues. The random forest method and evaluation of an unknown test cohort of tissues using receiver operator characteristic curve analysis revealed that metastatic tissues can be differentiated by a median area under the curve of 0.86 (p = 1.7 × 10−8–7.5 × 10−3) in 1000 random runs. Analysis of variable importance demonstrated an above median contribution for decision-making of at least one CpG site in each of the genes, suggesting superior informativity for sites annotated to NHLH2 and NKX6-2. Thus, DNA methylation of NKX6-2 is associated with the metastatic state of RCC tissues and contributes to a four-gene-based statistical predictor of tumoral and metastatic renal tissues.

Evaluating the tumor immune profile based on a three-gene prognostic risk model in HER2 positive breast cancer

To date, there have not been great breakthroughs in immunotherapy for HER2 positive breast cancer (HPBC). This study aimed to build a risk model that might contribute to predicting prognosis and discriminating the immune landscape in patients with HPBC. We analyzed the tumor immune profile of HPBC patients from the TCGA using the ESTIMATE algorithm. Thirty survival-related differentially expressed genes were selected according to the ImmuneScore and StromalScore. A prognostic risk model consisting of PTGDR, PNOC and CCL23 was established by LASSO analysis, and all patients were classified into the high- and low-risk score groups according to the risk scores. Subsequently, the risk model was proven to be efficient and reliable. Immune related pathways were the dominantly enriched category. ssGSEA showed stronger immune infiltration in the low-risk score group, including the infiltration of TILs, CD8 T cells, NK cells, DCs, and so on. Moreover, we found that the expression of immune checkpoint genes, including PD-L1, CTLA-4, TIGIT, TIM-3 and LAG-3, was significantly upregulated in the low-risk score group. All the results were validated with corresponding data from the GEO database. In summary, our investigation indicated that the risk model composed of PTGDR, PNOC and CCL23 has potential to predict prognosis and evaluate the tumor immune microenvironment in HPBC patients. More importantly, HPBC patients with a low-risk scores are likely to benefit from immune treatment.

Pregnancy exposure to synthetic phenols and placental DNA methylation - An epigenome-wide association study in male infants from the EDEN cohort

In utero exposure to environmental chemicals, such as synthetic phenols, may alter DNA methylation in different tissues, including placenta - a critical organ for fetal development. We studied associations between prenatal urinary biomarker concentrations of synthetic phenols and placental DNA methylation. Our study involved 202 mother-son pairs from the French EDEN cohort. Nine phenols were measured in spot urine samples collected between 22 and 29 gestational weeks. We performed DNA methylation analysis of the fetal side of placental tissues using the IlluminaHM450 BeadChips. We evaluated methylation changes of individual CpGs in an adjusted epigenome-wide association study (EWAS) and identified differentially methylated regions (DMRs). We performed mediation analysis to test whether placental tissue heterogeneity mediated the association between urinary phenol concentrations and DNA methylation. We identified 46 significant DMRs (≥5 CpGs) associated with triclosan (37 DMRs), 2,4-dichlorophenol (3), benzophenone-3 (3), methyl- (2) and propylparaben (1). All but 2 DMRs were positively associated with phenol concentrations. Out of the 46 identified DMRs, 7 (6 for triclosan) encompassed imprinted genes (APC, FOXG1, GNAS, GNASAS, MIR886, PEG10, SGCE), which represented a significant enrichment. Other identified DMRs encompassed genes encoding proteins responsible for cell signaling, transmembrane transport, cell adhesion, inflammatory, apoptotic and immunological response, genes encoding transcription factors, histones, tumor suppressors, genes involved in tumorigenesis and several cancer risk biomarkers. Mediation analysis suggested that placental cell heterogeneity may partly explain these associations. This is the first study describing the genome-wide modifications of placental DNA methylation associated with pregnancy exposure to synthetic phenols or their precursors. Our results suggest that cell heterogeneity might mediate the effects of triclosan exposure on placental DNA methylation. Additionally, the enrichment of imprinted genes within the DMRs suggests mechanisms by which certain exposures, mainly to triclosan, could affect fetal development.

Residential PM2.5 exposure and the nasal methylome in children

RATIONALE

PM_2.5-induced adverse effects on respiratory health may be driven by epigenetic modifications in airway cells. The potential impact of exposure duration on epigenetic alterations in the airways is not yet known.

OBJECTIVES

We aimed to study associations of fine particulate matter PM_2.5 exposure with DNA methylation in nasal cells.

METHODS

We conducted nasal epigenome-wide association analyses within 503 children from Project Viva (mean age 12.9 y), and examined various exposure durations (1-day, 1-week, 1-month, 3-months and 1-year) prior to nasal sampling. We used residential addresses to estimate average daily PM_2.5 at 1 km resolution. We collected nasal swabs from the anterior nares and measured DNA methylation (DNAm) using the Illumina MethylationEPIC BeadChip. We tested 719,075 high quality autosomal CpGs using CpG-by-CpG and regional DNAm analyses controlling for multiple comparisons, and adjusted for maternal education, household smokers, child sex, race/ethnicity, BMI z-score, age, season at sample collection and cell-type heterogeneity. We further corrected for bias and genomic inflation. We tested for replication in a cohort from the Netherlands (PIAMA).

RESULTS

In adjusted analyses, we found 362 CpGs associated with 1-year PM_2.5 (FDR < 0.05), 20 CpGs passing Bonferroni correction (P < 7.0x10^-8) and 10 Differentially Methylated Regions (DMRs). In 445 PIAMA participants (mean age 16.3 years) 11 of 203 available CpGs replicated at P < 0.05. We observed differential DNAm at/near genes implicated in cell cycle, immune and inflammatory responses. There were no CpGs or regions associated with PM_2.5 levels at 1-day, 1-week, or 1-month prior to sample collection, although 2 CpGs were associated with past 3-month PM_2.5.

CONCLUSION

We observed wide-spread DNAm variability associated with average past year PM_2.5 exposure but we did not detect associations with shorter-term exposure. Our results suggest that nasal DNAm marks reflect chronic air pollution exposure.

Integrated bioinformatics identifies the dysregulation induced by aberrant gene methylation in colorectal carcinoma

Colorectal carcinoma (CRC) is one of the most common cancers, and is associated with a poor clinical outcome. The key genes and potential prognostic markers in colorectal carcinoma remain to be identified and explored for clinical application. DNA expression/methylation profiles were downloaded from the Gene Expression Omnibus (GEO) database to identify differentially expressed/methylated genes (DEGs and DEMs). A total of 255 genes and 372 genes were identified as being up-regulated and down-regulated, respectively, in GSE113513, GSE81558, and GSE89076. There were a total of 3350 hypermethylated genes and 443 hypomethylated genes identified in GSE48684. Twenty genes were found to be hypermethylated as well as down-regulated, and a functional enrichment analysis revealed that these genes were mainly involved in cancer-related pathways. Among these 20 genes, GPM6A, HAND2 and C2orf40 were related to poor outcomes in cancer patients based on a survival analysis. Concurrent decreases of GPM6A, HAND2 and C2orf40 protein expression were observed in highly-differentiated colorectal carcinoma tissues, and higher expression levels were found in undifferentiated or minimally-differentiated colorectal carcinoma tissues. In conclusion, 20 genes were found to be downregulated and hypermethylated in CRC, among which GPM6A, HAND2 and C2orf40 were explored for their potential prognostic value.

Whole-Genome Methylation Study of Congenital Lung Malformations in Children

Background and Objectives

The treatment of asymptomatic patients with congenital pulmonary malformations (CPMs) remains controversial, partially because the relationship between congenital lung malformations and malignancy is still undefined. Change in methylation pattern is a crucial event in human cancer, including lung cancer. We therefore studied all differentially methylated regions (DMRs) in a series of CPMs in an attempt to find methylation anomalies in genes already described in association with malignancy.

Methods

The DNA extracted from resected congenital lung malformations and control lung tissue was screened using Illumina MethylationEPIC arrays. Comparisons between the group of malformed samples or the malformed samples of same histology or each malformed sample and the controls and between a pleuropulmonary blastoma (PPB) and controls were performed. Moreover, each malformed sample was pairwise compared with its respective control. All differentially methylated regions (DMRs) with an adjusted p-value <0,05 were studied.

Results

Every comparison highlighted a number of DMRs closed to genes involved either in cell proliferation or in embryonic development or included in the Cancer Gene Census. Their abnormal methylation had been already described in lung tumors.

Conclusions

Methylation anomalies already described in lung tumors and also shared by the PPB were found in congenital lung malformations, regardless the histology. The presence of methylation abnormalities is suggestive of a correlation between congenital lung malformations and some step of malignant transformation.

Distinguishing Glioblastoma Subtypes by Methylation Signatures

Glioblastoma, also called glioblastoma multiform (GBM), is the most aggressive cancer that initiates within the brain. GBM is produced in the central nervous system. Cancer cells in GBM are similar to stem cells. Several different schemes for GBM stratification exist. These schemes are based on intertumoral molecular heterogeneity, preoperative images, and integrated tumor characteristics. Although the formation of glioblastoma is remarkably related to gene methylation, GBM has been poorly classified by epigenetics. To classify glioblastoma subtypes on the basis of different degrees of genes' methylation, we adopted several powerful machine learning algorithms to identify numerous methylation features (sites) associated with the classification of GBM. The features were first analyzed by an excellent feature selection method, Monte Carlo feature selection (MCFS), resulting in a feature list. Then, such list was fed into the incremental feature selection (IFS), incorporating one classification algorithm, to extract essential sites. These sites can be annotated onto coding genes, such as CXCR4, TBX18, SP5, and TMEM22, and enriched in relevant biological functions related to GBM classification (e.g., subtype-specific functions). Representative functions, such as nervous system development, intrinsic plasma membrane component, calcium ion binding, systemic lupus erythematosus, and alcoholism, are potential pathogenic functions that participate in the initiation and progression of glioblastoma and its subtypes. With these sites, an efficient model can be built to classify the subtypes of glioblastoma.

Identification of Differentially Methylated CpG Sites in Fibroblasts from Keloid Scars

As a part of an abnormal healing process of dermal injuries and irritation, keloid scars arise on the skin as benign fibroproliferative tumors. Although the etiology of keloid scarring remains unsettled, considerable recent evidence suggested that keloidogenesis may be driven by epigenetic changes, particularly, DNA methylation. Therefore, genome-wide scanning of methylated cytosine-phosphoguanine (CpG) sites in extracted DNA from 12 keloid scar fibroblasts (KF) and 12 control skin fibroblasts (CF) (six normal skin fibroblasts and six normotrophic fibroblasts) was conducted using the Illumina Human Methylation 450K BeadChip in two replicates for each sample. Comparing KF and CF used a Linear Models for Microarray Data (Limma) model revealed 100,000 differentially methylated (DM) CpG sites, 20,695 of which were found to be hypomethylated and 79,305 were hypermethylated. The top DM CpG sites were associated with TNKS2, FAM45B, LOC723972, GAS7, RHBDD2 and CAMKK1. Subsequently, the most functionally enriched genes with the top 100 DM CpG sites were significantly (p ≤ 0.05) associated with SH2 domain binding, regulation of transcription, DNA-templated, nucleus, positive regulation of protein targeting to mitochondrion, nucleoplasm, Swr1 complex, histone exchange, and cellular response to organic substance. In addition, NLK, CAMKK1, LPAR2, CASP1, and NHS showed to be the most common regulators in the signaling network analysis. Taken together, these findings shed light on the methylation status of keloids that could be implicated in the underlying mechanism of keloid scars formation and remission.

A comprehensive analysis of metabolomics and transcriptomics in non-small cell lung cancer

Non-small cell lung cancer (NSCLC) remains a leading cause of cancer death globally. More accurate and reliable diagnostic methods/biomarkers are urgently needed. Joint application of metabolomics and transcriptomics technologies possesses the high efficiency of identifying key metabolic pathways and functional genes in lung cancer patients. In this study, we performed an untargeted metabolomics analysis of 142 NSCLC patients and 159 healthy controls; 35 identified metabolites were significantly different between NSCLC patients and healthy controls, of which 6 metabolites (hypoxanthine, inosine, L-tryptophan, indoleacrylic acid, acyl-carnitine C10:1, and lysoPC(18:2)) were chosen as combinational potential biomarkers for NSCLC. The area under the curve (AUC) value, sensitivity (SE), and specificity (SP) of these six biomarkers were 0.99, 0.98, and 0.99, respectively. Potential diagnostic implications of the metabolic characteristics in NSCLC was studied. The metabolomics results were further verified by transcriptomics analysis of 1027 NSCLC patients and 108 adjacent peritumoral tissues from TCGA database. This analysis identified 2202 genes with significantly different expressions in cancer cells compared to normal controls, which in turn defined pathways implicated in the metabolism of the compounds revealed by metabolomics analysis. We built a fully connected network of metabolites and genes, which shows a good correspondence between the transcriptome analysis and the metabolites selected for diagnosis. In conclusion, this work provides evidence that the metabolic biomarkers identified may be used for NSCLC diagnosis and screening. Comprehensive analysis of metabolomics and transcriptomics data offered a validated and comprehensive understanding of metabolism in NSCLC.

Hsa_circ_0038646 promotes cell proliferation and migration in colorectal cancer via miR-331-3p/GRIK3

Increasing evidence supports the essential roles of circular RNAs (circRNAs) and microRNAs (miRNAs/miRs) in different types of human cancer. For example, hsa_circ_0137008 functions as a sponge for mi-338-5p and inhibits the malignant phenotype in colorectal cancer. Furthermore, hsa_circ_RNA_0011780 downregulates FBXW7 by targeting miR-554a and suppressing the progression of non-small cell lung cancer. Thus far, only a single report has identified that the miRNA miR-331-3p exerts a pivotal effect on human colorectal cancer (CRC) evolution. However, both the up- and downstream regulatory mechanisms of miR-331-3p are unclear. In the present study, it was predicted via bioinformatics analysis that the circRNA, hsa_circ_0038646, and the glutamate receptor ionotropic kainate 3 (GRIK3) gene contain binding sites that can interact with miR-331-3p. Thus, hsa_circ_0038646/miR-331-3p/GRIK3 may be a novel therapeutic pathway for CRC. Reverse transcription-quantitative PCR and western blotting analyses were performed, as well as cell proliferation, luciferase reporter and Transwell migration assays. Hsa_circ_0038646 was overexpressed in both CRC cells and tissues, and this aberrant expression was positively related with increasing tumor grade. Knockdown of hsa_circ_0038646 significantly weakened human CRC cell proliferation and migration. It was shown that hsa_circ_0038646 can sponge miR-331-3p to suppress its expression, and that suppression of miR-331-3p can reverse the effects of hsa_circ_0038646 inhibition in CRC cells. It was determined that GRIK3 is a downstream target of miR-331-3p, and that hsa_circ_0038646 could increase the levels of GRIK3 by suppressing miR-331-3p in CRC cells. Restoring GRIK3 expression rescued the weakened CRC cell proliferation and migration following hsa_circ_0038646 knockdown. The present study indicated that hsa_circ_0038646 functions as a tumor promoter in CRC by increasing GRIK3 expression via sponging of miR-331-3p. The hsa_circ_0038646/miR-331-3p/GRIK3 axis may be a novel therapeutic and diagnostic target of CRC.

Identification of the differential expression of genes and upstream microRNAs in small cell lung cancer compared with normal lung based on bioinformatics analysis

Small cell lung cancer (SCLC) is one of the most lethal cancer, mainly attributing to its high tendency to metastasis. Mounting evidence has demonstrated that genes and microRNAs (miRNAs) are related to human cancer onset and progression including invasion and metastasis.An eligible gene dataset and an eligible miRNA dataset were downloaded from the Gene Expression Omnibus (GEO) database based our screening criteria. Differentially expressed genes (DE-genes) or DE-miRNAs for each dataset obtained by the R software package. The potential target genes of the top 10 DE-miRNAs were predicted by multiple databases. For annotation, visualization and integrated discovery, Metascape 3.0 was introduced to perform enrichment analysis for the DE-genes and the predicted target genes of the selected top 10 DE-miRNAs, including Pathway and Process Enrichment Analysis or protein-protein interaction enrichment analysis. The intersection of predicted target genes and DE-genes was taken as the final DE-genes. Then apply the predicted miRNAs-targets relationship of top 10 DE-miRNAs to the final DE-genes to gain more convinced DE-miRNAs, DE-genes and their one to one relationship.GSE19945 (miRNA microarray) and GSE40275 (gene microarray) datasets were selected and downloaded. 56 DE-miRNAs and 861 DE-genes were discovered. 297 miRNAs-targets relationships (284 unique genes) were predicted as the target of top 10 upregulating DE-miRNAs. 245 miRNAs-targets relationships (238 unique genes) were identified as the target of top 10 downregulating DE-miRNAs. The key results of enrichment analysis include protein kinase B signaling, transmembrane receptor protein tyrosine kinase signaling pathway, negative regulation of cell differentiation, response to growth factor, cellular response to lipid, muscle structure development, response to growth factor, signaling by Receptor Tyrosine Kinases, epithelial cell migration, cellular response to organic cyclic compound, Cell Cycle (Mitotic), DNA conformation change, cell division, DNA replication, cell cycle phase transition, blood vessel development, inflammatory response, Staphylococcus aureus infection, leukocyte migration, and myeloid leukocyte activation. Differential expression of genes-upstream miRNAs (RBMS3-hsa-miR-7-5p, NEDD9-hsa-miR-18a-5p, CRIM1-hsa-miR-18a-5p, TGFBR2-hsa-miR-9-5p, MYO1C-hsa-miR-9-5p, KLF4-hsa-miR-7-5p, EMP2-hsa-miR-1290, TMEM2-hsa-miR-18a-5p, CTGF-hsa-miR-18a-5p, TNFAIP3-hsa-miR-18a-5p, THBS1-hsa-miR-182-5p, KPNA2-hsa-miR-144-3p, GPR137C-hsa-miR-1-3p, GRIK3-hsa-miR-144-3p, and MTHFD2-hsa-miR-30a-3p) were identified in SCLC.RBMS3, NEDD9, CRIM1, KPNA2, GPR137C, GRIK3, hsa-miR-7-5p, hsa-miR-18a-5p, hsa-miR-144-3p, hsa-miR-1-3p along with the pathways included protein kinase B signaling, muscle structure development, Cell Cycle (Mitotic) and blood vessel development may gain a high chance to play a key role in the prognosis of SCLC, but more studies should be conducted to reveal it more clearly.

Histone-Related Genes Are Hypermethylated in Lung Cancer and Hypermethylated HIST1H4F Could Serve as a Pan-Cancer Biomarker

Lung cancer is the leading cause of cancer-related deaths worldwide. Cytologic examination is the current "gold standard" for lung cancer diagnosis, however, this has low sensitivity. Here, we identified a typical methylation signature of histone genes in lung cancer by whole-genome DNA methylation analysis, which was validated by The Cancer Genome Atlas (TCGA) lung cancer cohort (n = 907) and was further confirmed in 265 bronchoalveolar lavage fluid samples with specificity and sensitivity of 96.7% and 87.0%, respectively. More importantly, HIST1H4F was universally hypermethylated in all 17 tumor types from TCGA datasets (n = 7,344), which was further validated in nine different types of cancer (n = 243). These results demonstrate that HIST1H4F can function as a universal-cancer-only methylation (UCOM) marker, which may aid in understanding general tumorigenesis and improve screening for early cancer diagnosis. SIGNIFICANCE: These findings identify a new biomarker for cancer detection and show that hypermethylation of histone-related genes seems to persist across cancers.

FLT1 hypermethylation is involved in polycyclic aromatic hydrocarbons-induced cell transformation

Coke oven emissions (COEs) are common particle pollutants in occupational environment and the major constituents of COEs are polycyclic aromatic hydrocarbons (PAHs). Previously, we identified aberrant methylation of the fms related tyrosine kinase 1 (FLT1) gene over the course of benzo(a)pyrene (BaP)-induced cell transformation via genome-wide methylation array. To quantify FLT1 methylation, we established a bisulfite pyrosequencing assay and examined the FLT1 hypermethylation in several human cancers. The results revealed that 70.0% (21/30 pairs) of lung cancers harbored hypermethylated FLT1 and concomitant suppression of gene expression compared to the adjacent tissues. This implies that FLT1 hypermethylation might play a role in malignant cell transformation. In addition, FLT1 hypermethylation and gene suppression appeared in primary human lymphocytes in a dose-response manner following COEs treatment. To explore whether FLT1 methylation is correlated with COEs exposure and DNA damage, we recruited 144 male subjects who had been exposed to high levels of COEs and 84 male control subjects. Notably, the FLT1 methylation in peripheral blood lymphocytes (PBLCs) of the COEs-exposed group (19.8 ± 3.2%) was enhanced by 17.9% compared to that of the control group (16.8 ± 2.8%) (P < 0.001). The FLT1 methylation status was positively correlated with urinary 1-hydroxypyrene (1-OHP) levels, an internal exposure marker of PAHs (β = 0.029, 95% CI = 0.010-0.048, P = 0.003) and positively correlated with DNA damage (β_OTM = 0.024, 95% CI = 0.007-0.040, P = 0.005; β_{Tail DNA} = 0.035, 95% CI = 0.0017-0.054, P < 0.001) indicated by comet assay. Taken together, these findings indicate that FLT1 might be a tumor suppressor, and its hypermethylation might contribute to PAHs-induced carcinogenicity.

Glutamate Ionotropic Receptor Kainate Type Subunit 3 (GRIK3) promotes epithelial-mesenchymal transition in breast cancer cells by regulating SPDEF/CDH1 signaling

Glutamate Ionotropic Receptor Kainate Type Subunit 3 (GRIK3) is an important excitatory neurotransmitter receptor that plays a significant role in various neurodegenerative diseases. However, the biological functions of GRIK3 in malignancies are largely unknown because of limited related studies. Here, we primarily reported that the expression of GRIK3 was higher in breast cancer tissues than in adjacent noncancerous tissues. GRIK3 expression was also positively correlated with the prognosis of patients with breast cancer. GRIK3 promoted the proliferation and migration abilities of breast cancer cells and enhanced the growth of orthotopically implanted tumors. Mechanically, GRIK3 influenced a range of signaling pathways and key signal transducers, including two epithelial-mesenchymal transition regulators, SPDEF and CDH1. Heterogenous expression of SPDEF and CDH1 counteracted the migration and invasion abilities, respectively, of breast cancer cells induced by GRIK3. Moreover, overexpression of GRIK3 increased the expression of mesenchymal markers and decreased the expression of epithelial markers, resulting in the translocation of β-catenin into the nucleus and the increased β-catenin transcriptional activity. In conclusion, the present study reported a novel oncogenic role of GRIK3. Meanwhile, GRIK3, as a membrane receptor, may also serve as a potential therapeutic target for the treatment of breast cancer.

Protective Effect of Colla corii asini against Lung Injuries Induced by Intratracheal Instillation of Artificial Fine Particles in Rats

Environmental issues pose huge threats to public health, particularly the damage caused by fine particulate matter (PM_2.5). However, the mechanisms of injury require further investigation and medical materials that can protect the lungs from PM_2.5 are needed. We have found that Colla corii asini, a traditional Chinese medicine that has long been used to treat various ailments, is a good candidate to serve this purpose. To understand the mechanisms of PM_2.5-induced lung toxicity and the protective effects of Colla corii asini, we established a rat model of lung injury via intratracheal instillation of artificial PM_2.5 (aPM_2.5). Our results demonstrated that Colla corii asini significantly protected against lung function decline and pathologic changes. Inflammation was ameliorated by suppression of Arg-1 to adjust the disturbed metabolic pathways induced by aPM_2.5, such as arginine and nitrogen metabolism and aminoacyl-tRNA biosynthesis, for 11 weeks. Our work found that metabolomics was a useful tool that contributed to further understanding of PM_2.5-induced respiratory system damage and provided useful information for further pharmacological research on Colla corii asini, which may be valuable for therapeutic intervention.

A comprehensive methylation signature identifies lymph node metastasis in esophageal squamous cell carcinoma

Treatment modalities in esophageal squamous cell carcinoma (ESCC) depend largely on lymph node metastasis (LNM) status. With suboptimal detection sensitivity of existing imaging techniques, we propose a methylation signature which identifies patients with LNM with greater accuracy. This would allow precise stratification of high-risk patients requiring more aggressive treatment from low-risk ESCC patients who can forego radical surgery. An unbiased genome-wide methylation signature for LNM detection was established from an initial in silico discovery phase. The signature was tested in independent clinical cohorts comprising of 249 ESCC patients. The prognostic potential of the methylation signature was compared to clinical variables including LNM status. A 10-probe LNM associated signature (LNAS) was developed using stringent bioinformatics analyses. The area under the curve values for LNAS risk scores were 0.81 and 0.88 in the training and validation cohorts respectively, in association with lymphatic vessel invasion and tumor stage. High LNAS risk-score was also associated with worse overall survival [HR (95% CI) 3 (1.8-4.8), p < 0.0001 training and 3.9 (1.5-10.2), p = 0.001 validation cohort]. In conclusion, our novel methylation signature is a powerful biomarker that identifies LNM status robustly and is also associated with worse prognosis in ESCC patients.

Diagnostic role of Wnt pathway gene promoter methylation in non small cell lung cancer

Wnt signal pathway genes are known to be involved with cancer development. Here we tested the hypothesis whether DNA methylation of genes part of the Wnt signaling pathway could help the diagnosis of non-small cell lung cancer (NSCLC). The methylation levels of SFRP1, SFRP2, WIF1 and PRKCB in 111 NSCLC patients were evaluated by quantitative methylation-specific PCR (qMSP). Promoter methylation levels of four candidate genes were significantly higher in tumor tissues compared with the adjacent tissues. SFRP1, SFRP2 and PRKCB genes were all shown to be good predictors of NSCLC risk (SFRP1: AUC = 0.711; SFRP2: AUC = 0.631; PRKCB: AUC = 0.650). The combined analysis showed that the methylation status of the four genes had a sensitivity of 70.3% and a specificity of 73.9% in the prediction of NSCLC risk for study cohort. A higher diagnostic value with an AUC of 0.945 (95% CI: 0.923–0.967, sensitivity: 90.6%, specificity: 93.0%) was found in TCGA cohort. In addition, SFRP1 and SFRP2 hypermethylation events were specific to male patients. Further TCGA data mining analysis suggested that SFRP1_cg15839448, SFRP2_cg05774801, and WIF1_cg21383810 were inversely associated with the host gene expression. Moreover, GEO database analysis showed that 5′-Aza-deoxycytidine was able to upregulate gene expression in several lung cancer cell lines. Subsequent dual-luciferase reporter assay showed a crucial regulatory function of PRKCB promoter. In summary, our study showed that a panel of Wnt signal pathway genes (SFRP1, SFRP2, WIF1 and PRKCB) had the potential as methylation biomarkers in the diagnosis of NSCLC.

CRLF1 promotes malignant phenotypes of papillary thyroid carcinoma by activating the MAPK/ERK and PI3K/AKT pathways

Papillary thyroid carcinoma (PTC) is the one of the most common types of endocrine cancer and has a heterogeneous prognosis. Tumors from patients with poor prognosis may differentially express specific genes. Therefore, an analysis of The Cancer Genome Atlas (TCGA) database was performed and revealed that cytokine receptor-like factor 1 (CRLF1) may be a potential novel target for PTC treatment. The objective of the current study was to explore the expression of CRLF1 in PTC and to investigate the main functions and mechanisms of CRLF1 in PTC. PTC tissues exhibited higher CRLF1 expression at both the mRNA and protein levels than it did with normal thyroid tissues. High CRLF1 levels were associated with aggressive clinicopathological features and poor disease-free survival rates. By using loss-of-function and gain-of-function assays, we found that CRLF1 not only increased cell migration and invasion in vitro but also promoted tumor growth both in vitro and in vivo. In addition, CRLF1 induced epithelial–mesenchymal transitions. Overexpression of CRLF1 activated the ERK1/2 and AKT pathways. The oncogenic effects induced by CRLF1 were suppressed by treating the cells with the MEK inhibitor U0126 or the AKT inhibitor MK-2206. These results suggest that CRLF1 enhances cell proliferation and metastasis in PTC and thus may therefore be a potential therapeutic target for PTC.

A Panel of Novel Detection and Prognostic Methylated DNA Markers in Primary Non-Small Cell Lung Cancer and Serum DNA

Purpose: To establish a novel panel of cancer-specific methylated genes for cancer detection and prognostic stratification of early-stage non-small cell lung cancer (NSCLC).Experimental Design: Identification of differentially methylated regions (DMR) was performed with bumphunter on "The Cancer Genome Atlas (TCGA)" dataset, and clinical utility was assessed using quantitative methylation-specific PCR assay in multiple sets of primary NSCLC and body fluids that included serum, pleural effusion, and ascites samples.Results: A methylation panel of 6 genes (CDO1, HOXA9, AJAP1, PTGDR, UNCX, and MARCH11) was selected from TCGA dataset. Promoter methylation of the gene panel was detected in 92.2% (83/90) of the training cohort with a specificity of 72.0% (18/25) and in 93.0% (40/43) of an independent cohort of stage IA primary NSCLC. In serum samples from the later 43 stage IA subjects and population-matched 42 control subjects, the gene panel yielded a sensitivity of 72.1% (31/41) and specificity of 71.4% (30/42). Similar diagnostic accuracy was observed in pleural effusion and ascites samples. A prognostic risk category based on the methylation status of CDO1, HOXA9, PTGDR, and AJAP1 refined the risk stratification for outcomes as an independent prognostic factor for an early-stage disease. Moreover, the paralog group for HOXA9, predominantly overexpressed in subjects with HOXA9 methylation, showed poor outcomes.Conclusions: Promoter methylation of a panel of 6 genes has potential for use as a biomarker for early cancer detection and to predict prognosis at the time of diagnosis. Clin Cancer Res; 23(22); 7141-52. ©2017 AACR.

Whole genome DNA methylation profiling of oral cancer in ethnic population of Meghalaya, North East India reveals novel genes

Oral Squamous Cell Carcinoma (OSCC) is a serious and one of the most common and highly aggressive malignancies. Epigenetic factors such as DNA methylation have been known to be implicated in a number of cancer etiologies. The main objective of this study was to investigate physiognomies of Promoter DNA methylation patterns associated with oral cancer epigenome with special reference to the ethnic population of Meghalaya, North East India. The present study identifies 27,205 CpG sites and 3811 regions that are differentially methylated in oral cancer when compared to matched normal. 45 genes were found to be differentially methylated within the promoter region, of which 38 were hypermethylated and 7 hypomethylated. 14 of the hypermethylated genes were found to be similar to that of the TCGA-HNSCC study some of which are TSGs and few novel genes which may serve as candidate methylation biomarkers for OSCC in this poorly characterized ethnic group.

Proteomics analysis to reveal biological pathways and predictive proteins in the survival of high-grade serous ovarian cancer

High-grade serous ovarian cancer (HGSC) is an aggressive cancer with a worse clinical outcome. Therefore, studies about the prognosis of HGSC may provide therapeutic avenues to improve patient outcomes. Since genome alteration are manifested at the protein level, we integrated protein and mRNA data of ovarian cancer from The Cancer Genome Atlas (TCGA) and Clinical Proteomic Tumor Analysis Consortium (CPTAC) and utilized the sparse overlapping group lasso (SOGL) method, a new mechanism-driven variable selection method, to select dysregulated pathways and crucial proteins related to the survival of HGSC. We found that biosynthesis of amino acids was the main biological pathway with the best predictive performance (AUC = 0.900). A panel of three proteins, namely EIF2B1, PRPS1L1 and MAPK13 were selected as potential predictive proteins and the risk score consisting of these three proteins has predictive performance for overall survival (OS) and progression free survival (PFS), with AUC of 0.976 and 0.932, respectively. Our study provides additional information for further mechanism and therapeutic avenues to improve patient outcomes in clinical practice.

In silico identification of potential key regulatory factors in smoking-induced lung cancer

Background

Lung cancer is a leading cause of cancer-related death worldwide and is the most commonly diagnosed cancer. Like other cancers, it is a complex and highly heterogeneous disease involving multiple signaling pathways. Identifying potential therapeutic targets is critical for the development of effective treatment strategies.

Methods

We used a systems biology approach to identify potential key regulatory factors in smoking-induced lung cancer. We first identified genes that were differentially expressed between smokers with normal lungs and those with cancerous lungs, then integrated these differentially expressed genes (DEGs) with data from a protein-protein interaction database to build a network model with functional modules for pathway analysis. We also carried out a gene set enrichment analysis of DEG lists using the Kinase Enrichment Analysis (KEA), Protein-Protein Interaction (PPI) hubs, and KEGG (Kyoto Encyclopedia of Genes and Genomes) databases.

Results

Twelve transcription factors were identified as having potential significance in lung cancer (CREB1, NUCKS1, HOXB4, MYCN, MYC, PHF8, TRIM28, WT1, CUX1, CRX, GABP, and TCF3); three of these (CRX, GABP, and TCF) have not been previously implicated in lung carcinogenesis. In addition, 11 kinases were found to be potentially related to lung cancer (MAPK1, IGF1R, RPS6KA1, ATR, MAPK14, MAPK3, MAPK4, MAPK8, PRKCZ, and INSR, and PRKAA1). However, PRKAA1 is reported here for the first time. MEPCE, CDK1, PRKCA, COPS5, GSK3B, BRCA1, EP300, and PIN1 were identified as potential hubs in lung cancer-associated signaling. In addition, we found 18 pathways that were potentially related to lung carcinogenesis, of which 12 (mitogen-activated protein kinase, gonadotropin-releasing hormone, Toll-like receptor, ErbB, and insulin signaling; purine and ether lipid metabolism; adherens junctions; regulation of autophagy; snare interactions in vesicular transport; and cell cycle) have been previously identified.

Conclusion

Our systems-based approach identified potential key molecules in lung carcinogenesis and provides a basis for investigations of tumor development as well as novel drug targets for lung cancer treatment.

TRIM36 hypermethylation is involved in polycyclic aromatic hydrocarbons-induced cell transformation

Long term exposure to polycyclic aromatic hydrocarbons (PAHs) is associated with the increasing risk of lung cancer. To identify differentially hypermethylated genes associated with PAHs-induced carcinogenicity, we performed genome-wide DNA methylation analysis in 20 μM benzo(a)pyrene (BaP)-transformed human bronchial epithelial (HBE) cells at different stages of cell transformation. Several methylated genes (CNGA4, FLT1, GAREM1, SFMBT2, TRIM36) were differentially hypermethylated and their mRNA was suppressed in cells at both pre-transformed and transformed stages. Similar results were observed in HBE cells transformed by 20 μg/mL coke oven emissions (COEs) mixture collected from a coking manufacturing facility. In particular, hypermethylation of TRIM36 and suppression of TRIM36 expression were gradually enhanced over the time of COEs treatment. We developed bisulfite pyrosequencing assay and assessed TRIM36 methylation quantitatively. We found that hypermethylation of TRIM36 and reduced gene expression was prevalent in several types of human cancers. TRIM36 hypermethylation appeared in 90.0% (23/30) of Non-Small Cell Lung Cancer (NSCLCs) tissues compared to their paired adjacent tissues with an average increase of 1.32 fold. Furthermore, an increased methylation rate (5.90% v.s 7.38%) and reduced levels of TRIM36 mRNA were found in peripheral lymphocytes (PBLCs) of 151 COEs-exposed workers. In all subjects, TRIM36 hypermethylation was positively correlated with the level of urinary 1-hydroxypyrene (P < 0.001), an internal exposure marker of PAHs, and the DNA damage (P = 0.013). These findings suggest that aberrant hypermethylation of TRIM36 might be involved in the acquisition of malignant phenotype and could be served as a biomarker for risk assessment of PAHs exposure.

Analysis of DNA methylation of potential age-related methylation sites in canine peripheral blood leukocytes

Reliable methodology for predicting the age of mature dogs is currently unavailable. In this study, amplicon sequencing of 50 blood samples obtained from diseased dogs was used to measure methylation in seven DNA regions. Significant correlations between methylation level and age were identified in four of the seven regions. These four regions were then tested in samples from 31 healthy toy poodles, and correlations were detected in two regions. The age of another 11 dogs was predicted using data from the diseased dogs and the healthy poodles. The mean difference between the actual and calculated ages was 34.3 and 23.1 months, respectively. Further research is needed to identify additional sites of age-related methylation and allow accurate age prediction in dogs.

Aberrant gene-specific DNA methylation signature analysis in cervical cancer

Multicomponent molecular modifications such as DNA methylation may offer sensitive and specific cervical intraepithelial neoplasia and cervical cancer biomarkers. In this study, we tested cervical tissues at various stages of tumor progression for 5-methylcytosine and 5-hydroxymethylcytosine levels and also DNA promoter methylation profile of a panel of genes for its diagnostic potential. In total, 5-methylcytosine, 5-hydroxymethylcytosine, and promoter methylation of 33 genes were evaluated by reversed-phase high-performance liquid chromatography, enzyme-linked immunosorbent assay based technique, and bisulfate-based next generation sequencing. The 5-methylcytosine and 5-hydroxymethylcytosine contents were significantly reduced in squamous cell carcinoma and receiver operating characteristic curve analysis showed a significant difference in (1) 5-methylcytosine between normal and squamous cell carcinoma tissues (area under the curve = 0.946) and (2) 5-hydroxymethylcytosine levels among normal, squamous intraepithelial lesions and squamous cell carcinoma. Analyses of our next generation sequencing results and data from five independent published studies consisting of 191 normal, 10 low-grade squamous intraepithelial lesions, 21 high-grade squamous intraepithelial lesions, and 335 malignant tissues identified a panel of nine genes ( ARHGAP6, DAPK1, HAND2, NKX2-2, NNAT, PCDH10, PROX1, PITX2, and RAB6C) which could effectively discriminate among the various groups with sensitivity and specificity of 80%-100% (p < 0.05). Furthermore, 12 gene promoters (ARHGAP6, HAND2, LHX9, HEY2, NKX2-2, PCDH10, PITX2, PROX1, TBX3, IKBKG, RAB6C, and DAPK1) were also methylated in one or more of the cervical cancer cell lines tested. The global and gene-specific methylation of the panel of genes identified in our study may serve as useful biomarkers for the early detection and clinical management of cervical cancer.

Reduced Representation Bisulfite Sequencing Determination of Distinctive DNA Hypermethylated Genes in the Progression to Colon Cancer in African Americans

Background and Aims. Many studies have focused on the determination of methylated targets in colorectal cancer. However, few analyzed the progressive methylation in the sequence from normal to adenoma and ultimately to malignant tumors. This is of utmost importance especially in populations such as African Americans who generally display aggressive tumors at diagnosis and for whom markers of early neoplasia are needed. We aimed to determine methylated targets in the path to colon cancer in African American patients using Reduced Representation Bisulfite Sequencing (RRBS). Methods. Genomic DNA was isolated from fresh frozen tissues of patients with different colon lesions: normal, a tubular adenoma, a tubulovillous adenoma, and five cancers. RRBS was performed on these DNA samples to identify hypermethylation. Alignment, mapping, and confirmed CpG methylation analyses were performed. Preferential hypermethylated pathways were determined using Ingenuity Pathway Analysis (IPA). Results. We identified hypermethylated CpG sites in the following genes: L3MBTL1, NKX6-2, PREX1, TRAF7, PRDM14, and NEFM with the number of CpG sites being 14, 17, 10, 16, 6, and 6, respectively, after pairwise analysis of normal versus adenoma, adenoma versus cancer, and normal versus cancer. IPA mapped the above-mentioned hypermethylated genes to the Wnt/β-catenin, PI3k/AKT, VEGF, and JAK/STAT3 signaling pathways. Conclusion. This work provides insight into novel differential CpGs hypermethylation sites in colorectal carcinogenesis. Functional analysis of the novel gene targets is needed to confirm their roles in their associated carcinogenic pathways.

Network pharmacology of cancer: From understanding of complex interactomes to the design of multi-target specific therapeutics from nature

Despite massive investments in drug research and development, the significant decline in the number of new drugs approved or translated to clinical use raises the question, whether single targeted drug discovery is the right approach. To combat complex systemic diseases that harbour robust biological networks such as cancer, single target intervention is proved to be ineffective. In such cases, network pharmacology approaches are highly useful, because they differ from conventional drug discovery by addressing the ability of drugs to target numerous proteins or networks involved in a disease. Pleiotropic natural products are one of the promising strategies due to their multi-targeting and due to lower side effects. In this review, we discuss the application of network pharmacology for cancer drug discovery. We provide an overview of the current state of knowledge on network pharmacology, focus on different technical approaches and implications for cancer therapy (e.g. polypharmacology and synthetic lethality), and illustrate the therapeutic potential with selected examples green tea polyphenolics, Eleutherococcus senticosus, Rhodiola rosea, and Schisandra chinensis). Finally, we present future perspectives on their plausible applications for diagnosis and therapy of cancer.

Novel personalized pathway-based metabolomics models reveal key metabolic pathways for breast cancer diagnosis

Background

More accurate diagnostic methods are pressingly needed to diagnose breast cancer, the most common malignant cancer in women worldwide. Blood-based metabolomics is a promising diagnostic method for breast cancer. However, many metabolic biomarkers are difficult to replicate among studies.

Methods

We propose that higher-order functional representation of metabolomics data, such as pathway-based metabolomic features, can be used as robust biomarkers for breast cancer. Towards this, we have developed a new computational method that uses personalized pathway dysregulation scores for disease diagnosis. We applied this method to predict breast cancer occurrence, in combination with correlation feature selection (CFS) and classification methods.

Results

The resulting all-stage and early-stage diagnosis models are highly accurate in two sets of testing blood samples, with average AUCs (Area Under the Curve, a receiver operating characteristic curve) of 0.968 and 0.934, sensitivities of 0.946 and 0.954, and specificities of 0.934 and 0.918. These two metabolomics-based pathway models are further validated by RNA-Seq-based TCGA (The Cancer Genome Atlas) breast cancer data, with AUCs of 0.995 and 0.993. Moreover, important metabolic pathways, such as taurine and hypotaurine metabolism and the alanine, aspartate, and glutamate pathway, are revealed as critical biological pathways for early diagnosis of breast cancer.

Conclusions

We have successfully developed a new type of pathway-based model to study metabolomics data for disease diagnosis. Applying this method to blood-based breast cancer metabolomics data, we have discovered crucial metabolic pathway signatures for breast cancer diagnosis, especially early diagnosis. Further, this modeling approach may be generalized to other omics data types for disease diagnosis.

Electronic supplementary material

The online version of this article (doi:10.1186/s13073-016-0289-9) contains supplementary material, which is available to authorized users.

Analysis on the metabolite composition of serum samples from patients with papillary thyroid carcinoma using nuclear magnetic resonance

OBJECTIVE

Analysis of the metabolic differences among the papillary thyroid carcinoma (group T) patients, benign thyroid tumor patients (group B) and healthy controls (group H) by nuclear magnetic resonance hydrogen spectrum.

METHODS

collect twenty serum specimens each from group T, group B and group H. Collect image archive. Use Topspin software, AMIX software and SIMCA-P+ software to calibrate, integrate with PCA and PLS-DA, research the three groups' serum for endogenous metabolic differences.

RESULTS

The data of group T and group H established a discrimination model, and the model is correct (P<0.05). The content of metabolites in the serum of team T increased including valine, leucine, isoleucine, lactic acid, alanine, glutamic acid, lysine, glycine, while the lipids, choline, tyrosine decreased. The data of group B and group H established a discrimination model and the model is correct (P<0.05). The content of metabolites in the serum of team B increased including Trimethyl glycine, tyrosine, phenylalanine, valine, leucine, isoleucine, lactic acid, alanine, glutamic acid, while the Lipids and lysine reduced.

CONCLUSION

Compared with team H, there is an obvious metabolic difference in team T and team B. It not only involves glucose metabolism but also the metabolism of lipids, amino acids and nucleic acid.

Bayesian Network Inference Enables Unbiased Phenotypic Anchoring of Transcriptomic Responses to Cigarette Smoke in Humans

Microarray-based transcriptomic analysis has been demonstrated to hold the opportunity to study the effects of human exposure to, e.g., chemical carcinogens at the whole genome level, thus yielding broad-ranging molecular information on possible carcinogenic effects. Since genes do not operate individually but rather through concerted interactions, analyzing and visualizing networks of genes should provide important mechanistic information, especially upon connecting them to functional parameters, such as those derived from measurements of biomarkers for exposure and carcinogenic risk. Conventional methods such as hierarchical clustering and correlation analyses are frequently used to address these complex interactions but are limited as they do not provide directional causal dependence relationships. Therefore, our aim was to apply Bayesian network inference with the purpose of phenotypic anchoring of modified gene expressions. We investigated a use case on transcriptomic responses to cigarette smoking in humans, in association with plasma cotinine levels as biomarkers of exposure and aromatic DNA-adducts in blood cells as biomarkers of carcinogenic risk. Many of the genes that appear in the Bayesian networks surrounding plasma cotinine, and to a lesser extent around aromatic DNA-adducts, hold biologically relevant functions in inducing severe adverse effects of smoking. In conclusion, this study shows that Bayesian network inference enables unbiased phenotypic anchoring of transcriptomics responses. Furthermore, in all inferred Bayesian networks several dependencies are found which point to known but also to new relationships between the expression of specific genes, cigarette smoke exposure, DNA damaging-effects, and smoking-related diseases, in particular associated with apoptosis, DNA repair, and tumor suppression, as well as with autoimmunity.

Decreased expression of GRIM-19 by DNA hypermethylation promotes aerobic glycolysis and cell proliferation in head and neck squamous cell carcinoma

To identify novel tumor suppressor genes that are down-regulated by promoter hypermethylation in head and neck squamous cell carcinoma (HNSCC), genome-wide methylation profiling was performed using a methylated DNA immunoprecipitation (MeDIP) array in HNSCC and normal mucosa tissue samples. Promoter hypermethylation of the candidate gene, gene associated with retinoid-interferon induced mortality-19 (GRIM-19), was confirmed in HNSCC cell lines. Multivariate regression analysis determined that GRIM-19 hypermethylation was an independent significant factor for HNSCC diagnosis (OR:125.562; P < 0.001). HNSCC patients with lower ratio of GRIM-19/ACTB hypermethylation had increased overall and disease free survival. Furthermore, the optimal cutoff provided 90% sensitivity and 77% specificity of GRIM-19 hypermethylation as a diagnostic marker for HNSCC. Ectopic expression of GRIM-19 in HNSCC cells led to increased oxygen consumption, reduced glycolysis and decreased cell proliferation. HNSCC cells ectopically expressing GRIM-19 displayed increased p53 activity as well as decreased Stat3 and HIF-1α activities. Moreover, GRIM-19 knockdown not only resulted in decreased oxygen consumption and increased aerobic glycolysis but also promoted cell proliferation and tumorigenic capacity in HNSCC cells. Our data indicate that decreased GRIM-19 expression due to promoter hypermethylation may be important in head and neck carcinogenesis by promoting cell proliferation and regulating metabolic activity.

Novel Application of Junction Trees to the Interpretation of Epigenetic Differences among Lung Cancer Subtypes

In this era of precision medicine, understanding the epigenetic differences in lung cancer subtypes could lead to personalized therapies by possibly reversing these alterations. Traditional methods for analyzing microarray data rely on the use of known pathways. We propose a novel workflow, called Junction trees to Knowledge (J2K) framework, for creating interpretable graphical representations that can be derived directly from in silico analysis of microarray data. Our workflow has three steps, preprocessing (discretization and feature selection), construction of a Bayesian network and, its subsequent transformation into a Junction tree. We used data from the Cancer Genome Atlas to perform preliminary analyses of this J2K framework. We found relevant cliques of methylated sites that are junctions of the network along with potential methylation biomarkers in the lung cancer pathogenesis.