Gene expression and methylation profiles identified CXCL3 and CXCL8 as key genes for diagnosis and prognosis of colon adenocarcinoma

Nucleotide metabolism-associated drug resistance gene NDUFA4L2 promotes colon cancer progression and 5-FU resistance

Chemotherapy is an effective way to improve the prognosis of colorectal cancer patients, but patient resistance to chemotherapeutic agents is becoming a major obstacle to treatment. Nucleotide metabolism correlates with the progression of colorectal cancer and chemotherapy resistance, but the mechanisms involved need to be further investigated. We calculated the half-maximal inhibitory concentrations (IC50) of 5-Fluorouracil (5-FU) in colorectal cancer patients using the "oncopredict" package, screened nucleotide metabolism-related drug resistance genes, and constructed a risk score model. According to the Kaplan-Meier(KM) analysis, the overall survival (OS) and disease-free survival (PFS) of the high-risk group were significantly lower than those of the low-risk group. In addition, the nomogram we constructed had good performance in predicting OS in colon adenocarcinoma (COAD) patients. We validated NDUFA4L2 by cellular functionality experiments, animal tumorigenesis experiments and drug resistance experiments. It was demonstrated that NDUFA4L2 promoted the proliferation and migration of colon cancer cells, while the abnormal regulation of NDUFA4L2 affected the 5-FU resistance of colon cancer cells. In conclusion, we found that NDUFA4L2 promotes the progression and metastasis of colon cancer, as well as resistance to 5-FU chemotherapy.

Network Pharmacology Prediction and Molecular Docking-Based Strategy to Explore the Potential Mechanism of Gualou Xiebai Banxia Decoction against Myocardial Infarction

The aim of this study was to investigate targets through which Gualou Xiebai Banxia decoction aids in treating myocardial infarction (MI) using network pharmacology in combination with molecular docking. The principal active ingredients of Gualou Xiebai Banxia decoction were identified from the TCMSP database using the criteria of drug-likeness ≥30% and oral bioavailability ≥0.18. Interactions and pathway enrichment were investigated using protein-protein interaction (PPI) networks and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, respectively. Active component structures were docked with those of potential protein targets using AutoDock molecular docking relative softwares. HIF1A was of particular interest as it was identified by the PPI network, GO and KEGG pathway enrichment analyses. In conclusion, the use of network pharmacology prediction and molecular docking assessments provides further information on the active components and mechanisms of action Gualou Xiebai Banxia decoction.

Comprehensive analysis of the clinical and biological significances for chemokine CXCL3 in cholangiocarcinoma

Cholangiocarcinoma (CHOL) is a race malignant cancer arising from bile duct epithelial cells in clinical practice. C-X-C motif chemokine ligand 3 (CXCL3) is a member of chemokines family, which participates in the pathogenesis of various tumors. However, the association between CXCL3 and CHOL is unclear. This present study was to assess the role of CXCL3 expression in the progress of CHOL. TIMER, GEPIA, UALCAN, GSCA, LinkedOmics, Metascape and STRING databases were performed to evaluate the clinical and biological significances for CXCL3 with CHOL patients including expression, clinicopathological factors, immune cell infiltration, GO enrichment and KEGG pathway analyses, as well as PPI network analysis. The immunohistochemistry analysis of tissue microarray was conducted to detect the protein expression level, subcellular localization, clinicopathological factors and prognosis of CXCL3 in CHOL. The mRNA and protein expression levels of CXCL3 were markedly increased in CHOL tissues. The overexpression of CXCL3 was strongly associated with maximum tumor diameter of patients with CHOL. Additionally, there were negative correlations between the expression of CXCL3 and monocyte as well as Th17. Low infiltration of neutrophil indicated significantly shorter cumulative survival in CHOL patients. And CXCL3 was significantly associated with arm-level deletion of CD8+ T cell. Furthermore, functional network analysis suggested that CXCL3 and its associated genes were mainly enriched for chemotaxis, secretory granule membrane, cytokine activity and IL-17 signaling pathway. CXCL3 might potentially participate in the carcinogenesis of CHOL, which provided a direction for future research on the mechanism of CXCL3 in CHOL.

Single-cell transcriptomic analysis of normal and pathological tissues from the same patient uncovers colon cancer progression

The aim of the present study was to elucidate the evolutionary trajectory of colon cells from normal colon mucosa, to adenoma, then to carcinoma in the same microenvironment. Normal colon, adenoma and carcinoma tissues from the same patient were analyzed by single-cell sequencing, which perfectly simulated the process of time-dependent colon cancer due to the same microenvironment. A total of 22 cell types were identified. Results suggest the presence of dominant clones of same cells including C2 goblet cell, epithelial cell subtype 1 (Epi1), enterocyte cell subset 0 (Entero0), and Entero5 in carcinoma. Epi1 and Entero0 were Co-enriched in antibacterial and IL-17 signaling, Entero5 was enriched in immune response and mucin-type O-glycan biosynthesis. We discovered new colon cancer related genes including AC007952.4, NEK8, CHRM3, ANO7, B3GNT6, NEURL1, ODC1 and KCNMA1. The function of TBC1D4, LTB, C2CD4A, AND GBP4/5 in T cells needs to be clarified. We used colon samples from the same person, which provide new information for colon cancer therapy.

Autophagy-related IFNG is a prognostic and immunochemotherapeutic biomarker of COAD patients

Background

Numerous studies have shown autophagy affects cellular immune responses. This study aims to explore prognosis and immunotherapeutic biomarkers related to autophagy in colon adenocarcinoma (COAD).

Methods

Based on R software, we performed the ssGSEA, differential expression analysis, Kaplan-Meier survival analysis, correlation analysis, and enrichment analysis. For wet experiment, we did qRT-PCR, immunohistochemistry and CCK-8 experiments.

Results

Using autophagy-related genes (ARGs) and the ssGSEA, COAD patients were divided into low and high autophagy groups. For immune score, stromal score, tumor purity, tumor infiltrating immune cells, co-signaling molecules, tumor mutational burden, microsatellite instability, mismatch repair, immune-related pathways, immune signatures, somatic mutations and subtype analysis, high autophagy group might benefit more from immunotherapy. Among 232 ARGs, IFNG was generally significantly correlated with tumor immunotherapy biomarkers (PD-L1, CD8A and cytotoxic T lymphocytes (CTL)). The disease-free survival of high IFNG group was significantly longer than that of low group. On above-mentioned immune-related research, the high IFNG group reached the same conclusion. The qRT-PCR and IHC analysis confirmed that IFNG was significantly higher expressed in dMMR samples compared to pMMR samples. For chemotherapy, the autophagy and IFNG were significantly negatively related to the chemosensitivity to cisplatin; IFNG inhibitor glucosamine increased cisplatin chemoresistance while IFNG increased cisplatin chemosensitivity; IFNG could reverse glucosamine induced chemoresistance. The functional enrichment analysis of IFNG, PD-L1, CD8A and 20 similar proteins were related to the activation of the immune system. The GSEA and ceRNA network partly described interaction mechanisms of IFNG with PD-L1 and CD8A.

Conclusion

Autophagy score and IFNG expression were novel immunotherapy predictive biomarkers, which might play predictive effects through the JAK-STAT signaling pathway. IFNG might be a potential targeted therapy for cisplatin resistant colon cancer. Besides, IFNG was also a prognostic indicator.

Chemokines in colon cancer progression

Colon cancer is a major human cancer accounting for about a tenth of all cancer cases thus making it among the top three cancers in terms of incidence as well as mortality. Metastasis to distant organs, particularly to liver, is the primary reason for associated mortality. Chemokines, the chemo-attractants for various immune cells, have increasingly been reported to be involved in cancer initiation and progression, including in colon cancer. Here we discuss the available knowledge on the role of several chemokines, such as, CCL2, CCL3, CCL5, CXCL1, CXCL2, CXCL8 in colon cancer progression. CCL20 is one chemokine with emerging evidence for its role in influencing colon cancer tumor microenvironment through the documents effects on fibroblasts, macrophages and immune cells. We focus on CCL20 and its receptor CCR6 as promising factors that affect multiple levels of colon cancer progression. They interact with several cytokines and TLR receptors leading to increased aggressiveness, as supported by multitude of evidence from in vitro, in vivo studies as well as human patient samples. CCL20-CCR6 bring about their biological effects through regulation of several signaling pathways, including, ERK and NF-κB pathways, in addition to the epithelial-mesenchymal transition. Signaling involving CCL20-CCR6 has profound effect on colon cancer hepatic metastasis. Combined with elevated CCL20 levels in colon tumors and metastatic patients, the above information points to a need for further evaluation of chemokines as diagnostic and/or prognostic biomarkers.

Systematic Analysis of CXC Chemokine-Vascular Endothelial Growth Factor A Network in Colonic Adenocarcinoma from the Perspective of Angiogenesis

Background

Tumor angiogenesis plays a vital role in tumorigenesis, proliferation, and metastasis. Recently, vascular endothelial growth factor A (VEGFA) and CXC chemokines have been shown to play vital roles in angiogenesis. Exploring the expression level, gene regulatory network, prognostic value, and target prediction of the CXC chemokine-VEGFA network in colon adenocarcinoma (COAD) is crucial from the perspective of tumor angiogenesis.

Methods

In this study, we analyzed gene expression and regulation, prognostic value, target prediction, and immune infiltrates related to the CXC chemokine-VEGFA network in patients with COAD using multiple databases (cBioPortal, UALCAN, Human Protein Atlas, GeneMANIA, GEPIA, TIMER (version 2.0), TRRUST (version 2), LinkedOmics, and Metascape).

Results

Our results showed that CXCL1/2/3/5/6/8/11/16/17 and VEGFA were markedly overexpressed, while CXCL12/13/14 were underexpressed in patients with COAD. Moreover, genetic alterations in the CXC chemokine-VEGFA network found at varying rates in patients with COAD were as follows: CXCL1/2/17 (2.1%), CXCL3/16 (2.6%), CXCL5/14 (2.4%), CXCL6 (3%), CXCL8 (0.8%), CXCL11/13 (1.9%), CXCL12 (0.6%), and VEGFA (1.3%). Promoter methylation of CXCL1/2/3/11/13/17 was considerably lower in patients with COAD, whereas methylation of CXCL5/6/12/14 and VEGFA was considerably higher. Furthermore, CXCL9/10/11 and VEGFA expression was notably correlated with the pathological stages of COAD. In addition, patients with COAD with high CXCL8/11/14 or low VEGFA expression levels survived longer than patients with dissimilar expression levels. CXC chemokines and VEGFA form a complex regulatory network through coexpression, colocalization, and genetic interactions. Moreover, many transcription factor targets of the CXC chemokine-VEGFA network in patients with COAD were identified: RELA, NFKB1, ZFP36, XBP1, HDAC2, SP1, ATF4, EP300, BRCA1, ESR1, HIF1A, EGR1, STAT3, and JUN. We further identified the top three miRNAs involved in regulating each CXC chemokine within the network: miR-518C, miR-369-3P, and miR-448 regulated CXCL1; miR-518C, miR-218, and miR-493 regulated CXCL2; miR-448, miR-369-3P, and miR-221 regulated CXCL3; miR-423 regulated CXCL13; miR-378, miR-381, and miR-210 regulated CXCL14; miR-369-3P, miR-382, and miR-208 regulated CXCL17; miR-486 and miR-199A regulated VEGFA. Furthermore, the CXC chemokine-VEGFA network in patients with COAD was notably associated with immune infiltration.

Conclusions

This study revealed that the CXC chemokine-VEGFA network might act as a prognostic biomarker for patients with COAD. Moreover, our study provides new therapeutic targets for COAD, serving as a reference for further research in the future.

Expression of chemokine CXCL8/9/10/11/13 and its prognostic significance in head and neck cancer

BACKGROUND

Head and neck cancer (HNC) is a very popular cancer, with many primary sites and pathological types, at the top of the list of tumors. Chemokines are a class of small molecular basic proteins, whose N-terminal cysteine residues can be divided into four subunits by location and number, which significantly enhances the expression level in all kinds of cancers. However, in HNC, especially in head and neck squamous cell carcinoma, the chemokine CXCL8/9/10/11/13 has not been clearly explored for its diagnosis and prognosis.

METHODS

The ONCOMINE database was used to analyze the expression of chemokine family in various cancers. After CXCL8/9/10/11/13 was screened out, the expression of CXCL 8/9/11/13 in patients with HNC/normal people were analyzed by UALCAN database. The expression and pathological stages of CXCL 8/9/10/13 in HNC tissues were analyzed by the GEPIA database, and the relationship between its mRNA expression and the overall survival (OS) time of patients with HNC was analyzed by Kaplan-Meier plotter database. In addition, 171 co-expressed genes significantly related to CXCL8/9/10/11/13 mutation were screened by online tool cBioPortal, and the protein interaction network of these genes was constructed by STRING database. Finally, the potential functions of CXCL8/9/10/11/13 and its 171 co-expressed genes were explored by the enrichment and analysis function of David database.

RESULTS

Transcriptional expression of chemokine 8/9/10/11/13 was significantly increased in patients with HNC. Clinical stage of patients with HNC was significantly correlated with overexpression of CXCL9/10/11. In addition, the chemokine CXCL8/9/10/13 was significantly correlated with over-survival of patients with HNC, so it could be distinguished between short-term and long-term survival of patients with HNC. In conclusion, CXCL8/9/10/11/13 closely connected with the expression and prognosis of HNC.

CONCLUSION

In this study, our results suggest that chemokine CXCL8/9/10/11/13 may play a critical role in the development of HNC, and, according to relevant data, it may affect the survival and prognosis of patients with HNC.

Chemokines in progression, chemoresistance, diagnosis, and prognosis of colorectal cancer

Plenty of factors affect the oncogenesis and progression of colorectal cancer in the tumor microenvironment, including various immune cells, stromal cells, cytokines, and other factors. Chemokine is a member of the cytokine superfamily. It is an indispensable component in the tumor microenvironment. Chemokines play an antitumor or pro-tumor role by recruitment or polarization of recruiting immune cells. Meanwhile, chemokines, as signal molecules, participate in the formation of a cross talk among signaling pathways and non-coding RNAs, which may be involved in promoting tumor progression. In addition, they also function in immune escape. Chemokines are related to drug resistance of tumor cells and may even provide reference for the diagnosis, therapy, and prognosis of patients with colorectal cancer.

Inhibitory effect of lingonberry extract on HepG2 cell proliferation, apoptosis, migration, and invasion

Lingonberry (Vaccinium vitis-idaea L.) extract contains various active ingredients with strong inhibitory effects on cancer cell growth. HepG2 cells were treated with various concentrations of lingonberry extract, cell inhibition rate was measured by CCK-8 assay, and apoptosis rate by annexin-propidium iodide double-staining assay. The cell cycle was analyzed by flow cytometry, and cell migration and invasion by transwell assay. Real-time reverse transcription-PCR and western blotting were employed to analyze the expression of C-X-C motif chemokine ligand 3 (CXCL3). Ki-67, TUNEL, and transwell assays were used to verify the relationship between CXCL3 expression and cell proliferation, apoptosis, migration, and invasion. The composition of lingonberry extract was: 37.58% cyanidin-3-O-glucoside, 10.96% kaempferol 3-O-arabinoside, 4.52% epicatechin, 4.35% chlorogenic acid, 3.83% catechinic acid, 1.54% isoquercitrin, 1.05% 4-hydroxycinnamon acid, 1.03% cyanidin chloride, 0.85% 2,3-dihydroxybenzoic acid, 0.55% quercetin, 0.36% D-(-)-quininic acid, 0.96% caffeic acid, 0.16% ferulic acid, 0.12% oleanolic acid, and 0.03% ursolic acid. Lingonberry extract inhibited the proliferation of HepG2 cells in a dose-dependent manner. After 48 h exposure to 100 μg/mL extract the inhibition rate and IC₅₀ were 80.89±6.05% and 22.62 μg/mL, respectively. Lingonberry extract promoted late apoptosis in HepG2 cells and arrested the cell cycle at G2/M and S phases. Lingonberry extract also promoted the apoptosis of HepG2 cancer cells, inhibiting their proliferation, migration, and invasion by regulating the expression of CXCL3. This study offers new insight into the antihepatoma activity of lingonberry extract and provides a basis for the development of pilot antitumor drugs.

A comprehensive bioinformatics analysis to identify potential prognostic biomarkers among CC and CXC chemokines in breast cancer

Breast cancer (BC) is a major human health problem due to its increasing incidence and mortality rate. CC and CXC chemokines are associated with tumorigenesis and the progression of many cancers. Since the prognostic values of CC and CXC families' expression in various types of cancers are becoming increasingly evident, we aimed to conduct a comprehensive bioinformatics analysis elucidating the prognostic values of the CC and CXC families in BC. Therefore, TCGA, UALCAN, Kaplan–Meier plotter, bc-GenExMiner, cBioPortal, STRING, Enrichr, and TIMER were utilized for analysis. We found that high levels of CCL4/5/14/19/21/22 were associated with better OS and RFS, while elevated expression of CCL24 was correlated with shorter OS in BC patients. Also, high levels of CXCL9/13 indicated longer OS, and enhanced expression of CXCL12/14 was linked with better OS and RFS in BC patients. Meanwhile, increased transcription levels of CXCL8 were associated with worse OS and RFS in BC patients. In addition, our results showed that CCL5, CCL8, CCL14, CCL20, CCL27, CXCL4, and CXCL14 were notably correlated with the clinical outcomes of BC patients. Our findings provide a new point of view that may help the clinical application of CC and CXC chemokines as prognostic biomarkers in BC.

RNA-seq and Network Analysis Reveal Unique Chemokine Activity Signatures in the Synovial Tissue of Patients With Rheumatoid Arthritis

Purpose

This study aimed to provide a comprehensive understanding of the genome-wide expression patterns in the synovial tissue samples of patients with rheumatoid arthritis (RA) to investigate the potential mechanisms regulating RA occurrence and development.

Methods

Transcription profiles of the synovial tissue samples from nine patients with RA and 15 patients with osteoarthritis (OA) (control) from the East Asian population were generated using RNA sequencing (RNA-seq). Gene set enrichment analysis (GSEA) was used to analyze all the detected genes and the differentially expressed genes (DEGs) were identified using DESeq. To further analyze the DEGs, the Gene Ontology (GO) functional enrichment and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed. The protein-protein interaction (PPI) network of the DEGs was constructed using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and the hub genes were identified by topology clustering with the Molecular Complex Detection (MCODE)-Cytoscape. The most important hub genes were validated using quantitative real-time PCR (qRT-PCR).

Results

Of the 17,736 genes detected, 851 genes were identified as the DEGs (474 upregulated and 377 downregulated genes) using the false discovery rate (FDR) approach. GSEA revealed that the significantly enriched gene sets that positively correlated with RA were CD40 signaling overactivation, Th1 cytotoxic module, overactivation of the immune response, adaptive immune response, effective vs. memory CD8+ T cells (upregulated), and naïve vs. effective CD8+ T cells (downregulated). Biological process enrichment analysis showed that the DEGs were significantly enriched for signal transduction (P = 3.01 × 10-6), immune response (P = 1.65 × 10-24), and inflammatory response (P = 5.76 × 10-10). Molecule function enrichment analysis revealed that the DEGs were enriched in calcium ion binding (P = 1.26 × 10-5), receptor binding (P = 1.26 × 10-5), and cytokine activity (P = 2.01 × 10-3). Cellular component enrichment analysis revealed that the DEGs were significantly enriched in the plasma membrane (P = 1.91 × 10-31), an integral component of the membrane (P = 7.39 × 10-13), and extracellular region (P = 7.63 × 10-11). The KEGG pathway analysis showed that the DEGs were enriched in the cytokine-cytokine receptor interaction (P = 3.05 × 10-17), chemokine signaling (P = 3.50 × 10-7), T-cell receptor signaling (P = 5.17 × 10-4), and RA (P = 5.17 × 10-4) pathways. We confirmed that RA was correlated with the upregulation of the PPI network hub genes, such as CXCL13, CXCL6, CCR5, CXCR5, CCR2, CXCL3, and CXCL10, and the downregulation of the PPI network hub gene such as SSTR1.

Conclusion

This study identified and validated the DEGs in the synovial tissue samples of patients with RA, which highlighted the activity of a subset of chemokine genes, thereby providing novel insights into the molecular mechanisms of RA pathogenesis and identifying potential diagnostic and therapeutic targets for RA.

Exploration of Reduced Mitochondrial Content–Associated Gene Signature and Immunocyte Infiltration in Colon Adenocarcinoma by an Integrated Bioinformatic Analysis

Purpose: Mitochondrial dysfunction refers to cancer immune evasion. A novel 7-gene prognostic signature related to the mitochondrial DNA copy number was utilized to evaluate the immunocyte infiltration in colon cancer according to the risk scores and to predict the survival for colon cancer.

Experimental design: We performed an integrated bioinformatic analysis to analyze transcriptome profiling of the EB-treated mitochondrial DNA–defected NCM460 cell line with differentially expressed genes between tumor and normal tissues of COAD in TCGA. The LASSO analysis was utilized to establish a prognostic signature. ESTIMATE and CIBERSORT validated the differences of immunocyte infiltration between colon cancer patients with high- and low-risk scores.

Results: Our study identified a 7-gene prognostic signature (LRRN2, ANKLE1, GPRASP1, PRAME, TCF7L1, RAB6B, and CALB2). Patients with colon cancer were split into the high- and low-risk group by the risk scores in TCGA (training cohort: HR = 2.50 p < 0.0001) and GSE39582 (validation cohort: HR = 1.43 p < 0.05). ESTIMATE and CIBERSORT revealed diverseness of immune infiltration in the two groups, especially downregulated T-cell infiltration in the patients with high-risk scores. Finally, we validated the colon patients with a low expression of the mitochondrial number biomarker TFAM had less CD3+ and CD8+ T-cell infiltration in clinical specimens.

Conclusion: An mtDNA copy number-related 7-gene prognostic signature was investigated and evaluated, which may help to predict the prognosis of colon cancer patients and to guide clinical immunotherapy via immunocyte infiltration evaluation.

Bioinformatic Analyses and Experimental Verification Reveal that High FSTL3 Expression Promotes EMT via Fibronectin-1/α5β1 Interaction in Colorectal Cancer

Background: Colorectal cancer (CRC) is a typical cancer prevalent worldwide. Despite the conventional treatments, CRC has a poor prognosis due to relapse and metastasis. Moreover, there is a dearth of sensitive biomarkers for predicting prognosis in CRC.

Methods: This study used a bioinformatics approach combining validation experiments to examine the value of follistatin-like 3 (FSTL3) as a prognostic predictor and therapeutic target in CRC.

Results:FSTL3 was remarkably upregulated in the CRC samples. FSTL3 overexpression was significantly associated with a poor prognosis. FSTL3 was found to activate the epithelial-mesenchymal transition by promoting the binding of FN1 to α5β1. FSTL3 expression was also positively correlated with the abundance of the potent immunosuppressors, M2 macrophages.

Conclusion:FSTL3 overexpression affects CRC prognosis and thus, FSTL3 can be a prognostic biomarker and therapeutic target with potential applications in CRC.

Prognostic Score Model Based on Ten Differentially Methylated Genes for Predicting Clinical Outcomes in Patients with Adenocarcinoma of the Colon

Purpose

We aimed to screen novel genetic biomarkers for use in a prognostic score (PS) model for the accurate prediction of survival outcomes for patients with colon adenocarcinoma (COAD).

Methods

Gene expression and methylation data were downloaded from The Cancer Genome Atlas database, and the samples were randomly divided into training and validation sets for the screening of differentially methylated genes (DMGs) and differentially expressed genes (DEGs). Co-methylated genes were screened using weighted gene co-expression network analysis. Functional enrichment analysis was performed using the Database for Annotation, Visualization, and Integrated Discovery. Univariate and multivariate Cox regression analyses were performed to identify prognosis-related genes and clinical factors. Receiver operating characteristic curve analysis was carried out to evaluate the predictive performance of the PS model.

Results

In total, 1434 DEGs and 1038 DMGs were screened in the training set, among which 284 were found to be overlapping genes. For 127 of these overlapping genes, the methylation and expression levels were significantly negatively correlated. An optimal signature from 10 DMGs was identified to construct the PS model. Patients with a high PS seemed to have worse outcomes than those with a low PS. Moreover, cancer recurrence and the PS model status were independent prognostic factors.

Conclusion

This PS model based on an optimal 10-gene signature would help in the stratification of patients with COAD and improve the assessment of their clinical outcomes.

Development and validation of a risk prediction model and nomogram for colon adenocarcinoma based on methylation-driven genes

Evidence suggests that abnormal DNA methylation patterns play a crucial role in the etiology and pathogenesis of colon adenocarcinoma (COAD). In this study, we identified a total of 97 methylation-driven genes (MDGs) through a comprehensive analysis of the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Univariate Cox regression analysis identified four MDGs (CBLN2, RBM47, SLCO4C1, and TMEM220) associated with overall survival (OS) in COAD patients. A risk prediction model was then developed based on these four MDGs to predict the prognosis of COAD patients. We also created a nomogram that incorporated risk scores, age, and TNM stage to promote a personalized prediction of OS in COAD patients. Compared with the traditional TNM staging system, our new nomogram was better at predicting the OS of COAD patients. In cell experiments, we confirmed that the mRNA expression levels of CLBN2 and TMEM220 were regulated by the methylation of their promoter regions. Moreover, immunohistochemistry showed that CBLN2 and TMEM220 were potential prognostic biomarkers for COAD patients. In summary, we have established a risk prediction model and nomogram that might be effectively utilized to promote the prediction of OS in COAD patients.

CCDC167 as a potential therapeutic target and regulator of cell cycle-related networks in breast cancer

According to cancer statistics reported in 2020, breast cancer constitutes 30% of new cancer cases diagnosed in American women. Histological markers of breast cancer are expressions of the estrogen receptor (ER), the progesterone receptor (PR), and human epidermal growth factor receptor (HER)-2. Up to 80% of breast cancers are grouped as ER-positive, which implies a crucial role for estrogen in breast cancer development. Therefore, identifying potential therapeutic targets and investigating their downstream pathways and networks are extremely important for drug development in these patients. Through high-throughput technology and bioinformatics screening, we revealed that coiled-coil domain-containing protein 167 (CCDC167) was upregulated in different types of tumors; however, the role of CCDC167 in the development of breast cancer still remains unclear. Integrating many kinds of databases including ONCOMINE, MetaCore, IPA, and Kaplan-Meier Plotter, we found that high expression levels of CCDC167 predicted poor prognoses of breast cancer patients. Knockdown of CCDC167 attenuated aggressive breast cancer growth and proliferation. We also demonstrated that treatment with fluorouracil, carboplatin, paclitaxel, and doxorubicin resulted in decreased expression of CCDC167 and suppressed growth of MCF-7 cells. Collectively, these findings suggest that CCDC167 has high potential as a therapeutic target for breast cancer.

Analysis of the Prognosis and Therapeutic Value of the CXC Chemokine Family in Head and Neck Squamous Cell Carcinoma

The CXC chemokines belong to a family which includes 17 different CXC members. Accumulating evidence suggests that CXC chemokines regulate tumor cell proliferation, invasion, and metastasis in various types of cancers by influencing the tumor microenvironment. The different expression profiles and specific function of each CXC chemokine in head and neck squamous cell carcinoma (HNSCC) are not yet clarified. In our work, we analyzed the altered expression, interaction network, and clinical data of CXC chemokines in patients with HNSCC by using the following: the Oncomine dataset, cBioPortal, Metascape, String analysis, GEPIA, and the Kaplan–Meier plotter. The transcriptional level analysis suggested that the mRNA levels of CXCL1, CXCL2, CXCL3, CXCL5, CXCL6, CXCL8, CXCL9, CXCL10, CXCL11, and CXCL13 increased in HNSCC tissue samples when compared to the control tissue samples. The expression levels of CXCL9, CXCL10, CXCL11, CXCL12, and CXCL14 were associated with various tumor stages in HNSCC. Clinical data analysis showed that high transcription levels of CXCL2, CXCL3, and CXCL12, were linked with low relapse-free survival (RFS) in HNSCC patients. On the other hand, high CXCL14 levels predicted high RFS outcomes in HNSCC patients. Meanwhile, increased gene transcription levels of CXCL9, CXCL10, CXCL13, CXCL14, and CXCL17 were associated with a higher overall survival (OS) advantage in HNSCC patients, while high levels of CXCL1, and CXCL8 were associated with poor OS in all HNSCC patients. This study implied that CXCL1, CXCL2, CXCL3, CXCL8, and CXCL12 could be used as prognosis markers to identify low survival rate subgroups of patients with HNSCC as well as be potential suitable therapeutic targets for HNSCC patients. Additionally, CXCL9, CXCL10, CXCL13, CXCL14, and CXCL17 could be used as functional prognosis biomarkers to identify better survival rate subgroups of patients with HNSCC.

Key genes in youth colorectal cancer based on data mining and verification by reverse transcription-quantitative PCR

In recent years, among all patients with colorectal cancer, the proportion of young patients has been gradually increasing. However, the molecular mechanisms involved in colorectal cancer in the young are largely unknown. In the present study the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas datasets were integrated to elucidate the key gene biomarkers in these patients. The GSE41657 and GSE41258 datasets were downloaded from the GEO database. By screening for differentially expressed genes, Gene Ontology analysis, Kyoto Encyclopedia of Genes and Genomes pathway analysis, protein-protein interaction analysis, hub gene screening and survival analysis, two key genes, CXCL8 and VEGFA, which were enriched in cancer pathways, were obtained. Reverse transcription-quantitative (RT-q)PCR was performed to verify the outcome obtained by bioinformatics analysis. In conclusion, the present study identified two key genes using bioinformatics analysis and RT-qPCR validation. These results indicated that the candidate genes may be involved in the progression of colorectal cancer in young people, and these two genes may act as ideal prognostic indicators or therapeutic targets for colorectal cancer in the youth.

Aberrantly Methylated-Differentially Expressed Genes Identify Novel Atherosclerosis Risk Subtypes

Increasing evidence has indicated that modulation of epigenetic mechanisms, especially methylation and long-non-coding RNA (lncRNA) regulation, plays a pivotal role in the process of atherosclerosis; however, few studies focused on revealing the epigenetic-related subgroups during atherosclerotic progression using unsupervised clustering analysis. Hence, we aimed to identify the epigenetics-related differentially expressed genes associated with atherosclerosis subtypes and characterize their clinical utility in atherosclerosis. Eighty samples with expression data (GSE40231) and 49 samples with methylation data (GSE46394) from a large artery plaque were downloaded from the GEO database, and aberrantly methylated-differentially expressed (AMDE) genes were identified based on the relationship between methylation and expression. Furthermore, we conducted weighted correlation network analysis (WGCNA) and co-expression analysis to identify the core AMDE genes strongly involved in atherosclerosis. K-means clustering was used to characterize two subtypes of atherosclerosis in GSE40231, and then 29 samples were recognized as validation dataset (GSE28829). In a blood sample cohort (GSE90074), chi-square test and logistic analysis were performed to explore the clinical implication of the K-means clusters. Furthermore, significance analysis of microarrays and prediction analysis of microarrays (PAM) were applied to identify the signature AMDE genes. Moreover, the classification performance of signature AMDE gene-based classifier from PAM was validated in another blood sample cohort (GSE34822). A total of 1,569 AMDE mRNAs and eight AMDE long non-coding RNAs (lncRNAs) were identified by differential analysis. Through the WGCNA and co-expression analysis, 32 AMDE mRNAs and seven AMDE lncRNAs were identified as the core genes involved in atherosclerosis development. Functional analysis revealed that AMDE genes were strongly related to inflammation and axon guidance. In the clinical analysis, the atherosclerotic subtypes were associated with the severity of coronary artery disease and risk of adverse events. Eight genes, including PARP15, SERGEF, PDGFD, MRPL45, UBR1, STAU1, WIZ, and LSM4, were selected as the signature AMDE genes that most significantly differentiated between atherosclerotic subtypes. Ultimately, the area under the curve of signature AMDE gene-based classifier for atherosclerotic subtypes was 0.858 and 0.812 in GSE90074 and GSE34822, respectively. This study identified the AMDE genes (lncRNAs and mRNAs) that could be implemented in clinical clustering to recognize high-risk atherosclerotic patients.

A Prognostic Nomogram Model Based on mRNA Expression of DNA Methylation-Driven Genes for Gastric Cancer

PURPOSE

The exploration and interpretation of DNA methylation-driven genes might contribute to molecular classification, prognostic prediction and therapeutic choice. In this study, we built a prognostic risk model via integrating analysis of the transcriptome and methylation profile for patients with gastric cancer (GC).

METHODS

The mRNA expression profiles, DNA methylation profiles and corresponding clinicopathological information of 415 GC patients were downloaded from The Cancer Genome Atlas (TCGA). Differential expression and correlation analysis were performed to identify DNA methylation-driven genes. The candidate genes were selected by univariate Cox regression analyses followed by the least absolute shrinkage and selection operator (LASSO) regression. A prognostic risk nomogram model was then built together with clinicopathological parameters.

RESULTS

5 DNA methylation-driven genes (CXCL3, F5, GNAI1, GAMT and GHR) were identified by integrated analyses and selected to construct the prognostic risk model with clinicopathological parameters. High expression and low DNA hypermethylation of F5, GNAI1, GAMT and GHR, as well as low expression and high DNA hypomethylation of CXCL3 were significantly associated with poor prognosis rates, respectively. The high-risk group showed a significantly shorter prognosis than the low-risk group in the TCGA dataset (HR = 0.212, 95% CI = 0.139-0.322, P = 2e-15). The final nomogram model showed high predictive efficiency and consistency in the training and validation group.

CONCLUSION

We construct and validate a prognostic nomogram model for GC based on five DNA methylation-driven genes with high performance and stability. This nomogram model might be a powerful tool for prognosis evaluation in the clinic and also provided novel insights into the epigenetics in GC.

Vitexin enhances osteoblast differentiation through phosphorylation of Smad and expression of Runx2 at in vitro and ex vivo

Vitexin (apigenin-8-C-d-glucopyranoside) is a flavonoid isolated from natural sources. It has been employed as an anti-oxidant, anti-inflammatory, and anti-cancer agent, and is used as a traditional Chinese medicine to treat a variety of illnesses. The present study investigated the effect of vitexin on osteoblast differentiation of C3H10T1/2 mesenchymal stem cells, MC3T3-E1 preosteoblast, mouse calvarial primary cells, and primary bone marrow stem cells (BMSCs). RT-PCR and quantitative PCR demonstrated that vitexin increased mRNA expression of the osteogenic genes distal-less homeobox 5 (Dlx5) and Runxt-related transcription factor 2 (Runx2). Vitexin also increased the Dlx5 and Runx2 protein levels, Smad1/5/9 phosphorylation, and alkaline phosphatase (ALP) activity. In addition, vitexin increased Runx2-luciferase activity. Moreover, knockdown of Runx2 attenuated the increase in ALP activity induced by vitexin. These results demonstrate that vitexin enhances osteoblast differentiation via Runx2.

Comprehensive analysis of the expression and prognostic value of CXC chemokines in colorectal cancer

The C-X-C motif (CXC) chemokines play an important role in inflammatory processes and angiogenesis and are also associated with tumor development, progression and metastasis. They can be either promoting or inhibiting factors in colorectal cancers (CRC). The expression patterns and prognostic values of the CXC family still need further investigation. In this study, we investigated data related to transcription, translation, survival and tumor immune infiltration for CXC chemokines in patients with CRC from the ONCOMINE, GEPIA, cBioPortal, HPA and TIMER databases. We found that the expression levels of CXCL1-3, CXCL5, and CXCL8 were higher in CRC tissues than in colorectal tissues. Expression among stages significantly varied for CXCL1-3 and CXCL9-11. The survival analysis revealed that high transcriptional levels of CXCL4 and CXCL9-11 could serve as positive prognostic factors for patients with CRC. CXCL9-11 were highly associated with CD8+ T cells and natural killer (NK) cells in the tumor immune infiltration analysis, indicating their role in the antitumor immune response. This study implies that CXCL1-3, CXCL5, and CXCL8 are important factors during CRC oncogenesis and that CXCL9-11 could be new biomarkers for the prognosis of CRC.

Identification of epigenetic methylation-driven signature and risk loci associated with survival for colon cancer

Background

Abnormal methylation is associated with the survival of colon cancer. This study intended to discover a significant model based on methylation-driven genes (MDGs) and screen relative risk loci to assist with determining the prognoses of colon cancer patients.

Methods

We downloaded transcriptome expression profiles and 450K methylation data from the TCGA database. We then collected the two normalized profiles and utilized the MethylMix package to identify a significant signature showing the aberrantly methylated events highly correlated with expression levels. Also, functional enriched pathway analysis based on the ConsensusPathDB database was conducted to further explore the underlying cancer-related crosstalk among the identified MDGs. To find the significant MDGs for prognosis, we applied a univariate Cox regression model, and the hub signature was identified based on the stepwise regression method. A risk model based on MDGs was constructed from the multivariate Cox analysis, and a receiver operating characteristic (ROC) curve was drawn to assess the predictive value of the MDG signature. Additionally, the Kruskal-Wallis (K-W) test was conducted to compare differential distributions of risk scores across groups of clinical variables. Furthermore, the methylation sites relating to the hub genes were screened out and the prognostic genes were searched using the Cox regression method. Last, we carried out gene set enrichment analysis (GSEA) with the risk score levels serving as the phenotype base on the JAVA platform.

Results

A total of 514 colon cancer samples with transcriptome profiles, including 473 tumor samples and 41 matched normal samples, were downloaded. We also obtained 351 methylation profiles comprising 314 tumor samples and 37 normal samples. The 320 MDGs identified by MethylMix were enriched in the generic transcription pathway, RNA polymerase II transcription, activation of SMO, or glutathione metabolism. Furthermore, a 10-MDGs signature was selected as the hub prognostic marker, and the risk model was constructed from the multivariate Cox regression results. We also discovered multiple specific methylated sites that were highly associated with survival. Finally, the GSEA results suggested that several enriched pathways were associated with the identified risk drivers, including extracellular matrix (ECM) receptor interaction, chemokine receptor interaction, and pathways in cancer, as well as calcium signaling pathways.

Conclusions

We conducted a comprehensive investigation of the molecular mechanisms in colon cancer by discovering the risk methylation-driven signature combined with relative methylated sites and constructing a risk model to predict prognosis.