Hub Genes and Key Pathway Identification in Colorectal Cancer Based on Bioinformatic Analysis

Effect of acute exercise on gene expression in peripheral blood mononuclear cells of puberty children

Studies have shown that acute exercise alters the expression of circulating neutrophil and peripheral blood mononuclear cell (PBMC) genes, affecting a wide range of processes from cellular growth to the promotion of inflammatory and anti-inflammatory responses. In this study, we identified differential gene expression associated with acute exercise and PBMC in puberty children through the GEO database. We utilized bioinformatics technology to analyze the impact of acute exercise on PBMC and identified key genes involving the puberty children. Combining two datasets of gene expression, we identified 197 shared differentially expressed genes (DEGs) in PBMC before and after exercise. We conducted pathway analysis of these DEGs and built a gene co-expression network. The identification of hub genes was achieved through the utilization of protein-protein interaction (PPI) networks. 268 shared DEGs were identified in the GSE11761 dataset in pre- and post-exercise groups, while 352 differential genes were identified between the pre- and post-exercise groups of females in the GSE14642 dataset. A total of 197 shared genes were identified between the two datasets. Seven core genes were identified by MCODE and CytoHubba, namely IL2RB, KLRD1, GZMB, TBX21, PRF1, HAVCR2, and GZMA. Bioinformatics techniques are effective in screening and analyzing PBMC-associated DEGs in children undergoing acute pre- and post-exercise puberty. Microarray analysis of PBMCs in children undergoing puberty can identify molecules that may predict acute exercise responses. This study provides insights for further exploration of the mechanisms and targets of acute exercise on the organism.

Advances in PGD2/PTGDR2 signaling pathway in tumors: A review

Studies have shown that the prostaglandin (PG) family acts as an allergic inflammatory mediator in malignant diseases. Furthermore, prostaglandin E2 (PGE2) and its related receptors, as well as the prostaglandin D2 (PGD2)/PGD2 receptor (PTGDR2), play irreplaceable roles in tumorigenesis and anti-tumor therapy. Several experiments have demonstrated that PGD2 signaling through PTGDR2 not only directly inhibits cancer cell survival, proliferation, and migration but also reduces resistance toward conventional chemotherapeutic agents. Recent studies from our and other laboratories have shown that PGD2, its ligands, and related metabolites can significantly alter the tumor microenvironment (TME) by promoting the secretion of chemokines and cytokines, thereby inhibiting tumor progression. Additionally, reduced PGD2 expression has been associated with poor prognosis in patients with gastric, breast, lung, and pancreatic cancers, validating the preclinical findings and their clinical relevance. This review focuses on the current understanding of PGD2/PTGDR2 expression patterns and biological activity in cancer, proposing questions to guide the assessment of PGD2 and its receptors as potential targets for effective cancer therapies.

PGD2/PTGDR2 Signal Affects the Viability, Invasion, Apoptosis, and Stemness of Gastric Cancer Stem Cells and Prevents the Progression of Gastric Cancer

BACKGROUND

Prostaglandin D2 (PGD2) has been shown to restrict the occurrence and development of multiple cancers; nevertheless, its underlying molecular mechanism has not been fully elucidated. The present study investigated the effect of PGD2 on the biological function of the enriched gastric cancer stem cells (GCSCs), as well as its underlying molecular mechanism, to provide a theoretical basis and potential therapeutic drugs for gastric cancer (GC) treatment.

METHODS

The plasma PGD2 levels were detected by Enzyme-linked immunosorbent assay (ELISA). Silencing of lipocalin prostaglandin D synthetases (L-PTGDS) and prostaglandin D2 receptor 2 (PTGDR2) was carried out in GCSCs from SGC-7901 and HGC-27 cell lines. Cell Counting Kit-8, transwell, flow cytometry, and western blotting assays were used to determine cell viability, invasion, apoptosis, and stemness of GCSCs. In vivo xenograft models were used to assess tumor growth.

RESULTS

Clinically, it was found that the plasma PGD2 level decreased significantly in patients with GC. PGD2 suppressed viability, invasion, and stemness and increased the apoptosis of GCSCs. Downregulating L-PTGDS and PTGDR2 promoted viability, invasion, and stemness and reduced the apoptosis of GCSCs. Moreover, the inhibition of GCSCs induced by PGD2 was eliminated by downregulating the expression of PTGDR2. The results of in vivo experiments were consistent with those of in vitro experiments.

CONCLUSION

Our data suggest that PGD2 may be an important marker and potential therapeutic target in the clinical management of GC. L-PTGDS/PTGDR2 may be one of the critical targets for GC therapy. The PGD2/PTGDR2 signal affects the viability, invasion, apoptosis, and stemness of GCSCs and prevents the progression of GC.

DKK3 expression is correlated with poorer prognosis in head and neck squamous cell carcinoma: A bioinformatics study based on the TCGA database

OBJECTIVE

We previously reported that dickkopf WNT signaling pathway inhibitor 3 (DKK3) expression is correlated with poorer prognosis in head and neck squamous cell carcinoma (HNSCC). Here we investigated DKK3 expression by using The Cancer Genome Atlas (TCGA) public database and bioinformatic analyses.

METHODS

We used the RNA sequence data and divided the tumor samples into "DKK3-high" and "DKK3-low" groups according to median DKK3 expression. The correlations between DKK3 expression and the clinical data were investigated. Differentially expressed genes (DEGs) were detected using DESEq2 and analyzed by ShinyGO 0.77. A gene set enrichment analysis (GSEA) was also performed using GSEA software. The DEGs were also analyzed with TargetMine to establish the protein-protein interaction (PPI) network.

RESULTS

DKK3 expression was significantly increased in cancer samples, and a high DKK3 expression was significantly associated with shorter overall survival. We identified 854 DEGs, including 284 up-regulated and 570 down-regulated. Functional enrichment analyses revealed several Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways associated with extracellular matrix remodeling. The PPI network identified COL8A1, AGTR1, FN1, P4HA3, PDGFRB, and CEP126 as the key genes.

CONCLUSIONS

These results suggested the cancer-promoting ability of DKK3, the expression of which is a promising prognostic marker and therapeutic target for HNSCC.

Antioxidative and ROS-dependent apoptotic effects of Cuscuta reflexa Roxb. stem against human lung cancer: network pharmacology and in vitro experimental validation

Lung cancer remains a formidable global health challenge, necessitating the exploration of novel therapeutic approaches. This study investigates the potential of Cuscuta reflexa Roxb. stem extract as an anticancer agent against human lung cancer, focusing on its antioxidative and ROS-dependent apoptotic effects. Utilizing a combination of network pharmacology and in-vitro experimental validation, we delineate the multifaceted molecular mechanisms underlying the observed effects. The antioxidant potential of C. reflexa stem extract was evaluated by the 2,2-diphenyl-1-picrylhydrazyl (DPPH•), 2,2-azinobis (3-ethyl-benzothiazoline-6-sulfonic acid) (ABTS•+) and ferric reducing/antioxidant power (FRAP), hydroxyl free radical scavenging, reactive nitrogen oxide scavenging and super oxide anion radical scavenging assays. Furthermore, the antiproliferative and proapoptotic effect of C. reflexa stem extract was evaluated against A549 lung adenocarcinoma cell line using the consecrated sulforhodamine B (SBR) and Annexin V-PI assays. Additionally, the mitochondrial membrane potential (MMP) and the total reactive oxygen species (ROS) estimation assays were performed. As a result, network pharmacology analysis revealed a complex interaction network between the bioactive constituents of C. reflexa and key proteins implicated in lung cancer progression. The C. reflexa stem extract showed dose-dependent antioxidant activity against DPPH• (IC50 - 87.38 µg/mL), reactive nitrogen oxide (IC50 - 318.34 µg/mL), FRAP (IC50 - 359.96 µg/mL), hydroxy free radicals (IC50 - 526.12 µg/mL) than ABTS●+ (IC50 - 698.45 µg/mL) and super oxide anion (IC50 - 892.71 µg/mL) as well as cytotoxic activity against A549 cells (IC50 - 436.80 µg/mL). Observations of morphological features in treated cells have revealed hallmark of apoptosis properties. Furthermore, as a result of treatment with C. reflexa stem extract, ROS generation and mitochondrial depolarization were increased in A549 cells, suggesting that this treatment has significant apoptotic properties. . These findings highlight the potential utility of this natural extract as an innovative therapeutic strategy for lung cancer treatment. The integration of network pharmacology and experimental validation enhances our understanding of the underlying mechanisms and provide the way for further translational research.Communicated by Ramaswamy H. Sarma.

Colon cancer transcriptome

Over the last four decades, methodological innovations have continuously changed transcriptome profiling. It is now feasible to sequence and quantify the transcriptional outputs of individual cells or thousands of samples using RNA sequencing (RNA-seq). These transcriptomes serve as a connection between cellular behaviors and their underlying molecular mechanisms, such as mutations. This relationship, in the context of cancer, provides a chance to unravel tumor complexity and heterogeneity and uncover novel biomarkers or treatment options. Since colon cancer is one of the most frequent malignancies, its prognosis and diagnosis seem to be critical. The transcriptome technology is developing for an earlier and more accurate diagnosis of cancer which can provide better protectivity and prognostic utility to medical teams and patients. A transcriptome is a whole set of expressed coding and non-coding RNAs in an individual or cell population. The cancer transcriptome includes RNA-based changes. The combined genome and transcriptome of a patient may provide a comprehensive picture of their cancer, and this information is beginning to affect treatment decision-making in real-time. A full assessment of the transcriptome of colon (colorectal) cancer has been assessed in this review paper based on risk factors such as age, obesity, gender, alcohol use, race, and also different stages of cancer, as well as non-coding RNAs like circRNAs, miRNAs, lncRNAs, and siRNAs. Similarly, they have been examined independently in the transcriptome study of colon cancer.

Bioinformatics screening of colorectal-cancer causing molecular signatures through gene expression profiles to discover therapeutic targets and candidate agents

BACKGROUND

Detection of appropriate receptor proteins and drug agents are equally important in the case of drug discovery and development for any disease. In this study, an attempt was made to explore colorectal cancer (CRC) causing molecular signatures as receptors and drug agents as inhibitors by using integrated statistics and bioinformatics approaches.

METHODS

To identify the important genes that are involved in the initiation and progression of CRC, four microarray datasets (GSE9348, GSE110224, GSE23878, and GSE35279) and an RNA_Seq profiles (GSE50760) were downloaded from the Gene Expression Omnibus database. The datasets were analyzed by a statistical r-package of LIMMA to identify common differentially expressed genes (cDEGs). The key genes (KGs) of cDEGs were detected by using the five topological measures in the protein-protein interaction network analysis. Then we performed in-silico validation for CRC-causing KGs by using different web-tools and independent databases. We also disclosed the transcriptional and post-transcriptional regulatory factors of KGs by interaction network analysis of KGs with transcription factors (TFs) and micro-RNAs. Finally, we suggested our proposed KGs-guided computationally more effective candidate drug molecules compared to other published drugs by cross-validation with the state-of-the-art alternatives of top-ranked independent receptor proteins.

RESULTS

We identified 50 common differentially expressed genes (cDEGs) from five gene expression profile datasets, where 31 cDEGs were downregulated, and the rest 19 were up-regulated. Then we identified 11 cDEGs (CXCL8, CEMIP, MMP7, CA4, ADH1C, GUCA2A, GUCA2B, ZG16, CLCA4, MS4A12 and CLDN1) as the KGs. Different pertinent bioinformatic analyses (box plot, survival probability curves, DNA methylation, correlation with immune infiltration levels, diseases-KGs interaction, GO and KEGG pathways) based on independent databases directly or indirectly showed that these KGs are significantly associated with CRC progression. We also detected four TFs proteins (FOXC1, YY1, GATA2 and NFKB) and eight microRNAs (hsa-mir-16-5p, hsa-mir-195-5p, hsa-mir-203a-3p, hsa-mir-34a-5p, hsa-mir-107, hsa-mir-27a-3p, hsa-mir-429, and hsa-mir-335-5p) as the key transcriptional and post-transcriptional regulators of KGs. Finally, our proposed 15 molecular signatures including 11 KGs and 4 key TFs-proteins guided 9 small molecules (Cyclosporin A, Manzamine A, Cardidigin, Staurosporine, Benzo[A]Pyrene, Sitosterol, Nocardiopsis Sp, Troglitazone, and Riccardin D) were recommended as the top-ranked candidate therapeutic agents for the treatment against CRC.

CONCLUSION

The findings of this study recommended that our proposed target proteins and agents might be considered as the potential diagnostic, prognostic and therapeutic signatures for CRC.

Transcriptomic Signatures in Colorectal Cancer Progression

AIMS

Due to a large number of identified hub-genes encoding key molecular regulators, which are involved in signal transduction and metabolic pathways in cancers, it is relevant to systemize and update these findings.

BACKGROUND

Colorectal cancer (CRC) is the third leading cause of cancer death in the world, with high metastatic potential. Elucidating the pathogenic mechanisms and selection of novel biomarkers in CRC is of great clinical significance.

OBJECTIVE

This analytical review aims at the systematization of bioinformatics and experimental identification of hub-genes associated with CRC for a more consolidated understanding of common features in networks and pathways in CRC progression as well as hub-genes selection.

RESULTS

In total, 301 hub-genes were derived from 40 articles. The "core" consisted of 28 hub-genes (CCNB1, LPAR1, BGN, CXCL3, COL1A2, UBE2C, NMU, COL1A1, CXCL2, CXCL11, CDK1, TOP2A, AURKA, SST, CXCL5, MMP3, CCND1, TIMP1, CXCL8, CXCL1, CXCL12, MYC, CCNA2, GCG, GUCA2A, PAICS, PYY and THBS2) mentioned in not less than three articles and having clinical significance in cancerassociated pathways. Of them, there were two discrete clusters enriched in chemokine signaling and cell cycle regulatory genes. High expression levels of BGN and TIMP1 and low expression levels of CCNB1, CXCL3, CXCL2, CXCL2 and PAICS were associated with unfavorable overall survival of patients with CRC. Differently expressed genes such as LPAR1, SST, CXCL12, GUCA2A, and PYY were shown as down regulated, whereas BGN, CXCL3, UBE2C, NMU, CXCL11, CDK1, TOP2A, AURKA, MMP3, CCND1, CXCL1, MYC, CCNA2, PAICS were up regulated genes in CRC. It was also found that MMP3, THBS2, TIMP1 and CXCL12 genes were associated with metastatic CRC. Network analysis in ONCO.IO showed that upstream master regulators RELA, STAT3, SOX2, FOXM1, SMAD3 and NF-kB were connected with "core" hub-genes. Conclusión: Results obtained are of useful fundamental information on revealing the mechanism of pathogenicity, cellular target selection for optimization of therapeutic interventions, as well as transcriptomics prognostic and predictive biomarkers development.

Identification and verification of microRNA signature and key genes in the development of osteosarcoma with lung metastasis

BACKGROUND

Osteosarcoma (OS) is a heterogeneous malignant spindle cell tumor in children under the age of 20. This study aims to research the association between Solute Carrier Family 7 Member 8 (SLC7A8) as well as related genes and OS.

METHOD

OS and normal samples (GSE38698 and GSE85537) were downloaded from Gene Expression Omnibus dataset. The bioinformatics analysis was performed to distinguish 2 differentially expressed genes, prognostic candidate genes and functional enrichment pathway. Immunohistochemistry and quantitative real-time PCR were utilized for further study.

RESULTS

There were 5 DEMs and 10 differentially expressed genes in cancer tissues compared to normal tissues. According to the km-plot software, ARHGEF3, BSN, PQLC3, and SLC7A8 were significantly related to the overall survival of patients with OS. Furthermore, Multivariate analysis included that SLC7A8 was independent risk factors for OS patients. Furthermore, immunohistochemistry and quantitative real-time PCR outcomes indicated that the expression level of SLC7A8 and hsa-miR-506 was differentially expressed in lung metastasis OS tissues and non-metastasis tissues.

CONCLUSION

The prognostic model based on the miRNA-mRNA network could provide predictive significance for prognosis of OS patients, which would be worthy of clinical application. Our results concluded that SLC7A8 may play a key role in the development of OS.

Low Expression of AGPAT5 Is Associated With Clinical Stage and Poor Prognosis in Colorectal Cancer and Contributes to Tumour Progression

Background:

Colorectal cancer (CRC) has a high prevalence and poor prognosis. This study aimed to identify biomarkers related to the clinical stage (I-IV) of CRC.

Methods:

The LinkedOmics database was used as the discovery cohort, and two Gene Expression Omnibus (GEO) databases (GSE41258 and GSE422848) served as validation cohorts. The trend test of genes related to clinical stage (I-IV) of CRC patients was identified by the Jonckheere-Terpstra test. The cBioPortal database, Gene Expression Profiling Interactive Analysis (GEPIA) and PrognoScan databases were used to explore the expression change and prognostic value of clinical stage-related genes in CRC patients. CRC cells overexpressed AGPAT5 were constructed and used for cell counting kit-8 (CCK-8), flow cytometric, and wound healing assays in vitro.

Results:

We identified four clinical stage-related genes, GSR, AGPAT5, CRLF1, and NPR3, in CRC. The CNA frequencies of GSR, CRLF1, AGPAT5, and NPR3 occurred in 11%, 2.4%, 13%, and 3% of patients, respectively. The expression of GSR and AGPAT5 tended to decrease with CRC stage (I-IV) progression, and the expression of CRLF1 and NPR3 tended to increase with CRC stage (I-IV) progression. Compared with the normal group, AGPAT5 expression was markedly decreased in stage IV CRC. Higher GSR and AGPAT5 expression levels were associated with better overall survival (OS) and disease-free survival (DFS) in CRC patients. Lower CRLF1 and NPR3 expression levels were associated with better OS and DFS in CRC. GSR, CRLF1, AGPAT5, and NPR3 expression were related to CRC progression, microsatellite instability, and tumour purity in CRC. Furthermore, AGPAT5 was downregulated in CRC cell lines, and overexpression of AGPAT5 inhibited cell proliferation and migration and promoted cell apoptosis in CRC cells.

Conclusion:

Low AGPAT5 expression may serve as a poor prognostic factor and clinical stage biomarker in CRC. In addition, AGPAT5 acts as a tumour suppressor in CRC progression.

Identification of Key Gene Targets for Sensitizing Colorectal Cancer to Chemoradiation: an Integrative Network Analysis on Multiple Transcriptomics Data

PURPOSE

Colorectal cancer (CRC) is a main cause of morbidity and mortality in the world. Chemoradioresistance is a major problem in CRC treatment. Identification of novel therapeutic targets in order to overcome treatment resistance in CRC is necessary.

METHODS

In this study, gene expression omnibus (GEO) database was searched to find microarray datasets. Data normalization/analyzing was performed using ExAtlas. The gene ontology (GO) and pathway enrichment analysis was performed using g:Profiler. Protein-protein interaction network (PPIN) was constructed by Search Tool for the Retrieval of Interacting Genes (STRING) and analyzed using Cytoscape. Survival analysis was done using Kaplan-Meier curve method.

RESULTS

Forty-one eligible datasets were included in study. A total of 12,244 differentially expressed genes (DEGs) and 7337 unique DEGs were identified. Among them, 1187 DEGs were overlapped in ≥ 3 datasets. Fifty-five overlapped genes were considered as hub genes. Common hub genes in chemo/radiation/chemoradiation datasets were chosen as the essential candidate genes (n = 13). Forty-one hub gene and 7 essential candidate genes were contributed in the significant modules. The modules were mainly enriched in the signaling pathways of senescence, autophagy, NF-κB, HIF-1, stem cell pluripotency, notch, neovascularization, cell cycle, p53, chemokine, and PI3K-Akt. NGFR, FGF2, and PROM1 genes were significantly predictors of CRC patient's survival.

CONCLUSION

Our study revealed three-gene signatures as potential therapeutic targets and also candidate molecular markers in CRC chemoradioresistance.

A network-based pharmacological investigation to identify the mechanistic regulatory pathway of andrographolide against colorectal cancer

Traditional cancer treatments have posed numerous obstacles, including toxicity, multiple drug resistance, and financial cost. On the contrary, bioactive phytochemicals used in complementary alternative medicine have recently increased attention due to their potential to modulate a wide range of molecular mechanisms with a less toxic effect. Therefore, we investigated the potential regulatory mechanisms of andrographolide to treat colorectal cancer (CRC) using a network pharmacology approach. Target genes of andrographolide were retrieved from public databases (PharmMapper, Swiss target prediction, Targetnet, STITCH, and SuperPred), while targets related to CRC were retrieved from disease databases (Genecards and DisGeNet) and expression datasets (GSE32323 and GSE8671) were retrieved from gene expression omnibus (GEO). Protein-protein interaction networks (PPI) were generated using STRING and Cytoscape, and hub genes were identified by topology analysis and MCODE. Annotation of target proteins was performed using Gene Ontology (GO) database DAVID and signaling pathway enrichment analysis using the Kyoto Encyclopedia and Genome Database (KEGG). Survival and molecular docking analysis for the hub genes revealed three genes (PDGFRA, PTGS2, and MMP9) were involved in the overall survival of CRC patients, and the top three genes with the lowest binding energy include PDGFRA, MET, and MAPK1. MET gene upregulation and PDGFRA and PTGS2 gene downregulation are associated with the survival of CRC patients, as revealed by box plots and correlation analysis. In conclusion, this study has provided the first scientific evidence to support the use of andrographolide to inhibit cellular proliferation, migration, and growth, and induce apoptosis by targeting the hub genes (PDGFRA, PTGS2, MMP9, MAPK1, and MET) involved in CRC migration and invasion.

Clinical Data and Biocalculation Methods of GABRD Determine the Clinical Characteristics and Immune Relevance of Colorectal Cancer

Background

The aim of this study was to clarify the expression of gamma-aminobutyric acid type A receptor delta subunit (GABRD) gene in pan-cancer and its correlation with patient prognosis, and to investigate the function and possible mechanism of GABRD in colorectal cancer (CRC).

Methods

The Cancer Genome Atlas (TCGA) data were used to analyze the expression differences of GABRD in pan-cancer, and the correlation between GABRD and clinical prognosis of various tumors was analyzed by Cox regression method. According to the expression level of GABRD, Gene Function Annotation (GO) and Kyoto Encyclopedia of Genomes (KEGG) functional enrichment analysis were performed on the differentially expressed genes. Expression of GABRD gene and 44 marker genes of three types of RNA modification (m1A (10), m5C (13), m6A (21)) genes in different tumors was observed. Pearson correlation of GABRD gene and marker genes of five immune pathways was measured.

Results

: TCGA data analysis showed that GABRD was significantly upregulated in various tumor tissues, especially COAD and READCOAD. Survival analysis showed that GABRD was a prognostic protective factor in CRC (p < 0.001). The results of survival nomogram showed that GABRD, age, and tumor (T) lymph node (N) distant metastasis (M) stage were independent prognostic factors, and the survival model C-index was 0.724 (0.644-1). Gene enrichment and functional analysis showed that GABRD may be related to protein digestion and absorption, ECM-receptor interaction, extracellular structure organization, extracellular matrix organization, pancreatic secretion, and antimicrobial humoral response. The expression of GABRD was positively correlated in m1A-, m5C-, and m6A-related genes. The GABRD gene was found in B cell, T cell CD4, T cell CD8, neutrophil, macrophage in TCGA-COAD (N = 282), and TCGA-COADREAD (N = 373). The infiltration level and DC was significantly positively correlated (p < 0.05). Also, the Pearson correlation coefficient is the largest.

Conclusion

The involvement of GABRD in the occurrence and development of CRC may be related to protein digestion and absorption, ECM-receptor interaction, extracellular structure organization, extracellular matrix organization, pancreatic secretion, and antimicrobial humoral response. GABRD can be used as a molecular marker for the prognosis of CRC.

Prostanoid Signaling in Cancers: Expression and Regulation Patterns of Enzymes and Receptors

Cancer-associated disturbance of prostanoid signaling provides an aberrant accumulation of prostanoids. This signaling consists of 19 target genes, encoding metabolic enzymes and G-protein-coupled receptors, and prostanoids (prostacyclin, thromboxane, and prostaglandins E2, F2α, D2, H2). The study addresses the systems biology analysis of target genes in 24 solid tumors using a data mining pipeline. We analyzed differential expression patterns of genes and proteins, promoter methylation status as well as tissue-specific master regulators and microRNAs. Tumor types were clustered into several groups according to gene expression patterns. Target genes were characterized as low mutated in tumors, with the exception of melanoma. We found at least six ubiquitin ligases and eight protein kinases that post-translationally modified the most connected proteins PTGES3 and PTGIS. Models of regulation of PTGIS and PTGIR gene expression in lung and uterine cancers were suggested. For the first time, we found associations between the patient’s overall survival rates with nine multigene transcriptomics signatures in eight tumors. Expression patterns of each of the six target genes have predictive value with respect to cytostatic therapy response. One of the consequences of the study is an assumption of prostanoid-dependent (or independent) tumor phenotypes. Thus, pharmacologic targeting the prostanoid signaling could be a probable additional anticancer strategy.

Whole-exome sequencing of rectal cancer identifies locally recurrent mutations in the Wnt pathway

Locally recurrent rectal cancer (LRRC) leads to a poor prognosis and appears as a clinically predominant pattern of failure. In this research, whole-exome sequencing (WES) was performed on 21 samples from 8 patients to search for the molecular mechanisms of LRRC. The data was analyzed by bioinformatics. Gene Expression Profiling Interactive Analysis (GEPIA) and Human Protein Atlas (HPA) were performed to validate the candidate genes. Immunohistochemistry was used to detect the protein expression of LEF1 and CyclinD1 in LRRC, primary rectal cancer (PRC), and non-recurrent rectal cancer (NRRC) specimens. The results showed that LRRC, PRC, and NRRC had 668, 794, and 190 specific genes, respectively.

FGFR1 and MYC have copy number variants (CNVs) in PRC and LRRC, respectively. LRRC specific genes were mainly enriched in positive regulation of transcription from RNA polymerase II promoter, plasma membrane, and ATP binding. The specific signaling pathways of LRRC were Wnt signaling pathway, gap junction, and glucagon signaling pathway, etc. The transcriptional and translational expression levels of genes including NFATC1, PRICKLE1, SOX17, and WNT6 related to Wnt signaling pathway were higher in rectal cancer (READ) tissues than normal rectal tissues. The PRICKLE1 mutation (c.C875T) and WNT6 mutation (c.G629A) were predicted as “D (deleterious)”. Expression levels of LEF1 and cytokinin D1 proteins: LRRC > PRC > NRRC > normal rectal tissue. Gene variants in the Wnt signaling pathway may be critical for the development of LRRC. The present study may provide a basis for the prediction of LRRC and the development of new therapeutic drugs.

Novel diagnostic and prognostic biomarkers of colorectal cancer: Capable to overcome the heterogeneity-specific barrier and valid for global applications

INTRODUCTION

The heterogeneity-specific nature of the available colorectal cancer (CRC) biomarkers is significantly contributing to the cancer-associated high mortality rate worldwide. Hence, this study was initiated to investigate a system of novel CRC biomarkers that could commonly be employed to the CRC patients and helpful to overcome the heterogenetic-specific barrier.

METHODS

Initially, CRC-related hub genes were extracted through PubMed based literature mining. A protein-protein interaction (PPI) network of the extracted hub genes was constructed and analyzed to identify few more closely CRC-related hub genes (real hub genes). Later, a comprehensive bioinformatics approach was applied to uncover the diagnostic and prognostic role of the identified real hub genes in CRC patients of various clinicopathological features.

RESULTS

Out of 210 collected hub genes, in total 6 genes (CXCL12, CXCL8, AGT, GNB1, GNG4, and CXCL1) were identified as the real hub genes. We further revealed that all the six real hub genes were significantly dysregulated in colon adenocarcinoma (COAD) patients of various clinicopathological features including different races, cancer stages, genders, age groups, and body weights. Additionally, the dysregulation of real hub genes has shown different abnormal correlations with many other parameters including promoter methylation, overall survival (OS), genetic alterations and copy number variations (CNVs), and CD8+T immune cells level. Finally, we identified a potential miRNA and various chemotherapeutic drugs via miRNA, and real hub genes drug interaction network that could be used in the treatment of CRC by regulating the expression of real hub genes.

CONCLUSION

In conclusion, we have identified six real hub genes as potential biomarkers of CRC patients that could help to overcome the heterogenetic-specific barrier across different clinicopathological features.

Weighted Gene Co-expression Network Analysis Identified a Novel Thirteen-Gene Signature Associated With Progression, Prognosis, and Immune Microenvironment of Colon Adenocarcinoma Patients

Colon adenocarcinoma (COAD) is one of the most common malignant tumors and has high migration and invasion capacity. In this study, we attempted to establish a multigene signature for predicting the prognosis of COAD patients. Weighted gene co-expression network analysis and differential gene expression analysis methods were first applied to identify differentially co-expressed genes between COAD tissues and normal tissues from the Cancer Genome Atlas (TCGA)-COAD dataset and GSE39582 dataset, and a total of 309 overlapping genes were screened out. Then, our study employed TCGA-COAD cohort as the training dataset and an independent cohort by merging the GES39582 and GSE17536 datasets as the testing dataset. After univariate and multivariate Cox regression analyses were performed for these overlapping genes and overall survival (OS) of COAD patients in the training dataset, a 13-gene signature was constructed to divide COAD patients into high- and low-risk subgroups with significantly different OS. The testing dataset exhibited the same results utilizing the same predictive signature. The area under the curve of receiver operating characteristic analysis for predicting OS in the training and testing datasets were 0.789 and 0.868, respectively, which revealed the enhanced predictive power of the signature. Multivariate Cox regression analysis further suggested that the 13-gene signature could independently predict OS. Among the 13 prognostic genes, NAT1 and NAT2 were downregulated with deep deletions in tumor tissues in multiple COAD cohorts and exhibited significant correlations with poorer OS based on the GEPIA database. Notably, NAT1 and NAT2 expression levels were positively correlated with infiltrating levels of CD8+ T cells and dendritic cells, exhibiting a foundation for further research investigating the antitumor immune roles played by NAT1 and NAT2 in COAD. Taken together, the results of our study showed that the 13-gene signature could efficiently predict OS and that NAT1 and NAT2 could function as biomarkers for prognosis and the immune response in COAD.

Comprehensive analysis of the prognosis and immune infiltration for CXC chemokines in colorectal cancer

The C-X-C motif (CXC) chemokines are a family of chemotactic molecules that have been identified as potential prognostic markers and prospective therapeutic targets for many kinds of cancer types. Increasing evidence shows that CXC chemokines are associated with the progression of colorectal cancer (CRC); however, the correlations of CXC chemokines with prognostic and immune infiltrates in CRC remain to be clarified. In this study, we analyzed the mRNA expression level, prognostic data and immune infiltrates of CXC chemokines in CRC patients from the Gene Expression Profiling Interactive Analysis, Oncomine, cBioPortal and databases using GeneMANIA, STRING, DAVID 6.8, and TIMER. Our results showed that CXCL1/2/3/4/5/8/9/10/11/13/14/16 were significantly overexpressed in CRC tissues. Furthermore, expression of CXCL1/2/3/9/10/11 was associated with tumor stage in CRC. A significant association was also identified between the co-expression of CXCL16 with EGFR, KRAS and NRAS. In addition, the survival analysis suggested that high CXCL2/3/8/9/10/11/14 expression is correlated with clinical outcomes of CRC patients. Moreover, a significant association was observed between the CXCL8/9/10/11 expression and immune infiltration in colonic and rectal adenocarcinoma. Overall, CXC chemokines are not only implicated as prognostic biomarkers for CRC patients, but may also influence the immune status of CRC tissues.

Integration of gene expression data identifies key genes and pathways in colorectal cancer

Colorectal cancer (CRC) is one of the most common malignant tumor and prevalent cause of cancer-related death worldwide. In this study, we analyzed the gene expression profiles of patients with CRC with the aim of better understanding the molecular mechanism and key genes in CRC. Four gene expression profiles including, GSE9348, GSE41328, GSE41657, and GSE113513 were downloaded from GEO database. The data were processed using R programming language, in which 319 common differentially expressed genes including 94 up-regulated and 225 down-regulated were identified. The gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analyses were conducted to find the most significant enriched pathways in CRC. Based on the GO and KEGG pathway analysis, the most important dysregulated pathways were regulation of cell proliferation, biocarbonate transport, Wnt, and IL-17 signaling pathways, and nitrogen metabolism. The protein-protein interaction (PPI) network of the DEGs was constructed using Cytoscape software and hub genes including MYC, CXCL1, CD44, MMP1, and CXCL12 were identified as the most critical hub genes. The present study enhances our understanding of the molecular mechanisms of the CRC, which might potentially be applied in the treatment strategies of CRC as molecular targets and diagnostic biomarkers.