Identification and Verification of Core Genes in Colorectal Cancer

Identification and validation of metastasis-related gene ZG16 in the prognosis and progression in colorectal cancer

Background

Metastasis remains the leading cause of mortality among colorectal cancer (CRC) patients. Identification of new metastasis-related genes are critical to improve colorectal cancer prognosis.

Methods

Data on mRNA expression in metastatic and primary CRC was obtained from the Gene Expression Omnibus (GEO) database, including GSE81986, GSE41568, GSE71222, GSE21510, and GSE14333. Additionally, data concerning mRNA expression in colon cancer (COAD) and adjacent normal tissues were acquired from The Cancer Genome Atlas (TCGA) database. Hub genes were identified by weighted gene co-expression network analysis (WGCNA) and differential gene expression analysis. Moreover, we assessed the impact of hub gene expression on both overall survival (OS) and disease-free survival (DFS) in patients and identified ZG16 as a potential target. We generated CRC cell lines transfected with lentivirus OE-ZG16 to investigate proliferation, invasion, and migration in vitro. To further elucidate the involvement of ZG16, we utilized gene set enrichment analysis (GSEA) to identify enriched pathways, which were subsequently validated via Western blot analysis.

Results

Five datasets containing primary and metastatic CRC samples from GEO database and CRC samples from TCGA database were included in this study and 29 hub genes were identified by WGCNA and differentially expressed gene (DEG) analysis. Low expression of the hub genes (CLCA1 and ZG16) was associated with poor DFS and OS. We confirmed the low expression of ZG16 in CRC using external database and IHC analysis at both transcriptional and protein levels. In addition, the expression of ZG16 was notably elevated in NCM460 cells in comparison to CRC cell lines. The overexpression of ZG16 in CRC cells has been shown to inhibit the proliferation, invasion, and migration of CRC cells. Furthermore, the overexpression of ZG16 has been found to suppress the activation of the epithelial-mesenchymal transition (EMT) and Wnt/β-catenin signaling pathways in CRC.

Conclusion

ZG16 may serve as a promising therapeutic target for metastatic CRC treatment.

Value analysis of ITLN1 in the diagnostic and prognostic assessment of colorectal cancer

Background

Colorectal cancer (CRC) remains the leading cause of cancer death worldwide. Less than half of the patients are diagnosed when the cancer is locally advanced. Several studies have shown that intelectin-1 (ITLN1) can serve as a key prognostic and therapeutic target for CRC. The purpose of this study was to investigate the clinical value of ITLN1 in CRC and to analyse its potential as a predictive biomarker for CRC.

Methods

Colon adenocarcinoma (COAD) is the main type of CRC. COAD project in The Cancer Genome Atlas (TCGA) database served as the training cohort, and GSE39582 series in the Gene Expression Omnibus (GEO) database served as the external independent validation cohort. First, the difference in the expression level of ITLN1 between COAD tissue and normal tissue was analysed, and the results were verified via immunohistochemistry. The relationship between ITLN1 expression and the prognosis of COAD patients was evaluated via the heatmap and the Kaplan-Meier (KM) curve. The ITLN1 coexpressed gene set obtained by Pearson correlation analysis was used. The prognostic signatures that were significantly correlated with survival status were screened by Cox and least absolute shrinkage and selection operator (LASSO) regression analyses. Finally, a nomogram related to ITLN1 was constructed based on the risk score of the prognostic signature and routine clinicopathological variables.

Results

ITLN1 is significantly underexpressed in tumour tissues and can be used as a valuable tool to distinguish COAD. The high-expression group of ITLN1 was verified to have a greater survival rate. ITLN1 is significantly associated with a good prognosis in COAD patients. Six candidate genes (ITLN1 and MORC2, SH2D7, LGALS4, ATOH1, and NAT2) were selected for use in the Cox-LASSO regression analysis to calculate the risk score. Finally, a nomogram was constructed with a comprehensive risk score and clinicopathologic factors to successfully predict and verify the 1-year, 3-year, and 5-year survival probability.

Conclusions

Our study established ITLN1 as an effective tool for CRC screening, diagnosis, and prognostic assessment, provided a basis for further study of the molecular function of ITLN1, and provided new insights for the mechanistic exploration and treatment of CRC.

Guanylate cyclase-C Signaling Axis as a theragnostic target in colorectal cancer: a systematic review of literature

Introduction

Colorectal cancer (CRC) is a devastating disease that affects millions of people worldwide. Recent research has highlighted the crucial role of the guanylate cyclase-C (GC-C) signaling axis in CRC, from the early stages of tumorigenesis to disease progression. GC-C is activated by endogenous peptides guanylin (GU) and uroguanylin (UG), which are critical in maintaining intestinal fluid homeostasis. However, it has been found that these peptides may also contribute to the development of CRC. This systematic review focuses on the latest research on the GC-C signaling axis in CRC.

Methods

According to the aim of the study, a systematic literature search was conducted on Medline and PubMed databases. Ultimately, a total of 40 articles were gathered for the systematic review.

Results

Our systematic literature search revealed that alterations in GC-C signaling compartments in CRC tissue have demonstrated potential as diagnostic, prognostic, and therapeutic markers. This research highlights a potential treatment for CRC by targeting the GC-C signaling axis. Promising results from recent studies have explored the use of this signaling axis to develop new vaccines and chimeric antigen receptors that may be used in future clinical trials.

Conclusion

The findings presented in this review provide compelling evidence that targeting the GC-C signaling axis may be an advantageous approach for treating CRC.

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.

Proapoptotic and Antiproliferative Effects of the Desert Truffle Terfezia boudieri on Colon Cancer Cell Lines

Background

Colon cancer is the second leading cause of cancer-related mortality, and ranks third among cancers in terms of prevalence. Despite advances in early detection and treatment with chemotherapy and surgery, colon cancer continues to be associated with high recurrence rates, thereby resulting in a heavy disease burden. Moreover, the effectiveness of currently available treatment modalities is limited by the occurrence of toxic side effects. Hence, there is an urgent need to develop alternative treatments. Extracts from the black desert truffle Terfezia boudieri (T. boudieri) have shown promising anticancer properties. However, the cellular mechanisms underlying this activity remain poorly understood.

Methods

In this study, the colon cancer cell lines HCT-116 and Caco-2 were treated with either water or ethanolic extract of T. boudieri. Cell viability and the half-maximal inhibitory concentration were determined using MTT assays. Then, the activity of the more potent water extract was further verified using crystal violet assays, and its role in inhibiting colony formation and wound healing was investigated. Protein levels of p53, B-cell lymphoma 2 (Bcl-2), Bcl-2-associated X (Bax), cyclin D1 (CCND1), and c-Myc were measured in cells treated with different doses of the water extract.

Results

Treatment with the water extract of T. boudieri reduced the capacity of cells for wound healing and colony formation in a dose-dependent manner. The Bax/Bcl-2 ratio and p53 expression were elevated in both cell lines. In contrast, the levels of cyclin D1 and c-Myc were suppressed.

Conclusion

T. boudieri water extract exerted a cytotoxic effect on colon cancer cells, and blocked colony formation and wound healing potentially through inhibition of proliferation. Mechanistically, these effects are attributed to influence the mitochondrial pathway of apoptosis, proteins involved in cellular proliferation, and the cell cycle.

PYY modulates the tumorigenesis and progression of colorectal cancer unveiled by proteomics

Despite decrease in mortality caused by colorectal cancer (CRC), there remains no effective therapeutic method for patients with CRC. We attempted to screen biomarkers with therapeutic values in CRC. Proteomic analysis was performed on tumor, tumor-adjacent, and normal tissues derived from five patients with colon adenocarcinoma (COAD) via label-free proteome profiling. Differentially expressed proteins (DEPs) were identified, and functional annotation was performed based on the gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. The effect of marker proteins on CRC was determined via cell function experiments and using tumor organoid models. The localization of the marker proteins was determined via immunofluorescence. A total of 126 DEPs were identified in COAD tissues compared with normal tissues, of which Peptide YY (PYY) overlapped among the tumor, adjacent, and normal groups. DEPs in the cancer group vs. normal group were enriched in the regulation of cell cycle checkpoint, developmental process, focal adhesion, and apoptosis-related pathways. The low expression of PYY in CRC tissues was verified via qRT-PCR, western blotting, and immunohistochemistry. Overexpression of PYY promoted apoptosis and inhibited the proliferation, migration, and invasion of HCT116 and HT29 cells. Furthermore, PYY was secreted by neurons and its supplementation suppressed tumor organoid growth in a dose-dependent manner. In conclusion, PYY exerted inhibitory action on CRC and could be a therapeutic target for CRC.

DNAH7 mutations benefit colorectal cancer patients receiving immune checkpoint inhibitors

Background

Colorectal cancer (CRC) is a malignant tumor associated with a high mortality rate. While the advent of immune checkpoint inhibitors (ICIs) has been a gamechanger, only a small percentage of CRC patients benefit from ICIs. The pathological mechanism of CRC is not well understood, but somatic mutations, especially missense mutations, are believed to play an important role. This study examined the relationship between ICIs in colorectal cancer and missense mutations in the axonemal dynein heavy chain gene 7 (DNAH7).

Methods

A clinical cohort (n=690) and the CRC data from the publicly available Cancer Genome Atlas (TCGA) were examined. Gene Set Enrichment Analysis, ESTIMATE analysis, and clinical correlation analysis were performed to explore the effects and mechanisms of DNAH7 mutation on immunotherapy in colorectal cancer.

Results

The results showed that CRC patients with DNAH7 mutations can benefit more from ICIs (P<0.05). Patients with DNAH7 mutation had higher ESTIMATE scores, immune scores, and matrix scores, compared to patients without the DNAH7 mutation (P<0.001). The transport of small molecules, keratinization, asthma, autoimmune thyroid disease, allograft rejection, and other pathways were significantly enriched in DNAH7 mutated tissues (P<0.05). The top key genes associated with the DNAH7 mutation included AQP8, MS4A12, GUCA2B, and ZG16 (P<0.01).

Conclusions

The current study not only demonstrated the significance of DNAH7 as a risk factor and prognostic feature in CRC, but also revealed that DNAH7 mutations might affect the clinical efficacy of ICIs by impacting the tumor immune microenvironment.

Progress and challenges of multidrug resistance proteins in diseases

Chemotherapy remains the first choice for patients with advanced cancers when other treatments are ineffective. Multidrug resistance (MDR) is an unavoidable factor that negatively affects the effectiveness of cancer chemotherapy drugs. Researchers are trying to reduce MDR, improve the effectiveness of chemotherapeutic drugs, and alleviate patient suffering to positively contribute to disease treatment. MDR also occurs in inflammation and genetic disorders, which increases the difficulty of clinically beneficial treatments. The ATP-binding cassette (ABC) is an active transporter that plays an important role in the barrier and secretory functions of many normal cells. As the C subfamily in the ABC family, multidrug resistance proteins (MRPs/ABCCs) export a variety of antitumour drugs and are expressed in a variety of cancers. The present review summarises the role of MRPs in cancer and other diseases and recent research progress of MRP inhibitors to better examine the mechanism and function of MRPs, and establish a good relationship with clinical treatment.

Analysis of Key Genes for Slow Transit Constipation Based on RNA Sequencing

Purpose

This study aims to identify key genes in slow transit constipation (STC). We also sought to explore the potential link between STC and colorectal cancer.

Patients and Methods

mRNA expression profiles were obtained by RNA sequencing, and differentially expressed genes were identified. Functional enrichment analysis and a protein–protein interaction (PPI) network was explored, and differentially expressed genes common to STC and colorectal cancer were examined. Analysis of the effect of constipation and colorectal cancer common genes on the overall survival of colorectal cancer patients based on GEPIA database.

Results

Functional enrichment showed that significantly different genes are related to lymphocyte chemotaxis, positive regulation of inflammatory response, cellular response to tumor necrosis factor, extracellular region, extracellular space and chemokine activity. The hub gene for STC was found in the PPI network. In addition, AQP8 and CFD were common differential genes for STC and colorectal cancer. AQP8 affects overall survival in patients with colorectal cancer.

Conclusion

Our findings will contribute to understanding the pathology of STC at the molecular level, with the first discovery that AQP8 may be a hub gene in the transition from STC to colorectal cancer.

Efficacy and Safety of Preoperative Radiotherapy Versus Chemoradiotherapy in Advanced Rectal Cancer: A Meta-analysis of Randomized Controlled Trials

OBJECTIVE

This meta-analysis was conducted to evaluate the safety and efficacy of preoperative radiotherapy (RT) combined with surgery and preoperative chemoradiotherapy (CRT) combined with surgery for locally advanced rectal cancer.

METHODS

PubMed, EMBASE and Cochrane Library were searched to collect published randomized controlled trials of preoperative radiotherapy or preoperative CRT combined with surgery for the treatment of locally advanced rectal cancer. Studies were screened according to inclusion and exclusion criteria, and quality was evaluated; RevMan 5.3 software was used for meta-analysis.

RESULTS

In total, 7 related studies involving 3100 patients with locally advanced rectal cancer were evaluated. The pathological complete response rate, negative lymph node rate, R0 resection rate, and incidence of grade III/IV adverse reactions were lower in the RT group than in the CRT group. In the absence of postoperative chemotherapy, the 5-year local recurrence rate of RT was higher than that of CRT, but there was no significant difference between the groups among those who underwent postoperative chemotherapy. Moreover, there was no significant difference between the groups with regard to the 5-year survival rate, anal-preserving rate, or incidence of anastomotic leakage.

CONCLUSION

Preoperative CRT is better than preoperative RT for the treatment of advanced rectal cancer, though the adverse reaction rate is higher.

Exploring Immune-Related Prognostic Signatures in the Tumor Microenvironment of Colon Cancer

Background: Colon cancer is a common malignant tumor with poor prognosis. The aim of this study is to explore the immune-related prognostic signatures and the tumor immune microenvironment of colon cancer.

Methods: The mRNA expression data of TCGA-COAD from the UCSC Xena platform and the list of immune-related genes (IRGs) from the ImmPort database were used to identify immune-related differentially expressed genes (DEGs). Then, we constructed an immune-related risk score prognostic model and validated its predictive performance in the test dataset, the whole dataset, and two independent GEO datasets. In addition, we explored the differences in tumor-infiltrating immune cell types, tumor mutation burden (TMB), microsatellite status, and expression levels of immune checkpoints and their ligands between the high-risk and low-risk score groups. Moreover, the potential value of the identified immune-related signature with respect to immunotherapy was investigated based on an immunotherapeutic cohort (Imvigor210) treated with an anti-PD-L1 agent.

Results: Seven immune-related DEGs were identified as prognostic signatures. The areas under the curves (AUCs) of the constructed risk score model for overall survival (OS) were calculated (training dataset: 0.780 at 3 years, 0.801 at 4 years, and 0.766 at 5 years; test dataset: 0.642 at 3 years, 0.647 at 4 years, and 0.629 at 5 years; and the whole dataset: 0.642 at 3 years, 0.647 at 4 years, and 0.629 at 5 years). In the high-risk score group of the whole dataset, patients had worse OS, higher TMN stages, advanced pathological stages, and a higher TP53 mutation rate (p < 0.05). In addition, a high level of resting NK cells or M0 macrophages, and high TMB were significantly related to poor OS (p < 0.05). Also, we observed that high-risk score patients had a high expression level of PD-L1, PD-1, and CTLA-4 (p < 0.05). The patients with high-risk scores demonstrated worse prognosis than those with low-risk scores in multiple datasets (GSE39582: p = 0.0023; GSE17536: p = 0.0008; immunotherapeutic cohort without platinum treatment: p = 0.0014; immunotherapeutic cohort with platinum treatment: p = 0.0027).

Conclusion: We developed a robust immune-related prognostic signature that performed great in multiple cohorts and explored the characteristics of the tumor immune microenvironment of colon cancer patients, which may give suggestions for the prognosis and immunotherapy in the future.

Identification and verification of HCAR3 and INSL5 as new potential therapeutic targets of colorectal cancer

Background

Colorectal cancer (CRC) is one of the most common cancers of the gastrointestinal tract and ranks third in cancer-related deaths worldwide. This study was conducted to identify novel biomarkers related to the pathogenesis of CRC based upon a bioinformatics analysis, and further verify the biomarkers in clinical tumor samples and CRC cell lines.

Methods

A series of bioinformatics analyses were performed using datasets from NCBI-GEO and constructed a protein–protein interaction (PPI) network. This analysis enabled the identification of Hub genes, for which the mRNA expression and overall survival of CRC patients data distribution was explored in The Cancer Genome Atlas (TCGA) colon cancer and rectal cancer (COADREAD) database. Furthermore, the differential expression of HCAR3 and INLS5 was validated in clinical tumor samples by Real-time quantitative PCR analysis, western blotting analysis, and immunohistochemistry analysis. Finally, CRC cells over-expressing INSL5 were constructed and used for CCK8, cell cycle, and cell apoptosis validation assays in vitro.

Results

A total of 286 differentially expressed genes (DEGs) were screened, including 64 genes with increased expression and 143 genes with decreased expression in 2 CRC database, from which 10 key genes were identified: CXCL1, HCAR3, CXCL6, CXCL8, CXCL2, CXCL5, PPY, SST, INSL5, and NPY1R. Among these genes, HCAR3 and INSL5 had not previously been explored and were further verified in vitro.

Conclusions

HCAR3 expression was higher in CRC tissues and associated with better overall survival of CRC patients. INSL5 expression in normal tissue was higher than that in tumor tissue and its high expression was associated with a better prognosis for CRC. The overexpression of INSL5 significantly inhibited the proliferation and promoted the shearing of PARP of CRC cells. This integrated bioinformatics study presented 10 key hub genes associated with CRC. HCAR3 and INSL5 were expressed in tumor tissue and these were associated with poor survival and warrant further studies as potential therapeutic targets.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12957-021-02335-x.

Employing bioinformatics analysis to identify hub genes and microRNAs involved in colorectal cancer

The third leading cause of cancer-related deaths in the world, colorectal cancer (CRC) is a global health issue that should be addressed in both diagnostics and therapeutics to improve patient survival rate. Today, microarray data analysis is increasingly being used as a novel and effective method for classification of malignancies and making prognostic assessments. Built upon the concept of microarray data analysis and aimed at the identification of CRC-associated genes, our study has adopted an integrative analysis for the gene expression patterns of four microarray datasets in gene expression omnibus (GEO) and microRNAs (miRNAs) expression profiles. We downloaded four gene expression profiles, i.e., GSE37182, GSE25070, GSE10950, and GSE113513, miRNAs gene expression profiles and differentially expressed genes (DEGs). We used R software, the DAVID database, protein-protein interaction (PPI) networks, the Cytoscape program and receiver operating characteristic (ROC) curve for data analysis. Out of the four gene expression profiles, a total of 43 common DEGs were identified, including 10 hub genes, SLC26A3, CLCA1, GUCA2A, MS4A12, CLCA4, GUCA2B, KRT20, AQP8, MAOA, and ADH1A, and four differentially expressed miRNAs, miR-552, miR-423-5p, miR-502-3p, and miR-490-5p. The highly enriched modes of the signaling pathways among these DEGs were speculated to be involved in various processes including nitrogen metabolism, mineral absorption, pancreatic secretions, and tyrosine metabolism in Kyoto encyclopedia of genes and genomes (KEGG) database. According to our bioinformatics analysis, the DEGs identified in the present study could be considered as significant hallmarks in the molecular mechanisms of CRC development. Our findings may assist scientists with developing novel strategies not only for prediction of CRC, but also for screening and early diagnosis, and treatment of CRC patients.

miRNA Clusters with Up-Regulated Expression in Colorectal Cancer

Simple Summary

As miRNAs show the capacity to be used as CRC biomarkers, we analysed experimentally validated data about frequently up-regulated miRNA clusters in CRC tissue. We identified 15 clusters that showed increased expression in CRC: miR-106a/363, miR-106b/93/25, miR-17/92a-1, miR-181a-1/181b-1, miR-181a-2/181b-2, miR-181c/181d, miR-183/96/182, miR-191/425, miR-200c/141, miR-203a/203b, miR-222/221, mir-23a/27a/24-2, mir-29b-1/29a, mir-301b/130b and mir-452/224. Cluster positions in the genome are intronic or intergenic. Most clusters are regulated by several transcription factors, and by long non-coding RNAs. In some cases, co-expression of miRNA with other cluster members or host gene has been proven. miRNA expression patterns in cancer tissue, blood and faeces were compared. The members of the selected clusters target 181 genes. Their functions and corresponding pathways were revealed with the use of Panther analysis. Clusters miR-17/92a-1, miR-106a/363, miR-106b/93/25 and miR-183/96/182 showed the strongest association with metastasis occurrence and poor patient survival, implicating them as the most promising targets of translational research.

Abstract

Colorectal cancer (CRC) is one of the most common malignancies in Europe and North America. Early diagnosis is a key feature of efficient CRC treatment. As miRNAs can be used as CRC biomarkers, the aim of the present study was to analyse experimentally validated data on frequently up-regulated miRNA clusters in CRC tissue and investigate their members with respect to clinicopathological characteristics of patients. Based on available data, 15 up-regulated clusters, miR-106a/363, miR-106b/93/25, miR-17/92a-1, miR-181a-1/181b-1, miR-181a-2/181b-2, miR-181c/181d, miR-183/96/182, miR-191/425, miR-200c/141, miR-203a/203b, miR-222/221, mir-23a/27a/24-2, mir-29b-1/29a, mir-301b/130b and mir-452/224, were selected. The positions of such clusters in the genome can be intronic or intergenic. Most clusters are regulated by several transcription factors, and miRNAs are also sponged by specific long non-coding RNAs. In some cases, co-expression of miRNA with other cluster members or host gene has been proven. miRNA expression patterns in cancer tissue, blood and faeces were compared. Based on experimental evidence, 181 target genes of selected clusters were identified. Panther analysis was used to reveal the functions of the target genes and their corresponding pathways. Clusters miR-17/92a-1, miR-106a/363, miR-106b/93/25 and miR-183/96/182 showed the strongest association with metastasis occurrence and poor patient survival, implicating them as the most promising targets of translational research.

Identification of gene biomarkers and immune cell infiltration characteristics in rectal cancer

Background

Compared with colon cancer, the increase of morbidity is more significant for rectal cancer. The current study set out to identify novel and critical biomarkers or features that may be used as promising targets for early diagnosis and treatment monitoring of rectal cancer.

Methods

Microarray datasets of rectal cancer with a minimum sample size of 30 and RNA-sequencing datasets of rectal adenocarcinoma (READ) were downloaded from the Gene Expression Omnibus (GEO) database and The Cancer Genome Atlas (TCGA) database. The method of robust rank aggregation was utilized to integrate differentially expressed genes (DEGs). The protein-protein interaction (PPI) network of the DEGs was structured using the STRING platform, and hub genes were identified using the Cytoscape plugin cytoHubba and an UpSet diagram. R software was employed to perform functional enrichment analysis. Receiver operating characteristic (ROC) curves based on the GEO data and Kaplan-Meier curves based on the TCGA data were drawn to assess the diagnostic and prognostic values of the hub genes. Immune cell infiltration analysis was conducted with CIBERSORT, and the diagnostic value and correlations between prognostic genes and infiltrated immune cells were analyzed by principal component analysis (PCA), ROC curves, and correlation scatter plots.

Results

A total of 137 robust DEGs were obtained by integrating datasets in GEO. Twenty-four hub genes, including CHGA, TTR, SAA1, SPP1, MMP1, TGFBI, COL1A1, and PCK1, were identified as a diagnostic gene biomarker group for rectal cancer, and SAA1, SPP1, and SI were identified as potential novel prognostic biomarkers. Functionally, the hub genes were mainly involved in the rectal cancer related interleukin (IL)-17 and proximal tubule bicarbonate reclamation pathways. Twelve sensitive infiltrated immune cells were identified, and were correlated with prognostic genes.

Conclusions

The integrated gene biomarker group combined with immune cell infiltration can effectively indicate rectal cancer.

Identification of Hub Genes in Different Stages of Colorectal Cancer through an Integrated Bioinformatics Approach

Colorectal cancer (CRC) is the third most common cancer that contributes to cancer-related morbidity. However, the differential expression of genes in different phases of CRC is largely unknown. Moreover, very little is known about the role of stress-survival pathways in CRC. We sought to discover the hub genes and identify their roles in several key pathways, including oxidative stress and apoptosis in the different stages of CRC. To identify the hub genes that may be involved in the different stages of CRC, gene expression datasets were obtained from the gene expression omnibus (GEO) database. The differentially expressed genes (DEGs) common among the different datasets for each group were obtained using the robust rank aggregation method. Then, gene enrichment analysis was carried out with Gene Ontology and Kyoto Encyclopedia of Genes and Genomes databases. Finally, the protein-protein interaction networks were constructed using the Cytoscape software. We identified 40 hub genes and performed enrichment analysis for each group. We also used the Oncomine database to identify the DEGs related to stress-survival and apoptosis pathways involved in different stages of CRC. In conclusion, the hub genes were found to be enriched in several key pathways, including the cell cycle and p53 signaling pathway. Some of the hub genes were also reported in the stress-survival and apoptosis pathways. The hub DEGs revealed from our study may be used as biomarkers and may explain CRC development and progression mechanisms.

Role of Stress-Survival Pathways and Transcriptomic Alterations in Progression of Colorectal Cancer: A Health Disparities Perspective

Every year, more than a million individuals are diagnosed with colorectal cancer (CRC) across the world. Certain lifestyle and genetic factors are known to drive the high incidence and mortality rates in some groups of individuals. The presence of enormous amounts of reactive oxygen species is implicated for the on-set and carcinogenesis, and oxidant scavengers are thought to be important in CRC therapy. In this review, we focus on the ethnicity-based CRC disparities in the U.S., the negative effects of oxidative stress and apoptosis, and gene regulation in CRC carcinogenesis. We also highlight the use of antioxidants for CRC treatment, along with screening for certain regulatory genetic elements and oxidative stress indicators as potential biomarkers to determine the CRC risk and progression.

CLCA4 and MS4A12 as the significant gene biomarkers of primary colorectal cancer

Background: Primary colorectal cancer (PCRC) is a common digestive tract cancer in the elderly. However, the treatment effect of PCRC is still limited, and the long-term survival rate is low. Therefore, further exploring the pathogenesis of PCRC, and searching for specific molecular targets for diagnosis are the development trends of precise medical treatment, which have important clinical significance.

Methods: The public data were downloaded from Gene Expression Omnibus (GEO) database. Verification for repeatability of intra-group data was performed by Pearson’s correlation test and principal component analysis. Differentially expressed genes (DEGs) between normal and PCRC were identified, and the protein–protein interaction (PPI) network was constructed. Significant module and hub genes were found in the PPI network. A total of 192 PCRC patients were recruited between 2010 and 2019 from the Fourth Hospital of Hebei Medical University. RT-PCR was used to measure the relative expression of CLCA4 and MS4A12. Furthermore, the study explored the effect of expression of CLCA4 and MS4A12 for overall survival.

Results: A total of 53 DEGs were identified between PCRC and normal colorectal tissues. Ten hub genes concerned to PCRC were screened, namely CLCA4, GUCA2A, GCG, SST, MS4A12, PLP1, CHGA, PYY, VIP, and GUCA2B. The PCRC patients with low expression of CLCA4 and MS4A12 has a worse overall survival than high expression of CLCA4 and MS4A12 (P<0.05).

Conclusion: The research of DEGs in PCRC (53 DEGs, 10 hub genes, especially CLCA4 and MS4A12) and related signaling pathways is conducive to the differential analysis of the molecular mechanism of PCRC.

A Novel Prognostic Score Based on ZG16 for Predicting CRC Survival

Background

Colorectal cancer (CRC) is one of the lethal malignant tumors worldwide. However, the underlying mechanism of CRC and its biomarkers remain unclear. The aim of this study was to identify the key genes associated with CRC and to further explore their prognostic significance.

Methods

Four expression profile datasets (GSE41657, GSE74602, GSE113513, and GSE40967) downloaded from Gene Expression Omnibus (GEO) and one RNAseq dataset of CRC from The Cancer Genome Atlas (TCGA) database were included in our study. The Cox model was utilized for univariate or multivariate survival analysis. GEPIA and HAP database were adopted for verification of DEGs (ZG16). The decision curve analysis (DCA) and time-dependent ROC were chosen for evaluating the prognostic effectiveness of biomarkers.

Results

In total, 88 differentially expressed genes (DEGs) were identified, and the GO and KEGG enrichment analyses of DEGs were processed. After, the protein–protein interaction (PPI) network was constructed and 15 hub genes including ZG16 were identified. The differential expression of ZG16 between tumor and normal colorectal tissues were further verified in GEPIA and HAP database. Subsequent survival indicated that expression of ZG16 is negatively correlated with overall survival of OS and is an independent prognostic factor for CRC patients. Furthermore, the construction of a prognostic score containing ZG16, TNM stage and age exhibited superior effectiveness for predicting long-term survival of CRC patients. Additionally, our results were verified using the GSE40967 dataset, which indicated an improved performance of combined risk score based on ZG16 for predicting OS of CRC patients.

Conclusion

ZG16 is a potential parameter for predicting prognosis in CRC. Furthermore, a combination of ZG16, TNM stage, and age allows improved prognosis of CRC.