Screening and verifying key genes with poor prognosis in colon cancer through bioinformatics analysis

RRM2 promotes the proliferation of chicken myoblasts, inhibits their differentiation and muscle regeneration

During myogenesis and regeneration, the proliferation and differentiation of myoblasts play key regulatory roles and may be regulated by many genes. In this study, we analyzed the transcriptomic data of chicken primary myoblasts at different periods of proliferation and differentiation with protein‒protein interaction network, and the results indicated that there was an interaction between cyclin-dependent kinase 1 (CDK1) and ribonucleotide reductase regulatory subunit M2 (RRM2). Previous studies in mammals have a role for RRM2 in skeletal muscle development as well as cell growth, but the role of RRM2 in chicken is unclear. In this study, we investigated the effects of RRM2 on skeletal muscle development and regeneration in chickens in vitro and in vivo. The interaction between RRM2 and CDK1 was initially identified by co-immunoprecipitation and mass spectrometry. Through a dual luciferase reporter assay and quantitative real-time PCR, we identified the core promoter region of RRM2, which is regulated by the SP1 transcription factor. In this study, through cell counting kit-8 assays, 5-ethynyl-2'-deoxyuridine incorporation assays, flow cytometry, immunofluorescence staining, and Western blot analysis, we demonstrated that RRM2 promoted the proliferation and inhibited the differentiation of myoblasts. In vivo studies showed that RRM2 reduced the diameter of muscle fibers and slowed skeletal muscle regeneration. In conclusion, these data provide preliminary insights into the biological functions of RRM2 in chicken muscle development and skeletal muscle regeneration.

Pan-cancer analysis and in vitro validation of the oncogenic and prognostic roles of AURKA in human cancers

Background

Aurora kinase A (AURKA) plays a pivotal role in regulating cell mitosis and tumor progression. However, its prognostic significance across diverse cancer types remains relatively unexplored.

Methods

We conducted a comprehensive analysis of AURKA expression in various cancers using data from The Cancer Genome Atlas, Genotype-Tissue Expression, and The Human Protein Atlas databases. Our investigation encompassed an exploration of the associations between AURKA expression and clinical characteristics, shedding light on potential functional roles of AURKA. Additionally, we delved into the relationship between AURKA and the tumor microenvironment. To substantiate the role of AURKA, we carried out in vitro experiments in esophageal adenocarcinoma (EAC), prostate cancer (PRAD), and pancreatic cancer (PAAD) cells.

Results

Our analysis revealed that AURKA is prominently overexpressed in a majority of the cancer types under investigation. Elevated AURKA expression correlated closely with poorer prognosis and advanced tumor stages. AURKA was found to be associated with key pathways involved in the cell cycle and arachidonic acid metabolism. Moreover, AURKA expression exhibited significant correlations with immunoregulatory genes and immune cell profiles. Notably, in vitro experiments demonstrated that silencing AURKA expression resulted in reduced cell viability in EAC, PRAD, and PAAD cells, as well as a decrease in clone formation, cell cycle elongation, diminished cell invasion and reduced spheroid size in EAC cells (OE33 and OE19).

Conclusion

Our study elucidates the oncogenic role of AURKA and underscores its prognostic value across a spectrum of cancers, including EAC. These findings suggest that AURKA holds promise as a predictive biomarker for EAC and various other tumor types.

Colorectal Cancer Diagnosis: The Obstacles We Face in Determining a Non-Invasive Test and Current Advances in Biomarker Detection

Simple Summary

Colorectal cancer (CRC) is one of the most common cancers in the western world. CRC originates from precursor adenomatous polyps, which may over time develop into cancer. Endoscopic evaluation remains the gold-standard investigation for the disease. In the absence of molecular tools for early detection, the removal of neoplastic adenomas via polypectomy remains an important measure to prevent dysplastic adenomas from evolving into invasive carcinoma. Colonoscopy is an intrusive procedure that provides an uncomfortable experience for patients. Kits for testing for the presence of blood hemoglobin in the stool are now widely used, and DNA methylation-based detection kits have been approved in the USA for testing the stool and plasma, but few other molecular biomarkers have found their way into medical practice. This review summarizes current trends in the detection and screening of CRC and provides a definitive review of emerging molecular biomarkers for CRC.

Abstract

Globally, colorectal cancer (CRC) is the third most common cancer, with 1.4 million new cases and over 700,000 deaths per annum. Despite being one of the most common cancers, few molecular approaches to detect CRC exist. Carcinoembryonic antigen (CEA) is a known serum biomarker that is used in CRC for monitoring disease recurrence or response to treatment. However, it can also be raised in multiple benign conditions, thus having no value in early detection or screening for CRC. Molecular biomarkers play an ever-increasing role in the diagnosis, prognosis, and outcome prediction of disease, however, only a limited number of biomarkers are available and none are suitable for early detection and screening of CRC. A PCR-based Epi proColon^® blood plasma test for the detection of methylated SEPT9 has been approved by the USFDA for CRC screening in the USA, alongside a stool test for methylated DNA from CRC cells. However, these are reserved for patients who decline traditional screening methods. There remains an urgent need for the development of non-invasive molecular biomarkers that are highly specific and sensitive to CRC and that can be used routinely for early detection and screening. A molecular approach to the discovery of CRC biomarkers focuses on the analysis of the transcriptome of cancer cells to identify differentially expressed genes and proteins. A systematic search of the literature yielded over 100 differentially expressed CRC molecular markers, of which the vast majority are overexpressed in CRC. In terms of function, they largely belong to biological pathways involved in cell division, regulation of gene expression, or cell proliferation, to name a few. This review evaluates the current methods used for CRC screening, current availability of biomarkers, and new advances within the field of biomarker detection for screening and early diagnosis of CRC.

Identification of hub genes for early detection of bone metastasis in breast cancer

BACKGROUND

Globally, among all women, the most frequently detected and diagnosed and the most lethal type of cancer is breast cancer (BC). In particular, bone is one of the most frequent distant metastases 24in breast cancer patients and bone metastasis arises in approximately 80% of advanced patients. Thus, we need to identify and validate early detection markers that can differentiate metastasis from non-metastasis breast cancers.

METHODS

GSE55715, GSE103357, and GSE146661 gene expression profiling data were downloaded from the GEO database. There was 14 breast cancer with bone metastasis samples and 8 breast cancer tissue samples. GEO2R was used to screen for differentially expressed genes (DEGs). The volcano plots, Venn diagrams, and annular heatmap were generated by using the ggplot2 package. By using the cluster Profiler R package, KEGG and GO enrichment analyses of DEGs were conducted. Through PPI network construction using the STRING database, key hub genes were identified by cytoHubba. Finally, K-M survival and ROC curves were generated to validate hub gene expression.

RESULTS

By GO enrichment analysis, 143 DEGs were enriched in the following GO terms: extracellular structure organization, extracellular matrix organization, leukocyte migration class II protein complex, collagen tridermic protein complex, extracellular matrix structural constituent, growth factor binding, and platelet-derived growth factor binding. In the KEGG pathway enrichment analysis, DEGs were enriched in Staphylococcus aureus infection, Complement and coagulation cascades, and Asthma. By PPI network analysis, we selected the top 10 genes, including SLCO2B1, STAB1, SERPING1, HLA-DOA, AIF1, GIMAP4, C1orf162, HLA-DMB, ADAP2, and HAVCR2. By using TCGA and THPA databases, we validated 2 genes, SERPING1 and GIMAP4, that were related to the early detection of bone metastasis in BC.

CONCLUSIONS

2 abnormally expressed hub genes could play a pivotal role in the breast cancer with bone metastasis by affecting bone homeostasis imbalance in the bone microenvironment.

Secondary colon cancer in patients with ulcerative colitis: a systematic review and meta-analysis

BACKGROUND

A meta-analysis was conducted on the incidence of colon cancer in patients with ulcerative colitis (UC). This study aimed to evaluate the correlation between UC and colon cancer, and provide a theoretical guidance for clinical diagnoses and treatments of UC.

METHODS

Articles were searched in Chinese database with "ulcerative colitis", "UC", "colon cancer", "colorectal cancer", "incidence", and "meta-analysis" as the search terms. Articles were searched in English database with "ulcerative colitis", "UC", "colon cancer", "incidence rate", and "meta-analysis" as the search terms. Moreover, articles with the topic of "correlation between UC and colon cancer" were screened. The quality of articles was assessed using Rev Man 5.3 software provided by Cochrane system.

RESULTS

Eleven articles were included, most of which were of medium and high quality. Results of meta-analysis showed that 12,216 patients with UC were included in this study, and 110 patients developed colon cancer. There was statistical heterogeneity (Chi2=103.10, I2=90%, P<0.00001). Random-effect model analyses showed that there were no significant differences between colon cancer in patients with UC and those without colon cancer (Z=12.44, P<0.00001). A systematic review of articles found that the course and development of colon cancer in patients with UC might affect the occurrence of colon cancer. UC was a risk factor for colorectal cancer.

DISCUSSION

It was found that the course of disease and the occurrence and development of UC might affect the occurrence of colon cancer through a systematic review of articles. UC was one of the risk factors of colorectal cancer.

Identification of 5 Hub Genes Related to the Early Diagnosis, Tumour Stage, and Poor Outcomes of Hepatitis B Virus-Related Hepatocellular Carcinoma by Bioinformatics Analysis

BACKGROUND

The majority of primary liver cancers in adults worldwide are hepatocellular carcinomas (HCCs, or hepatomas). Thus, a deep understanding of the underlying mechanisms for the pathogenesis and carcinogenesis of HCC at the molecular level could facilitate the development of novel early diagnostic and therapeutic treatments to improve the approaches and prognosis for HCC patients. Our study elucidates the underlying molecular mechanisms of HBV-HCC development and progression and identifies important genes related to the early diagnosis, tumour stage, and poor outcomes of HCC.

METHODS

GSE55092 and GSE121248 gene expression profiling data were downloaded from the Gene Expression Omnibus (GEO) database. There were 119 HCC samples and 128 nontumour tissue samples. GEO2R was used to screen for differentially expressed genes (DEGs). Volcano plots and Venn diagrams were drawn by using the ggplot2 package in R. A heat map was generated by using Heatmapper. By using the clusterProfiler R package, KEGG and GO enrichment analyses of DEGs were conducted. Through PPI network construction using the STRING database, key hub genes were identified by cytoHubba. Finally, KM survival curves and ROC curves were generated to validate hub gene expression.

RESULTS

By GO enrichment analysis, 694 DEGs were enriched in the following GO terms: organic acid catabolic process, carboxylic acid catabolic process, carboxylic acid biosynthetic process, collagen-containing extracellular matrix, blood microparticle, condensed chromosome kinetochore, arachidonic acid epoxygenase activity, arachidonic acid monooxygenase activity, and monooxygenase activity. In the KEGG pathway enrichment analysis, DEGs were enriched in arachidonic acid epoxygenase activity, arachidonic acid monooxygenase activity, and monooxygenase activity. By PPI network construction and analysis of hub genes, we selected the top 10 genes, including CDK1, CCNB2, CDC20, BUB1, BUB1B, CCNB1, NDC80, CENPF, MAD2L1, and NUF2. By using TCGA and THPA databases, we found five genes, CDK1, CDC20, CCNB1, CENPF, and MAD2L1, that were related to the early diagnosis, tumour stage, and poor outcomes of HBV-HCC.

CONCLUSIONS

Five abnormally expressed hub genes of HBV-HCC are informative for early diagnosis, tumour stage determination, and poor outcome prediction.