The Role of Nuclear Receptor Subfamily 1 Group H Member 4 (NR1H4) in Colon Cancer Cell Survival through the Regulation of c-Myc Stability

Recent advances in CRISPR-Cas systems for colorectal cancer research and therapeutics

INTRODUCTION

Colon cancer, ranked as the fourth leading global cause of cancer death, exhibits a complex progression marked by genetic variations. Over the past decade, the utilization of diverse CRISPR systems has propelled accelerated research into colorectal cancer (CRC) treatment.

AREAS COVERED

CRISPR/Cas9, a key player in this research, identifies new oncogenes, tumor suppressor genes (TSGs), and drug-resistance genes. Additionally, it facilitates the construction of experimental models, conducts genome-wide library screening, and develops new therapeutic targets, especially for targeted knockout in vivo or molecular targeted drug delivery, contributing to personalized treatments and significantly enhancing the care of colon cancer patients. In this review, we provide insights into the mechanism of the CRISPR/Cas9 system, offering a comprehensive exploration of its applications in CRC, spanning screening, modeling, gene functions, diagnosis, and gene therapy. While acknowledging its transformative potential, the article  highlights the challenges and limitations of CRISPR systems.

EXPERT OPINION

The application of CRISPR/Cas9 in CRC research provides a promising avenue for personalized treatments. Its potential for identifying key genes and enabling experimental models and genome-wide screening enhances patient care. This review underscores the significance of CRISPR-Cas9 gene editing technology across basic research, diagnosis, and the treatment landscape of colon cancer.

The obeticholic acid can positively regulate the cancerous behavior of MCF7 breast cancer cell line

BACKGROUND

The diagnosis and treatment processes of cancer are among the main challenges of medical science in recent decades. The use of different therapeutic agents is one of the most common methods frequently utilized for cancer treatment. Accumulating evidence points to a potential effect of Obeticholic acid (OCA), a specific ligand for farnesoid X receptor, on the regulation of cancer-associated pathways. In spite of tremendous efforts to introduce OCA into the clinical setting, there is a great deal of uncertainty about its impact on breast cancer treatment. This study was performed to evaluate the effects of OCA on breast cancer.

METHODS AND RESULTS

In this experiment, the MCF-7 (Michigan Cancer Foundation-7) cell line was treated with 0.1 µM OCA, and cancerous characteristics of the MCF-7 cell line was evaluated by the MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl-2 H-tetrazolium bromide) assay, gelatin zymography, western blot, Real-time PCR, flow cytometry, and ELISA techniques. The results indicated that OCA increased the rate of apoptosis and the expression levels of PPARα (Peroxisome proliferator-activated receptor alpha) and TIMP-1 (tissue inhibitor of metalloproteinase-1) genes in this cell line, while it reduced the mRNA levels of MMP7 (matrix metalloproteinase 7) and Bcl-2 (B-cell lymphoma 2) genes, as well as the protein levels of the active form of AKT (protein kinase B), Erk1/2 (extracellular signal-regulated kinase 1/2) and STAT3 (Signal transducers and activators of transcription-3). Also, OCA decreased the activity of MMP9, while it increased the secretion of VEGF-A (vascular endothelial growth factor-A).

CONCLUSIONS

It seems that OCA can exert anti-cancer effects on the MCF-7 cells by reducing growth, proliferation, migration, invasion, and regulation of the expression of genes involved in cancer-associated pathways. However, it should be noted that further studies are warranted to establish this concept, especially the increase of VEGF-A can be considered a challenge for the results of this study.

Synthetic lethality in large-scale integrated metabolic and regulatory network models of human cells

Synthetic lethality (SL) is a promising concept in cancer research. A wide array of computational tools has been developed to predict and exploit synthetic lethality for the identification of tumour-specific vulnerabilities. Previously, we introduced the concept of genetic Minimal Cut Sets (gMCSs), a theoretical approach to SL developed for genome-scale metabolic networks. The major challenge in our gMCS framework is to go beyond metabolic networks and extend existing algorithms to more complex protein-protein interactions. In this article, we take a step further and incorporate linear regulatory pathways into our gMCS approach. Extensive algorithmic modifications to compute gMCSs in integrated metabolic and regulatory models are presented in detail. Our extended approach is applied to calculate gMCSs in integrated models of human cells. In particular, we integrate the most recent genome-scale metabolic network, Human1, with 3 different regulatory network databases: Omnipath, Dorothea and TRRUST. Based on the computed gMCSs and transcriptomic data, we discovered new essential genes and their associated synthetic lethal for different cancer cell lines. The performance of the different integrated models is assessed with available large-scale in-vitro gene silencing data. Finally, we discuss the most relevant gene essentiality predictions based on published literature in cancer research.

Application of CRISPR-Cas9 gene editing technology in basic research, diagnosis and treatment of colon cancer

Colon cancer is the fourth leading cause of cancer death worldwide, and its progression is accompanied by a complex array of genetic variations. CRISPR/Cas9 can identify new drug-resistant or sensitive mutations in colon cancer, and can use gene editing technology to develop new therapeutic targets and provide personalized treatments, thereby significantly improving the treatment of colon cancer patients. CRISPR/Cas9 systems are driving advances in biotechnology. RNA-directed Cas enzymes have accelerated the pace of basic research and led to clinical breakthroughs. This article reviews the rapid development of CRISPR/Cas in colon cancer, from gene editing to transcription regulation, gene knockout, genome-wide CRISPR tools, therapeutic targets, stem cell genomics, immunotherapy, metabolism-related genes and inflammatory bowel disease. In addition, the limitations and future development of CRISPR/Cas9 in colon cancer studies are reviewed. In conclusion, this article reviews the application of CRISPR-Cas9 gene editing technology in basic research, diagnosis and treatment of colon cancer.

CEBPB regulates the bile acid receptor FXR to accelerate colon cancer progression by modulating aerobic glycolysis

BACKGROUND

Aerobic glycolysis is a main characteristic of tumors, and inhibited glycolysis impedes the tumor development. Farnesoid X Receptor (FXR) mainly regulates bile acid metabolism. In this research, we mainly investigated whether FXR was involved in the regulation of glycolysis in colon cancer.

METHODS

The differential expression analysis was performed on FXR and Enhancer Binding Protein Beta (CEBPB) data in colon cancer downloaded from The Cancer Genome Atlas (TCGA) database. Western blot and qRT-PCR were used to detect the expression levels of CEBPB and FXR. The upstream gene of FXR was predicted through bioinformatic analysis. ChIP and dual luciferease assays were performed to confirm the targeted relationship between CEBPB and FXR. Gene Set Enrichment Analysis (GSEA) was performed on FXR. Finally, the glycolysis capabilities of cells in each treatment group were detected. CCK-8, colony formation assay and flow cytometry were performed to test proliferation and apoptosis of colon cancer cells.

RESULTS

FXR was lowly expressed at the cell level in colon cancer. In vitro assays verified the antitumor effect of FXR on colon cancer. ChIP and dual luciferase assays verified that transcription factor CEBPB bound with the promotor region of FXR, and negatively regulated the expression of FXR. Cell function assays proved that silenced expression of FXR promoted glycolysis, which promoted the development of colon cancer cells.

CONCLUSION

The study on FXR-regulated glycolysis of colon cancer cells helps us to further understand the molecular mechanism by which FXR regulated the development of colon cancer cells.

Cholecystectomy promotes colon carcinogenesis by activating the Wnt signaling pathway by increasing the deoxycholic acid level

Purpose

Cholecystectomy (XGB) is widely recognized as a risk factor for colon cancer (CC). Continuous exposure of the colonic epithelium to deoxycholic acid (DCA) post-XGB may exert cytotoxic effects and be involved in the progression of CC. However, the functions of the XGB-induced DCA increase and the underlying mechanism remain unclear.

Methods

Colitis-associated CC (CAC) mouse models constructed by AOM-DSS inducement were used to confirm the effect of XGB on the CC progression. Hematoxylin & eosin staining was performed to assess the tumor morphology of CAC mouse models tissues. Various cell biological assays including EdU, live-cell imaging, wound-healing assays, and flow cytometry for cell cycle and apoptosis were used to evaluate the effect of DCA on CC progression. The correlation among XGB, DCA, and CC and their underlying mechanisms were detected with immunohistochemistry, mass spectrometry, transcriptome sequencing, qRT-PCR, and western blotting.

Results

Here we proved that XGB increased the plasma DCA level and promoted colon carcinogenesis in a colitis-associated CC mouse model. Additionally, we revealed that DCA promoted the proliferation and migration of CC cells. Further RNA sequencing showed that 120 mRNAs were upregulated, and 118 downregulated in DCA-treated CC cells versus control cells. The upregulated mRNAs were positively correlated with Wnt signaling and cell cycle-associated pathways. Moreover, DCA treatment could reduced the expression of the farnesoid X receptor (FXR) and subsequently increased the levels of β-Catenin and c-Myc in vitro and in vivo. Moreover, the FXR agonist GW4064 decreased the proliferation of CC cells by repressing the expression of β-catenin.

Conclusion

We concluded that XGB-induced DCA exposure could promote the progression of CC by inhibiting FXR expression and enhancing the Wnt-β-catenin pathway.

Identification of an Innate Immune-Related Prognostic Signature in Early-Stage Lung Squamous Cell Carcinoma

Background

Early-stage lung squamous cell carcinoma (LUSC) progression is accompanied by changes in immune microenvironments and the expression of immune-related genes (IRGs). Identifying innate IRGs associated with prognosis may improve treatment and reveal new immunotherapeutic targets.

Methods

Gene expression profiles and clinical data of early-stage LUSC patients were obtained from the Gene Expression Omnibus and The Cancer Genome Atlas databases and IRGs from the InnateDB database. Univariate and multivariate Cox regression and LASSO regression analyses were performed to identify an innate IRG signature model prognostic in patients with early-stage LUSC. The predictive ability of this model was assessed by time-dependent receiver operator characteristic curve analysis, with the independence of the model-determined risk score assessed by univariate and multivariate Cox regression analyses. Overall survival (OS) in early-stage LUSC patients was assessed using a nomogram and decision curve analysis (DCA). Functional and biological pathways were determined by gene set enrichment analysis, and differences in biological functions and immune microenvironments between the high- and low-risk groups were assessed by ESTIMATE and the CIBERSORT algorithm.

Results

A signature involving six IRGs (SREBF2, GP2, BMX, NR1H4, DDX41, and GOPC) was prognostic of OS. Samples were divided into high- and low-risk groups based on median risk scores. OS was significantly shorter in the high-risk than in the low-risk group in the training (P < 0.001), GEO validation (P = 0.00021) and TCGA validation (P = 0.034) cohorts. Multivariate Cox regression analysis showed that risk score was an independent risk factor for OS, with the combination of risk score and T stage being optimally predictive of clinical benefit. GSEA, ESTIMATE, and the CIBERSORT algorithm showed that immune cell infiltration was higher and immune-related pathways were more strongly expressed in the low-risk group.

Conclusion

A signature that includes these six innate IRGs may predict prognosis in patients with early-stage LUSC.

Adhesion of Platelets to Colon Cancer Cells Is Necessary to Promote Tumor Development in Xenograft, Genetic and Inflammation Models

Simple Summary

Platelets are small, anucleate, metabolically active cells and they represent an important linkage between tissue damage and inflammatory response. Several studies focused on the central role of platelets in inflammation and tumor development through their direct interaction with other cell types. Mice lacking the vascular adhesion molecules P-selectin exhibited a reduction in tumor metastases. We demonstrated that P-selectin-ablated platelets reduced tumor growth in a xenograft adenocarcinoma model. Furthermore, the lack of P-selectin decreased colon cancer progression in genetic mouse models and in chemically-induced colitis colorectal carcinogenesis. Our results suggest that platelets-cancer cells crosstalk via P-selectin is fundamental for tumor development.

Abstract

Platelets represent the linkage between tissue damage and inflammatory response with a putative role in tumorigenesis. Given the importance of the microenvironment in colon cancer development, we elucidated the eventual role of platelets-cancer cells crosstalk in in vivo colon cancer models. To evaluate the involvement of platelets in intestinal tumorigenesis, we first analyzed if the ablation of β-integrin P-selectin that drives platelets-cell adhesion, would contribute to platelets-colon cancer cell interaction and drive cancer progression. In a xenograft tumor model, we observed that when tumors are inoculated with platelets, the ablation of P-selectin significantly reduced tumor growth compared to control platelets. Furthermore, in genetic models, as well as in chronic colitis-associated colorectal carcinogenesis, P-selectin ablated mice displayed a significant reduction in tumor number and size compared to control mice. Taken together, our data highlights the importance of platelets in the tumor microenvironment for intestinal tumorigenesis. These results support the hypothesis that a strategy aimed to inhibit platelets adhesion to tumor cells are able to block tumor growth and could represent a novel therapeutic approach to colon cancer treatment.

Construction and prognostic analysis of miRNA-mRNA regulatory network in liver metastasis from colorectal cancer

Background

Colorectal cancer (CRC) is one of the most common cancers in the world, and liver metastasis is the leading cause of colorectal cancer-related deaths. However, the mechanism of liver metastasis in CRC has not been clearly elucidated.

Methods

Three datasets from the Gene Expression Omnibus (GEO) database were analyzed to obtain differentially expressed genes (DEGs), which were subjected to functional enrichment analysis and protein-protein interaction analysis. Subsequently, mRNA-miRNA network was constructed, and the associated DEGs and DEMs were performed for prognostic analysis. Finally, we did infiltration analysis of growth arrest specific 1 (GAS1)-associated immune cells.

Results

We obtained 325 DEGs and 9 differentially expressed miRNAs (DEMs) between primary CRC and liver metastases. Enrichment analysis and protein-protein interactions (PPI) further revealed the involvement of DEGs in the formation of the inflammatory microenvironment and epithelial-mesenchymal transition (EMT) during the liver metastases process in CRC. Survival analysis demonstrated that low-expressed GAS1 as well as low-expressed hsa-miR-33b-5p was a favorable prognostic indicator of overall survival. Further exploration of GAS1 revealed that its expression was interrelated with the infiltration of immune cells in tumor tissues.

Conclusions

In summary, DEGs, DEMs, and their interactions found in liver metastasis of CRC may provide a basis for further understanding of the mechanism of CRC metastasis.

Identification of a Metabolism-Related Risk Signature Associated With Clinical Prognosis in Glioblastoma Using Integrated Bioinformatic Analysis

Altered metabolism of glucose, lipid and glutamine is a prominent hallmark of cancer cells. Currently, cell heterogeneity is believed to be the main cause of poor prognosis of glioblastoma (GBM) and is closely related to relapse caused by therapy resistance. However, the comprehensive model of genes related to glucose-, lipid- and glutamine-metabolism associated with the prognosis of GBM remains unclear, and the metabolic heterogeneity of GBM still needs to be further explored. Based on the expression profiles of 1,395 metabolism-related genes in three datasets of TCGA/CGGA/GSE, consistent cluster analysis revealed that GBM had three different metabolic status and prognostic clusters. Combining univariate Cox regression analysis and LASSO-penalized Cox regression machine learning methods, we identified a 17-metabolism-related genes risk signature associated with GBM prognosis. Kaplan-Meier analysis found that obtained signature could differentiate the prognosis of high- and low-risk patients in three datasets. Moreover, the multivariate Cox regression analysis and receiver operating characteristic curves indicated that the signature was an independent prognostic factor for GBM and had a strong predictive power. The above results were further validated in the CGGA and GSE13041 datasets, and consistent results were obtained. Gene set enrichment analysis (GSEA) suggested glycolysis gluconeogenesis and oxidative phosphorylation were significantly enriched in high- and low-risk GBM. Lastly Connectivity Map screened 54 potential compounds specific to different subgroups of GBM patients. Our study identified a novel metabolism-related gene signature, in addition the existence of three different metabolic status and two opposite biological processes in GBM were recognized, which revealed the metabolic heterogeneity of GBM. Robust metabolic subtypes and powerful risk prognostic models contributed a new perspective to the metabolic exploration of GBM.