Downregulation of CLCA4 expression is associated with the development and progression of colorectal cancer

Network pharmacology: an efficient but underutilized approach in oral, head and neck cancer therapy-a review

The application of network pharmacology (NP) has advanced our understanding of the complex molecular mechanisms underlying diseases, including neck, head, and oral cancers, as well as thyroid carcinoma. This review aimed to explore the therapeutic potential of natural network pharmacology using compounds and traditional Chinese medicines for combating these malignancies. NP serves as a pivotal tool that provides a comprehensive view of the interactions among compounds, genes, and diseases, thereby contributing to the advancement of disease treatment and management. In parallel, this review discusses the significance of publicly accessible databases in the identification of oral, head, and neck cancer-specific genes. These databases, including those for head and neck oral cancer, head and neck cancer, oral cancer, and genomic variants of oral cancer, offer valuable insights into the genes, miRNAs, drugs, and genetic variations associated with these cancers. They serve as indispensable resources for researchers, clinicians, and drug developers, contributing to the pursuit of precision medicine and improved treatment of these challenging malignancies. In summary, advancements in NP could improve the globalization and modernization of traditional medicines and prognostic targets as well as aid in the development of innovative drugs. Furthermore, this review will be an eye-opener for researchers working on drug development from traditional medicines by applying NP approaches.

Modulation of TMEM16B channel activity by the calcium-activated chloride channel regulator 4 (CLCA4) in human cells

The Ca2+-activated Cl- channel regulator CLCA1 potentiates the activity of the Ca2+-activated Cl- channel (CaCC) TMEM16A by directly engaging the channel at the cell surface, inhibiting its reinternalization and increasing Ca2+-dependent Cl- current (ICaCC) density. We now present evidence of functional pairing between two other CLCA and TMEM16 protein family members, namely CLCA4 and the CaCC TMEM16B. Similar to CLCA1, (i) CLCA4 is a self-cleaving metalloprotease, and the N-terminal portion (N-CLCA4) is secreted; (ii) the von Willebrand factor type A (VWA) domain in N-CLCA4 is sufficient to potentiate ICaCC in HEK293T cells; and (iii) this is mediated by the metal ion-dependent adhesion site motif within VWA. The results indicate that, despite the conserved regulatory mechanism and homology between CLCA1 and CLCA4, CLCA4-dependent ICaCC are carried by TMEM16B, rather than TMEM16A. Our findings show specificity in CLCA/TMEM16 interactions and suggest broad physiological and pathophysiological links between these two protein families.

Construction of a new prognostic model for colorectal cancer based on bulk RNA-seq combined with The Cancer Genome Atlas data

Background

Colorectal cancer (CRC) is one of the leading causes of cancer-related deaths, and improving the prognosis of CRC patients is an urgent concern. The aim of this study was to explore new immunotherapy targets to improve survival in CRC patients.

Methods

We analyzed CRC-related single-cell data GSE201348 from the Gene Expression Omnibus (GEO) database, and identified differentially expressed genes (DEGs). Subsequently, we performed differential analysis on the rectum adenocarcinoma (READ) and colon adenocarcinoma (COAD) transcriptome sequencing data [The Cancer Genome Atlas (TCGA)-CRC queue] and clinical data downloaded from TCGA database. Subgroup analysis was performed using CIBERSORTx and cluster analysis. Finally, biomarkers were identified by one-way cox regression as well as least absolute shrinkage and selection operator (LASSO) analysis.

Results

In this study, we analyzed CRC-related single-cell data GSE201348, and identified 5,210 DEGs. Subsequently, we performed differential analysis on the TCGA-CRC queue database, and obtained 4,408 DEGs. Then, we categorized the cancer samples in the sequencing data into three groups (k1, k2, and k3), with significant differences observed between the k1 and k2 groups via survival analysis. Further differential analysis on the samples in the k1 and k2 groups identified 1,899 DEGs. A total of 77 DEGs were selected among those DEGs obtained from three differential analyses. Through subsequent Cox univariate analysis and LASSO analysis, seven biomarkers (RETNLB, CLCA4, UGT2A3, SULT1B1, CCL24, BMP5, and ATOH1) were identified and selected to establish a risk score (RS).

Conclusions

To sum up, this study demonstrates the potential of the seven-gene prognostic risk model as instrumental variables for predicting the prognosis of CRC.

Insights into the molecular mechanisms and signalling pathways of epithelial to mesenchymal transition (EMT) in colorectal cancer: A systematic review and bioinformatic analysis of gene expression

Colorectal cancer (CRC) is ranked as the second leading cause of mortality worldwide, mainly due to metastasis. Epithelial to mesenchymal transition (EMT) is a complex cellular process that drives CRC metastasis, regulated by changes in EMT-associated gene expression. However, while numerous genes have been identified as EMT regulators through various in vivo and in vitro studies, little is known about the genes that are differentially expressed in CRC tumour tissue and their signalling pathway in regulating EMT. Using an integration of systematic search and bioinformatic analysis, gene expression profiles of CRC tumour tissues were compared to non-tumour adjacent tissues to identify differentially expressed genes (DEGs), followed by performing systematic review on common identified DEGs. Fifty-eight common DEGs were identified from the analysis of 82 tumour tissue samples obtained from four gene expression datasets (NCBI GEO). These DEGS were then systematically searched for their roles in modulating EMT in CRC based on previously published studies. Following this, 10 common DEGs (CXCL1, CXCL8, MMP1, MMP3, MMP7, TACSTD2, VIP, HPGD, ABCG2, CLCA4) were included in this study and subsequently subjected to further bioinformatic analysis. Their roles and functions in modulating EMT in CRC were discussed in this review. This study enhances our understanding of the molecular mechanisms underlying EMT and uncovers potential candidate genes and pathways that could be targeted in CRC.

Weighted gene co-expression network analysis for hub genes in colorectal cancer

BACKGROUND

This study is designed to explore hub genes participating in colorectal cancer (CRC) development through weighted gene co-expression network analysis (WGCNA).

METHODS

Expression profiles of CRC and normal samples were retrieved from the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA), and were subjected to WGCNA to filter differentially expressed genes with significant association with CRC. Functional enrichment analysis and protein-protein interaction (PPI) analysis were carried out to filter the candidate genes, further and survival analysis was performed for the candidate genes to obtain potential regulatory hub genes in CRC. Expression analysis was conducted for the candidate genes and a multifactor model was established.

RESULTS

After differential analysis and WGCNA, 289 candidate genes were filtered from the GEO and TCGA. Further functional enrichment analysis demonstrated possible regulatory pathways and functions. PPI analysis filtered 15 hub genes and survival analysis indicated a significant correlation of CLCA1, CLCA4, and CPT1A with prognosis of patients with CRC. The multifactor Cox risk model established based on the three genes revealed that if the three genes were a gene set, they had well predictive capacity for the prognosis of patients with CRC.

CONCLUSIONS

CLCA1, CLCA4, and CPT1A express at low levels in CRC and function as core anti-tumor genes. As a gene set, they can predict prognosis well.

Differential Gene Expression of Checkpoint Markers and Cancer Markers in Mouse Models of Spontaneous Chronic Colitis

The presence of checkpoint markers in cancer cells aids in immune escape. The identification of checkpoint markers and early cancer markers is of utmost importance to gain clarity regarding the relationship between colitis and progressive inflammation leading to cancer. Herein, the gene expression levels of checkpoint makers, cancer-related pathways, and cancer genes in colon tissues of mouse models of chronic colitis (Winnie and Winnie-Prolapse mice) using next-generation sequencing are determined. Winnie mice are a result of a Muc2 missense mutation. The identification of such genes and their subsequent expression and role at the protein level would enable novel markers for the early diagnosis of cancer in IBD patients. The differentially expressed genes in the colonic transcriptome were analysed based on the Kyoto Encyclopedia of Genes and Genomes pathway. The expression of several oncogenes is associated with the severity of IBD, with Winnie-Prolapse mice expressing a large number of key genes associated with development of cancer. This research presents a number of new targets to evaluate for the development of biomarkers and therapeutics.

A novel enterocyte-related 4-gene signature for predicting prognosis in colon adenocarcinoma

Background

Colon adenocarcinoma (COAD) is a fatal disease, and its cases are constantly increasing worldwide. Further, the therapeutic and management strategies for patients with COAD are still unsatisfactory due to the lack of accurate patient classification and prognostic models. Therefore, our study aims to identify prognostic markers in patients with COAD and construct a cell subtype-specific prognostic model with high accuracy and robustness.

Methods

Single-cell transcriptomic data of six samples were retrieved from the Gene expression omnibus (GEO) database. The cluster annotation and cell-cell communication analysis identified enterocytes as a key player mediating signal communication networks. A four-gene signature prognostic model was constructed based on the enterocyte-related differentially expressed genes (ERDEGs) in patients with COAD of the Cancer Genome Atlas cohort. The prognostic model was validated on three external validation cohorts from the GEO database. The correlation between immune cell infiltration, immunotherapy response, drug sensitivity, and the four-gene signature prognostic model was investigated. Finally, immunohistochemistry (IHC) was performed to determine the expression of the four genes.

Results

We found that the proportion of epithelial cells was obviously large in COAD samples. Further analysis of epithelial cells showed that the activity of the enterocytes was highest in the cell-cell communication network. Based on enterocyte data, 30 ERDEGs were identified and a 4-gene prognostic model including CPM, CLCA4, ELOVL6, and ATP2A3 was developed and validated. The risk score derived from this model was considered as an independent variable factor to predict overall survival. The patients were divided into high- and low-risk groups based on the median riskscore value. The correlation between immune cell infiltration, immunotherapy response, immune status, clinical characteristics, drug sensitivity, and risk score was analyzed. IHC confirmed the expression of signature genes in tissues from normal individuals, patients with polyps, and COAD.

Conclusion

In this study, we constructed and validated a novel four-gene signature prognostic model, which could effectively predict the response to immunotherapy and overall survival in patients with COAD. More importantly, this model provides useful insight into the management of colon cancer patients and aids in designing personalized therapy.

An integrative transcriptome analysis reveals potential predictive, prognostic biomarkers and therapeutic targets in colorectal cancer

BACKGROUND

A deep understanding of potential molecular biomarkers and therapeutic targets related to the progression of colorectal cancer (CRC) from early stages to metastasis remain mostly undone. Moreover, the regulation and crosstalk among different cancer-driving molecules including messenger RNAs (mRNAs), long non-coding RNAs (lncRNAs) and micro-RNAs (miRNAs) in the transition from stage I to stage IV remain to be clarified, which is the aim of this study.

METHODS

We carried out two separate differential expression analyses for two different sets of samples (stage-specific samples and tumor/normal samples). Then, by the means of robust dataset analysis we identified distinct lists of differently expressed genes (DEGs) for Robust Rank Aggregation (RRA) and weighted gene co-expression network analysis (WGCNA). Then, comprehensive computational systems biology analyses including mRNA-miRNA-lncRNA regulatory network, survival analysis and machine learning algorithms were also employed to achieve the aim of this study. Finally, we used clinical samples to carry out validation of a potential and novel target in CRC.

RESULTS

We have identified the most significant stage-specific DEGs by combining distinct results from RRA and WGCNA. After finding stage-specific DEGs, a total number of 37 DEGs were identified to be conserved across all stages of CRC (conserved DEGs). We also found DE-miRNAs and DE-lncRNAs highly associated to these conserved DEGs. Our systems biology approach led to the identification of several potential therapeutic targets, predictive and prognostic biomarkers, of which lncRNA LINC00974 shown as an important and novel biomarker.

CONCLUSIONS

Findings of the present study provide new insight into CRC pathogenesis across all stages, and suggests future assessment of the functional role of lncRNA LINC00974 in the development of CRC.

Identification of Hub Genes in Colorectal Adenocarcinoma by Integrated Bioinformatics

An improved understanding of the molecular mechanism of colorectal adenocarcinoma is necessary to predict the prognosis and develop new target gene therapy strategies. This study aims to identify hub genes associated with colorectal adenocarcinoma and further analyze their prognostic significance. In this study, The Cancer Genome Atlas (TCGA) COAD-READ database and the gene expression profiles of GSE25070 from the Gene Expression Omnibus were collected to explore the differentially expressed genes between colorectal adenocarcinoma and normal tissues. The weighted gene co-expression network analysis (WGCNA) and differential expression analysis identified 82 differentially co-expressed genes in the collected datasets. Enrichment analysis was applied to explore the regulated signaling pathway in colorectal adenocarcinoma. In addition, 10 hub genes were identified in the protein–protein interaction (PPI) network by using the cytoHubba plug-in of Cytoscape, where five genes were further proven to be significantly related to the survival rate. Compared with normal tissues, the expressions of the five genes were both downregulated in the GSE110224 dataset. Subsequently, the expression of the five hub genes was confirmed by the Human Protein Atlas database. Finally, we used Cox regression analysis to identify genes associated with prognosis, and a 3-gene signature (CLCA1–CLCA4–GUCA2A) was constructed to predict the prognosis of patients with colorectal cancer. In conclusion, our study revealed that the five hub genes and CLCA1–CLCA4–GUCA2A signature are highly correlated with the development of colorectal adenocarcinoma and can serve as promising prognosis factors to predict the overall survival rate of patients.

Integrated Analysis of Necroptosis-Related Genes for Prognosis, Immune Microenvironment Infiltration, and Drug Sensitivity in Colon Cancer

Background

Necroptosis, is intimately linked to tumor development and prognosis and has been considered as a target for anticancer therapy. However, the role of necroptosis-related genes (NRGs) in colon cancer is unclear.

Methods

In the present study, we screened 76 NRGs from previous studies and described the landscape of transcriptomic and genetic variation of NRGs in colon cancer (CC) patient samples. Molecular subtypes of necroptosis in colon cancer were identified by clustering analysis, and these molecular subtypes were linked to patient prognosis and TME cell infiltration characteristics. Then, the NRS-score for predicting overall survival (OS) was built based on the TCGA database and validated in the GSE39582 cohort for its predictive power in CC patients. Besides, the ESTIMATE and CIBERSORT algorithms were applied to explore the relationship between NRS-score and tumor immune microenvironment.

Results

We identified two molecular subtypes associated with necroptosis in CC, which have diverse prognosis and immune microenvironment characteristics. Based on the differentially expressed genes between the two molecular subtypes, we further developed a necroptosis risk score signature, referred to as NRS-score. High NRS-score was associated with poor prognosis in CC through immunosuppressive microenvironment and immune escape mechanisms. The nomogram based on NRS-score showed excellent ability to predict prognosis. In addition, NRS-score presented a positive correlation with tumor mutational burden (TMB) and immune checkpoint blockade (ICB) expression and was closely correlated with multiple anticancer agent susceptibility.

Conclusion

This work revealed a close relationship between necroptosis and the prognosis and immune microenvironment of colon cancer. The NRS-score based on the 8-gene signature may be used to predict the sensitivity of immunotherapy and chemotherapy in colon cancer patients, and provides a foundation for future studies targeting necroptosis and its immune microenvironment.

Analyzing large scale gene expression data in colorectal cancer reveals important clues; CLCA1 and SELENBP1 downregulated in CRC not in normal and not in adenoma

Early detection of colorectal cancer (CRC) increases the chances of survival and reduces the therapeutic problems and costs of treatment. Since molecular biomarkers can help us diagnose colorectal cancer early, we need to identify novel gene for predicting the early stages of tumorigenesis. Here, we integrated five independent CRC gene expression datasets derived from expression profiling by array comparing CRC with normal samples in: GSE21510, GSE4107, GSE25071, GSE15781 dataset, and GSE8671 dataset, including 64 samples from 32 patients comparing 32 colonic normal mucosa with 32 colorectal adenoma. To detect genes that expressed differentially in experimental circumstances of these datasets, we used web tool of GEO2R to compare groups of samples in the GEO data series. Furthermore, we constructed the protein-protein interactions network by STRING database for mostly downregulated genes and the expression of their members in PPI network were studied into five datasets separately. Also, the level of expression of selected biomarker genes in different stages of CRC compared to normal was studied. Our data revealed 17 common downregulated genes (average fold change (FC) in five tests ≥6) in CRC in comparison with normal (Test 1 to Test 4) and in adenoma compared with normal (Test 5). Studying of gene expression of PPI network members of these downregulated genes led to identifying of CLCA1, SELENBP1, CWC25, ACOT11, GUCY2C and ALDH1A1 as suppressor genes and PTGS2, PROCR, MOCS3 and NFS1 as oncogenes which respectively downregulated and upregulated in CRC. Since decreasing of gene expression was seen in CRC comparing with normal and due to no different expression seen for these 10 genes in adenoma, they, especially CLCA1 and SELENBP1, could be considered as biomarkers for early detection of CRC. Before using these signature genes in the clinic; however, further validations are required.

Expression of the CLCA4 Gene in Esophageal Carcinoma and Its Impact on the Biologic Function of Esophageal Carcinoma Cells

Background

Esophageal carcinoma (ESCA) is one of the malignant tumors with a high mortality rate worldwide, which seriously affects people's health. Calcium-activated chloride channel 4 (CLCA4) was reported to be a tumor inhibitor in hepatocellular carcinoma. Nevertheless, the role of CLCA4 in ESCA is still unclear.

Methods

RT-qPCR and western blot assay were used to test the expression pattern of CLCA4 in ESCA tissues and cells. CCK-8 assay was performed to detect the effect of CLCA4 overexpression on cell proliferation in ESCA cells. Transwell assay was used to measure the effect of CLCA4 upregulation on migration and invasion abilities of ESCA cells. Animal experiments were conducted to investigate the role of CLCA4 upregulation in tumor growth in vivo.

Results

CLCA4 was significantly reduced in ESCA tissues and correlated with T stage, differentiation, and lymph node metastasis. CLCA4 overexpression was found to inhibit cell proliferation, migration, invasion, and EMT progression in ESCA cells. Moreover, CLCA4 overexpression suppressed tumor growth in vivo.

Conclusion

CLCA4 was suggested to act as a tumor inhibitor in ESCA and might be a therapeutic target gene for the treatment of patients with ESCA.