Intracellular AGR2 transduces PGE2 stimuli to promote epithelial-mesenchymal transition and metastasis of colorectal cancer

Role and recent progress of P2Y12 receptor in cancer development

P2Y12 receptor (P2Y12R) is an adenosine-activated G protein-coupled receptor (GPCR) that plays a central role in platelet function, hemostasis, and thrombosis. P2Y12R activation can promote platelet aggregation and adhesion to cancer cells, promote tumor angiogenesis, and affect the tumor immune microenvironment (TIME) and tumor drug resistance, which is conducive to the progression of cancers. Meanwhile, P2Y12R inhibitors can inhibit this effect, suggesting that P2Y12R may be a potential therapeutic target for cancer. P2Y12R is involved in cancer development and metastasis, while P2Y12R inhibitors are effective in inhibiting cancer. However, a new study suggests that long-term use of P2Y12R inhibitors may increase the risk of cancer and the mechanism remains to be explored. In this paper, we reviewed the structural and functional characteristics of P2Y12R and its role in cancer. We explored the role of P2Y12R inhibitors in different tumors and the latest advances by summarizing the basic and clinical studies on the effects of P2Y12R inhibitors on tumors.

Biological factors driving colorectal cancer metastasis

Approximately 20% of colorectal cancer (CRC) patients present with metastasis at diagnosis. Among Stage I-III CRC patients who undergo surgical resection, 18% typically suffer from distal metastasis within the first three years following initial treatment. The median survival duration after the diagnosis of metastatic CRC (mCRC) is only 9 mo. mCRC is traditionally considered to be an advanced stage malignancy or is thought to be caused by incomplete resection of tumor tissue, allowing cancer cells to spread from primary to distant organs; however, increasing evidence suggests that the mCRC process can begin early in tumor development. CRC patients present with high heterogeneity and diverse cancer phenotypes that are classified on the basis of molecular and morphological alterations. Different genomic and nongenomic events can induce subclone diversity, which leads to cancer and metastasis. Throughout the course of mCRC, metastatic cascades are associated with invasive cancer cell migration through the circulatory system, extravasation, distal seeding, dormancy, and reactivation, with each step requiring specific molecular functions. However, cancer cells presenting neoantigens can be recognized and eliminated by the immune system. In this review, we explain the biological factors that drive CRC metastasis, namely, genomic instability, epigenetic instability, the metastatic cascade, the cancer-immunity cycle, and external lifestyle factors. Despite remarkable progress in CRC research, the role of molecular classification in therapeutic intervention remains unclear. This review shows the driving factors of mCRC which may help in identifying potential candidate biomarkers that can improve the diagnosis and early detection of mCRC cases.

Identification and validation of immune and cuproptosis - related genes for diabetic nephropathy by WGCNA and machine learning

Background

As the leading cause of chronic kidney disease, diabetic kidney disease (DKD) is an enormous burden for all healthcare systems around the world. However, its early diagnosis has no effective methods.

Methods

First, gene expression data in GEO database were extracted, and the differential genes of diabetic tubulopathy were obtained. Immune-related genesets were generated by WGCNA and immune cell infiltration analyses. Then, differentially expressed immune-related cuproptosis genes (DEICGs) were derived by the intersection of differential genes and genes related to cuproptosis and immune. To investigate the functions of DEICGs, volcano plots and GO term enrichment analysis was performed. Machine learning and protein-protein interaction (PPI) network analysis helped to finally screen out hub genes. The diagnostic efficacy of them was evaluated by GSEA analysis, receiver operating characteristic (ROC) curve, single-cell RNA sequencing and the Nephroseq website. The expression of hub genes at the animal level by STZ -induced and db/db DKD mouse models was further verified.

Results

Finally, three hub genes, including FSTL1, CX3CR1 and AGR2 that were up-regulated in both the test set GSE30122 and the validation set GSE30529, were screened. The areas under the curve (AUCs) of ROC curves of hub genes were 0.911, 0.935 and 0.922, respectively, and 0.946 when taking as a whole. Correlation analysis showed that the expression level of three hub genes demonstrated their negative relationship with GFR, while those of FSTL1 displayed a positive correlation with the level of serum creatinine. GSEA was enriched in inflammatory and immune-related pathways. Single-nucleus RNA sequencing indicated the main distribution of FSTL1 in podocyte and mesangial cells, the high expression of CX3CR1 in leukocytes and the main localization of AGR2 in the loop of Henle. In mouse models, all three hub genes were increased in both STZ-induced and db/db DKD models.

Conclusion

Machine learning was combined with WGCNA, immune cell infiltration and PPI analyses to identify three hub genes associated with cuproptosis, immunity and diabetic nephropathy, which all have great potential as diagnostic markers for DKD and even predict disease progression.

Prostaglandin E2 and myocarditis; friend or foe?

This review article summarizes the role of prostaglandin E2 (PGE2) and its receptors (EP1-EP4) as it relates to the inflammatory cardiomyopathy, myocarditis. During the COVID-19 pandemic, the onset of myocarditis in a subset of patients prompted a debate on the use of nonsteroidal anti-inflammatory drugs (NSAIDs), like ibuprofen, which act to inhibit the actions of prostaglandins. This review aims to further understanding of the role of PGE2 in the pathogenesis or protection of the myocardium in myocarditis. Inflammatory cardiomyopathies encompass a broad spectrum of disorders, all characterized by cardiac inflammation. Therefore, for the purpose of this review, the authors have placed particular emphasis on etiologies of myocarditis where effects of PGE2 have been documented.

PI3K/AKT signaling pathway as a critical regulator of epithelial-mesenchymal transition in colorectal tumor cells

Colorectal cancer (CRC) is one of the most frequent gastrointestinal malignancies that are considered as a global health challenge. Despite many progresses in therapeutic methods, there is still a high rate of mortality rate among CRC patients that is associated with poor prognosis and distant metastasis. Therefore, investigating the molecular mechanisms involved in CRC metastasis can improve the prognosis. Epithelial-mesenchymal transition (EMT) process is considered as one of the main molecular mechanisms involved in CRC metastasis, which can be regulated by various signaling pathways. PI3K/AKT signaling pathway has a key role in CRC cell proliferation and migration. In the present review, we discussed the role of PI3K/AKT pathway CRC metastasis through the regulation of the EMT process. It has been shown that PI3K/AKT pathway can induce the EMT process by down regulation of epithelial markers, while up regulation of mesenchymal markers and EMT-specific transcription factors that promote CRC metastasis. This review can be an effective step toward introducing the PI3K/AKT/EMT axis to predict prognosis as well as a therapeutic target among CRC patients. Video Abstract.

TGM2, HMGA2, FXYD3, and LGALS4 genes as biomarkers in acquired oxaliplatin resistance of human colorectal cancer: A systems biology approach

Acquired resistance to oxaliplatin is considered as the primary reason for failure in colorectal cancer (CRC) therapy. Identifying the underlying resistance mechanisms may improve CRC treatment. The present study aims to identify the key genes involved in acquired oxaliplatin-resistant in CRC by confirming the oxaliplatin resistance index (OX-RI). To this aim, two public microarray datasets regarding oxaliplatin-resistant CRC cells with different OX-RI, GSE42387, and GSE76092 were downloaded from GEO database to identify differentially expressed genes (DEGs). The results indicated that the OX-RI affects the gene expression pattern significantly. Then, 54 common DEGs in both datasets including 18 up- and 36 down-regulated genes were identified. Protein-protein interaction (PPI) analysis revealed 13 up- (MAGEA6, TGM2, MAGEA4, SCHIP1, ECI2, CD33, AKAP12, MAGEA12, CALD1, WFDC2, VSNL1, HMGA2, and MAGEA2B) and 12 down-regulated (PDZK1IP1, FXYD3, ALDH2, CEACAM6, QPRT, GRB10, TM4SF4, LGALS4, ALDH3A1, USH1C, KCNE3, and CA12) hub genes. In the next step, two novel up-regulated hub genes including ECI2 and SCHIP1 were identified to be related to oxaliplatin resistance. Functional enrichment and pathway analysis indicated that metabolic pathways, proliferation, and epithelial-mesenchymal transition may play dominant roles in CRC progression and oxaliplatin resistance. In the next procedure, two in vitro oxaliplatin-resistant sub-lines including HCT116/OX-R4.3 and HCT116/OX-R10 cells with OX-IR 3.93 and 10.06 were established, respectively. The results indicated the up-regulation of TGM2 and HMGA2 in HCT116/OX-R10 cells with high OX-RI and down-regulation of FXYD3, LGALS4, and ECI2 in both cell types. Based on the results, TGM2, HMGA2, FXYD3, and LGALS4 genes are related to oxaliplatin-resistant CRC and may serve as novel therapeutic targets.

AGR2: a secreted protein worthy of attention in diagnosis and treatment of breast cancer

AGR2 is a secreted protein widely existing in breast. In precancerous lesions, primary tumors and metastatic tumors, the expression of AGR2 is increased, which has aroused our interest. This review introduces the gene and protein structure of AGR2. Its endoplasmic reticulum retention sequence, protein disulfide isomerase active site and multiple protein binding sequences endow AGR2 with diverse functions inside and outside breast cancer cells. This review also enumerates the role of AGR2 in the progress and prognosis of breast cancer, and emphasizes that AGR2 can be a promising biomarker and a target for immunotherapy of breast cancer, providing new ideas for early diagnosis and treatment of breast cancer.

Transcription factor c-Rel regulated by E5 affects the whole process after HPV16 infection through miR-133a-modulated feedback loop aim at mir-379-369 cluster

BACKGROUND

During the development of cervical cancer, HPV infection causes a series of changes in transcription factors and microRNAs. But their relationships with pathogenic processes are not clear.

METHODS

Base on previous study, to analyse the relationship among HPV16 infection and the related transcription factors, related miRNAs, so as to further understand the molecular mechanism of HPV16 infection to cervical cancer, around the HPV16 related miRNAs we have reported, the methods of bioinformatics prediction, histology, cell model in vitro and molecular interaction were used for prediction and validation respectively RESULTS: The results showed that NF-κB family members(c-Rel, p65 and p50) were identified as main HPV16rmiR-transcription factors. They have different expressive characteristics in cervical lesions and play tumorigenesis or progression roles in different periods of HPV16 infection. c-Rel, p65 and p50 act as mediators which link the HPV16 E5 and HPV16 related miRNAs. Among them, c-Rel affects the occurrence and progression of cervical cancer during whole HPV16 infection stage through miR133a-3p-modulated mir-379-369 cluster with a positive feedback way which targeted c-Rel itself and its positive regulator AKT3.

CONCLUSION

So in the course of HPV16 infection, the E5, c-Rel, and miR-133a-3p form a positive feedback system which aim at mir-379-369 cluster for the whole process from HPV16 infection to cervical cancer.

Identification of AGR2 Gene-Specific Expression Patterns Associated with Epithelial-Mesenchymal Transition

The TGF-β signaling pathway is involved in numerous cellular processes, and its deregulation may result in cancer development. One of the key processes in tumor progression and metastasis is epithelial to mesenchymal transition (EMT), in which TGF-β signaling plays important roles. Recently, AGR2 was identified as a crucial component of the cellular machinery responsible for maintaining the epithelial phenotype, thereby interfering with the induction of mesenchymal phenotype cells by TGF-β effects in cancer. Here, we performed transcriptomic profiling of A549 lung cancer cells with CRISPR-Cas9 mediated AGR2 knockout with and without TGF-β treatment. We identified significant changes in transcripts associated with focal adhesion and eicosanoid production, in particular arachidonic acid metabolism. Changes in transcripts associated with the focal adhesion pathway were validated by RT-qPCR of COL4A1, COL4A2, FLNA, VAV3, VEGFA, and VINC mRNAs. In addition, immunofluorescence showed the formation of stress fibers and vinculin foci in cells without AGR2 and in response to TGF-β treatment, with synergistic effects observed. These findings imply that both AGR2 downregulation and TGF-β have a role in focal adhesion formation and cancer cell migration and invasion. Transcripts associated with arachidonic acid metabolism were downregulated after both AGR2 knockout and TGF-β treatment and were validated by RT-qPCR of GPX2, PTGS2, and PLA2G4A. Since PGE₂ is a product of arachidonic acid metabolism, its lowered concentration in media from AGR2-knockout cells was confirmed by ELISA. Together, our results demonstrate that AGR2 downregulation and TGF-β have an essential role in focal adhesion formation; moreover, we have identified AGR2 as an important component of the arachidonic acid metabolic pathway.

Endoplasmic Reticulum Stress-Related Signature for Predicting Prognosis and Immune Features in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) with cancer cells under endoplasmic reticulum (ER) stress has a poor prognosis. This study is aimed at discovering credible biomarkers for predicting the prognosis of HCC based on ER stress-related genes (ERSRGs). We constructed a novel four-ERSRG prognostic risk model, including PON1, AGR2, SSR2, and TMCC1, through a series of bioinformatic approaches, which can accurately predict survival outcomes in HCC patients. Higher risk scores were linked to later grade, recurrence, advanced TNM stage, later T stage, and HBV infection. In addition, 20 fresh frozen tumors and normal tissues from HCC patients were collected and used to validate the genes expressed in the signature by qRT-PCR and immunohistochemical (IHC) assays. Moreover, we found the ER stress-related signature could reflect the infiltration levels of different immune cells in the tumor microenvironment (TME) and forecast the efficacy of immune checkpoint inhibitor (ICI) treatment. Finally, we created a nomogram incorporating this ER stress-related signature. In conclusion, our constructed four-gene risk model associated with ER stress can accurately predict survival outcomes in HCC patients, and the model's risk score is associated with the poor clinical classification.