Screening Driving Transcription Factors in the Processing of Gastric Cancer

Effects of COL1A1 and SYTL2 on inflammatory cell infiltration and poor extracellular matrix remodeling of the vascular wall in thoracic aortic aneurysm

BACKGROUND

Thoracic aortic aneurysm (TAA) is a fatal cardiovascular disease, the pathogenesis of which has not yet been clarified. This study aimed to identify and validate the diagnostic markers of TAA to provide a strong theoretical basis for developing new methods to prevent and treat this disease.

METHODS

Gene expression profiles of the GSE9106, GSE26155, and GSE155468 datasets were acquired from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were identified using the "limma" package in R. Least absolute shrinkage and selection operator (LASSO), support vector machine-recursive feature elimination (SVM-RFE), random forest, and binary logistic regression analyses were used to screen the diagnostic marker genes. Single-sample gene set enrichment analysis (ssGSEA) was used to estimate immune cell infiltration in TAA.

RESULTS

A total of 16 DEGs were identified. The enrichment and functional correlation analyses showed that DEGs were mainly associated with inflammatory response pathways and collagen-related diseases. Collagen type I alpha 1 chain ( COL1A1 ) and synaptotagmin like 2 ( SYTL2 ) were identified as diagnostic marker genes with a high diagnostic value for TAA. The expression of COL1A1 and SYTL2 was considerably higher in TAA vascular wall tissues than in the corresponding normal tissues, and there were significant differences in the infiltration of immune cells between TAA and normal vascular wall tissues. Additionally, COL1A1 and SYTL2 expression were associated with the infiltration of immune cells in the vascular wall tissue. Single-cell analysis showed that COL1A1 in TAA was mainly derived from fibroblasts and SYTL2 mainly from cluster of differentiation (CD)8 + T cells. In addition, single-cell analysis indicated that fibroblasts and CD8 + T cells in TAA were significantly higher than those in normal arterial wall tissue.

CONCLUSIONS

COL1A1 and SYTL2 may serve as diagnostic marker genes for TAA. The upregulation of SYTL2 and COL1A1 may be involved in the inflammatory infiltration of the vessel wall and poor extracellular matrix remodeling, promoting the progression of TAA.

ZNF263 cooperates with ZNF31 to promote the drug resistance and EMT of pancreatic cancer through transactivating RNF126

The poor prognosis of pancreatic ductal adenocarcinoma (PDAC) is attribute to the aggressive local invasion, distant metastasis and drug resistance of PDAC patients, which was strongly accelerated by epithelial-mesenchymal transition (EMT). In current study, we systematically investigate the role of ZNF263/RNF126 axis in the initiation of EMT in PDAC in vitro and vivo. ZNF263 is firstly identified as a novel transactivation factor of RNF126. Both ZNF263 and RNF126 were overexpressed in PDAC tissues, which were associated with multiple advanced clinical stages and poor prognosis of PDAC patients. ZNF263 overexpression promoted cell proliferation, drug resistance and EMT in vitro via activating RNF126 following by the upregulation of Cyclin D1, N-cad, and MMP9, and the downregulation of E-cad, p21, and p27. ZNF263 silencing contributed to the opposite phenotype. Mechanistically, ZNF263 transactivated RNF126 via binding to its promoter. Further investigations revealed that ZNF263 interacted with ZNF31 to coregulate the transcription of RNF126, which in turn promoted ubiquitination-mediated degradation of PTEN. The downregulation of PTEN activated AKT/Cyclin D1 and AKT/GSK-3β/β-catenin signaling, thereby promoting the malignant phenotype of PDAC. Finally, the coordination of ZNF263 and RNF126 promotes subcutaneous tumor size and distant liver metastasis in vivo. ZNF263, as an oncogene, promotes proliferation, drug resistance and EMT of PDAC through transactivating RNF126.

Transcription factor ZNF263 enhances EGFR-targeted therapeutic response and reduces residual disease in lung adenocarcinoma

EGF receptor (EGFR) tyrosine kinase inhibitors (TKIs) have achieved clinical success in lung adenocarcinoma (LUAD). However, tumors often show profound but transient initial response and then gain resistance. We identify transcription factor ZNF263 as being significantly decreased in osimertinib-resistant or drug-tolerant persister LUAD cells and clinical residual tumors. ZNF263 overexpression improves the initial response of cells and delays the formation of persister cells with osimertinib treatment. We further show that ZNF263 binds and recruits DNMT1 to the EGFR gene promoter, suppressing EGFR transcription with DNA hypermethylation. ZNF263 interacts with nuclear EGFR, impairing the EGFR-STAT5 interaction to enhance AURKA expression. Overexpressing ZNF263 also makes tumor cells with wild-type EGFR expression or refractory EGFR mutations more susceptible to EGFR inhibition. More importantly, lentivirus or adeno-associated virus (AAV)-mediated ZNF263 overexpression synergistically suppresses tumor growth and regrowth with osimertinib treatment in xenograft animal models. These findings suggest that enhancing ZNF263 may achieve complete response in LUAD with EGFR-targeted therapies.

A Deep Neural Network for Gastric Cancer Prognosis Prediction Based on Biological Information Pathways

Background

Gastric cancer (GC) is one of the deadliest cancers in the world, with a 5-year overall survival rate of lower than 20% for patients with advanced GC. Genomic information is now frequently employed for precision cancer treatment due to the rapid advancements of high-throughput sequencing technologies. As a result, integrating multiomics data to construct predictive models for the GC patient prognosis is critical for tailored medical care.

Results

In this study, we integrated multiomics data to design a biological pathway-based gastric cancer sparse deep neural network (GCS-Net) by modifying the P-NET model for long-term survival prediction of GC. The GCS-Net showed higher accuracy (accuracy = 0.844), area under the curve (AUC = 0.807), and F1 score (F1 = 0.913) than traditional machine learning models. Furthermore, the GCS-Net not only enables accurate patient survival prognosis but also provides model interpretability capabilities lacking in most traditional deep neural networks to describe the complex biological process of prognosis. The GCS-Net suggested the importance of genes (UBE2C, JAK2, RAD21, CEP250, NUP210, PTPN1, CDC27, NINL, NUP188, and PLK4) and biological pathways (Mitotic Anaphase, Resolution of Sister Chromatid Cohesion, and SUMO E3 ligases) to GC, which is consistent with the results revealed in biological- and medical-related studies of GC.

Conclusion

The GCS-Net is an interpretable deep neural network built using biological pathway information whose structure represents a nonlinear hierarchical representation of genes and biological pathways. It can not only accurately predict the prognosis of GC patients but also suggest the importance of genes and biological pathways. The GCS-Net opens up new avenues for biological research and could be adapted for other cancer prediction and discovery activities as well.

Overexpression of FOXC1 Promotes Tumor Metastasis by Activating the Wnt/β-Catenin Signaling Pathway in Gastric Cancer

BACKGROUND

Forkhead box protein C1 (FOXC1) is a transcription factor overexpressed in multiple cancers and is associated with poor prognosis. However, the function of FOXC1 in gastric cancer remains largely unknown.

AIM

This study aims to explore the role of FOXC1 in promoting gastric cancer metastasis.

METHODS

FOXC1 expression in gastric cancer patients was measured using real-time PCR and western blot. The association of FOXC1 with patient survival was assessed using public dataset. Gastric cancer cells with FOXC1 overexpression or knockdown were established. Cell metastatic ability was assessed by the expression of epithelial-mesenchymal transition (EMT)-related genes (E-cadherin, N-cadherin, vimentin) and matrix metalloproteinase-9 (MMP-9) as well as by migration and invasion assays. Chromatin immunoprecipitation was used to evaluate the interaction between FOXC1 and β-catenin. The in vivo effect of FOXC1 and β-catenin was assessed in metastatic animal models.

RESULTS

FOXC1 is overexpressed in gastric cancer and is associated with disease progression and poor patient survival. FOXC1 overexpression leads to the down-regulation of epithelial marker (E-cadherin) and the up-regulation of mesenchymal makers (N-cadherin, vimentin) and MMP-9, consistent with enhanced EMT. Moreover, cell migration and invasion are also activated, indicating increased metastatic ability. Notably, FOXC1 binds to the promoter region of β-catenin and transactivates β-catenin expression, which is responsible for the activation of EMT and metastasis in cells overexpressing FOXC1, while β-catenin knockdown can suppress the metastasis-induced by FOXC1.

CONCLUSIONS

FOXC1 promotes gastric cancer metastasis by activating Wnt/β-catenin signaling pathway, which may serve as a promising therapeutic target for gastric cancer treatment.

Prognostic Role of M6A-Associated Immune Genes and Cluster-Related Tumor Microenvironment Analysis: A Multi-Omics Practice in Stomach Adenocarcinoma

N6-methylandrostenedione (m6A) methylation plays a very important role in the development of malignant tumors. The immune system is the key point in the progression of tumors, particularly in terms of tumor treatment and drug resistance. Tumor immunotherapy has now become a hot spot and a new approach for tumor treatment. However, as far as the stomach adenocarcinoma (STAD) is concerned, the in-depth research is still a gap in the m6A-associated immune markers. The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases is extremely important for our research, where we obtained gene mutation, gene expression data and relevant clinical information of STAD patients. Firstly, the samples from GEO were used as external validation groups, while the TCGA samples were divided into a training group and an internal validation group randomly. Using the way of Single factor COX-LASSO- and multi-factor Cox to construct the prognostic model. Then, all samples were subjected to cluster analysis to generate high and low expression groups of immune gene. Meanwhile, we also collected the correlation between these types and tumor microenvironment. On this basis, a web version of the dynamic nomogram APP was developed. In addition, we performed microenvironmental correlation, copy number variation and mutation analyses for model genes. The prognostic model for STAD developed here demonstrated a very strong predictive ability. The results of cluster analysis manifested that the immune gene low expression group had lower survival rate and higher degree of immune infiltration. Therefore, the immune gene low expression group was associated with lower survival rates and a higher degree of immune infiltration. Gene set enrichment analysis suggested that the potential mechanism might be related to the activation of immunosuppressive functions and multiple signaling pathways. Correspondingly, the web version of the dynamic nomogram APP produced by the DynNom package has successfully achieved rapid and accurate calculation of patient survival rates. Finally, the multi-omics analysis of model genes further enriched the research content. Interference of RAB19 was confirmed to facilitate migration of STAD cells in vitro, while its overexpression inhibited these features. The prognostic model for STAD constructed in this study is accurate and efficient based on multi-omics analysis and experimental validation. Additionally, the results of the correlation analysis between the tumor microenvironment and m6Ascore are the basics of further exploration of the pathophysiological mechanism in STAD.

Low Level of PALMD Contributes to the Metastasis of Uveal Melanoma

Uveal melanoma (UM) is a highly aggressive disease. There is an urgent need to develop the metastasis prediction markers of UM. This study aims to detect the key role of PALMD in UM metastasis. Transcriptome sequencing results of 2 sets of UM metastatic samples (GSE22138 and GSE156877) were downloaded from the Gene Expression Omnibus (GEO), and 18 overlapping differentially expressed genes were screened out, including PALMD. PALMD was significantly underexpressed in metastatic UM tissue. Low expression of PALMD was associated with poor prognosis in UM patients. The decreased expression of PALMD promoted the invasion and migration of 92-1 and Mel270 cells, while the high expression of PALMD inhibited the invasion and migration of UM cells. Furthermore, the levels of matrix metallopeptidase (MMP) 2 and MMP9 increased after transfection of siRNAs specifically targeting PALMD, whereas the levels of MMP2 and MMP9 were decreased after PALMD overexpression. However, PALMD did not affect the proliferation of UM cells. In addition, ZNF263 promoted the transcription of PALMD through the putative binding sequence using the JASPAR database, luciferase reporter gene analysis and chromatin immunoprecipitation assay. In summary, the expression of PALMD regulated by ZNF263 plays an important role in UM metastasis.

ARID3A promotes the chemosensitivity of colon cancer by inhibiting AKR1C3

ARID3A is upregulated in colorectal cancer and can promote the proliferation and metastasis of cancer cells. However, patients with higher level of ARID3A have a better prognosis. This study aimed to uncover the mechanism by which ARID3A benefits the prognosis of colon cancer. Our results indicated that ARID3A upregulation enhanced the chemosensitivity of colon cancer cells to 5-Fluorouracil (5-FU), whereas ARID3A downregulation inhibited the chemosensitivity of colon cancer cells to 5-FU. Through database analysis, we found that AKR1C3, a drug resistance related gene, was the target of ARID3A. Moreover, AKR1C3 was downregulated in colon cancer tissues compared to normal tissues. Next, we assessed the interaction between AKR1C3 and ARID3A, and found that ARID3A inhibited the transcription of AKR1C3, leading to the downregulation of AKR1C3 in colon cancer cells. We also verified that AKR1C3 inhibited the chemosensitivity of colon cancer cells to 5-FU. Moreover, patients with higher ratio of ARID3A to AKR1C3 had a better prognosis. This study suggested that ARID3A promoted chemosensitivity of colon cancer cells by inhibiting AKR1C3 in colon cancer. The ratio of ARID3A to AKR1C3 is a good marker to predict the prognosis of colon cancer patients. This article is protected by copyright. All rights reserved.

Identification of Crucial Genes and Diagnostic Value Analysis in Major Depressive Disorder Using Bioinformatics Analysis

AIM AND OBJECTIVE

Despite the prevalence and burden of major depressive disorder (MDD), our current understanding of the pathophysiology is still incomplete. Therefore, this paper aims to explore genes and evaluate their diagnostic ability in the pathogenesis of MDD.

METHODS

Firstly, the expression profiles of mRNA and microRNA were downloaded from the gene expression database and analyzed by the GEO2R online tool to identify differentially expressed genes (DEGs) and differentially expressed microRNAs (DEMs). Then, the DAVID tool was used for functional enrichment analysis. Secondly, the comprehensive protein- protein interaction (PPI) network was analyzed using Cytoscape, and the network MCODE was applied to explore hub genes. Thirdly, the receiver operating characteristic (ROC) curve of the core gene was drawn to evaluate clinical diagnostic ability. Finally, mirecords was used to predict the target genes of DEMs.

RESULTS

A total of 154 genes were identified as DEGs, and 14 microRNAs were identified as DEMs. Pathway enrichment analysis showed that DEGs were mainly involved in hematopoietic cell lineage, PI3K-Akt signaling pathway, cytokinecytokine receptor interaction, chemokine signaling pathway, and JAK-STAT signaling pathway. Three important modules are identified and selected by the MCODE clustering algorithm. The top 12 hub genes including CXCL16, CXCL1, GNB5, GNB4, OPRL1, SSTR2, IL7R, MYB, CSF1R, GSTM1, GSTM2, and GSTP1 were identified as important genes for subsequent analysis. Among these important hub genes, GSTM2, GNB4, GSTP1 and CXCL1 have good diagnostic ability. Finally, by combining these four genes, the diagnostic ability of MDD can be improved to 0.905, which is of great significance for the clinical diagnosis of MDD.

CONCLUSION

Our results indicate that GSTM2, GNB4, GSTP1 and CXCL1 have potential diagnostic markers and are of great significance in clinical research and diagnostic application of MDD. This result needs a large sample study to further confirm the pathogenesis of MDD.

FOXD1-AS1 regulates FOXD1 translation and promotes gastric cancer progression and chemoresistance by activating the PI3K/AKT/mTOR pathway

Gastric cancer (GC) is a common gastrointestinal cancer with a high global mortality. Recent reports have suggested that long noncoding RNA (lncRNA) are implicated in multiple aspects of GC, including pathogenesis, progression, and therapeutic response. Herein, we investigated the function of FOXD1-AS1 in GC progression and chemoresistance. Expression of FOXD1-AS1 was low in normal stomach tissues but was upregulated in GC cell lines. Silencing of FOXD1-AS1 impaired GC cell proliferation and motility in vitro, and repressed tumor growth and metastasis in vivo. Importantly, FOXD1-AS1 upregulation increased the resistance of GC cells to cisplatin. Moreover, we found that FOXD1-AS1 promoted FOXD1 protein translation through the eIF4G-eIF4E-eIF4A translational complex. We also demonstrated that FOXD1-AS1 released eIF4E from phosphorylated 4E-BP1 and thereby strengthened the interaction of eIF4E with eIF4G by activating the PI3K/AKT/mTOR pathway. Activation of the PI3K/AKT/mTOR pathway was due to the post-transcriptional upregulation of PIK3CA, in turn induced by FOXD1-AS1-mediated sequestering of microRNA (miR)-466. Furthermore, we verified that FOXD1-AS1 facilitated GC progression and cisplatin resistance in a FOXD1-dependent manner. In conclusion, FOXD1-AS1 aggravates GC progression and chemoresistance by promoting FOXD1 translation via PIK3CA/PI3K/AKT/mTOR signaling. These findings highlight a novel target for treatment of patients GC, particularly patients with cisplatin resistance.

A zinc finger family protein, ZNF263, promotes hepatocellular carcinoma resistance to apoptosis via activation of ER stress-dependent autophagy

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer death worldwide. Endoplasmic reticulum stress (ERS) is generally activated in HCC and is important for the sensitivity of HCC to anticancer drugs. ERS-dependent autophagy is a crucial mechanism affecting the sensitivity of HCC to anticancer drugs, but the mechanism by which ERS regulates autophagy is not well understood. Zinc finger protein 263 (ZNF263) is a transcription factor member of the zinc finger family. However, its functional role in HCC remains to be studied. In the current study, we investigated the role of ZNF263 in regulating ERS-induced chemoresistance in HCC and its possible mechanism. We found that ZNF263 was the most significant ERS-specific super-enhancer bounding transcriptional factor and was up-regulated in HCC patients and cell lines. Further, ZNF263 expression correlated with ERS, clinical stage and shorter survival in HCC patients. ZNF263 knockdown by RNA interference results in decreased proliferation, apoptosis resistance, and chemoresistance. Further study showed that ZNF263 increased chemoresistance by activating ERS-related autophagy. In conclusion, our study highlights ZNF263 as a functional ERS-related tumor activator and indicates it as a potential target for HCC therapy.

ZNF263 is a transcriptional regulator of heparin and heparan sulfate biosynthesis

Heparin is the most widely prescribed biopharmaceutical in production globally. Its potent anticoagulant activity and safety makes it the drug of choice for preventing deep vein thrombosis and pulmonary embolism. In 2008, adulterated material was introduced into the heparin supply chain, resulting in several hundred deaths and demonstrating the need for alternate sources of heparin. Heparin is a fractionated form of heparan sulfate derived from animal sources, predominantly from connective tissue mast cells in pig mucosa. While the enzymes involved in heparin biosynthesis are identical to those for heparan sulfate, the factors regulating these enzymes are not understood. Examination of the promoter regions of all genes involved in heparin/heparan sulfate assembly uncovered a transcription factor-binding motif for ZNF263, a C2H2 zinc finger protein. CRISPR-mediated targeting and siRNA knockdown of ZNF263 in mammalian cell lines and human primary cells led to dramatically increased expression levels of HS3ST1, a key enzyme involved in imparting anticoagulant activity to heparin, and HS3ST3A1, another glucosaminyl 3-O-sulfotransferase expressed in cells. Enhanced 3-O-sulfation increased binding to antithrombin, which enhanced Factor Xa inhibition, and binding of neuropilin-1. Analysis of transcriptomics data showed distinctively low expression of ZNF263 in mast cells compared with other (non-heparin-producing) immune cells. These findings demonstrate a novel regulatory factor in heparan sulfate modification that could further advance the possibility of bioengineering anticoagulant heparin in cultured cells.

High Expression of TTYH3 is Related to Poor Clinical Outcomes in Human Gastric Cancer

Ion channels play important roles in regulating various cellular processes and malignant transformation. Expressions of some chloride channels have been suggested to be associated with patient survival in gastric cancer (GC). However, little is known about the expression and function of TTYH3, a gene encoding a chloride ion channel, in cancer progression. Here, we comprehensively analyzed the expression of TTYH3 and its clinical outcome in GC using publicly available cancer gene expression and patient survival data through various databases. We examined the differences of TTYH3 expression between cancers and their normal tissues using the Oncomine, UALCAN, and GEO (Gene Expression Omnibus) databases. TTYH3 expression was investigated from immunohistochemistry images using the Human Protein Atlas database. Copy number alterations and mutations of TTYH3 were analyzed using cBioPortal. The co-expression profile of TTYH3 in GC was revealed using Oncomine. The gene ontology and pathway analyses were done using those co-expressed genes via the Enrichr tool to explore the predicted signaling pathways in GC. TTYH3 mRNA and protein levels in GC were significantly greater than those in normal tissue. Kaplan–Meier analysis revealed the upregulation of TTYH3 expression, which was significantly correlated with worse patient survival. Collectively, our data suggest that TTYH3 might be a potential prognostic marker for GC patients.

Regulation of GKN1 expression in gastric carcinogenesis: A problem to resolve (Review)

Gastrokine 1 (GKN1) is a protein expressed on the surface mucosa cells of the gastric antrum and fundus, which contributes to maintaining gastric homeostasis, inhibits inflammation and is a tumor suppressor. The expression of GKN1 decreases in mucosa that are either inflamed or infected by Helicobacter pylori, and is absent in gastric cancer. The measurement of circulating GKN1 concentration, the protein itself, or the mRNA in gastric tissue may be of use for the early diagnosis of cancer. The mechanisms that modulate the deregulation or silencing of GKN1 expression have not been completely described. The modification of histones, methylation of the GKN1 promoter, or proteasomal degradation of the protein have been detected in some patients; however, these mechanisms do not completely explain the absence of GKN1 or the reduction in GKN1 levels. Only NKX6.3 transcription factor has been shown to be a positive modulator of GKN1 transcription, although others also have an affinity with sequences in the promoter of this gene. While microRNAs (miRNAs) are able to directly or indirectly regulate the expression of genes at the post‑transcriptional level, the involvement of miRNAs in the regulation of GKN1 has not been reported. The present review analyzes the information reported on the determination of GKN1 expression and the regulation of its expression at the transcriptional, post‑transcriptional and post‑translational levels; it proposes an integrated model that incorporates the regulation of GKN1 expression via transcription factors and miRNAs in H. pylori infection.

The multisystemic functions of FOXD1 in development and disease

Transcription factors (TFs) participate in a wide range of cellular processes due to their inherent function as essential regulatory proteins. Their dysfunction has been linked to numerous human diseases. The forkhead box (FOX) family of TFs belongs to the "winged helix" superfamily, consisting of proteins sharing a related winged helix-turn-helix DNA-binding motif. FOX genes have been extensively present during vertebrates and invertebrates' evolution, participating in numerous molecular cascades and biological functions, such as embryonic development and organogenesis, cell cycle regulation, metabolism control, stem cell niche maintenance, signal transduction, and many others. FOXD1, a forkhead TF, has been related to different key biological processes such as kidney and retina development and embryo implantation. FOXD1 dysfunction has been linked to different pathologies, thereby constituting a diagnostic biomarker and a promising target for future therapies. This paper aims to present, for the first time, a comprehensive review of FOXD1's role in mouse development and human disease. Molecular, structural, and functional aspects of FOXD1 are presented in light of physiological and pathogenic conditions, including its role in human disease aetiology, such as cancer and recurrent pregnancy loss. Taken together, the information given here should enable a better understanding of FOXD1 function for basic science researchers and clinicians.