Identification of novel hub genes associated with gastric cancer using integrated bioinformatics analysis

CD44 and RHAMM Are Microenvironmental Sensors with Dual Metastasis Promoter and Suppressor Functions

The progression of primary tumors to metastases remains a significant roadblock to the treatment of most cancers. Emerging evidence has identified genes that specifically affect metastasis and are potential therapeutic targets for managing tumor progression. However, these genes can have dual tumor promoter and suppressor functions that are contextual in manifestation, and that complicate their development as targeted therapies. CD44 and RHAMM/HMMR are examples of multifunctional proteins that can either promote or suppress metastases, as demonstrated in experimental models. These two proteins can be viewed as microenvironmental sensors and this minireview addresses the known mechanistic underpinnings that may determine their metastasis suppressor versus promoter functions. Leveraging this mechanistic knowledge for CD44, RHAMM, and other multifunctional proteins is predicted to improve the precision of therapeutic targeting to achieve more effective management of metastasis.

Therapeutic effect of microRNA-21 on differentially expressed hub genes in gastric cancer based on systems biology

Gastric cancer (GC) is a leading cause of mortality for many people. Cancer's initiating factors are poorly understood. miR-21 has a crucial function in several malignancies, particularly GC. Furthermore, it has been shown that miR-21 is critical for the emergence and advancement of GC. This work intends to identify new genes which expression is associated with the activity of mir-21 in GC and to investigate the effect of downregulation of mir-21 on these genes and gastric tumorigenesis. We utilized the gene expression profiles of GCs from an Array database (GSE13911) from the Gene Expression Omnibus (GEO) dataset to find differentially expressed genes (DEGs) between control and gastric cancer groups. Using weighted gene correlation network analysis (WGCNA) in R, the Gene co-expression network was reconstructed. The microRNA-mRNA network was then reconstructed using the miRWalk database, and by investigating the microRNA-mRNA network, the genes that have an association with mir-21 were found. To implement the functional investigation, MKN and AGS cell lines were transfected with anti-miR-21 next. Subsequently, MTT proliferation was utilized to assess the cell's vitality. qRT-PCR was then used to evaluate the anticipated levels of gene expression in both GC cell lines. This study discovered and predicted CCL28, NR3C2, and SNYPO2 as the targets of miR-21 (GC), which are downregulated through gastric tumorigenesis, showing great potential as therapeutic and diagnostic targets. The suppression of miR-21 in gastric GC cells led to the inhibition of cell proliferation and decreased expression of CCL28, NR3C2, and SNYPO2 genes. This study established that miR-21, via downregulating these genes, contributes significantly to the development of GC. In addition, systems biology techniques identified CCL28, NR3C2, and SNYPO2 genes as possible GC surveillance and therapy components.

Identification of differentially expressed genes associated with the pathogenesis of gastric cancer by bioinformatics analysis

AIM

Gastric cancer (GC) is one of the most diagnosed cancers worldwide. GC is a heterogeneous disease whose pathogenesis has not been entirely understood. Besides, the GC prognosis for patients remains poor. Hence, finding reliable biomarkers and therapeutic targets for GC patients is urgently needed.

METHODS

GSE54129 and GSE26942 datasets were downloaded from Gene Expression Omnibus (GEO) database to detect differentially expressed genes (DEGs). Then, gene set enrichment analyses and protein-protein interactions were investigated. Afterward, ten hub genes were identified from the constructed network of DEGs. Then, the expression of hub genes in GC was validated. Performing survival analysis, the prognostic value of each hub gene in GC samples was investigated. Finally, the databases were used to predict microRNAs that could regulate the hub genes. Eventually, top miRNAs with more interactions with the list of hub genes were introduced.

RESULTS

In total, 203 overlapping DEGs were identified between both datasets. The main enriched KEGG pathway was "Protein digestion and absorption." The most significant identified GO terms included "primary alcohol metabolic process," "basal part of cell," and "extracellular matrix structural constituent conferring tensile strength." Identified hub modules were COL1A1, COL1A2, TIMP1, SPP1, COL5A2, THBS2, COL4A1, MUC6, CXCL8, and BGN. The overexpression of seven hub genes was associated with overall survival. Moreover, among the list of selected miRNAs, hsa-miR-27a-3, hsa-miR-941, hsa-miR-129-2-3p, and hsa-miR-1-3p, were introduced as top miRNAs targeting more than five hub genes.

CONCLUSIONS

The present study identified ten genes associated with GC, which may help discover novel prognostic and diagnostic biomarkers as well as therapeutic targets for GC. Our results may advance the understanding of GC occurrence and progression.

System biology analysis to develop diagnostic biomarkers, monitoring pathological indexes, and novel therapeutic approaches for immune targeting based on maggot bioactive compounds and polyphenolic cocktails in mice with gastric cancer

Early diagnosis and prognosis are prerequisites for mitigating mortality in gastric cancer (GaCa). Identifying some causative or sensitive elements (coding RNA (cRNA)-non-cRNAs (ncRNAs)) can be very helpful in the early diagnosis of GaCa. Notably, despite significant development in the GaCa treatment, the outcome of patients does not remain satisfactory due to limitations such as multi-drug resistance and tumor relapse. Therefore, more attention has been drawn to complementary therapies and the use of supplements. In this regard, Polyphenol natural compounds (PNC) and maggot larvae (MaLa) alone or in combination were administered along with chemotherapy (paclitaxel) to N-methyl-N-nitrosourea (MNU)- induced murine tumor model. In addition, in order to identify potential diagnostic or prognostic biomarkers, transcriptomics analysis was performed through a bioinformatics approach. Then transcription profile of ncRNAs with their target hub genes was assessed through qPCR Real-Time, Western blot, and ELISA. According to the bioinformatics results, 17 hub genes (e.g., IL-6, CXCL8, MKI67, IL-2, IL-4, IL-10, IL-1β, SPP1, LOX, COL1A1, and IFN-γ) were explored that contribute towards inflammation and oxidative stress and ultimately GaCa development. Upstream of the mentioned hub genes, regulatory factors (lncRNA XIST and NEAT1) were also identified and introduced as prognosis and diagnosis biomarkers for GaCa. Our results showed that PNC alone and in combination with MaLa was able to reduce the size and number of tumors, which is related to the reduction of genes expression levels (including IL-6, CXCL8, MKI67, IL-2, IL-4, IL-10, IL-1β, SPP1, LOX, COL1A1, IFN-γ, NEAT1, and XIST). In conclusion, PNC and MaLa have the potential to be considered as complementary and improving chemotherapy due to their effective compounds. Also, the introduced hub gene and lncRNA in addition to diagnostic and prognostic biomarkers can be used as druggable proteins for novel therapeutic targeting of GaCa.

Roles of DSCC1 and GINS1 in gastric cancer

Gastric carcinoma is a common malignant tumor originating from gastric mucosal epithelium. However, role of DS-cell cycle-dependent protein 1 (DSCC1) and GINS1 in gastric carcinoma remains unclear. The gastric carcinoma datasets GSE79973 and GSE118916 were downloaded from gene expression omnibus. Multiple datasets were merged and batched. Differentially expressed genes (DEGs) were screened and weighted gene co-expression network analysis was performed. Functional enrichment analysis, gene set enrichment analysis and immune infiltration analysis were performed. Construction and analysis of protein-protein interaction Network. Survival analysis and comparative toxicogenomics database were performed. A heat map of gene expression was drawn. Target Scan screen miRNAs regulating DEGs. Two thousand forty-four DEGs were identified. According to gene ontology analysis, in biological process, they were mainly enriched in cell migration, transforming growth factor β receptor signaling pathway, angiogenesis, and steroid metabolism process. In cellular component, they were mainly enriched in extracellular vesicles, basement membrane, endoplasmic reticulum lumen, and extracellular space. In molecular function, they focused on extracellular matrix structural components, protein binding, platelet-derived growth factor binding, and catalytic activity. In Kyoto encyclopedia of genes and genomes, they were mainly enriched in protein digestion and absorption, metabolic pathways, fatty acid degradation, Glycerophospholipid metabolism, ether lipid metabolism. Gene set enrichment analysis showed that DEGs were mainly enriched in transforming growth factor β receptor signaling pathway, steroid metabolism process, basement membrane, endoplasmic reticulum lumen, structural components of extracellular matrix, platelet-derived growth factor binding, Glycerophospholipid metabolism, ether lipid metabolism. The results of immune infiltration analysis showed that expression of T cell CD4 memory resting was lower in the samples of gastric cancer. The core genes (TRIP13, CHEK1, DSCC1, GINS1) are protective factors, their expression shows a downward trend with increase of risk score. Comparative toxicogenomics database analysis showed that TRIP13, CHEK1, DSCC1, GINS1 were related to gastric tumors, gastric diseases, tumors, inflammation, and necrosis. DSCC1 and GINS1 are highly expressed in gastric cancer. Higher expression levels of DSCC1 and GINS1, worse the prognosis.

Decoding SEC24 Homolog D, COPII coat complex component accuracy as a signature gene in three human cancers

Although an increasing body of evidence supports the crucial role of the SEC24 Homolog D, COPII Coat Complex Component (SEC24D) gene in the initiation and progression of cancer, a comprehensive pan-cancer analysis of this gene is still lacking. In this study, we conducted an extensive investigation of SEC24D, aiming to elucidate its potential role and underlying mechanisms across multiple human tumors. Our analysis relied on data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. To validate our findings, we employed RNA sequencing (RNA-seq), targeted bisulfite sequencing (bisulfite-seq) molecular techniques. Our findings revealed elevated mRNA (Messenger RNA) and protein levels of SEC24D in different tumor tissues. However, the up-regulation of SEC24D was significantly correlated with shorter overall survival (OS), metastasis, and various clinical parameters in esophageal cancer (ESCA), lung adenocarcinoma (LUAD), and kidney renal papillary cell carcinoma (KIRP). Expression validation analysis via RNA-seq and targeted bisulfite-seq analyses, further confirmed the higher expression of SEC24D in LUAD cancer cell lines as compared to normal controls. The DNA methylation level of SEC24D was found to be decreased in ESCA, LUAD, and KIRP samples. DNA methylation analysis via bisulfite-seq analysis also validate the lower promoter methylation level of SE24D in LUAD cell lines relative to controls. Moreover, we observed a significant association between the elevated expression of SEC24D and the levels of infiltrating cells, such as B cells, neutrophils, macrophages, CD8+ T cells, and CD4+ T cells. Analysis of SEC24-related genes revealed that "Protein processing in endoplasmic reticulum, SNARE interaction in vesicular transport, Legionellosis, Pathogenic Escherichia coli infection" were mainly involved in the functional mechanism of SEC24D in ESCA, LUAD, and KIRP. Moreover, we also suggested a few valuable drugs (Acetaminophen, Acteoside, Cyclosporine, Polydatin, Estradiol, Estradiol, Quercetin) for treating ESCA, LUAD, and KIRP patients with respect to overexpressed SEC24D. To summarize, this comprehensive pan-cancer study investigated the association between SEC24D expression and clinical parameters in ESCA, LUAD, KIRP. The study provides valuable insights for further exploring the functional and therapeutic aspects of SEC24D and underscores its predictive significance in the carcinogenesis and prognosis of these specific cancer types.

A prognostic gene signature for gastric cancer and the immune infiltration-associated mechanism underlying the signature gene, PLG

BACKGROUND

Globally, gastric cancer (GC) is a common and lethal solid malignant tumor. Identifying the molecular signature and its functions can provide mechanistic insights into GC development and new methods for targeted therapy.

METHODS

Differentially expressed genes (DEGs) and prognostic genes (from univariate Cox regression analysis) were overlapped to obtain prognostic DEGs. Subsequently, molecular modules and the functions of these prognostic DEGs were identified by Metascape and Gene Ontology (GO)/Kyoto Encyclopedia of Genes and Genomes (KEGG)/Gene Set Enrichment Analysis (GSEA) enrichment analyses, respectively. Protein-protein interaction (PPI) networks of up- and down-regulated prognostic DEGs in GC were analyzed using the MCC algorithm of the Cytohubba plug-in in Cytoscape. The prognostic gene signature was defined on hub genes of the PPI networks by least absolute shrinkage and selection operator (LASSO)-Cox regression analysis. Furthermore, the expressional level of PLG in our clinical GC samples was validated by quantitative PCR (qPCR), western blotting, and immunohistochemistry (IHC). Subsequently, the PLG expression-correlation analysis was performed to assess the role of PLG in GC progression. Immune infiltration analysis was performed by single-sample gene set enrichment analysis (ssGSEA) to assess the inhibitory effect of PLG on immune infiltration.

RESULTS

Firstly, Up- and down-regulated prognostic DEGs and hub genes in protein-protein interaction (PPI) networks in GC were identified. A prognostic five-gene signature (i.e., PLG, SPARC, FGB, SERPINE1, and KLHL41) was identified. Among the five genes, the relationship between plasminogen (PLG) and GC remains largely unclear. Moreover, the functions of PLG-correlated genes in GC, like 'fibrinolysis', 'hemostasis', 'ion channel complex', and 'transporter complex' were identified. In addition, PLG expression correlated negatively with the infiltration of almost all immune cell types. Interestingly, the expression of PLG was significantly and highly correlated with that of CD160, an immune checkpoint inhibitor.

CONCLUSION

Our findings defined a new five-gene signature for predicting GC prognosis, but more validation is required to assess the effects and mechanism of the five genes, especially PLG, for the development of new GC therapies.

The positive feedback loop of MAD2L1/TYK2/STAT3 induces progression in B-cell acute lymphoblastic leukaemia

PURPOSE

Mitotic arrest deficient 2 like 1 (MAD2L1) has been extensively studied in several malignancies; however, its role in B-cell acute lymphoblastic leukaemia (B-ALL) remains unclear.

METHODS

The expression of MAD2L1 was evaluated by real-time quantitative polymerase chain reaction. The biological functions of MAD2L1 in B-ALL were explored through Cell Counting Kit-8 (CCK-8), 5-Ethynyl-2'-deoxyuridine assay (EDU), transwell assay, flow cytometry and xenograft models. The Western blotting and co-immunoprecipitation were utilized to evaluate the interplay between MAD2L1 and the TYK2/STAT3 pathway. The luciferase reporter and chromatin immunoprecipitation (ChIP) assay were employed to identify interactions between STAT3 and MAD2L1.

RESULTS

We demonstrated that MAD2L1 was markedly upregulated in B-ALL, and its expression level not only correlated with the relapse and remission of the condition but also with a poor prognosis. MAD2L1 promoted the proliferation, migration and invasion of B-ALL cells in vitro and in vivo, whereas MAD2L1 knockdown had the opposite effects. Mechanistically, MAD2L1 induces the progression of B-ALL by activating the TYK2/STAT3 signaling pathway to phosphorylate. Interestingly, STAT3 induces the expression of MAD2L1 by binding directly to its promoter region, resulting in a positive-feedback loop of MAD2L1/TYK2/STAT3.

CONCLUSION

This study uncovered a reciprocal loop of MAD2L1/TYK2/STAT3, which contributed to the development of B-ALL. Therefore, MAD2L1 can be considered a potential diagnostic biomarker as well as a novel therapeutic target for B-ALL.

Specific Blood RNA Profiles in Individuals with Acute Spinal Cord Injury as Compared with Trauma Controls

Background

Spinal cord injury (SCI) is known to cause a more robust systemic inflammatory response than general trauma without CNS injury, inducing severe secondary organ damage, especially the lung and liver. Related studies are principally focused on the mechanisms underlying repair and regeneration in the injured spinal cord tissue. However, the specific mechanism of secondary injury after acute SCI is widely overlooked, compared with general trauma.

Methods

Two datasets of GSE151371 and GSE45376 related to the blood samples and spinal cord after acute SCI were selected to identify the differentially expressed genes (DEGs). In GSE151371, functional enrichment analysis on specific DEGs of blood samples was performed. And the top 15 specific hub genes were identified from intersectional genes between the specific upregulated DEGs of blood samples in GSE151371 and the upregulated DEGs of the spinal cord in GSE45376. The specific functional enrichment analysis and the drug candidates of the hub genes and the miRNAs-targeted hub genes were also analyzed and predicted.

Results

DEGs were identified, and a total of 64 specific genes were the intersection of upregulated genes of the spinal cord in GSE45376 and upregulated genes of human blood samples in GSE151371. The top 15 hub genes including HP, LCN2, DLGAP5, CEP55, HMMR, CDKN3, PRTN3, SKA3, MPO, LTF, CDC25C, MMP9, NEIL3, NUSAP1, and CD163 were calculated from the 64 specific genes. Functional enrichment analysis of the top 15 hub genes revealed inflammation-related pathways. The predicted miRNAs-targeted hub genes and drug candidates of hub genes were also performed to put forward reasonable treatment strategies.

Conclusion

The specific hub genes of acute SCI as compared with trauma without CNS injury were identified. The functional enrichment analysis of hub genes showed a specific immune response. Several predicted drugs of hub genes were also obtained. The hub genes and the predicted miRNAs may be potential biomarkers and therapeutic targets and require further validation.

Multi-Transcriptomic Analysis Reveals the Heterogeneity and Tumor-Promoting Role of SPP1/CD44-Mediated Intratumoral Crosstalk in Gastric Cancer

GC is a fatal disease with high heterogeneity and invasiveness. Recently, SPP1 has been reported to be involved in the tumor progression of multiple human cancers; however, the role of SPP1 in GC heterogeneity and whether it is associated with the invasiveness and mortality of GC remain unclear. Here, we combined multiple RNA sequencing approaches to evaluate the impact of SPP1 on GC. Through bulk RNA sequencing (bulk RNA-seq) and immunohistochemistry (IHC), we found that SPP1 was highly expressed in GC, and high levels of SPP1 were associated with macrophage infiltration, an advanced tumor stage, and higher mortality for advanced GC patients. Furthermore, through simultaneous single-cell and spatial analysis, we demonstrated that SPP1⁺ macrophages are tumor-specific macrophages unique to cancer and enriched in the deep layer of GC tissue. Cell-cell communication analysis revealed that SPP1/CD44 interactions between SPP1⁺ macrophages and their localized tumor epithelial cells could activate downstream target genes in epithelial cells to promote dynamic changes in intratumor heterogeneity. Moreover, these activated genes were found to be closely associated with poor clinical GC outcomes and with cancer-related pathways that promote GC progression, as shown by survival analysis and enrichment analysis, respectively. Collectively, our study reveals that tumor-specific SPP1⁺ macrophages drive the architecture of intratumor heterogeneity to evolve with tumor progression and that SPP1 may serve as a prognostic marker for advanced GC patients, as well as a potential therapeutic target for GC.

Identification of Novel Hub Genes Associated with Psoriasis Using Integrated Bioinformatics Analysis

Psoriasis is a chronic, prolonged, and recurrent inflammatory skin disease and the current therapeutics can only alleviate the symptoms rather than cure it completely. Therefore, we aimed to identify the molecular signatures and specific biomarkers of psoriasis to provide novel clues for psoriasis and targeted therapy. In the present study, the Gene Expression Omnibus (GEO) database was used to retrieve three microarray datasets (GSE166388, GSE50790 and GSE42632) and to explore the differentially expressed genes (DEGs) in psoriasis using the Affy package in R software. The gene ontology (GO) and Kyoto Encyclopedia of Gene and Genome (KEGG) pathway enrichment were utilized to determine the common DEGs and their capabilities. The STRING database was used to develop DEG-encoded proteins and a protein-protein interaction network (PPI) and the Cytohubba plugin to classify hub genes. Using the NetworkAnalyst platform, we detected transcription factors (TFs), microRNAs and drug candidates interacting with hub genes. In addition, the expression levels of hub genes in HaCaT cells were detected by western blot. We screened the up- and downregulated DEGs from the transcriptome microarrays of corresponding psoriasis patients. Functional enrichment of DEGs in psoriasis was mainly associated with positive regulation of leukocyte cell-cell adhesion and T cell activation, cytokine binding, cytokine activity and the Wnt signaling pathway. Through further data processing, we obtained 57 intersecting genes in the three datasets and probed them in STRING to determine the interaction of their expressed proteins and we obtained the critical 10 hub genes in the Cytohubba plugin, including TOP2A, CDKN3, MCM10, PBK, HMMR, CEP55, ASPM, KIAA0101, ESC02, and IL-1β. Using these hub genes as targets, we obtained 35 TFs and 213 miRNAs that may regulate these genes and 33 potential therapeutic agents for psoriasis. Furthermore, the expression levels of TOP2A, MCM10, PBK, ASPM, KIAA0101 and IL-1β were observably increased in HaCaT cells. In conclusion, we identified potential biomarkers, risk factors and drugs for psoriasis.

Enhanced ZNF521 expression induces an aggressive phenotype in human ovarian carcinoma cell lines

Epithelial ovarian carcinoma (EOC) is the most lethal gynecological tumor, that almost inevitably relapses and develops chemo-resistance. A better understanding of molecular events underlying the biological behavior of this tumor, as well as identification of new biomarkers and therapeutic targets are the prerequisite to improve its clinical management. ZNF521 gene amplifications are present in >6% of OCs and its overexpression is associated with poor prognosis, suggesting that it may play an important role in OC. Increased ZNF521 expression resulted in an enhancement of OC HeyA8 and ES-2 cell growth and motility. Analysis of RNA isolated from transduced cells by RNA-Seq and qRT-PCR revealed that several genes involved in growth, proliferation, migration and tumor invasiveness are differentially expressed following increased ZNF521 expression. The data illustrate a novel biological role of ZNF521 in OC that, thanks to the early and easy detection by RNA-Seq, can be used as biomarker for identification and treatment of OC patients.

Identification and Verification of Potential Biomarkers in Gastric Cancer By Integrated Bioinformatic Analysis

Background: Gastric cancer (GC) is a common cancer with high mortality. This study aimed to identify its differentially expressed genes (DEGs) using bioinformatics methods.

Methods: DEGs were screened from four GEO (Gene Expression Omnibus) gene expression profiles. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed. A protein–protein interaction (PPI) network was constructed. Expression and prognosis were assessed. Meta-analysis was conducted to further validate prognosis. The receiver operating characteristic curve (ROC) was analyzed to identify diagnostic markers, and a nomogram was developed. Exploration of drugs and immune cell infiltration analysis were conducted.

Results: Nine up-regulated and three down-regulated hub genes were identified, with close relations to gastric functions, extracellular activities, and structures. Overexpressed Collagen Type VIII Alpha 1 Chain (COL8A1), Collagen Type X Alpha 1 Chain (COL10A1), Collagen Triple Helix Repeat Containing 1 (CTHRC1), and Fibroblast Activation Protein (FAP) correlated with poor prognosis. The area under the curve (AUC) of ADAM Metallopeptidase With Thrombospondin Type 1 Motif 2 (ADAMTS2), COL10A1, Collagen Type XI Alpha 1 Chain (COL11A1), and CTHRC1 was >0.9. A nomogram model based on CTHRC1 was developed. Infiltration of macrophages, neutrophils, and dendritic cells positively correlated with COL8A1, COL10A1, CTHRC1, and FAP. Meta-analysis confirmed poor prognosis of overexpressed CTHRC1.

Conclusion: ADAMTS2, COL10A1, COL11A1, and CTHRC1 have diagnostic values in GC. COL8A1, COL10A1, CTHRC1, and FAP correlated with worse prognosis, showing prognostic and therapeutic values. The immune cell infiltration needs further investigations.

The Predictive Competing Endogenous RNA Regulatory Networks and Potential Prognostic and Immunological Roles of Cyclin A2 in Pan-Cancer Analysis

Although accumulating evidence has verified the relationship between CCNA2 and cancers, no pan-cancer analysis about the function and the upstream molecular mechanism of CCNA2 is available. For the first time, we analyzed potential oncogenic roles of CCNA2 in 33 cancer types via The Cancer Genome Atlas (TCGA) database. Overexpression of CCNA2 is widespread in almost all cancer types, and it is related to poor prognosis and advanced pathological stages in most cases. Moreover, we conducted upstream miRNAs and lncRNAs of CCNA2 to establish upstream regulatory networks in kidney renal clear cell carcinoma (LINC00997/miR-27b-3p/CCNA2), liver hepatocellular carcinoma (SNHG16, GUSBP11, FGD5-AS1, LINC00630, CD27-AS1, LINC00997/miR-22-3p/CCNA2, miR-29b-3p/CCNA2, miR-29c-3p/CCNA2, and miR-204-5p/CCNA2), and lung adenocarcinoma (miRNA-218-5p/CCNA2 and miR-204-5p/CCNA2) by expression analysis, survival analysis, and correlation analysis. The CCNA2 expression is positively correlated with Th2 cell infiltration and negatively correlated with CD4+ central memory and effector memory T-cell infiltration in different cancer types. Furthermore, CCNA2 is positively associated with expressions of immune checkpoints (CD274, CTLA4, HAVCR2, LAG3, PDCD1, and TIGIT) in most cancer types. Our first CCNA2 pan-cancer study contributes to understanding the prognostic and immunological roles and potential upstream molecular mechanisms of CCNA2 in different cancers.

Collagen Family and Other Matrix Remodeling Proteins Identified by Bioinformatics Analysis as Hub Genes Involved in Gastric Cancer Progression and Prognosis

Gastric cancer has remained in the top five cancers for over ten years, both in terms of incidence and mortality due to the shortage of biomarkers for disease follow-up and effective therapies. Aiming to fill this gap, we performed a bioinformatics assessment on our data and two additional GEO microarray profiles, followed by a deep analysis of the 40 differentially expressed genes identified. PPI network analysis and MCODE plug-in pointed out nine upregulated hub genes coding for proteins from the collagen family (COL12A1, COL5A2, and COL10A1) or involved in the assembly (BGN) or degradation of collagens (CTHRC1), and also associated with cell adhesion (THBS2 and SPP1) and extracellular matrix degradation (FAP, SULF1). Those genes were highly upregulated at the mRNA and protein level, the increase being correlated with pathological T stages. The high expression of BGN (p = 8 × 10⁻¹²), THBS2 (p = 1.2 × 10⁻⁶), CTHRC1 (p = 1.1 × 10⁻⁴), SULF1 (p = 3.8 × 10⁻⁴), COL5A1 (p = 1.3 × 10⁻⁴), COL10A1 (p = 5.7 × 10⁻⁴), COL12A1 (p = 2 × 10⁻³) correlated with poor overall survival and an immune infiltrate based especially on immunosuppressive M2 macrophages (p-value range 4.82 × 10⁻⁷–1.63 × 10⁻¹³). Our results emphasize that these genes could be candidate biomarkers for GC progression and prognosis and new therapeutic targets.

Impact of Cancer Stem Cells on Therapy Resistance in Gastric Cancer

Gastric cancer (GC) is the fourth leading cause of cancer death worldwide, with an average 5-year survival rate of 32%, being of 6% for patients presenting distant metastasis. Despite the advances made in the treatment of GC, chemoresistance phenomena arise and promote recurrence, dissemination and dismal prognosis. In this context, gastric cancer stem cells (gCSCs), a small subset of cancer cells that exhibit unique characteristics, are decisive in therapy failure. gCSCs develop different protective mechanisms, such as the maintenance in a quiescent state as well as enhanced detoxification procedures and drug efflux activity, that make them insusceptible to current treatments. This, together with their self-renewal capacity and differentiation ability, represents major obstacles for the eradication of this disease. Different gCSC regulators have been described and used to isolate and characterize these cell populations. However, at the moment, no therapeutic strategy has achieved the effective targeting of gCSCs. This review will focus on the properties of cancer stem cells in the context of therapy resistance and will summarize current knowledge regarding the impact of the gCSC regulators that have been associated with GC chemoradioresistance.

General Features and Novel Gene Signatures That Identify Epstein-Barr Virus-Associated Epithelial Cancers

Epstein-Barr virus (EBV) is associated with various types of human malignancies, including nasopharyngeal carcinoma (NPC), EBV-associated gastric carcinoma (EBVaGC), and oral squamous cell carcinoma (OSCC). The present study aimed to identify gene signatures and common signaling pathways that can be used to predict the prognosis of EBV-associated epithelial cancers (EBVaCAs) by performing an integrated bioinformatics analysis of cell lines and tumor tissues. We identified 12 differentially expressed genes (DEGs) in the EBVaCA cell lines. Among them, only four DEGs, including BAMBI, SLC26A9, SGPP2, and TMC8, were significantly upregulated. However, SLC26A9 and TMC8, but not BAMBI and SGPP2, were significantly upregulated in EBV-positive tumor tissues compared to EBV-negative tumor tissues. Next, we identified IL6/JAK/STAT3 and TNF-α/NF-κB signaling pathways as common hallmarks of EBVaCAs. The expression of key genes related to the two hallmarks was upregulated in both EBV-infected cell lines and EBV-positive tumor tissues. These results suggest that SLC26A9 and TMC8 might be gene signatures that can effectively predict the prognosis of EBVaCAs and provide new insights into the molecular mechanisms of EBV-driven epithelial cancers.

RHAMM Is a Multifunctional Protein That Regulates Cancer Progression

The functional complexity of higher organisms is not easily accounted for by the size of their genomes. Rather, complexity appears to be generated by transcriptional, translational, and post-translational mechanisms and tissue organization that produces a context-dependent response of cells to specific stimuli. One property of gene products that likely increases the ability of cells to respond to stimuli with complexity is the multifunctionality of expressed proteins. Receptor for hyaluronan-mediated motility (RHAMM) is an example of a multifunctional protein that controls differential responses of cells in response-to-injury contexts. Here, we trace its evolution into a sensor-transducer of tissue injury signals in higher organisms through the detection of hyaluronan (HA) that accumulates in injured microenvironments. Our goal is to highlight the domain and isoform structures that generate RHAMM's function complexity and model approaches for targeting its key functions to control cancer progression.