Analysis of functional hub genes identifies CDC45 as an oncogene in non-small cell lung cancer - a short report

Untargeted metabolomics identifies indole-3-propionic acid to relieve Ang II-induced endothelial dysfunction in aortic dissection

Indole-3-propionic acid (IPA), a gut microbiota-derived metabolite of tryptophan, has been proven to fulfill an essential function in cardiovascular disease (CVD) and nerve regeneration disease. However, the role of IPA in aortic dissection (AD) has not been revealed. We aimed to investigate the role of IPA in the pathogenesis of AD and the underlying mechanisms of IPA in endothelial dysfunction. Untargeted metabolomics has been employed to screen the plasma metabolic profile of AD patients in comparison with healthy individuals. Network pharmacology provides insights into the potential molecular mechanisms underlying IPA. 3-aminopropionitrile fumarate (BAPN) and angiotensin II (Ang II) were administered to induce AD in mice, while human umbilical vein endothelial cells (HUVECs) were employed for in vitro validation of the signaling pathways predicted by network pharmacology. A total of 224 potentially differential plasma metabolites were identified in the AD patients, with 110 up-regulated metabolites and 114 down-regulated metabolites. IPA was the most significantly decreased metabolite involved in tryptophan metabolism. Bcl2, caspase3, and AKT1 were predicted as the target genes of IPA by network pharmacology and molecular docking. IPA suppressed Ang II-induced apoptosis, intracellular ROS generation, inflammation, and endothelial tight junction (TJ) loss. Animal experiments demonstrated that administration of IPA alleviated the occurrence and severity of AD in mice. Taken together, we identified a previously unexplored association between tryptophan metabolite IPA and AD, providing a novel perspective on the underlying mechanism through which IPA mitigates endothelial dysfunction to protect against AD.

CDC45 promotes the stemness and metastasis in lung adenocarcinoma by affecting the cell cycle

OBJECTIVE

This study aimed to assess the functions of cell division cycle protein 45 (CDC45) in Non-small cell lung cancer (NSCLC) cancer and its effects on stemness and metastasis.

METHODS

Firstly, differentially expressed genes related to lung cancer metastasis and stemness were screened by differential analysis and lasso regression. Then, in vitro, experiments such as colony formation assay, scratch assay, and transwell assay were conducted to evaluate the impact of CDC45 knockdown on the proliferation and migration abilities of lung cancer cells. Western blotting was used to measure the expression levels of related proteins and investigate the regulation of CDC45 on the cell cycle. Finally, in vivo model with subcutaneous injection of lung cancer cells was performed to verify the effect of CDC45 on tumor growth.

RESULTS

This study identified CDC45 as a key gene potentially influencing tumor stemness and lymph node metastasis. Knockdown of CDC45 not only suppressed the proliferation and migration abilities of lung cancer cells but also caused cell cycle arrest at the G2/M phase. Further analysis revealed a negative correlation between CDC45 and cell cycle-related proteins, stemness-related markers, and tumor mutations. Mouse experiments confirmed that CDC45 knockdown inhibited tumor growth.

CONCLUSION

As a novel regulator of stemness, CDC45 plays a role in regulating lung cancer cell proliferation, migration, and cell cycle. Therefore, CDC45 may serve as a potential target for lung cancer treatment and provide a reference for further mechanistic research and therapeutic development.

Validation of CDC45 as a novel biomarker for diagnosis and prognosis of gastric cancer

Background

Cell division cycle protein 45 (CDC45) has been demonstrated to play vital roles in the progression of various malignancies. However, the clinical significance of CDC45 in gastric cancer (GC) remains unreported.

Method

In this study, we employed the TCGA database and the TCGA & GTEx dataset to compare the mRNA expression levels of CDC45 between gastric cancer tissues and adjacent or normal tissues (p < 0.05 was considered statistically significant), which was further validated in multiple datasets including GSE13911, GSE29272, GSE118916, GSE66229, as well as RT-qPCR. Furthermore, we harnessed the Human Protein Atlas (HPA) to evaluate the protein expression of CDC45, which was subsequently verified through immunohistochemistry (IHC). To ascertain the diagnostic utility of CDC45, receiver operating characteristic (ROC) curves and the area under the ROC curve (AUC) were calculated in TCGA database, and further validated it in TCGA & GTEx and GSE66229 datasets. The Kaplan-Meier method was used to reveal the prognostic importance of CDC45 in The Cancer Genome Atlas (TCGA) database and authenticated through the GSE66229, GSE84433, and GSE84437 datasets. Through cBioPortal, we identified co-expressed genes of CDC45, and pursued enrichment analysis. Additionally, we availed gene set enrichment analysis (GSEA) to annotate the biological functions of CDC45.

Results

Differential expression analysis revealed that CDC45 was significantly upregulated at both the mRNA and protein levels in GC (all p < 0.05). Remarkably, CDC45 emerged as a promising prognostic indicator and a novel diagnostic biomarker for GC. In a comprehensive the drug susceptibility analysis, we found that patients with high expression of CDC45 had high sensitivity to various chemotherapeutic agents, among which 5-fluorouracil, docetaxel, cisplatin, and elesclomol were most evident. Furthermore, our findings suggested a plausible association between CDC45 and immune cell infiltration. Enrichment analysis revealed that CDC45 and its associated genes may play crucial roles in muscle biofunction, whereas GSEA demonstrated significant enrichment of gene sets pertaining to G protein-coupled receptor ligand binding and G alpha (i) signaling events.

Conclusion

Our study elucidates that upregulation of CDC45 is intricately associated with immune cell infiltration and holds promising potential as a favorable prognostic marker and a novel diagnostic biomarker for GC.

Upregulation of lnc-FOXD2-AS1, CDC45, and CDK1 in patients with primary non-M3 AML is associated with a worse prognosis

Acute myeloid leukemia (AML) is a heterogeneous hematologic malignancy with an unfavorable outcome. The present research aimed to identify novel biological targets for AML diagnosis and treatment. In this study, we performed an in-silico method to identify antisense RNAs (AS-RNAs) and their related co-expression genes. GSE68172 was selected from the AML database of the Gene Expression Omnibus and compared using the GEO2R tool to find DEGs. Antisense RNAs were selected from all the genes that had significant expression and a survival plot was drawn for them in the GEPIA database, FOXD2-AS1 was chosen for further investigation based on predetermined criteria (logFC ≥|1| and P < 0.05) and its noteworthy association between elevated expression level and a marked reduction in the overall survival (OS) in patients diagnosed with AML. The GEPIA database was utilized to investigate FOXD2-AS1-related co-expression and similar genes. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis and gene ontology (GO) function analysis of the mentioned gene lists were performed using the DAVID database. The protein-protein interaction (PPI) network was then constructed using the STRING database. Hub genes were screened using Cytoscape software. Pearson correlation analysis was conducted using the GEPIA database to explore the relationship between FOXD2-AS1 and the hub genes. The transcription of the selected coding and non-coding genes, including FOXD2-AS1, CDC45, CDC20, CDK1, and CCNB1, was validated in 150 samples, including 100 primary AML non-M3 blood samples and 50 granulocyte colony stimulating factor (G-CSF)-mobilized healthy donors, using quantitative Real-Time PCR (qRT-PCR). qRT-PCR results displayed significant upregulation of lnc-FOXD2-AS1, CDC45, and CDK1 in primary AML non-M3 blood samples compared to healthy blood samples (P = 0.0032, P = 0.0078, and P = 0.0117, respectively). The expression levels of CDC20 and CCNB1 were not statistically different between the two sets of samples (P = 0.8315 and P = 0.2788, respectively). We identified that AML patients with upregulation of FOXD2-AS1, CDK1, and CDC45 had shorter overall survival (OS) and Relapse-free survival (RFS) compared those with low expression of FOXD2-AS1, CDK1, and CDC45. Furthermore, the receiver operating characteristic (ROC) curve showed the potential biomarkers of lnc -FOXD2-AS1, CDC45, and CDK1 in primary AML non-M3 blood samples. This research proposed that the dysregulation of lnc-FOXD2-AS1, CDC45, and CDK1 can contribute to both disease state and diagnosis as well as treatment. The present study proposes the future evolution of the functional role of lnc-FOXD2-AS1, CDC45, and CDK1 in AML development.

Genome-wide expression profiling reveals novel biomarkers in epithelial ovarian cancer

Epithelial ovarian cancer (EOC) is the most aggressive and frequent malignancy detected among women worldwide. The pathophysiology of OC should, therefore be better understood to identify diagnostic, prognostic, and predictive novel biomarkers necessary for early detection, management, and prognostication. In this study, we aimed to investigate transcriptomic landscape and biomarker through RNA-seq data analysis. Further analysis by Protein Protein network identified top 10 Differentially Expressed Genes (DEGs). KEGG pathway enrichment analysis revealed the significant enrichment of DEGs in basal cell carcinoma, cell cycle and FoxO signalling pathway. The RNA-seq results of 10 DEGs were validated by QRT-PCR and TCGA database. Correlation studies were also performed between gene expression and clinical characteristics followed by survival analysis. Finally, 8 DEGs (CDKN1A, BCL6, CDC45, WNT2, TLR5, AQP5) including two novel DEGs (CSN1S1 and NKILA) were identified showing significant correlations with EOC characteristics. These may serve as interesting biomarkers and novel treatment targets and warrant further investigation into the functional outcome of EOC.

IGF2BP2 promotes glycolysis and hepatocellular carcinoma stemness by stabilizing CDC45 mRNA via m6A modification

A growing number of studies have shown the prognostic importance of Cell division cycle protein 45 (CDC45) in hepatocellular carcinoma (HCC). This study aims to investigate the biological function and mechanism of CDC45 in HCC. The differential expression and prognostic significance of CDC45 in HCC and normal tissues were analyzed by bioinformatics. CDC45 was knocked down and the biological effects of CDC45 in HCC in vitro and in vivo were measured. Subsequently, using RNA m6A colorimetry and Methylated RNA Immunoprecipitation (MeRIP), the levels of m6A modification of total RNA and CDC45 were evaluated in cells. RIP was applied to establish that CDC45 and insulin-like growth factor 2 mRNA-binding protein 2 (IGF2BP2) interact. A test using actinomycin D was performed to gauge the stability of the CDC45 mRNA. Furthermore, the regulatory role of IGF2BP2 on CDC45 expression in HCC progression was explored by overexpressing IGF2BP2. High expression of CDC45 was correlated with poor prognosis in HCC patients. Knocking down CDC45 inhibited HCC cell proliferation, migration, invasion, EMT, stemness, and glycolysis, and promoted apoptosis, which was verified through in vitro experiments. Additionally, IGF2BP2 was highly expressed in HCC cells, and it was found to interact with CDC45. Knocking down IGF2BP2 resulted in reduced stability of CDC45 mRNA. Moreover, overexpression of IGF2BP2 promoted HCC cell proliferation, migration, invasion, EMT, stemness, and glycolysis, while inhibiting apoptosis, which was reversed by knocking down CDC45. In general, IGF2BP2 promoted HCC glycolysis and stemness by stabilizing CDC45 mRNA via m6A modification. [Figure: see text].

Construction and Analysis of ceRNA Networks Reveal the Key Genes Associated with Bovine Herpesvirus Type 1 Infection

Background

Virus infection can cause the changes of lncRNA expression levels to regulate the interaction between virus and host, but the relationship between BHV-1 infection and lncRNA has not been reported.

Methods

In this study, in order to reveal the molecular mechanism of RNA in BoHV-1 infection, the Madin-Darby bovine kidney (MDBK) cells were infected with BoHV-1, transcriptome sequencing were performed by next-generation sequencing at 18 h or 24 h or 33 h of viral infection and then based on the competitive endogenous RNA (ceRNA) theory, lncRNA-miRNA-mRNA networks were constructed using these high-throughput sequencing data. The network analysis, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed for functional annotation and exploration of ncRNA ceRNAs in BoHV-1 infection.

Results

The results showed that 48 lncRNAs, 123 mRNAs and 20 miRNAs as differentially expressed genes, and the mitogen activated protein kinase (MAPK) pathway and calcium signaling pathway were significantly enriched in the ceRNA network. Some differentially expressed lncRNA genes were randomly selected for verification by RT-qPCR, and the results showed that their expression trend was consistent with the results of transcriptome sequencing data.

Conclusion

This study revealed that BoHV-1 infection can affect the expression of RNAs in MDBK cells and the regulation of ceRNA network to carry out corresponding biological functions in the host, but further experimental studies are still necessary to prove the hub genes function in ceRNA network and the molecular mechanism in BoHV-1 infection.

ZFP36 loss-mediated BARX1 stabilization promotes malignant phenotypes by transactivating master oncogenes in NSCLC

Non-small cell lung cancer (NSCLC) is the most common type of lung cancer, with high morbidity and mortality worldwide. Although the dysregulation of BARX1 expression has been shown to be associated with malignant cancers, including NSCLC, the underlying mechanism remains elusive. In this study, we identified BARX1 as a common differentially expressed gene in lung squamous cell carcinoma and adenocarcinoma. Importantly, we uncovered a novel mechanism behind the regulation of BARX1, in which ZFP36 interacted with 3'UTR of BARX1 mRNA to mediate its destabilization. Loss of ZFP36 led to the upregulation of BARX1, which further promoted the proliferation, migration and invasion of NSCLC cells. In addition, the knockdown of BARX1 inhibited tumorigenicity in mouse xenograft. We demonstrated that BARX1 promoted the malignant phenotypes by transactivating a set of master oncogenes involved in the cell cycle, DNA synthesis and metastasis. Overall, our study provides insights into the mechanism of BARX1 actions in NSCLC and aids a better understanding of NSCLC pathogenesis.

A network medicine approach for identifying diagnostic and prognostic biomarkers and exploring drug repurposing in human cancer

Cancer is a heterogeneous disease mainly driven by abnormal gene perturbations in regulatory networks. Therefore, it is appealing to identify the common and specific perturbed genes from multiple cancer networks. We developed an integrative network medicine approach to identify novel biomarkers and investigate drug repurposing across cancer types. We used a network-based method to prioritize genes in cancer-specific networks reconstructed using human transcriptome and interactome data. The prioritized genes show extensive perturbation and strong regulatory interaction with other highly perturbed genes, suggesting their vital contribution to tumorigenesis and tumor progression, and are therefore regarded as cancer genes. The cancer genes detected show remarkable performances in discriminating tumors from normal tissues and predicting survival times of cancer patients. Finally, we developed a network proximity approach to systematically screen drugs and identified dozens of candidates with repurposable potential in several cancer types. Taken together, we demonstrated the power of the network medicine approach to identify novel biomarkers and repurposable drugs in multiple cancer types. We have also made the data and code freely accessible to ensure reproducibility and reusability of the developed computational workflow.

Systematic pan‑cancer analysis identifies CDC45 as having an oncogenic role in human cancers

Cell division cycle 45 (CDC45) is an essential protein required for the initiation of DNA replication. In the present study, the role of CDC45 across 33 cancers was systematically investigated. It was observed that the expression of CDC45 was significantly upregulated in most cancers, exhibiting a marked negative correlation with the overall survival. Next, there was no significant difference in prognosis between the genomically altered and unaltered groups with respect to clinical outcomes. A decreased level of CDC45 at the DNA promoter region was also identified in several cancers. Furthermore, CDC45 expression was associated with the levels of tumor-infiltrating immune cells in some specific cancer types. In addition, CDC45 was associated with m⁶A methylation, and CDC45 expression was primarily positively correlated with ‘writers’ and ‘readers’ in various cancers, particularly HNRNPC, RBM15 and YTHDC1. Gene enrichment analysis was also performed. In addition, the AUC of each cancer with respect to its 1-, 3-, and 5-year survival rates were explored. Finally, CCK-8 assays, EdU assays and cell cycle analysis were conducted. In conclusion, the present study demonstrated that CDC45 may be a potential biomarker and target for cancer treatment.

Role of RBMS3 Novel Potential Regulator of the EMT Phenomenon in Physiological and Pathological Processes

RNA-binding protein 3 (RBMS3) plays a significant role in embryonic development and the pathogenesis of many diseases, especially cancer initiation and progression. The multiple roles of RBMS3 are conditioned by its numerous alternative expression products. It has been proven that the main form of RBMS3 influences the regulation of microRNA expression or stabilization. The absence of RBMS3 activates the Wnt/β-catenin pathway. The expression of c-Myc, another target of the Wnt/β-catenin pathway, is correlated with the RBMS3 expression. Numerous studies have focused solely on the interaction of RBMS3 with the epithelial-mesenchymal transition (EMT) protein machinery. EMT plays a vital role in cancer progression, in which RBMS3 is a new potential regulator. It is also significant that RBMS3 may act as a prognostic factor of overall survival (OS) in different types of cancer. This review presents the current state of knowledge about the role of RBMS3 in physiological and pathological processes, with particular emphasis on carcinogenesis. The molecular mechanisms underlying the role of RBMS3 are not fully understood; hence, a broader explanation and understanding is still needed.

Identification of the prognostic and therapeutic values of cyclin E1 (CCNE1) gene expression in Lung Adenocarcinoma and Lung Squamous Cell Carcinoma: A database mining approach

Cyclin E1 (CCNE1) is a protein-coding gene that belongs to the Cyclin family of genes which controls the G1/S phase transition of the cell cycle. Previously, its abnormal expression pattern has been examined and found to be correlated with ovarian and breast cancer progression. Herein, we exploited a bioinformatics and database mining strategy to unveil the therapeutic and prognostic significance of CCNE1 gene expression in Lung Adenocarcinoma (LUAD) and Lung Squamous Cell Carcinoma (LUSC). CCNE1 gene was reported to be highly expressed in LUAD and LUSC tissues. Its promoter and coding sequences were reported to be aberrantly methylated in LUAD and LUSC tissues than in normal tissues. Moreover, around 12 somatic mutations (frequency: 0.7%) were recorded in the CCNE1 coding region from different studies involving LUAD and LUSC patients' whole genome sequences. The CCNE1 gene expression was also correlated with LUAD and LUSC patients' overall and disease-specific survival. Immune infiltration analysis revealed the association between CCNE1 gene expression and the abundance of numerous immune cells (i.e., T cells and B Cells) infiltration in LUAD and LUSC patients. Two previously known genes involved in oncogenic processes i.e., CDC45 and PDCD5 were identified as the most highly co-expressed genes of CCNE1 in LUAD and LUSC tissues. Altogether, the CCNE1 gene and its transcriptional and translational products may serve as a prognostic or therapeutic target in the diagnosis and treatment of LUAD and LUSC patients. The scientific findings of this study should assist in translating CCNE1 into clinical practice for lung cancer diagnosis and treatment.

Construction of miRNA-lncRNA-mRNA co-expression network affecting EMT-mediated cisplatin resistance in ovarian cancer

Platinum resistance is one of the major concerns in ovarian cancer treatment. Recent evidence shows the critical role of epithelial-mesenchymal transition (EMT) in this resistance. Epithelial-like ovarian cancer cells show decreased sensitivity to cisplatin after cisplatin treatment. Our study prospected the association between epithelial phenotype and response to cisplatin in ovarian cancer. Microarray dataset GSE47856 was acquired from the GEO database. After identifying differentially expressed genes (DEGs) between epithelial-like and mesenchymal-like cells, the module identification analysis was performed using weighted gene co-expression network analysis (WGCNA). The gene ontology (GO) and pathway analyses of the most considerable modules were performed. The protein-protein interaction network was also constructed. The hub genes were specified using Cytoscape plugins MCODE and cytoHubba, followed by the survival analysis and data validation. Finally, the co-expression of miRNA-lncRNA-TF with the hub genes was reconstructed. The co-expression network analysis suggests 20 modules relating to the Epithelial phenotype. The antiquewhite4, brown and darkmagenta modules are the most significant non-preserved modules in the Epithelial phenotype and contain the most differentially expressed genes. GO, and KEGG pathway enrichment analyses on these modules divulge that these genes were primarily enriched in the focal adhesion, DNA replication pathways and stress response processes. ROC curve and overall survival rate analysis show that the co-expression pattern of the brown module's hub genes could be a potential prognostic biomarker for ovarian cancer cisplatin resistance.

Chromatin Separation Regulators Predict the Prognosis and Immune Microenvironment Estimation in Lung Adenocarcinoma

Background: Abnormal chromosome segregation is identified to be a common hallmark of cancer. However, the specific predictive value of it in lung adenocarcinoma (LUAD) is unclear.

Method: The RNA sequencing and the clinical data of LUAD were acquired from The Cancer Genome Atlas (TACG) database, and the prognosis-related genes were identified. The Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) were carried out for functional enrichment analysis of the prognosis genes. The independent prognosis signature was determined to construct the nomogram Cox model. Unsupervised clustering analysis was performed to identify the distinguishing clusters in LUAD-samples based on the expression of chromosome segregation regulators (CSRs). The differentially expressed genes (DEGs) and the enriched biological processes and pathways between different clusters were identified. The immune environment estimation, including immune cell infiltration, HLA family genes, immune checkpoint genes, and tumor immune dysfunction and exclusion (TIDE), was assessed between the clusters. The potential small-molecular chemotherapeutics for the individual treatments were predicted via the connectivity map (CMap) database.

Results: A total of 2,416 genes were determined as the prognosis-related genes in LUAD. Chromosome segregation is found to be the main bioprocess enriched by the prognostic genes. A total of 48 CSRs were found to be differentially expressed in LUAD samples and were correlated with the poor outcome in LUAD. Nine CSRs were identified as the independent prognostic signatures to construct the nomogram Cox model. The LUAD-samples were divided into two distinct clusters according to the expression of the 48 CSRs. Cell cycle and chromosome segregation regulated genes were enriched in cluster 1, while metabolism regulated genes were enriched in cluster 2. Patients in cluster 2 had a higher score of immune, stroma, and HLA family components, while those in cluster 1 had higher scores of TIDES and immune checkpoint genes. According to the hub genes highly expressed in cluster 1, 74 small-molecular chemotherapeutics were predicted to be effective for the patients at high risk.

Conclusion: Our results indicate that the CSRs were correlated with the poor prognosis and the possible immunotherapy resistance in LUAD.

Case Report: Balanced Reciprocal Translocation t (17; 22) (p11.2; q11.2) and 10q23.31 Microduplication in an Infertile Male Patient Suffering From Teratozoospermia

Two chromosomal abnormalities are described in an infertile man suffering from teratozoospermia: balanced reciprocal translocation t (17; 22) (p11.2; q11.2) and a microduplication in the region 10q23.31. Twenty genes located on the breakpoints of translocation (e.g., ALKBH5, TOP3A, SPECC1L, and CDC45) are selected due to their high expression in testicular tissues and might be influenced by chromosome translocation. Four genes located on the breakpoints of microduplication including FLJ37201, KIF20B, LINC00865, and PANK1 result in an increased dosage of genes, representing an imbalance in the genome. These genes have been reported to be associated with developmental disorders/retardation and might be risk factors affecting spermatogenesis. Bioinformatics analysis is carried out on these key genes, intending to find the pathogenic process of reproduction in the context of the translocation and microduplication encountered in the male patient. The combination of the two chromosomal abnormalities carries additional risks for gametogenesis and genomic instability and is apparently harmful to male fertility. Overall, our findings could contribute to the knowledge of male infertility caused by genetic factors.

Identification of Potential Biomarkers for Pan-Cancer Diagnosis and Prognosis Through the Integration of Large-Scale Transcriptomic Data

Cancer is one of the leading causes of death worldwide, bringing a significant burden to human health and society. Accurate cancer diagnosis and biomarkers that can be used as robust therapeutic targets are of great importance as they facilitate early and effective therapies. Shared etiology among cancers suggests the existence of pan-cancer biomarkers, performance of which could benefit from the large sample size and the heterogeneity of the studied patients. In this study, we conducted a systematic RNA-seq study of 9,213 tumors and 723 para-cancerous tissue samples of 28 solid tumors from the Cancer Genome Atlas (TCGA) database, and 7,008 normal tissue samples from the Genotype-Tissue Expression (GTEx) database. By differential gene expression analysis, we identified 214 up-regulated and 186 downregulated differentially expressed genes (DEGs) in more than 80% of the studied tumors, respectively, and obtained 20 highly linked up- and downregulated hub genes from them. These markers have rarely been reported in multiple tumors simultaneously. We further constructed pan-cancer diagnostic models to classify tumors and para-cancerous tissues using 10 up-regulated hub genes with an AUC of 0.894. Survival analysis revealed that these hub genes were significantly associated with the overall survival of cancer patients. In addition, drug sensitivity predictions for these hub genes in a variety of tumors obtained several broad-spectrum anti-cancer drugs targeting pan-cancer. Furthermore, we predicted immunotherapy sensitivity for cancers based on tumor mutational burden (TMB) and the expression of immune checkpoint genes (ICGs), providing a theoretical basis for the treatment of tumors. In summary, we identified a set of biomarkers that were differentially expressed in multiple types of cancers, and these biomarkers can be potentially used for diagnosis and used as therapeutic targets.

Molecular mechanisms and differences in lynch syndrome developing into colorectal cancer and endometrial cancer based on gene expression, methylation, and mutation analysis

Purpose

The aim of this study was to screen biomarkers specific to Lynch syndrome (LS) with colorectal cancer (CRC) or endometrial cancer (EC) to explore the mechanisms by which LS develops into CRC and EC and their differences.

Methods

Differentially expressed or differentially methylated genes and differential mutations were identified in 10 LS, 50 CRC, and 50 EC patients from TCGA, and genes overlapping between LS and CRC or EC (named SGs-LCs and SGs-LEs, respectively) were identified. Afterward, we annotated the enriched GO terms and pathways and constructed a protein–protein interaction (PPI) network. Finally, samples from 10 clinical cases with MSI-H/MSS CRC and EC were collected to verify the mutations and their correlations with five LS pathogenic genes in the SGs-LCs and SGs-LEs.

Results

A total of 494 SGs-LCs and 104 SGs-LEs were identified and enriched in 106 and 14 GO terms, respectively. There were great differences in the gene count and enriched terms between SGs-LCs and SGs-LEs. In the PPI network, SST, GCG, SNAP25, and NPY had the highest degree of connection among the SGs-LCs, and KIF20A and NUF2 had the highest degree of connection among the SGs-LE. In the SGs-LCs and SGs-LEs, the genes whose expression levels affected the survival of LS, CRC or EC patients were quite different.

Conclusions

COL11A1 was found to be mutated in MSS CRC patients, similar to the mutations of MSH6. SST, GCG, SNAP25, and NPY may be biomarkers for the development of LS into CRC, and KIF20A and NUF2 may be markers of LS developing into EC.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10552-021-01543-w.

The RNA-Binding Motif Protein Family in Cancer: Friend or Foe?

The RNA-binding motif (RBM) proteins are a class of RNA-binding proteins named, containing RNA-recognition motifs (RRMs), RNA-binding domains, and ribonucleoprotein motifs. RBM proteins are involved in RNA metabolism, including splicing, transport, translation, and stability. Many studies have found that aberrant expression and dysregulated function of RBM proteins family members are closely related to the occurrence and development of cancers. This review summarizes the role of RBM proteins family genes in cancers, including their roles in cancer occurrence and cell proliferation, migration, and apoptosis. It is essential to understand the mechanisms of these proteins in tumorigenesis and development, and to identify new therapeutic targets and prognostic markers.

Laryngeal Squamous Cell Carcinoma: Clinical Significance and Potential Mechanism of Cell Division Cycle 45

Background: Cell division cycle 45 (CDC45) plays an important role in the occurrence and development of numerous carcinomas, but its effect in laryngeal squamous cell carcinoma (LSCC) remains unclear. Materials and Methods: The messenger RNA and protein expression levels of CDC45 in LSCC were evaluated with a t test and the standard mean difference (SMD). The ability of CDC45 expression to distinguish the LSCC was assessed through receiver operating characteristic (ROC) curves. Gene set enrichment analysis (GSEA), protein-protein interaction, public databases, and online tools were used to explore the potential molecular mechanism of CDC45 in LSCC. Results: A high expression of CDC45 was identified in LSCC (SMD = 2.61, 95% confidence interval [1.62-3.61]). Through ROC curves, the expression of CDC45 makes it feasible to distinguish the LSCC group from the non-LSCC counterpart. CDC45 was relevant to the progression-free interval of LSCC patients (log-rank p = 0.03). GSEAs show that CDC45 is related to the cell cycle. CDC45, CDC6, KIF2C, and AURKB were identified as hub genes of LSCC. E2F1 may be the regulatory transcription factor of CDC45. Conclusions: High expression of CDC45 likely demonstrates carcinogenic effects in LSCC, and CDC45 is a potential target in screening and treatment of LSCC.

Expression and prognosis of CDC45 in cervical cancer based on the GEO database

Cervical cancer is one of the most common malignant tumors in women, and its morbidity and mortality are increasing year by year worldwide. Therefore, an urgent and challenging task is to identify potential biomarkers for cervical cancer. This study aims to identify the hub genes based on the GEO database and then validate their prognostic values in cervical cancer by multiple databases. By analysis, we obtained 83 co-expressed differential genes from the GEO database (GSE63514, GSE67522 and GSE39001). GO and KEGG enrichment analysis showed that these 83 co-expressed it mainly involved differential genes in DNA replication, cell division, cell cycle, etc.. The PPI network was constructed and top 10 genes with protein-protein interaction were selected. Then, we validated ten genes using some databases such as TCGA, GTEx and oncomine. Survival analysis demonstrated significant differences in CDC45, RFC4, TOP2A. Differential expression analysis showed that these genes were highly expressed in cervical cancer tissues. Furthermore, univariate and multivariate cox regression analysis indicated that CDC45 and clinical stage IV were independent prognostic factors for cervical cancer. In addition, the HPA database validated the protein expression level of CDC45 in cervical cancer. Further studies investigated the relationship between CDC45 and tumor-infiltrating immune cells via CIBERSORT. Finally, gene set enrichment analysis (GSEA) showed CDC45 related genes were mainly enriched in cell cycle, chromosome, catalytic activity acting on DNA, etc. These results suggested CDC45 may be a potential biomarker associated with the prognosis of cervical cancer.

Identifying key genes and small molecule compounds for nasopharyngeal carcinoma by various bioinformatic analysis

Nasopharyngeal carcinoma (NPC) is one of the most prevalent head and neck cancer in southeast Asia. It is necessary to proceed further studies on the mechanism of occurrence and development of NPC.In this study, we employed the microarray dataset GSE12452 and GSE53819 including 28 normal samples and 49 nasopharyngeal carcinoma samples downloaded from the Gene Expression Omnibus(GEO) to analysis. R software, STRING, CMap, and various databases were used to screen differentially expressed genes (DEGs), construct the protein-protein interaction (PPI) network, and proceed small molecule compounds analysis, among others.Totally, 424 DEGs were selected from the dataset. DEGs were mainly enriched in extracellular matrix organization, cilium organization, PI3K-Akt signaling pathway, collagen-containing extracellular matrix, and extracellular matrix-receptor interaction, among others. Top 10 upregulated and top 10 downregulated hub genes were identified as hub DEGs. Piperlongumine, apigenin, menadione, 1,4-chrysenequinone, and chrysin were identified as potential drugs to prevent and treat NPC. Besides, the effect of genes CDK1, CDC45, RSPH4A, and ZMYND10 on survival of NPC was validated in GEPIA database.The data revealed novel aberrantly expressed genes and pathways in NPC by bioinformatics analysis, potentially providing novel insights for the molecular mechanisms governing NPC progression. Although further studies needed, the results demonstrated that the expression levels of CDK1, CDC45, RSPH4A, and ZMYND10 probably affected survival of NPC patients.

The Indication of Poor Prognosis by High Expression of ENO1 in Squamous Cell Carcinoma of the Lung

The purpose of this study is to investigate the significance of alpha-enolase (ENO1) expression in squamous cell carcinoma of the lung (LUSC), its prognostic value, and prospective molecular mechanism. Using multiplatforms data, including in-house immunohistochemistry, in-house real-time fluorescence quantitative polymerase chain reaction (RT-qPCR), in-house microarray, and public high-throughput data, the expression significance and prognostic role of ENO1 in LUSC tissues were analyzed comprehensively. With the combination of all eligible cases, compared with 941 non-LUSC lung tissues, ENO1 was significantly overexpressed in 1163 cases of LUSC (standardized mean difference (SMD) = 1.23, 95% confidence interval (CI) = 0.76–1.70, P < 0.001). ENO1 also displayed a great ability to differentiate LUSC tissues from non-LUSC lung tissues (AUC = 0.8705) with the comprehensive sensitivity being 0.88 [0.83–0.92], and comprehensive specificity being 0.89 [0.84–0.94]). Moreover, in 1860 cases of LUSC with survival information, patients with higher expression of ENO1 had poorer prognosis (hazard ratio (HR) = 1.20, 95% CI = 1.01–1.43, P = 0.043). ENO1 and its related genes mainly participated in the pathways of cell division and proliferation. In conclusion, the upregulation of ENO1 could affect the carcinogenesis and unfavorable outcome of LUSC.

Identification of potential core genes and pathways predicting pathogenesis in head and neck squamous cell carcinoma

Head and neck squamous cell carcinoma (HNSCC) is the most common subtype of head and neck cancer; however, its pathogenesis and potential therapeutic targets remain largely unknown. In the present study, we analyzed three gene expression profiles and screened differentially expressed genes (DEGs) between HNSCC and normal tissues. The DEGs were subjected to gene ontology (GO), Kyoto encyclopedia of genes and genomes (KEGG), protein–protein interaction (PPI), and survival analyses, while the connectivity map (CMap) database was used to predict candidate small molecules that may reverse the biological state of HNSCC. Finally, we measured the expression of the most relevant core gene in vitro and examined the effect of the top predicted potential drug against the proliferation of HNSCC cell lines. Among the 208 DEGs and ten hub genes identified, CDK1 and CDC45 were associated with unfavorable HNSCC prognosis, and three potential small molecule drugs for treating HNSCC were identified. Increased CDK1 expression was confirmed in HNSCC cells, and menadione, the top predicted potential drug, exerted significant inhibitory effects against HNSCC cell proliferation and markedly reversed CDK1 expression. Together, the findings of the present study suggest that the ten hub genes and pathways identified may be closely related to HNSCC pathogenesis. In particular, CDK1 and CDC45 overexpression could be reliable biomarkers for predicting unfavorable prognosis in patients with HNSCC, while the new candidate small molecules identified by CMap analysis provide new avenues for the development of potential drugs to treat HNSCC.

Silencing SIX1 by miR-7160 inhibits non-small cell lung cancer cell growth

The homeoprotein SIX1 is upregulated in non-small cell lung cancer (NSCLC) and associated with NSCLC tumorigenesis and progression. We identified microRNA-7160 (miR-7160) as a SIX1-targeting miRNA. RNA immunoprecipitation results confirmed a direct binding between miR-7160 and SIX1 mRNA in NSCLC cells. In the primary and established NSCLC cells, forced overexpression of miR-7160 downregulated SIX1 and inhibited cancer cell growth, proliferation, migration and invasion. Furthermore, miR-7160 overexpression induced apoptosis activation in NSCLC cells. Conversely, miR-7160 inhibition elevated SIX1 expression and enhanced NSCLC cell progression in vitro. Restoring SIX1 expression, by an untranslated region-depleted SIX1 expression construct, reversed miR-7160-induced anti-NSCLC cell activity. CRISPR/Cas9-inudced knockout of SIX1 mimicked miR-7160-induced actions and produced anti-NSCLC cell activity. In vivo, intratumoral injection of miR-7160-expressing lentivirus downregulated SIX1 mRNA and inhibited NSCLC xenograft growth in severe combined immunodeficient mice. Significantly, miR-7160 expression is downregulated in human NSCLC tissues and is correlated with SIX1 mRNA upregulation. Collectively, miR-7160 silenced SIX1 and inhibited NSCLC cell growth in vitro and in vivo.

TRPM2-AS Promotes Bladder Cancer by Targeting miR-22-3p and Regulating GINS2 mRNA Expression

Background

Bladder cancer (BLCA) refers to the malignancy growth that spreads from the bladder linings to the bladder muscles. However, the impact of miR-22-3p and lncRNA TRPM2-AS on this tumor has generated divergent views in the literature. This research aimed to study the effects of lncRNA TRPM2-AS on BLCA and its interaction with miR-22-3p and GINS2 mRNA.

Methods

qRT-PCR was employed to measure the expression of TRPM2-AS, miR-22-3p and GINS2 mRNA in bladder tissues and cells. The subcellular localization of TRPM2-AS in T24 and 5637 cell lines was identified using a cell fractionation system. Luciferase assay, RIP assay and RNA pull-down assay were later performed to validate the direct binding relationship between TRPM2-AS, miR-22-3p and GINS2 mRNA. Several experiments were conducted to determine the viability, proliferation, colony formation and apoptosis of the cell lines.

Results

Findings indicated that TRPM2-AS was significantly upregulated in BLCA tissues and cell lines. Apart from that, it was observed that TRPM2-AS knockdown significantly inhibited the viability, proliferation and colony formation of BCLA cells, but it promoted the apoptosis of the BCLA cells. A significant downstream target of TRPM2-AS, miR-22-3p was found to show a lower expression level in BLCA tissues and cell lines. However, the inhibition of miR-22-3p considerably enhanced BLCA cell phenotypes. As well as discovering that GINS2 mRNA was a downstream target of miR-22-3p and was significantly upregulated in BLCA, experimental results also indicated that the knockdown of GINS2 suppressed BLCA cell phenotypes.

Conclusion

This research confirmed that TRPM2-AS could promote BCLA by binding to miR-22-3p to increase GINS2 expression. This novel interactome in BLCA cell lines might provide more insights into BLCA therapy.

Prognostic implications of cell division cycle protein 45 expression in hepatocellular carcinoma

Background

The overall prognosis of hepatocellular carcinoma (HCC) is poor and novel prognostic biomarkers might better monitor the progression of HCC. Cell division cycle protein 45 (CDC45) plays a key role in DNA replication and considered to be involved in tumorigenesis. This study investigated CDC45 expression in tumour tissues and defined its prognostic value in HCC patients.

Methods

We used immunohistochemistry (IHC) staining to examine the expression of CDC45 in tumour tissue specimens and compare them with adjacent normal tissue specimens using a constructed tissue microarray (TMA) and analyzed how clinical features are related to HCC prognosis. Functional enrichment analyses were used to describe significantly involved hallmark pathways of differentially expressed genes (DEGs, which were screened out according to the high or low expression of CDC45 in tumour tissues).

Results

Our findings showed that the proteome expression of CDC45 was evidently downregulated in HCC tissues compared with matched normal tissues (P < 0.0001). Although we did not find any differences in terms of vascular invasion, metastasis, lymphatic infiltration, or Edmondson grade between patients with high and low CDC45 expression, low CDC45 expression was significantly correlated with microvascular invasion (P = 0.046). Multivariate analysis indicated that CDC45 expression (P = 0.035) was an independent prognostic factor for the overall survival (OS) rate of HCC patients. Patients with CDC45 expression was positively correlated with OS rates among HCC patients (P < 0.05). Functional annotations indicated that CDC45 is involved in the most significant pathways, including the cell cycle, DNA replication, chemical carcinogenesis and drug metabolism–cytochrome P450 pathways.

Discussion

Our findings showed that low proteomic level of CDC45 was associated with a poor prognosis in HCC patients, indicating that CDC45 might be a novel prognostic marker.

Microarray Data Mining and Preliminary Bioinformatics Analysis of Hepatitis D Virus-Associated Hepatocellular Carcinoma

Several studies have demonstrated that chronic hepatitis delta virus (HDV) infection is associated with a worsening of hepatitis B virus (HBV) infection and increased risk of hepatocellular carcinoma (HCC). However, there is limited data on the role of HDV in the oncogenesis of HCC. This study is aimed at assessing the potential mechanisms of HDV-associated hepatocarcinogenesis, especially to screen and identify key genes and pathways possibly involved in the pathogenesis of HCC. We selected three microarray datasets: GSE55092 contains 39 cancer specimens and 81 paracancer specimens from 11 HBV-associated HCC patients, GSE98383 contains 11 cancer specimens and 24 paracancer specimens from 5 HDV-associated HCC patients, and 371 HCC patients with the RNA-sequencing data combined with their clinical data from the Cancer Genome Atlas (TCGA). Afterwards, 948 differentially expressed genes (DEGs) closely related to HDV-associated HCC were obtained using the R package and filtering with a Venn diagram. We then performed gene ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis to determine the biological processes (BP), cellular component (CC), molecular function (MF), and KEGG signaling pathways most enriched for DEGs. Additionally, we performed Weighted Gene Coexpression Network Analysis (WGCNA) and protein-to-protein interaction (PPI) network construction with 948 DEGs, from which one module was identified by WGCNA and three modules were identified by the PPI network. Subsequently, we validated the expression of 52 hub genes from the PPI network with an independent set of HCC dataset stored in the Gene Expression Profiling Interactive Analysis (GEPIA) database. Finally, seven potential key genes were identified by intersecting with key modules from WGCNA, including 3 reported genes, namely, CDCA5, CENPH, and MCM7, and 4 novel genes, namely, CDC6, CDC45, CDCA8, and MCM4, which are associated with nucleoplasm, cell cycle, DNA replication, and mitotic cell cycle. The CDCA8 and stage of HCC were the independent factors associated with overall survival of HDV-associated HCC. All the related findings of these genes can help gain a better understanding of the role of HDV in the underlying mechanism of HCC carcinogenesis.

Identification of Hub Genes as Potential Prognostic Biomarkers in Cervical Cancer Using Comprehensive Bioinformatics Analysis and Validation Studies

Background

Cervical cancer belongs to one of the most common female cancers; yet, the exact underlying mechanisms are still elusive. Recently, microarray and sequencing technologies have been widely used for screening biomarkers and molecular mechanism discovery in cancer studies. In this study, we aimed to analyse the microarray datasets using comprehensive bioinformatics tools and identified novel biomarkers associated with the prognosis of patients with cervical cancer.

Methods

The differentially expressed genes (DEGs) from Gene Expression Omnibus (GEO) datasets including GSE138080, GSE113942 and GSE63514 were analysed using GEO2R tool. The functional enrichment analysis was performed using g:Profiler tool. The protein-protein interaction (PPI) network construction and hub genes identification were performed using the STRING database and Cytoscape software, respectively. The hub genes were subjected to expression and survival analysis in the cervical cancer. The EdU incorporation and Cell Counting Kit-8 assays were performed to evaluate the effects of hub gene knockdown on the proliferation of cervical cancer cells.

Results

A total of 89 overlapping DEGs (63 up-regulated and 26 down-regulated genes) were identified in the microarray datasets. The functional enrichment analysis indicated that the overlapping DEGs were mainly associated with "DNA replication" and "cell cycle". Furthermore, the PPI network analysis revealed that the network contains 87 nodes and 309 edges. Sub-module analysis using the Molecular Complex Detection tool identified 21 hub genes from the PPI network. The expression levels of the 21 hub genes were all up-regulated in the cervical cancer tissues when compared to normal cervical tissues as analysed by GEPIA tool. The survival analysis showed that the low expression of cell division cycle 45 (CDC45), GINS complex subunit 2 (GINS2), minichromosome maintenance complex component 2 (MCM2) and proliferating cell nuclear antigen (PCNA) was significantly correlated with the shorter overall survival of patients with cervical cancer. Moreover, the protein expression levels of GINS2, MCM2 and PCNA, but not CDC45, were significantly up-regulated in the cervical cancer tissues when compared to normal cervical tissues. Finally, knockdown of MCM2 significantly suppressed the proliferation of HeLa and SiHa cells.

Conclusion

In conclusion, we screened a total of 89 overlapping DEGs from the GEO datasets, and further analysis identified four hub genes (CDC45, GINS2, MCM2 and PCNA) that were likely associated with the prognosis of patients with cervical cancer. MCM2 knockdown repressed the cervical cancer cell proliferation. The current findings may provide novel insights into understanding the pathophysiology of cervical cancer and develop therapeutic targets for patients with cervical cancer.

The underlying molecular mechanism and identification of transcription factor markers for laryngeal squamous cell carcinoma

The screening and treatment of laryngeal squamous cell carcinoma (LSCC) still perplexes clinicians, making it necessary to explore new markers. To this end, this research examined the underlying molecular mechanism of LSCC based on high-throughput datasets (n = 249) from multiple databases. It also identified transcription factors (TFs) independently associated with LSCC prognosis. Through Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses, differential expression genes of LSCC were deemed relevant to the extracellular matrix and its related structures or pathways, suggesting that the extracellular matrix plays an important role in LSCC. At the same time, several hub genes that may also have important roles in LSCC were identified via protein–protein interaction analysis, including CDC45, TPX2, AURKA, KIF2C, NUF, MUC1, MUC7, MUC4, MUC15, and MUC21. Eight unreported LSCC prognostic TFs – BCAT1, CHD4, FOXA2, GATA6, HNF1A, HOXB13, MAFF, and TCF4 – were screened via Kaplan–Meier curves. Cox analysis determined for the first time that HOXB13 expression and gender were independently associated with LSCC prognosis. Compared to control tissues, elevated expression of HOXB13 was found in LSCC tissues (standardized mean difference = 0.44, 95% confidence interval [0.13–0.76]). HOXB13 expression also makes it feasible to screen LSCC from non-LSCC (area under the curve = 0.77), and HOXB13 may play an essential role in LSCC by regulating HOXB7. In conclusion, HOXB13 may be a novel marker for LSCC clinical screening and treatment.

KIF14 and KIF23 Promote Cell Proliferation and Chemoresistance in HCC Cells, and Predict Worse Prognosis of Patients with HCC

Background

Hepatocellular carcinoma (HCC) is one of the most common human malignant tumors. The prognosis of HCC patients is still unsatisfying. In this study, we performed the integrated bioinformatics analysis to identify potential biomarkers and biological pathways in HCC.

Methods

Gene expression profiles were obtained from the Gene Expression Omnibus database (GSE55048, GSE55758, and GSE56545) for the screening of the common differentially expressed genes (DEGs) between HCC tissues and matched non-tumor tissues. DEGs were subjected to Gene Ontology, KEGG pathway, and Reactome pathway analysis. The hub genes were identified by using protein–protein interaction (PPI) network analysis. The hub genes in HCC were further subjected to overall survival analysis of HCC patients. The hub genes were further validated by in vitro functional assays.

Results

A total of 544 common differentially expressed genes were screened from three datasets. Gene Ontology, KEGG and Reactome analysis results showed that DEGs are significantly associated with the biological process of cell cycle, cell division, and DNA replication. PPI network analysis identified 20 hub genes from the DEGs. These hub genes except CENPE were all significantly up-regulated in the HCC tissues when compared to non-tumor tissues. The Kaplan–Meier survival analysis results showed that the high expression of the 20 hub genes was associated with shorter survival of the HCC patients. Further validation studies showed that knockdown of KIF14 and KIF23 both suppressed the proliferative potential, increased the caspase-3/-7 activity, up-regulated Bax expression, and promoted the invasive and migratory abilities in the HCC cells. In addition, knockdown of KIF14 and KIF23 enhanced chemosensitivity to cisplatin and sorafenib in the HCC cells. Finally, the high expression of KIF14 and KIF23 was associated with shorter progression-free survival, recurrence-free survival, and disease-specific survival of patients with HCC.

Conclusion

In conclusion, the present study performed the integrated bioinformatics analysis and showed that KIF14 and KIF23 silence attenuated cell proliferation, invasion, and migration, and promoted chemosensitivity of HCC cells. KIF14 and KIF23 may serve as potential biomarkers for predicting the worse prognosis of patients with HCC.

COL3A1, COL6A3, and SERPINH1 Are Related to Glucocorticoid-Induced Osteoporosis Occurrence According to Integrated Bioinformatics Analysis

Background

Glucocorticoid-induced osteoporosis (GIOP) represents the most frequently seen type of secondary osteoporosis, a systemic skeleton disorder. Numerous factors are associated with GIOP occurrence, but there are no specific diagnostic and therapeutic biomarkers for GIOP so far.

Material/Methods

In this work, gene modules related to GIOP were screened through weighted gene coexpression network analysis. Moreover, protein-protein interaction (PPI) networks and gene set enrichment analysis (GSEA) were carried out for hub genes. In addition, microarray GSE30159 dataset was used as a training set to analyze gene expression within bone biopsy samples from patients with endogenous Cushing’s syndrome with GIOP and from normal controls. GSE129228 was used as the test set for investigating the hub gene involvement within GIOP.

Results

According to our results, the turquoise module showed clinical significance, and 10 genes (COL3A1, POSTN, COL6A3, COL14A1, SERPINH1, ASPN, OGN, THY1, NID2, and TNMD) were discovered to be the “real” hub genes within coexpression as well as PPI networks. GSEA showed that the interaction of extracellular matrix receptors together with the focal adhesion pathway had significant enrichment within samples with high COL3A1 and COL6A3 expression. After the results from both test and training sets were overlapped, SERPINH1 was also significantly altered between GIOP and normal control samples.

Conclusions

COL3A1, COL6A3, and SERPINH1 were identified to be the candidate biomarkers for GIOP.

The New Paradigm of Network Medicine to Analyze Breast Cancer Phenotypes

Breast cancer (BC) is a heterogeneous and complex disease as witnessed by the existence of different subtypes and clinical characteristics that poses significant challenges in disease management. The complexity of this tumor may rely on the highly interconnected nature of the various biological processes as stated by the new paradigm of Network Medicine. We explored The Cancer Genome Atlas (TCGA)-BRCA data set, by applying the network-based algorithm named SWItch Miner, and mapping the findings on the human interactome to capture the molecular interconnections associated with the disease modules. To characterize BC phenotypes, we constructed protein-protein interaction modules based on "hub genes", called switch genes, both common and specific to the four tumor subtypes. Transcriptomic profiles of patients were stratified according to both clinical (immunohistochemistry) and genetic (PAM50) classifications. 266 and 372 switch genes were identified from immunohistochemistry and PAM50 classifications, respectively. Moreover, the identified switch genes were functionally characterized to select an interconnected pathway of disease genes. By intersecting the common switch genes of the two classifications, we selected a unique signature of 28 disease genes that were BC subtype-independent and classification subtype-independent. Data were validated both in vitro (10 BC cell lines) and ex vivo (66 BC tissues) experiments. Results showed that four of these hub proteins (AURKA, CDC45, ESPL1, and RAD54L) were over-expressed in all tumor subtypes. Moreover, the inhibition of one of the identified switch genes (AURKA) similarly affected all BC subtypes. In conclusion, using a network-based approach, we identified a common BC disease module which might reflect its pathological signature, suggesting a new vision to face with the disease heterogeneity.

Identification of pancreatic cancer type related factors by Weighted Gene Co-Expression Network Analysis

This study aims to identify the core modules associated with pancreatic cancer (PC) types and the ncRNAs and transcription factors (TFs) that regulate core module genes by weighted gene co-expression network analysis (WGCNA). WGCNA was used to analyze the union of genes related to PC in NCBI and OMIM databases and the differentially expressed genes screened by TCGA-PAAD database. Samples were clustered according to gene expression in gene modules and Fisher exact method was performed. GO and KEGG were used for enrichment analysis to visually display module genes and screen driver genes. Hypergeometric test method was used to calculate pivot nodes among ncRNAs, TFs and mRNA based on RAID 2.0 and TRRUST v2 databases. The blue and yellow modules were identified as the core modules associated with PC types. MST1R, TMPRSS, MIR198, SULF1, COL1A1 and FAP were the core genes in the modules. Hypergeometric test results showed that ANCR, miR-3134, MT1DP, LOC154449, LOC28329 and other ncRNAs were key factors driving blue module genes, while LINC-ROR, UCA1, SNORD114-4, HEIH, SNORD114-6 and other ncRNAs were key factors driving yellow module genes. TFs with significant regulatory effect on blue module included LCOR, PIAS4, ZEB1, SNAI2, SMARCA4, etc. and on yellow module included HOXC6, PER2, HOXD3, TWIST2, VHL, etc. The core modules associated with PC types were proved as yellow and blue modules, and important ncRNAs and TFs regulating yellow and blue modules were found. This study provides relevant evidence for further identification of PC types.

Long Noncoding MAGI2-AS3 Suppresses Several Cellular Processes of Lung Squamous Cell Carcinoma Cells by Regulating miR-374a/b-5p/CADM2 Axis

Background

Lung squamous cell carcinoma (LUSC) accounts for approximately 30% of all lung cancers that possesses the highest occurrence and mortality in all cancer types. Long noncoding RNAs have been reported to modulate tumor development for several decades.

Aim of the Study

This research aims to investigate the role of MAGI2-AS3 in LUSC.

Methods

RT-qPCR tested genes (including MAGI2-AS3, miR-374a/b-5p and CADM2) expression. Cell proliferation was detected by colony formation and EdU assays. Cell migration and invasion were evaluated by transwell assay. Flow cytometry analysis of apoptotic cells and Western blot analysis on apoptosis-related genes were applied to measure cell apoptosis. Nuclear-cytoplasmic fractionation and FISH assay positioned MAGI2-AS3. The combination between miR-374a/b-5p and MAGI2-AS3 (or CADM2) was determined by luciferase reporter assay and RIP assay.

Results

MAGI2-AS3 inhibited the proliferative, migratory and invasive capability of LUSC cells with upregulated expression. Additionally, MAGI2-AS3 overexpression promoted cell apoptosis. We discovered that MAGI2-AS3 was located in the cytoplasm. Hereafter, we found out that MAGI2-AS3 targeted miR-374a/b-5p. CADM2 was targeted by miR-374a/b-5p. Finally, rescue assays indicated that the promoting effects of miR-374a/b-5p amplification on biological activities were restored by CADM2 addition.

Conclusion

In conclusion, lncRNA MAGI2-AS3 suppressed LUSC by regulating miR-374a/b-5p/CADM2 axis, which might potentially serve as a therapeutic marker for LUSC patients.

Potential Prognostic and Diagnostic Values of CDC6, CDC45, ORC6 and SNHG7 in Colorectal Cancer

Background

Colorectal cancer (CRC) is a common human malignancy. The aims of this study are to investigate the gene expression profile of CRC and to explore potential strategy for CRC diagnosis, therapy and prognosis.

Methods

We use affy and Limma package of Bioconductor R to do differential expression genes (DEGs) and differential expression lncRNAs (DELs) analysis from the gene datasets (GSE8671, GSE21510, GSE32323, GSE39582 and TCGA) respectively. Then, DEGs were analyzed by GO and KEGG pathway and Kaplan-Meier survival curve and Cox regression analyses were used to find aberrantly expressed genes associated with survival outcome of CRC patients. Real-time PCR assay was used to verify the aberrantly expressed genes expression in CRC samples.

Results

306 up-regulation and 213 down-regulation common DEGs were found. A total of 485 DELs were identified, of which 241 up-regulated and 244 down-regulated. Then, GO and KEGG pathway analyses showed that DEGs were involved in cell cycle, mineral absorption, DNA replication, and Nitrogen metabolism. Among them, Kaplan-Meier survival curve and Cox regression analyses revealed that CDC6, CDC45, ORC6 and SNHG7 levels were significantly associated with survival outcome of CRC patients. Finally, real-time PCR assay was used to verify that the CDC6, CDC45, ORC6 and SNHG7 expression were up-regulated in 198 CRC samples compared with the expression levels in individual-matched adjacent mucosa samples.

Conclusion

CDC6, CDC45, ORC6 and SNHG7 are implicated in CRC initiation and progression and could be explored as potential diagnosis, therapy and prognosis targets for CRC.

Weighted Gene Co-Expression Network Analysis Identified Cancer Cell Proliferation as a Common Phenomenon During Perineural Invasion

Purpose

Perineural invasion (PNI) is the neoplastic invasion of nerves by cancer cells, a process that may prove to be another metastatic route besides direct invasion, lymphatic spread, and vascular dissemination. Given the increasing incidence and association with poor prognosis, revealing the pathogenesis of perineural invasion is of great importance.

Materials and methods

Four datasets related to PNI were downloaded from the Gene Expression Omnibus database and used to construct weighted gene co-expression network analysis (WGCNA). The intersection of potential pathways obtained from further correlation and enrichment analyses of different datasets was validated by the coculture model of Schwann cells (SCs), flow cytometry and immunohistochemistry (IHC).

Results

GSE7055 and GSE86544 datasets were brought into the analysis for there were some significant modules related to PNI, while GSE103479 and GSE102238 datasets were excluded for insignificant differences. In total, 13,841 genes from GSE86544 and 10,809 genes from GSE7055 were used for WGCNA. As a consequence, 19 and 26 modules were generated, respectively. The purple module of GSE86544 and the dark gray module of GSE7055 were positively correlated with perineural invasion. Further correlation and enrichment analyses of genes from the two modules suggested that these genes were mainly enriched in cell cycle processes; especially, the terms S/G2/M phase were enriched. Three kinds of cells grew vigorously after coculture with SCs ex vivo. The Ki67 staining of the cervical cancer samples revealed that the Ki67 index of cancer cells surrounding nerves was higher than of those distant ones.

Conclusion

Our work has identified cancer cell proliferation as a common response to neural cancerous microenvironments, proving a foundation for cancer cell colonization and metastasis.