A functional single nucleotide polymorphism at the promoter region of cyclin A2 is associated with increased risk of colon, liver, and lung cancers

The crosstalk between miRNAs and signaling pathways in human cancers: Potential therapeutic implications

MicroRNAs (miRNAs) are increasingly recognized as central players in the regulation of eukaryotic physiological processes. These small double stranded RNA molecules have emerged as pivotal regulators in the intricate network of cellular signaling pathways, playing significant roles in the development and progression of human cancers. The central theme in miRNA-mediated regulation of signaling pathways involves their ability to target and modulate the expression of pathway components. Aberrant expression of miRNAs can either promote or suppress key signaling events, influencing critical cellular processes such as proliferation, apoptosis, angiogenesis, and metastasis. For example, oncogenic miRNAs often promote cancer progression by targeting tumor suppressors or negative regulators of signaling pathways, thereby enhancing pathway activity. Conversely, tumor-suppressive miRNAs frequently inhibit oncogenic signaling by targeting key components within these pathways. This complex regulatory crosstalk underscores the significance of miRNAs as central players in shaping the signaling landscape of cancer cells. Furthermore, the therapeutic implications of targeting miRNAs in cancer are substantial. miRNAs can be manipulated to restore normal signaling pathway activity, offering a potential avenue for precision medicine. The development of miRNA-based therapeutics, including synthetic miRNA mimics and miRNA inhibitors, has shown promise in preclinical and clinical studies. These strategies aim to either enhance the activity of tumor-suppressive miRNAs or inhibit the function of oncogenic miRNAs, thereby restoring balanced signaling and impeding cancer progression. In conclusion, the crosstalk between miRNAs and signaling pathways in human cancers is a dynamic and influential aspect of cancer biology. Understanding this interplay provides valuable insights into cancer development and progression. Harnessing the therapeutic potential of miRNAs as regulators of signaling pathways opens up exciting opportunities for the development of innovative cancer treatments with the potential to improve patient outcomes. In this chapter, we provide an overview of the crosstalk between miRNAs and signaling pathways in the context of cancer and highlight the potential therapeutic implications of targeting this regulatory interplay.

Missense variants in CYP4B1 associated with increased risk of lung cancer among Chinese Han population

INTRODUCTION

Understanding the etiology and risk factors of lung cancer (LC) is the key to developing scientific and effective prevention and control strategies for LC. CYP4B1 genetic polymorphism has been reported to be associated with susceptibility to various diseases. We aimed to explore the association between CYP4B1 genetic variants and LC susceptibility.

METHODS

One thousand three hundred thirty-nine participants were recruited to perform an association analysis through SNPStats online software. Statistical analysis of this study was mainly completed by SPSS 22.0 software. False-positive report probability analysis (FPRP) to detect whether the positive findings were noteworthy. Finally, the interaction of SNP-SNP in LC risk was evaluated by multi-factor dimensionality reduction.

RESULTS

We found evidence that missense variants in CYP4B1 (rs2297810, rs4646491, and rs2297809) are associated with LC susceptibility. In particular, genotype GA of CYP4B1-rs2297810 was significantly associated with an increased risk of LC in both overall and stratified analyses (genotype GA: OR (95% CI) = 1.35 (1.08-1.69), p = 0.010). CYP4B1-rs4646491 (overdominant: OR (95% CI) = 1.30 (1.04-1.62), p = 0.023) and CYP4B1-rs2297809 (genotype CT: OR (95% CI) = 1.26 (1.01-1.59), p = 0.046) are also associated with an increased risk of LC. FPRP analysis showed that all positive results in this study are noteworthy findings CONCLUSION: Three missense variants in CYP4B1 (rs2297810, rs4646491, and rs2297809) are associated with increasing risk of LC.

Mechanism of Glycitein in the Treatment of Colon Cancer Based on Network Pharmacology and Molecular Docking

INTRODUCTION

The prevalence of colon cancer remains high across the world. The early diagnosis of colon cancer is challenging. Moreover, patients with colon cancer frequently suffer from poor prognoses.

METHODS

Differentially expressed genes (DEGs) in colon cancer were acquired based on TCGA-COAD dataset screening. DEGs were input into the Connectivity Map (CMap) database to screen small molecule compounds with the potential to reverse colon cancer pathological function. Glycitein ranked first among the screened small-molecule compounds. We downloaded the main targets of glycitein from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) database and constructed protein-protein interaction (PPI) networks of those which were closely related to targets by the Search Tool for the Retrieval of Interaction Gene/Proteins (STRING). Five potential targets of glycitein for treating colon cancer were identified (CCNA2, ESR1, ESR2, MAPK14, and PTGS2). These targets were used as seeds for random walk with restart (RWR) analysis of PPI networks. Then, the interaction network of glycitein-colon cancer-related genes was constructed based on the top 50 genes in affinity coefficients. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted on the potential genes targeted by glycitein in colon cancer treatment and those that were closely bound up with targets.

RESULTS

GO analysis demonstrated that the enrichment of these genes was primarily discovered in biological functions including regulation of fibroblast proliferation, response to oxygen levels, and epithelial cell proliferation. The KEGG analysis results illustrated that the signaling pathways where these genes were mostly involved consisted of the mitogen-activated protein kinase signaling pathway, the phosphatidylinositol-3-kinase-Akt signaling pathway, and the p53 signaling pathway. Finally, stable binding of glycitein to five potential targets in colon cancer was verified by molecular docking.

CONCLUSION

This study elucidated the key targets and main pathways of glycitein on the basis of network pharmacology and preliminarily analyzed molecular mechanisms in the treatment of colon cancer. A scientific basis is provided for glycitein application in treating colon cancer.

Identification of potential hub genes associated with the pathogenesis and prognosis of hepatocellular carcinoma via integrated bioinformatics analysis

Objective

The objective was to identify potential hub genes associated with the pathogenesis and prognosis of hepatocellular carcinoma (HCC).

Methods

Gene expression profile datasets were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) between HCC and normal samples were identified via an integrated analysis. A protein–protein interaction network was constructed and analyzed using the STRING database and Cytoscape software, and enrichment analyses were carried out through DAVID. Gene Expression Profiling Interactive Analysis and Kaplan–Meier plotter were used to determine expression and prognostic values of hub genes.

Results

We identified 11 hub genes (CDK1, CCNB2, CDC20, CCNB1, TOP2A, CCNA2, MELK, PBK, TPX2, KIF20A, and AURKA) that might be closely related to the pathogenesis and prognosis of HCC. Enrichment analyses indicated that the DEGs were significantly enriched in metabolism-associated pathways, and hub genes and module 1 were highly associated with cell cycle pathway.

Conclusions

In this study, we identified key genes of HCC, which indicated directions for further research into diagnostic and prognostic biomarkers that could facilitate targeted molecular therapy for HCC.

NEIL3 may act as a potential prognostic biomarker for lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma (LUAD) is the leading cause of cancer-related death. This study aimed to develop and validate reliable prognostic biomarkers and signature.

METHODS

Differentially expressed genes were identified based on three Gene Expression Omnibus (GEO) datasets. Based on 1052 samples' data from our cohort, GEO and The Cancer Genome Atlas, we explored the relationship of clinicopathological features and NEIL3 expression to determine clinical effect of NEIL3 in LUAD. Western blotting (22 pairs of tumor and normal tissues), Real-time quantitative PCR (19 pairs of tumor and normal tissues), and immunohistochemical analyses (406-tumor tissues subjected to microarray) were conducted. TIMER and ImmuCellAI analyzed relationship between NEIL3 expression and the abundance of tumor-infiltrating immune cells in LUAD. The co-expressed-gene prognostic signature was established based on the Cox regression analysis.

RESULTS

This study identified 502 common differentially expressed genes and confirmed that NEIL3 was significantly overexpressed in LUAD samples (P < 0.001). Increased NEIL3 expression was related to advanced stage, larger tumor size and poor overall survival (p < 0.001) in three LUAD cohorts. The proportions of natural T regulatory cells and induced T regulatory cells increased in the high NEIL3 group, whereas those of B cells, Th17 cells and dendritic cells decreased. Gene set enrichment analysis indicated that NEIL3 may activate cell cycle progression and P53 signaling pathway, leading to poor outcomes. We identified nine prognosis-associated hub genes among 370 genes co-expressed with NEIL3. A 10-gene prognostic signature including NEIL3 and nine key co-expressed genes was constructed. Higher risk-score was correlated with more advanced stage, larger tumor size and worse outcome (p < 0.05). Finally, the signature was verified in test cohort (GSE50081) with superior diagnostic accuracy.

CONCLUSIONS

This study suggested that NEIL3 has the potential to be an immune-related therapeutic target and an independent predictor of LUAD prognosis. We also developed a prognostic signature for LUAD with a precise diagnostic accuracy.

Predicting lung adenocarcinoma prognosis with a novel risk scoring based on platelet-related gene expression

Lung adenocarcinoma is the most common subtype of non-small cell lung cancer, and platelet receptor-related genes are related to its occurrence and progression. A new prognostic indicator based on platelet receptor-related genes was developed with multivariate COX analysis. Prognostic markers based on platelet-related risk score perform moderately in prognosis prediction. The functional annotation of this risk model in high-risk patients shows that the pathways related to cell cycle, glycolysis and platelet-derived related factors are rich. It is worth noting that somatic mutation analysis shows that TTN and MUC16 have higher mutation burdens in high-risk patients. Moreover, the differential genes of high- and low-risk groups are regulated by copy number variation and miRNA. And we provide a free online nomogram web tool based on clinical factors and the risk score (https://wsxzaq.shinyapps.io/wsxzaq_nomogram/). The score has been verified among three independent external cohorts (GSE13213, GSE68465 and GSE72094), and is still an independent risk factor for lung adenocarcinoma. In addition, among the other 6 cancers, the OS prognosis of high and low-risk groups of PRS is different (P < 0.05). Our research results have screened multiple platelet differential genes with clinical significance and constructed a meaningful prognostic risk score (PRS).

Identifying Common Genes Related to Platelet and Immunity for Lung Adenocarcinoma Prognosis Prediction

Background

Although 1000s of immune-related and platelet receptor-related genes have been identified in lung adenocarcinoma, their role in prognosis prediction remains unclear.

Methods

We downloaded mRNA data from the Cancer Genome Atlas Dataset (TCGA), and GSE68465 or GSE14814 data sets from the Gene Expression Omnibus (GEO) database.

Results

The high-risk group’s overall survival (OS) time was lower than that of the low-risk group’s in TCGA (p = 1.15e-03). Additionally, the risk score was an independent prognostic survival factor for lung adenocarcinoma patients in TCGA (HR = 2.136, 95%CI = 1.553–2.937, p < 0.001). The model’s prognostic performance was verified with two independent GEO cohorts (GSE68465 and GSE14814). We also developed a nomogram and provided free webpage prediction tools.¹ The mechanism of the high-risk group in this risk score may be have been related to somatic mutations and copy number changes. In addition, this risk score can distinguish the prognosis of the other two cancers (ACC, p < 0.001 and KIRP, p < 0.001). Also, among the other seven cancers, the OS prognosis for high and low risk groups show wide variation (p < 0.05).

Conclusion

Our research demonstrates that CCNA2 and TGFB2 are potential diagnostic and prognostic biomarkers, as well as therapeutic targets in lung adenocarcinoma (LUAD). We also determined a novel and reliable prognostic score for lung adenocarcinoma prognosis. The online nomogram prediction tool that contains this risk score may also help clinical medical staff.

Screening for genes and subnetworks associated with atypical teratoid/rhabdoid tumors using bioinformatics analysis

Objectives: Atypical teratoid/rhabdoid tumors (AT/RTs) are rare, fast-growing lesions of central nervous system and their prognosis is poor. Nowadays, multimodal managements, including surgery, chemotherapy and radiation therapy are advocated; however, low survival rate and severe neurocognitive toxicity of chemotherapy as well as the irreversible long-term sequelae of irradiation in infants and young children with AT/RTs are alarming. The aim of our study is to provide valid biological information for more tailored advance therapy for these lesions.Methods: Gene expression profile of GSE94349 was downloaded from GEO database and was analyzed using limma R package. Function and enrichment analyses of DEGs were performed based on DAVID database. PPI network construction, hub gene selection and module analysis were conducted in Cytoscape software.Results: In this study, 224 up-regulated genes and 572 down-regulated genes were selected as DEGs. The up-regulated genes were mainly enriched in molecular function and cell component, which mainly included protein binding and nucleus, respectively. The down-regulated DEGs were significantly involved in cell component such as plasma membrane and integral component of membrane. Cell cycle and retrograde endocannabinoid signaling were the main KEGG pathway of up and down DEGs, respectively. CDK1, CCNA2, CDC20, TOP2A were identified as hub genes and two significant network modules were also obtained.Conclusions: Our study may help to further understand the molecular characteristics and provide more tailored targets for future treatment of AT/RTs. Hub genes CDK1, CCNA2, CDC20, TOP2A as well as cell cycle signaling pathway may be new more tailored targets for future treatment of AT/RTs.

PNA Clamping in Nucleic Acid Amplification Protocols to Detect Single Nucleotide Mutations Related to Cancer

This review describes the application of peptide nucleic acids (PNAs) as clamps that prevent nucleic acid amplification of wild-type DNA so that DNA with mutations may be observed. These methods are useful to detect single-nucleotide polymorphisms (SNPs) in cases where there is a small amount of mutated DNA relative to the amount of normal (unmutated/wild-type) DNA. Detecting SNPs arising from mutated DNA can be useful to diagnose various genetic diseases, and is especially important in cancer diagnostics for early detection, proper diagnosis, and monitoring of disease progression. Most examples use PNA clamps to inhibit PCR amplification of wild-type DNA to identify the presence of mutated DNA associated with various types of cancer.

Weighted gene co-expression network analysis identifies CCNA2 as a treatment target of prostate cancer through inhibiting cell cycle

Prostate cancer is a malignant tumor disease that seriously harms the lives of middle-aged and elderly men. Weighted gene co-expression analysis can be used to construct gene co-expression networks to explore gene sets and genes that are significantly correlated with clinical features. In this study, the transcriptome data of prostate cancer on TCGA was analyzed by weighted gene co-expression network, and the gene with a significant correlation with disease Gleason stage and tumor T stage was identified: CCNA2. CCNA2 was significantly associated with biochemical recurrence, disease-free survival and overall survival rate of prostate cancer. The ability of cancer cell proliferation, invasion and metastasis was decreased after down-regulated expression of CCNA2 in prostate cancer cell lines. Flow cytometry revealed that tumor cells were arrested in the S phase after down-regulated the expression of CCNA2. Taken together, we used WGCNA and obtain a gene CCNA2 which is significantly associated with the prognosis of prostate cancer, which may be an indicator of the prognosis of prostate cancer and a new therapeutic target.

Screening and Identification of Potential Prognostic Biomarkers in Adrenocortical Carcinoma

Objective: Adrenocortical carcinoma (ACC) is a rare but aggressive malignant cancer that has been attracting growing attention over recent decades. This study aims to integrate protein interaction networks with gene expression profiles to identify potential biomarkers with prognostic value in silico. Methods: Three microarray data sets were downloaded from the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs) according to the normalization annotation information. Enrichment analyses were utilized to describe biological functions. A protein-protein interaction network (PPI) of the DEGs was developed, and the modules were analyzed using STRING and Cytoscape. LASSO Cox regression was used to identify independent prognostic factors. The Kaplan-Meier method for the integrated expression score was applied to analyze survival outcomes. A receiver operating characteristic (ROC) curve was constructed with area under curve (AUC) analysis to determine the diagnostic ability of the candidate biomarkers. Results: A total of 150 DEGs and 24 significant hub genes with functional enrichment were identified as candidate prognostic biomarkers. LASSO Cox regression suggested that ZWINT, PRC1, CDKN3, CDK1 and CCNA2 were independent prognostic factors in ACC. In multivariate Cox analysis, the integrated expression scores of the modules showed statistical significance in predicting disease-free survival (DFS, P = 0.019) and overall survival (OS, P < 0.001). Meanwhile, ROC curves were generated to validate the ability of the Cox model to predict prognosis. The AUC index for the integrated genes scores was 0.861 (P < 0.0001). Conclusion: In conclusion, the present study identifies DEGs and hub genes that may be involved in poor prognosis and early recurrence of ACC. The expression levels of ZWINT, PRC1, CDKN3, CDK1 and CCNA2 are of high prognostic value, and may help us understand better the underlying carcinogenesis or progression of ACC. Further studies are required to elucidate molecular pathogenesis and alteration in signaling pathways for these genes in ACC.

Identification of key biomarkers and potential molecular mechanisms in lung cancer by bioinformatics analysis

Lung cancer is one of the most widespread neoplasms worldwide. To identify the key biomarkers in its carcinogenesis and development, the mRNA microarray datasets GSE102287, GSE89047, GSE67061 and GSE74706 were obtained from the Gene Expression Omnibus database. GEO2R was used to identify the differentially expressed genes (DEGs) in lung cancer. The Database for Annotation, Visualization and Integrated Discovery was used to analyze the functions and pathways of the DEGs, while the Search Tool for the Retrieval of Interacting Genes/Proteins and Cytoscape were used to obtain the protein-protein interaction (PPI) network. Kaplan Meier curves were used to analyze the effect of the hub genes on overall survival (OS). Module analysis was completed using Molecular Complex Detection in Cytoscape, and one co-expression network of these significant genes was obtained with cBioPortal. A total of 552 DEGs were identified among the four microarray datasets, which were mainly enriched in 'cell proliferation', 'cell growth', 'cell division', 'angiogenesis' and 'mitotic nuclear division'. A PPI network, composed of 44 nodes and 886 edges, was constructed, and its significant module had 16 hub genes in the whole network: Opa interacting protein 5, exonuclease 1, PCNA clamp-associated factor, checkpoint kinase 1, hyaluronan-mediated motility receptor, maternal embryonic leucine zipper kinase, non-SMC condensin I complex subunit G, centromere protein F, BUB1 mitotic checkpoint serine/threonine kinase, cyclin A2, thyroid hormone receptor interactor 13, TPX2 microtubule nucleation factor, nucleolar and spindle associated protein 1, kinesin family member 20A, aurora kinase A and centrosomal protein 55. Survival analysis of these hub genes revealed that they were markedly associated with poor OS in patients with lung cancer. In summary, the hub genes and DEGs delineated in the research may aid the identification of potential targets for diagnostic and therapeutic strategies in lung cancer.

Examining the key genes and pathways in hepatocellular carcinoma development from hepatitis B virus‑positive cirrhosis

To identify the key genes and pathways in the development of hepatocellular carcinoma (HCC) from hepatitis B virus (HBV)-positive liver cirrhosis, differentially expressed genes (DEGs) between HCC and liver cirrhosis tissue samples from the GSE17548 gene expression profile dataset were screened. A total of 1,845 DEGs were identified, including 1,803 upregulated and 42 downregulated genes. Gene Ontology, Kyoto Encyclopedia of Genes and Genomes (KEGG) and protein-protein interaction (PPI) network analyses were performed. It was identified that the ‘cell cycle’ and ‘progesterone-mediated oocyte maturation’ KEGG pathways were significantly enriched in the DEGs. In addition, the high expression of the hub genes from the PPI network (including cyclin dependent kinase 1, cyclin B1, cyclin B2, mitotic arrest deficient 2 like 1, BUB1 mitotic checkpoint serine/threonine kinase and cyclin A2; P=0.00116, 0.00021, 0.04889, 0.00222, 0.00015 and 0.00647, respectively) was associated with a decrease in overall survival for patients with HCC as identified using survival and expression data from The Cancer Genome Atlas. The identified hub genes and pathways may help to elucidate the molecular mechanisms of HCC progression from HBV-positive liver cirrhosis. Additionally, they may be useful as therapeutic targets or serve as novel biomarkers for HCC prognosis prediction.

HOTAIR upregulates an 18-gene cell cycle-related mRNA network in glioma

HOTAIR is a tumor promoting long non-coding RNA (lncRNA) with roles in multiple cancers. However, the role of HOTAIR in glioma has not been well charaterized. Genes that positively correlated with HOTAIR were identified from the Chinese Glioma Genome Atlas and constructed into an interacting network. In total, 18 genes with P-values <0.01 were further extracted and constructed into a subnetwork. Real-time PCR, western blot and immunofluorescence analyses were employed to examine the expression of the genes after HOTAIR overexpression or knockdown. Intracranial glioblastoma multiform (GBM) models were used to test the potential of HOTAIR as a glioma therapy target. It was discovered that the 18 genes that most significantly correlated with HOTAIR expression formed a cell cycle-related mRNA network, which is positively regulated by HOTAIR. Furthermore, HOTAIR knockdown inhibited mouse intracranial GBM model formation. HOTAIR positively regulates a cell cycle-related mRNA network in glioma, and could be a potential therapeutic target for treating glioma.

A polymorphism in the promoter region of PD-L1 serves as a binding-site for SP1 and is associated with PD-L1 overexpression and increased occurrence of gastric cancer

PD-L1 is a member of the B7 family co-inhibitory molecules and plays a critical role in tumor immune escape. In this study, we found a polymorphism rs10815225 in the PD-L1 promoter region was significantly associated with the occurrence of gastric cancer. The GG homozygous frequency was higher in the cancer patients than that in the precancerous lesions, which was higher than that in the health controls. This polymorphism locates in the binding-site of Sp1 transcription factor (SP1). The expression level of PD-L1 mRNA in the GG homozygous cancer patients was apparently higher than that in the GC heterozygotes. Luciferase reporter results showed that SP1 bonded to rs10815225 G-allelic PD-L1 promoter instead of C-allelic. Upregulation and knockdown of SP1 resulted in elevation and attenuation of PD-L1 in SGC-7901 cells, respectively. The chromatin immunoprecipitation results further confirmed the binding of SP1 to the promoter of PD-L1. Additionally, rs10815225 was found to be in disequilibrium with a functional polymorphism rs4143815 in the PD-L1 3'-UTR, and the haplotypes of these two polymorphisms were also markedly related to gastric cancer risk. These results revealed a novel mechanism underlying genetic polymorphisms influencing PD-L1 expression modify gastric cancer susceptibility.

PCR-Based Detection Methods for Single-Nucleotide Polymorphism or Mutation: Real-Time PCR and Its Substantial Contribution Toward Technological Refinement

Single-nucleotide polymorphisms (SNPs) and single-nucleotide mutations result from the substitution of only a single base. The SNP or mutation can be relevant to disease susceptibility, pathogenesis of disease, and efficacy of specific drugs. It is important to detect SNPs or mutations clinically. Methods to distinguish/detect SNPs or mutations should be highly specific and sensitive. In this regard, polymerase chain reaction (PCR) has provided the necessary analytical performance for many molecular analyses. PCR-based methods for SNP/mutation detection are broadly categorized into two types-(1) polymorphic or mutant allele-directed specific analysis using primers matched with substituted nucleotide or using oligonucleotides to block or clamp the nontargeted template, and (2) melting curve analysis, which is combined with the real-time PCR techniques using hydrolysis probes, hybridization probes, or double-stranded DNA-binding fluorescent dyes. Innovative and novel approaches as well as technical improvements have made SNP- or mutation-detection methods increasingly more sophisticated. These advances include DNA/RNA preparation and subsequent amplification steps, and miniaturization of PCR instruments such that testing may be performed with relative ease in clinical laboratories or as a point-of-care test in clinical settings.

Screening for genes and subnetworks associated with pancreatic cancer based on the gene expression profile

The present study aimed to screen for potential genes and subnetworks associated with pancreatic cancer (PC) using the gene expression profile. The expression profile GSE 16515 was downloaded from the Gene Expression Omnibus database, which included 36 PC tissue samples and 16 normal samples. Limma package in R language was used to screen differentially expressed genes (DEGs), which were grouped as up‑ and downregulated genes. Then, PFSNet was applied to perform subnetwork analysis for all the DEGs. Moreover, Gene Ontology (GO) and REACTOME pathway enrichment analysis of up‑ and downregulated genes was performed, followed by protein‑protein interaction (PPI) network construction using Search Tool for the Retrieval of Interacting Genes Search Tool for the Retrieval of Interacting Genes. In total, 1,989 DEGs including 1,461 up‑ and 528 downregulated genes were screened out. Subnetworks including pancreatic cancer in PC tissue samples and intercellular adhesion in normal samples were identified, respectively. A total of 8 significant REACTOME pathways for upregulated DEGs, such as hemostasis and cell cycle, mitotic were identified. Moreover, 4 significant REACTOME pathways for downregulated DEGs, including regulation of β‑cell development and transmembrane transport of small molecules were screened out. Additionally, DEGs with high connectivity degrees, such as CCNA2 (cyclin A2) and PBK (PDZ binding kinase), of the module in the protein‑protein interaction network were mainly enriched with cell‑division cycle. CCNA2 and PBK of the module and their relative pathway cell‑division cycle, and two subnetworks (pancreatic cancer and intercellular adhesion subnetworks) may be pivotal for further understanding of the molecular mechanism of PC.

Genome-wide association study follow-up identifies cyclin A2 as a regulator of the transition through cytokinesis during terminal erythropoiesis

Genome-wide association studies (GWAS) hold tremendous promise to improve our understanding of human biology. Recent GWAS have revealed over 75 loci associated with erythroid traits, including the 4q27 locus that is associated with red blood cell size (mean corpuscular volume). The close linkage disequilibrium block at this locus harbors the CCNA2 gene that encodes cyclin A2. CCNA2 mRNA is highly expressed in human and murine erythroid progenitor cells and regulated by the essential erythroid transcription factor GATA1. To understand the role of cyclin A2 in erythropoiesis, we have reduced expression of this gene using short hairpin RNAs in a primary murine erythroid culture system. We demonstrate that cyclin A2 levels affect erythroid cell size by regulating the passage through cytokinesis during the final cell division of terminal erythropoiesis. Our study provides new insight into cell cycle regulation during terminal erythropoiesis and more generally illustrates the value of functional GWAS follow-up to gain mechanistic insight into hematopoiesis.

TRAIL pathway is associated with inhibition of colon cancer by protopanaxadiol

Among important components of American ginseng, protopanaxadiol (PPD) showed more active anticancer potential than other triterpenoid saponins. In this study, we determined the in vivo effects of PPD in a mouse cancer model first. Then, using human colorectal cancer cell lines, we observed significant cancer cell growth inhibition by promoting G1 cell cycle redistribution and apoptosis. Subsequently, we characterized the downstream genes targeted by PPD in HCT-116 cancer cells. Using Affymetrix high density GeneChips, we obtained the gene expression profile of the cells. Microarray data indicated that the expression levels of 76 genes were changed over two-fold after PPD, of which 52 were upregulated while the remaining 24 were downregulated. Ingenuity pathway analysis of top functions affected was carried out. Data suggested that by regulating the interactions between p53 and DR4/DR5, the tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) pathway played a key role in the action of PPD, a promising colon cancer inhibitory compound.

Preclinical evaluation of transcriptional targeting strategy for human hepatocellular carcinoma in an orthotopic xenograft mouse model

Gene regulation of many key cell-cycle players in S-, G(2) phase, and mitosis results from transcriptional repression in their respective promoter regions during the G(0) and G(1) phases of cell cycle. Within these promoter regions are phylogenetically conserved sequences known as the cell-cycle-dependent element (CDE) and cell-cycle genes homology regions (CHR) sites. Thus, we hypothesize that transcriptional regulation of cell-cycle regulation via the CDE/CHR region together with liver-specific apolipoprotein E (apoE)-hAAT promoter could bring about a selective transgene expression in proliferating human hepatocellular carcinoma. We show that the newly generated vector AH-6CC-L2C could mediate hepatocyte-targeted luciferase gene expression in tumor cells and freshly isolated short-term hepatocellular carcinoma cultures from patient biopsy. In contrast, normal murine and human hepatocytes infected with AH-6CC-L2C expressed minimal or low luciferase activities. In the presence of prodrug 5-fluorocytosine (5-FC), AH-6CC-L2C effectively suppressed the growth of orthotopic hepatocellular carcinoma patient-derived xenograft mouse model via the expression of yeast cytosine deaminase (yCD) that converts 5-FC to anticancer metabolite 5-fluoruracil. More importantly, we show that combination treatment of AH-6CC-L2C with an EZH2 inhibitor, DZNep, that targets EpCAM-positive hepatocellular carcinoma, can bring about a greater therapeutic efficacy compared with a single treatment of virus or inhibitor. Our study showed that targeting proliferating human hepatocellular carcinoma cells through the transcriptional control of therapeutic gene could represent a feasible approach against hepatocellular carcinoma.

Novel high-speed droplet-allele specific-polymerase chain reaction: application in the rapid genotyping of single nucleotide polymorphisms

BACKGROUND

Single nucleotide alterations such as single nucleotide polymorphisms (SNP) and single nucleotide mutations are associated with responses to drugs and predisposition to several diseases, and they contribute to the pathogenesis of malignancies. We developed a rapid genotyping assay based on the allele-specific polymerase chain reaction (AS-PCR) with our droplet-PCR machine (droplet-AS-PCR).

METHODS

Using 8 SNP loci, we evaluated the specificity and sensitivity of droplet-AS-PCR. Buccal cells were pretreated with proteinase K and subjected directly to the droplet-AS-PCR without DNA extraction. The genotypes determined using the droplet-AS-PCR were then compared with those obtained by direct sequencing.

RESULTS

Specific PCR amplifications for the 8 SNP loci were detected, and the detection limit of the droplet-AS-PCR was found to be 0.1-5.0% by dilution experiments. Droplet-AS-PCR provided specific amplification when using buccal cells, and all the genotypes determined within 9 min were consistent with those obtained by direct sequencing.

CONCLUSIONS

Our novel droplet-AS-PCR assay enabled high-speed amplification retaining specificity and sensitivity and provided ultra-rapid genotyping. Crude samples such as buccal cells were available for the droplet-AS-PCR assay, resulting in the reduction of the total analysis time. Droplet-AS-PCR may therefore be useful for genotyping or the detection of single nucleotide alterations.

Haploinsufficiency of Tumor Suppressor Genes is Driven by the Cumulative Effect of microRNAs, microRNA Binding Site Polymorphisms and microRNA Polymorphisms: An In silico Approach

Haploinsufficiency of tumor suppressor genes, wherein the reduced production and activity of proteins results in the inability of the cell to maintain normal cellular function, is one among the various causes of cancer. However the precise molecular mechanisms underlying this condition remain unclear. Here we hypothesize that single nucleotide polymorphisms (SNPs) in the 3′untranslated region (UTR) of mRNAs and microRNA seed sequence (miR-SNPs) may cause haploinsufficiency at the level of proteins through altered binding specificity of microRNAs (miRNAs). Bioinformatics analysis of haploinsufficient genes for variations in their 3′UTR showed that the occurrence of SNPs result in the creation of new binding sites for miRNAs, thereby bringing the respective mRNA variant under the control of more miRNAs. In addition, 19 miR-SNPs were found to result in non-specific binding of microRNAs to tumor suppressors. Networking analysis suggests that the haploinsufficient tumor suppressor genes strongly interact with one another, and any subtle alterations in this network will contribute to tumorigenesis.

Expression of PRPF31 and TFPT: regulation in health and retinal disease

PRPF31, a gene located at chromosome 19q13.4, encodes the ubiquitous splicing factor PRPF31. The gene lies in a head-to-head arrangement with TFPT, a poorly characterized gene with a role in cellular apoptosis. Mutations in PRPF31 have been implicated in autosomal dominant retinitis pigmentosa (adRP), a frequent and important cause of blindness worldwide. Disease associated with PRPF31 mutations is unusual, in that there is often non-penetrance of the disease phenotype in affected families, caused by differential expression of PRPF31. This study aimed to characterize the basic promoter elements of PRPF31 and TFPT. Luciferase reporter constructs were made, using genomic DNA from an asymptomatic individual with a heterozygous deletion of the entire putative promoter region. Fragments were tested by the dual-luciferase reporter assay in HeLa and RPE-1 cell lines. A comparison was made between the promoter regions of symptomatic and asymptomatic mutation-carrying individuals. A patient (CAN493) with adRP was identified, harbouring a regulatory region mutation; both alleles were assayed by the dual-luciferase reporter assay. Luciferase assays led to the identification of core promoters for both PRPF31 and TFPT; despite their shared gene architecture, the two genes appear to be controlled by slightly different regulatory regions. One functional polymorphism was identified in the PRPF31 promoter that increased transcriptional activation. The change was not, however, consistent with the observed symptomatic-asymptomatic phenotypes in a family affected by PRPF31-adRP. Analysis of the mutant promoter fragment from CAN493 showed a >50% reduction in promoter activity, suggesting a disease mechanism of functional haploinsufficiency-the first report of this disease mechanism in adRP.