The expression of embryonic liver development genes in hepatitis C induced cirrhosis and hepatocellular carcinoma

Construction and validation of a prognostic model based on ten signature cell cycle-related genes for early-stage lung squamous cell carcinoma

BACKGROUND

We performed a bioinformatics analysis to screen for cell cycle-related differentially expressed genes (DEGs) and constructed a model for the prognostic prediction of patients with early-stage lung squamous cell carcinoma (LSCC).

METHODS

From a gene expression omnibus (GEO) database, the GSE157011 dataset was randomly divided into an internal training group and an internal testing group at a 1:1 ratio, and the GSE30219, GSE37745, GSE42127, and GSE73403 datasets were merged as the external validation group. We performed single-sample gene set enrichment analysis (ssGSEA), univariate Cox analysis, and difference analysis, and identified 372 cell cycle-related genes. Additionally, we combined LASSO/Cox regression analysis to construct a prognostic model. Then, patients were divided into high-risk and low-risk groups according to risk scores. The internal testing group, discovery set, and external verification set were used to assess model reliability. We used a nomogram to predict patient prognoses based on clinical features and risk values. Clinical relevance analysis and the Human Protein Atlas (HPA) database were used to verify signature gene expression.

RESULTS

Ten cell cycle-related DEGs (EIF2B1, FSD1L, FSTL3, ORC3, HMMR, SETD6, PRELP, PIGW, HSD17B6, and GNG7) were identified and a model based on the internal training group constructed. From this, patients in the low-risk group had a higher survival rate when compared with the high-risk group. Time-dependent receiver operating characteristic (tROC) and Cox regression analyses showed the model was efficient and accurate. Clinical relevance analysis and the HPA database showed that DEGs were significantly dysregulated in LSCC tissue.

CONCLUSION

Our model predicted the prognosis of early-stage LSCC patients and demonstrated potential applications for clinical decision-making and individualized therapy.

Hsa-miR-422a Originated from Short Interspersed Nuclear Element Increases ARID5B Expression by Collaborating with NF-E2

MicroRNAs (miRNAs) are a class of small non-coding RNAs that regulate the expression of target messenger RNA (mRNA) complementary to the 3' untranslated region (UTR) at the post-transcriptional level. Hsa-miR-422a, which is commonly known as miRNA derived from transposable element (MDTE), was derived from short interspersed nuclear element (SINE). Through expression analysis, hsa-miR-422a was found to be highly expressed in both the small intestine and liver of crab-eating monkey. AT-Rich Interaction Domain 5 B (ARID5B) was selected as the target gene of hsa-miR-422a, which has two binding sites in both the exon and 3'UTR of ARID5B. To identify the interaction between hsa-miR-422a and ARID5B, a dual luciferase assay was conducted in HepG2 cell line. The luciferase activity of cells treated with the hsa-miR-422a mimic was upregulated and inversely downregulated when both the hsa-miR-422a mimic and inhibitor were administered. Nuclear factor erythroid-2 (NF-E2) was selected as the core transcription factor (TF) via feed forward loop analysis. The luciferase expression was downregulated when both the hsa-miR-422a mimic and siRNA of NF-E2 were treated, compared to the treatment of the hsa-miR-422a mimic alone. The present study suggests that hsa-miR-422a derived from SINE could bind to the exon region as well as the 3'UTR of ARID5B. Additionally, hsa-miR-422a was found to share binding sites in ARID5Bwith several TFs, including NF-E2. The hsa-miR-422a might thus interact with TF to regulate the expression of ARID5B, as demonstrated experimentally. Altogether, hsa-miR-422a acts as a super enhancer miRNA of ARID5Bby collaborating with TF and NF-E2.

Transcription factor Atf1-dependent degradation of the mitotic cyclin Cdc13 is regulated by multiple factors in Schizosaccharomyces pombe

The bZIP transcription factor Atf1 is a key player in the transcriptional program of the Schizosaccharomyces pombe cell cycle. It also controls both the synthesis and degradation of the mitotic cyclin Cdc13. Temporal regulation of these opposing functions of Atf1 is critical for the fidelity of cell division. Our investigations revealed that an increase in activity of the mitogen-activated protein kinase (MAPK) Spc1 during mitotic exit and the consequent phosphorylation of Atf1 along with the prevailing high activity of cyclin-dependent kinase Cdc2 regulates Cdc13 degradation. Our results also indicate the possibility of a complex interplay between Cdc2 inhibitory kinase Wee1, the anaphase promoting complex and Atf1 during mitotic exit. These observations provide evidence of new regulatory mechanisms of mitotic exit.

Modelling liver cancer microenvironment using a novel 3D culture system

The tumor microenvironment and its contribution to tumorigenesis has been a focal highlight in recent years. A two-way communication between the tumor and the surrounding microenvironment sustains and contributes to the growth and metastasis of tumors. Progression and metastasis of hepatocellular carcinoma (HCC) have been reported to be exceedingly influenced by diverse microenvironmental cues. In this study, we present a 3D-culture model of liver cancer to better mimic in vivo tumor settings. By creating novel 3D co-culture model that combines free-floating and scaffold-based 3D-culture techniques of liver cancer cells and fibroblasts, we aimed to establish a simple albeit reproducible ex vivo cancer microenvironment model that captures tumor-stroma interactions. The model presented herein exhibited unique gene expression and protein expression profiles when compared to 2D and 3D mono-cultures of liver cancer cells. Our results showed that in vivo like conditions cannot be mimicked by simply growing cancer cells as spheroids, but by co-culturing them with 3D fibroblast with which they were able to crosstalk. This was evident by the upregulation of several pathways involved in HCC, and the increase in secreted factors by co-cultured cancer cells, many of which are also involved in tumor-stroma interactions. Compared to the conventional 2D culture, the proposed model exhibits an increase in the expression of genes associated with development, progression, and poor prognosis of HCC. Our results correlated with an aggressive outcome that better mirrors in vivo HCC, and therefore, a more reliable platform for molecular understanding of HCC.

Inhibition of FSTL3 abates the proliferation and metastasis of renal cell carcinoma via the GSK-3β/β-catenin signaling pathway

Renal cell carcinoma (RCC) is a lethal malignancy of the genitourinary system. Follistatin-like 3 (FSTL3), which mediates cell differentiation and growth, acts as a biomarker of tumors and participates in cancer development and progression. Presently, the FSTL3’s functions in RCC were investigated. Quantitative reverse transcription PCR (qRT-PCR), Western Blot, and enzyme linked immunosorbent assay (ELISA) were conducted to verify FSTL3 expression in RCC tissues and cell lines. BrdU assay and CCK8 experiment were made to monitor cell proliferation. Transwell was implemented to examine the invasion of the cells. Flow cytometry analyzed cell apoptosis, and Western Blot evaluated the protein levels of E-cadherin, Twist, and Slug. In the meantime, the protein profiles of the GSK-3β, β-catenin, and TGF-β signaling pathways were ascertained. Moreover, the Xenograft tumor model was constructed in nude mice for measuring tumor growth in vivo. The statistics showed that FSTL3 presented an overexpression in RCC, and patients with a lower expression of FSTL3 manifested a better prognosis. Down-regulated FSTL3 hampered the proliferation, invasion, EMT, and tumor growth of RCC cells and caused cell apoptosis. On the contrary, FSTL3 overexpression enhanced the malignant behaviors of RCC cells. Furthermore, FSTL3 knockdown bolstered GSK-3β, suppressed β-catenin, and reduced BMP1-SMAD pathway activation. Inhibited β-catenin substantially mitigated FSTL3-mediated promoting functions in RCC. In short, FSTL3 functions as an oncogene in RCC by modulating the GSK-3β/β-catenin signaling pathway.

Up-Regulation of FSTL3, Regulated by lncRNA DSCAM-AS1/miR-122-5p Axis, Promotes Proliferation and Migration of Non-Small Cell Lung Cancer Cells

Background

Follistatin-like 3 (FSTL3) binds and inactivates activin, a growth factor with cell growth and differentiation. Previous studies reported that it is overexpressed in invasive breast cancers, and its expression and function in non-small cell lung cancer (NSCLC) remain unclear.

Materials and Methods

Immunohistochemistry was employed to probe the expression of FSTL3 in NSCLC tissues. Real-time PCR (RT-PCR) was applied to detect the expression of lncRNA DSCAM-AS1 and miR-122-5p. A549 cells and H1299 cells were used as cell models. The biological influence of FSTL3 on cells was studied using CCK-8 assay, wound healing assay and transwell assay in vitro, respectively. In vivo subcutaneous xenotransplanted tumor model and tail vein injection model in mice were also constructed to validate the roles of FSTL3. Interactions between miR-122-5p and FSTL3, DSCAM-AS1 and miR-122-5p were determined by bioinformatics analysis, RT-PCR, and dual-luciferase reporter assay.

Results

FSTL3 and DSCAM-AS1 were remarkably up-regulated in NSCLC samples, and miR-122-5p was down-regulated. FSTL3 was associated with worse prognosis of NSCLC patients. FSTL3 knockdown markedly inhibited the viability, migration and invasion of NSCLCs in vitro and in vivo. DSCAM-AS1 could down-regulate miR-122-5p via sponging it, and FSTL3 was a target gene of miR-122-5p.

Conclusion

Taken together, our study identified that FSTL3 was a new oncogene of NSCLC, which was regulated by DSCAM-AS1 and miR-122-5p. These findings suggested that FSTL3, DSCAM-AS1 and miR-122-5p might serve as a new valuable therapeutic target for NSCLC.

Uncovering the potential differentially expressed miRNAs as diagnostic biomarkers for hepatocellular carcinoma based on machine learning in The Cancer Genome Atlas database

The present study aimed to identify novel diagnostic differentially expressed microRNAs (miRNAs/miRs) in order to understand the molecular mechanisms underlying hepatocellular carcinoma. The expression data of miRNA and mRNA were downloaded for differential expression analysis. Optimal diagnostic differentially expressed miRNA biomarkers were identified via a random forest algorithm. Classification models were established to distinguish patients with hepatocellular carcinoma and normal individuals. A regulatory network between optimal diagnostic differentially expressed miRNA and differentially expressed mRNAs was then constructed. The GSE63046 dataset and in vitro experiments were used to validate the expression of the optimal diagnostic differentially expressed miRNAs identified. In addition, diagnostic and prognostic analyses of optimal diagnostic differentially expressed miRNAs were performed. In total, 14 differentially expressed miRNAs (all upregulated) and 2,982 differentially expressed mRNAs (1,989 upregulated and 993 downregulated) were identified. hsa-miR-10b-5p, hsa-miR-10b-3p, hsa-miR-224-5p, hsa-miR-183-5p and hsa-miR-182-5p were considered as the optimal diagnostic biomarkers for hepatocellular carcinoma. The mRNAs targeted by these five miRNAs included secreted frizzled related protein 1 (SFRP1), endothelin receptor type B (EDNRB), nuclear receptor subfamily 4 group A member 3 (NR4A3), four and a half LIM domains 2 (FHL2), NK3 homeobox 1 (NKX3-1), interleukin 6 signal transducer (IL6ST) and forkhead box O1 (FOXO1). ‘Bile acid biosynthesis and cholesterol’ was the most enriched signaling pathways of these target mRNAs. The expression validation of the five miRNAs was consistent with the present bioinformatics analysis. Notably, hsa-miR-10b-5p and hsa-miR-10b-3p had a significant prognosis value for patients with hepatocellular carcinoma. In conclusion, the five differentially expressed miRNAs may be considered as diagnostic biomarkers for patients with hepatocellular carcinoma. In addition, the differential expression levels of the targets of these five mRNAs, including SFRP1, EDNRB, NR4A3, FHL2, NKX3−1, IL6ST and FOXO1, may be involved in hepatocellular carcinoma tumorigenesis.

Circulating tumor DNA/circulating tumor cells and the applicability in different causes induced hepatocellular carcinoma

In 2015, liquid biopsy was rated one of the top 10 breakthrough technologies of the year by MIT Technology Review. Liquid biopsy is a type of in vitro diagnostic method involving a noninvasive blood test. It is also a breakthrough technology used to detect tumors and cancers and assist in therapeutic strategies. The most widely used markers are circulating tumor cells (CTCs) and circulating tumor DNA (ctDNA). Primary carcinoma of the liver is a malignancy of hepatocytes or intrahepatic biliary epithelial cells. The most common type of liver cancer is hepatocellular carcinoma (HCC), the causes of which mainly include infection with hepatitis B virus (HBV) and/or hepatitis C virus (HCV), alcohol abuse, aflatoxicosis, and nonalcoholic fatty liver disease/ nonalcoholic steatohepatitis. As there are few typical clinical characteristics during the early stage of the disease, early diagnosis of HCC is very challenging. However, CTCs and ctDNA carry tumor-specific information. Therefore, the detection and analysis of CTCs and ctDNA can provide evidence for the early diagnosis of HCC and guide treatment. Furthermore, several studies have indicated that different inducers of HCC cause different DNA mutations, and accordingly, detection of specific mutations in ctDNA will facilitate the determination of the HCC type and help physicians provide distinctive therapies.

Dickkopf-1 and Amphiregulin as Novel Biomarkers and Potential Therapeutic Targets in Hepatocellular Carcinoma

Background: Hepatocellular carcinoma (HCC) is a highly fatal tumor which represents a major health problem worldwide. Due to asymptomatic nature of HCC, most patients present with the progressive stage of disease, so, unfortunately, there are no effective therapies. Existing techniques for HCC surveillance and diagnosis lack the required accuracy. Therefore, searching for new diagnostic and/or therapeutic tools could improve patient survival. This study aimed to estimate the diagnostic role of Dickkopf-1 (DKK1) and amphiregulin (AREG) and to find out their correlation with different clinicopathological parameters in HCC patients. Materials and Methods: Serum levels of DKK1 and AREG in 55 HCC patients, 20 cirrhotic patients, and 15 healthy subjects as control group were measured using the ELISA technique. Results: Both of DKK1 and AREG showed a significant increase in the HCC group compared to cirrhotic and healthy groups. DKK1 at a cutoff point of 8.92 ng/ml showed that the area under the curve (AUC) was 0.826 with 87.3% sensitivity and 82.9% specificity. DKK1 showed a significant correlation with tumor size, liver dysfunction, and poor performance status in HCC patients. AREG at a cutoff point of 8.74 pg/ml showed a sensitivity of 74.5% but low specificity (47.1%). AREG showed a significant correlation with portal vein thrombosis and tumor metastasis in HCC patients. Conclusion: Serum DKK1 could be a diagnostic biomarker for HCC. Both of DKK1 and AREG may play significant roles in tumor progression and may offer promising therapeutic targets in HCC patients.

Association of FHIT expression and FHIT gene hypermethylation with liver cancer risk: a PRISMA-compliant meta-analysis

Background

There have been suggestions that fragile histidine triad protein (FHIT) expression and FHIT gene hypermethylation were crucial to the pathogenesis of liver cancer. However, the conclusions remained unclear because of small sample size, disease subtype, and different detection techniques. Therefore, we performed a meta-analysis to estimate the associations of FHIT expression and FHIT gene hypermethylation with liver cancer pathogenesis.

Methods

Studies that were published in electronic databases, such as PubMed, Web of Knowledge, China National Knowledge Infrastructure (CNKI), VIP, and WanFang, were retrieved and selected for the meta-analysis. Relative risk (RR) and 95% confidence interval (CI) were calculated to determine the correlations of FHIT expression and FHIT gene hyper-methylation with liver cancer pathogenesis with Stata 12.0 software.

Results

A total of 17 papers that evaluated the associations of FHIT expression (14 articles) and FHIT gene methylation (3 articles) with liver cancer pathogenesis were included in this meta-analysis. In the overall analysis, the pooled relative risk was 1.93 (95% CI =1.72–2.17), which indicated a significant association between FHIT low expression and liver cancer risk. According to the results of clinical information, there were significant associations of FHIT expression with TNM-stage (RR =2.13, 95% CI =1.72–2.64), tumor size (RR =1.67, 95% CI =1.36–2.05), and merger of cirrhosis (RR =1.34, 95% CI =1.06–1.69) of liver cancer in the Chinese population. In addition, the FHIT gene hypermethylation was significantly associated with the risk of liver cancer (RR =1.45, 95% CI =1.08–1.93).

Conclusion

The FHIT expression and hypermethylation of FHIT gene were significantly associated with the risk of liver cancer, especially in the Chinese population. Furthermore, the results indicated significant associations between FHIT low expression and TNM-stage, tumor size, and merging of cirrhosis of liver cancer in the Chinese population.

ATF2, a paradigm of the multifaceted regulation of transcription factors in biology and disease

Stringent transcriptional regulation is crucial for normal cellular biology and organismal development. Perturbations in the proper regulation of transcription factors can result in numerous pathologies, including cancer. Thus, understanding how transcription factors are regulated and how they are dysregulated in disease states is key to the therapeutic targeting of these factors and/or the pathways that they regulate. Activating transcription factor 2 (ATF2) has been studied in a number of developmental and pathological conditions. Recent findings have shed light on the transcriptional, post-transcriptional, and post-translational regulatory mechanisms that influence ATF2 function, and thus, the transcriptional programs coordinated by ATF2. Given our current knowledge of its multiple levels of regulation and function, ATF2 represents a paradigm for the mechanistic complexity that can regulate transcription factor function. Thus, increasing our understanding of the regulation and function of ATF2 will provide insights into fundamental regulatory mechanisms that influence how cells integrate extracellular and intracellular signals into a genomic response through transcription factors. Characterization of ATF2 dysfunction in the context of pathological conditions, particularly in cancer biology and response to therapy, will be important in understanding how pathways controlled by ATF2 or other transcription factors might be therapeutically exploited. In this review, we provide an overview of the currently known upstream regulators and downstream targets of ATF2.

Regulation of hepatocyte identity and quiescence

The liver is a highly differentiated organ with a central role in metabolism, detoxification and systemic homeostasis. To perform its multiple tasks, liver parenchymal cells, the hepatocytes, express a large complement of enabling genes defining their complex phenotype. This phenotype is progressively acquired during fetal development and needs to be maintained in adulthood to guarantee the individual's survival. Upon injury or loss of functional mass, the liver displays an extraordinary regenerative response, mainly based on the proliferation of hepatocytes which otherwise are long-lived quiescent cells. Increasing observations suggest that loss of hepatocellular differentiation and quiescence underlie liver malfunction in chronic liver disease and pave the way for hepatocellular carcinoma development. Here, we briefly review the essential mechanisms leading to the acquisition of liver maturity. We also identify the key molecular factors involved in the preservation of hepatocellular homeostasis and finally discuss potential strategies to preserve liver identity and function.

Epigenetic biomarkers in liver cancer

Liver cancer (hepatocellular carcinoma or HCC) is a major cancer worldwide. Research in this field is needed to identify biomarkers that can be used for early detection of the disease as well as new approaches to its treatment. Epigenetic biomarkers provide an opportunity to understand liver cancer etiology and evaluate novel epigenetic inhibitors for treatment. Traditionally, liver cirrhosis, proteomic biomarkers, and the presence of hepatitis viruses have been used for the detection and diagnosis of liver cancer. Promising results from microRNA (miRNA) profiling and hypermethylation of selected genes have raised hopes of identifying new biomarkers. Some of these epigenetic biomarkers may be useful in risk assessment and for screening populations to identify who is likely to develop cancer. Challenges and opportunities in the field are discussed in this chapter.

Splicing regulator SLU7 is essential for maintaining liver homeostasis

A precise equilibrium between cellular differentiation and proliferation is fundamental for tissue homeostasis. Maintaining this balance is particularly important for the liver, a highly differentiated organ with systemic metabolic functions that is endowed with unparalleled regenerative potential. Carcinogenesis in the liver develops as the result of hepatocellular de-differentiation and uncontrolled proliferation. Here, we identified SLU7, which encodes a pre-mRNA splicing regulator that is inhibited in hepatocarcinoma, as a pivotal gene for hepatocellular homeostasis. SLU7 knockdown in human liver cells and mouse liver resulted in profound changes in pre-mRNA splicing and gene expression, leading to impaired glucose and lipid metabolism, refractoriness to key metabolic hormones, and reversion to a fetal-like gene expression pattern. Additionally, loss of SLU7 also increased hepatocellular proliferation and induced a switch to a tumor-like glycolytic phenotype. Slu7 governed the splicing and/or expression of multiple genes essential for hepatocellular differentiation, including serine/arginine-rich splicing factor 3 (Srsf3) and hepatocyte nuclear factor 4α (Hnf4α), and was critical for cAMP-regulated gene transcription. Together, out data indicate that SLU7 is central regulator of hepatocyte identity and quiescence.