Downregulation of Rap1 promotes 5-fluorouracil-induced apoptosis in hepatocellular carcinoma cell line HepG2

Decoding the possible mechanism of action of Paeoniflorigenone in combating Aflatoxin B1-induced liver cancer: an investigation using network pharmacology and bioinformatics analysis

Moutan cortex has demonstrated antitumor properties attributed to its bioactive compound Paeoniflorigenone (PA). Nevertheless, there is limited research on the efficacy of PA in the prevention and treatment of hepatocellular carcinoma (HCC). We aimed to investigate the potential pharmacological mechanisms of PA in the treatment of Aflatoxin B1 (AFB1)-induced hepatocarcinogenesis using network pharmacology and bioinformatics analysis approaches. Through various databases and bioinformatics analysis approaches, 34 shared targets were identified as potential candidate genes for PA in fighting liver cancer caused by AFB1. Pathway analysis revealed involvement in cell cycle, HIF-1, and Rap1 pathways. A risk assessment model was developed using LASSO regression, showing an association between the identified genes and the tumor immune microenvironment. The genes within the risk model were found to be linked to the immune response in liver cancer. Molecular docking studies indicated that PA interacts with its targets through hydrogen bonding and hydrophobic interactions. This study provides insights into the possible mechanisms of PA in liver cancer treatment and offers a predictive model for assessing the risk level of individuals with liver cancer. These findings have significant implications for the therapeutic strategies in managing liver cancer patients.

Methylation-regulated tumor suppressor gene PDE7B promotes HCC invasion and metastasis through the PI3K/AKT signaling pathway

BACKGROUND

Hepatocellular carcinoma (HCC) has a high mortality rate, and the mechanisms underlying tumor development and progression remain unclear. However, inactivated tumor suppressor genes might play key roles. DNA methylation is a critical regulatory mechanism for inactivating tumor suppressor genes in HCC. Therefore, this study investigated methylation-related tumor suppressors in HCC to identify potential biomarkers and therapeutic targets.

METHODS

We assessed genome-wide DNA methylation in HCC using whole genome bisulfite sequencing (WGBS) and RNA sequencing, respectively, and identified the differential expression of methylation-related genes, and finally screened phosphodiesterase 7B (PDE7B) for the study. The correlation between PDE7B expression and clinical features was then assessed. We then analyzed the changes of PDE7B expression in HCC cells before and after DNA methyltransferase inhibitor treatment by MassArray nucleic acid mass spectrometry. Furthermore, HCC cell lines overexpressing PDE7B were constructed to investigate its effect on HCC cell function. Finally, GO and KEGG were applied for the enrichment analysis of PDE7B-related pathways, and their effects on the expression of pathway proteins and EMT-related factors in HCC cells were preliminarily explored.

RESULTS

HCC exhibited a genome-wide hypomethylation pattern. We screened 713 hypomethylated and 362 hypermethylated mCG regions in HCC and adjacent normal tissues. GO analysis showed that the main molecular functions of hypermethylation and hypomethylation were "DNA-binding transcriptional activator activity" and "structural component of ribosomes", respectively, whereas KEGG analysis showed that they were enriched in "bile secretion" and "Ras-associated protein-1 (Rap1) signaling pathway", respectively. PDE7B expression was significantly down-regulated in HCC tissues, and this low expression was negatively correlated with recurrence and prognosis of HCC. In addition, DNA methylation regulates PDE7B expression in HCC. On the contrary, overexpression of PDE7B inhibited tumor proliferation and metastasis in vitro. In addition, PDE7B-related genes were mainly enriched in the PI3K/ATK signaling pathway, and PDE7B overexpression inhibited the progression of PI3K/ATK signaling pathway-related proteins and EMT.

CONCLUSION

PDE7B expression in HCC may be regulated by promoter methylation. PDE7B can regulate the EMT process in HCC cells through the PI3K/AKT pathway, which in turn affects HCC metastasis and invasion.

Downregulating miR-184 relieves calcium oxalate crystal-mediated renal cell damage via activating the Rap1 signaling pathway

BACKGROUND

Renal calculi are a very prevalent disease with a high incidence. Calcium oxalate (CaOx) is a primary constituent of kidney stones. Our paper probes the regulatory function and mechanism of miR-184 in CaOx-mediated renal cell damage.

METHODS

CaOx was used to treat HK2 cells and human podocytes (HPCs) to simulate kidney cell damage. The qRT-PCR technique checked the profiles of miR-184 and IGF1R. The examination of cell proliferation was conducted employing CCK8. TUNEL staining was used to monitor cell apoptosis. Western blot analysis was used to determine the protein profiles of apoptosis-concerned related proteins (including Mcl1, Bcl-XL, and Caspase-3), the NF-κB, Nrf2/HO-1, and Rap1 signaling pathways. ELISA confirmed the levels of the inflammatory factors IL-6, TNF-α, MCP1, and ICAM1. The targeting relationship between miR-184 and IGF1R was validated by dual luciferase assay and RNA immunoprecipitation assay.

RESULTS

Glyoxylate-induced rat kidney stones model and HK2 and HPC cells treated with CaOx demonstrated an increase in the miR-184 profile. Inhibiting miR-184 relieved CaOx-mediated renal cell inflammation, apoptosis and oxidative stress and activated the Rap1 pathway. IGF1R was targeted by miR-184. IGF1R activation by IGF1 attenuated the effects of miR-184 on renal cell damage, and Hippo pathway suppression reversed the inhibitory effect of miR-184 knockdown on renal cell impairment.

CONCLUSIONS

miR-184 downregulation activates the Rap1 signaling pathway to ameliorate renal cell damage mediated by CaOx.

Prediction of liver cancer prognosis based on immune cell marker genes

Introduction

Monitoring the response after treatment of liver cancer and timely adjusting the treatment strategy are crucial to improve the survival rate of liver cancer. At present, the clinical monitoring of liver cancer after treatment is mainly based on serum markers and imaging. Morphological evaluation has limitations, such as the inability to measure small tumors and the poor repeatability of measurement, which is not applicable to cancer evaluation after immunotherapy or targeted treatment. The determination of serum markers is greatly affected by the environment and cannot accurately evaluate the prognosis. With the development of single cell sequencing technology, a large number of immune cell-specific genes have been identified. Immune cells and microenvironment play an important role in the process of prognosis. We speculate that the expression changes of immune cell-specific genes can indicate the process of prognosis.

Method

Therefore, this paper first screened out the immune cell-specific genes related to liver cancer, and then built a deep learning model based on the expression of these genes to predict metastasis and the survival time of liver cancer patients. We verified and compared the model on the data set of 372 patients with liver cancer.

Result

The experiments found that our model is significantly superior to other methods, and can accurately identify whether liver cancer patients have metastasis and predict the survival time of liver cancer patients according to the expression of immune cell-specific genes.

Discussion

We found these immune cell-specific genes participant multiple cancer-related pathways. We fully explored the function of these genes, which would support the development of immunotherapy for liver cancer.

Thymoquinone Suppresses Angiogenesis in DEN-Induced Hepatocellular Carcinoma by Targeting miR-1-3p

Hepatocellular carcinoma (HCC) is characterized by its high vascularity and metastasis. Thymoquinone (TQ), the main bio-active constituent of Nigella sativa, has shown anticancer and hepatoprotective effects. TQ's anticancer effect is mediated through miRNA regulation. miR-1-3p plays a significant role in various cancers but its role in HCC invasiveness remains poorly understood. Bio-informatics analysis predicted that the 3'-UTR of TIMP3 is a target for miR-1-3p; Rats were equally divided into four groups: Group 1, the negative control; Group 2 received TQ; Group 3 received DEN; and Group 4 received DEN after pretreatment with TQ. The expression of TIMP3, MMP2, MMP9, and VEGF in rats' liver was determined immunohistochemically. RT-qPCR was used to measure the miR-1-3p level in rats' liver, and TIMP3, MMP2, MMP9, and VEGF in the HepG2 cells after being transfected with miR-1-3p mimic or inhibitor; In rats pretreated with TQ, a decreased expression of MMP2, MMP9 and VEGF, and increased expression levels of TIMP3 and miR-1-3p were detected. Treating the HepG2 cells with miR-1-3p mimic led to the upregulation of TIMP3 and downregulation of MMP2, MMP9, and VEGF, and showed a significant delay in wound healing; These results suggested that the anti-angiogenic effect of TQ in HCC may be mediated through the regulation of miR-1-3p.

Circ_0006404 enhances hepatocellular carcinoma progression by regulating miR-624

Growing studies have demonstrated that circRNAs (circular RNAs) act potential roles in tumor metastasis and progression. However, the expression and function of circ_0006404 in hepatocellular carcinoma (HCC) remain to be investigated. The expression of circ_0006404 and miR-624 was detected by qRT-PCR. CCK-8 assay, flow cytometry, and wound healing were performed to determine cell proliferation, cycle, and migration. The target of circ_0006404 was studied by bioinformatics and luciferase activity analysis. Our data indicated that circ_0006404 was overexpressed in HCC specimens and cells and ectopic expression of circ_0006404 increased HCC cell growth, cycle, and migration. Moreover, we showed that miR-624 was downregulated in HCC specimens and cells and miR-624 expression was negatively correlated with circ_0006404 expression in HCC specimens. Circ_0006404 sponged miR-624 in HCC cell, and the overexpression of circ_0006404 suppressed miR-624 expression in HCC cell. Furthermore, circ_0006404 induced HCC cell growth, cycle, and migration via regulating miR-624. These results elucidated that circ_0006404 facilitated HCC progression and might act as one new biomarker for this carcinoma.

Data Centric Molecular Analysis and Evaluation of Hepatocellular Carcinoma Therapeutics Using Machine Intelligence-Based Tools

PURPOSE

Computational approaches have been used at different stages of drug development with the purpose of decreasing the time and cost of conventional experimental procedures. Lately, techniques mainly developed and applied in the field of artificial intelligence (AI), have been transferred to different application domains such as biomedicine.

METHODS

In this study, we conducted an investigative analysis via data-driven evaluation of potential hepatocellular carcinoma (HCC) therapeutics in the context of AI-assisted drug discovery/repurposing. First, we discussed basic concepts, computational approaches, databases, modeling approaches, and featurization techniques in drug discovery/repurposing. In the analysis part, we automatically integrated HCC-related biological entities such as genes/proteins, pathways, phenotypes, drugs/compounds, and other diseases with similar implications, and represented these heterogeneous relationships via a knowledge graph using the CROssBAR system.

RESULTS

Following the system-level evaluation and selection of critical genes/proteins and pathways to target, our deep learning-based drug/compound-target protein interaction predictors DEEPScreen and MDeePred have been employed for predicting new bioactive drugs and compounds for these critical targets. Finally, we embedded ligands of selected HCC-associated proteins which had a significant enrichment with the CROssBAR system into a 2-D space to identify and repurpose small molecule inhibitors as potential drug candidates based on their molecular similarities to known HCC drugs.

CONCLUSIONS

We expect that these series of data-driven analyses can be used as a roadmap to propose early-stage potential inhibitors (from database-scale sets of compounds) to both HCC and other complex diseases, which may subsequently be analyzed with more targeted in silico and experimental approaches.

A novel DNA methylation-based model that effectively predicts prognosis in hepatocellular carcinoma

PURPOSE

To build a novel predictive model for hepatocellular carcinoma (HCC) patients based on DNA methylation data.

METHODS

Four independent DNA methylation datasets for HCC were used to screen for common differentially methylated genes (CDMGs). Gene Ontology (GO) enrichment, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were used to explore the biological roles of CDMGs in HCC. Univariate Cox analysis and least absolute shrinkage and selection operator (LASSO) Cox analysis were performed to identify survival-related CDMGs (SR-CDMGs) and to build a predictive model. The importance of this model was assessed using Cox regression analysis, propensity score-matched (PSM) analysis and stratification analysis. A validation group from the Cancer Genome Atlas (TCGA) was constructed to further validate the model.

RESULTS

Four SR-CDMGs were identified and used to build the predictive model. The risk score of this model was calculated as follows: risk score = (0.01489826 × methylation level of WDR69) + (0.15868618 × methylation level of HOXB4) + (0.16674959 × methylation level of CDKL2) + (0.16689301 × methylation level of HOXA10). Kaplan-Meier analysis demonstrated that patients in the low-risk group had a significantly longer overall survival (OS; log-rank P-value =0.00071). The Cox model multivariate analysis and PSM analysis identified the risk score as an independent prognostic factor (P<0.05). Stratified analysis results further confirmed this model performed well. By analyzing the validation group, the results of receiver operating characteristic (ROC) curve analysis and survival analysis further validated this model.

CONCLUSION

Our DNA methylation-based prognosis predictive model is effective and reliable in predicting prognosis for patients with HCC.

Amyloid precursor protein regulates 5-fluorouracil resistance in human hepatocellular carcinoma cells by inhibiting the mitochondrial apoptotic pathway

Hepatocellular carcinoma (HCC) is a malignant tumor with high morbidity and mortality globally. It accounts for the majority of primary liver cancer cases. Amyloid precursor protein (APP), a cell membrane protein, plays a vital role in the pathogenesis of Alzheimer's disease, and has been found to be implicated in tumor growth and metastasis. Therefore, to understand the relationship between APP and 5-fluorouracil (5-FU) resistance in liver cancer, Cell Counting Kit-8, apoptosis and cell cycle assays, western blotting, and reverse transcription-quantitative polymerase chain reaction (qPCR) analysis were performed. The results demonstrated that APP expression in Bel7402-5-FU cells was significantly up-regulated, as compared with that in Bel7402 cells. Through successful construction of APP-silenced (siAPP) and overexpressed (OE) Bel7402 cell lines, data revealed that the Bel7402-APP^751-OE cell line was insensitive, while the Bel7402-siAPP cell line was sensitive to 5-FU in comparison to the matched control group. Furthermore, APP overexpression decreased, while APP silencing increased 5-FU-induced apoptosis in Bel7402 cells. Mechanistically, APP overexpression and silencing can regulate the mitochondrial apoptotic pathway and the expression of apoptotic suppressor genes (B-cell lymphoma-2 (Bcl-2) and B-cell lymphoma-extra large (Bcl-xl)). Taken together, these results preliminarily revealed that APP overexpression contributes to the resistance of liver cancer cells to 5-FU, providing a new perspective for drug resistance.

Role of Rap1 in DNA damage response: implications in stem cell homeostasis and cancer

Mammalian Rap1 is a part of the telomere binding complex named shelterin and is one of the most conserved telomeric proteins. With its essential requirement in lower species to its becoming necessary in higher species, it appears to have gained and lost several functions simultaneously evolving with telomeres. Mammalian Rap1 has been reported to play a role in inflammation, metabolism, and oxidative stress. Mammalian Rap1 has also been found to regulate DNA damage response from telomeres in senescent cells. Recently our group uncovered its novel role in stem cell maintenance, and modulation of the chemotherapeutic response. Mechanistically it was found to function as an adaptor via protein-protein interactions and to modulate the response to DNA damage. In the current review we highlight newly identified functions of Rap1 in regulating telomeric and general DNA damage response with its impact at the cellular and organismal levels.

Clinical and genomic landscape of hepatocellular carcinoma subtypes with various proportions of nonleukocyte stromal cells

BACKGROUND

Hepatocellular carcinoma (HCC) is one of the most common malignancies and inflicts high mortality worldwide. The effect of tumor microenvironment components on HCC oncogenesis remains unknown. In particular, the nonleukocyte portion of the stromal fraction (SF) is poorly understood.

METHODS

We comprehensively evaluated the proportional cell counts and gene expression data from The Cancer Genome Atlas (TCGA) to examine the contributions of cell components to the tumor microenvironment. Single-cell sequencing data from the Gene Expression Omnibus (GEO) were also analyzed to verify the association between the nonleukocyte SF and genes. We classified HCC using a hierarchical clustering method based on diversity of nonleukocyte SF-related gene expression among different components, and we used an appropriate GEO dataset to verify the clusters with a support vector machine (SVM) model. The prognosis of subtypes and their relationship with tumor microenvironmental cell proportions, clinicopathogenesis factors, and other indicators were evaluated.

RESULTS

Based on linear regression, 711 genes related to nonleukocyte SF were selected from the TCGA dataset. We classified HCC into three subtypes using genes related to the nonleukocyte SF. Additionally, the GEO single-cell sequencing data confirmed the relationship between genes and the nonleukocyte SF. The tumor microenvironment of Type 2 contained the most significant mutually reinforcing interaction between the nonleukocyte SF and tumor cells. Meanwhile, Type 2 patients had the poorest prognosis and the most severe tumor-node-metastasis (TNM) stages, histological grades, etc. The analysis based on the GEO dataset verified the classification results with an SVM model. Type 2 was associated with worse clinicopathological characteristics, including tumor grading and staging, than the other types. In addition, the pathway analysis revealed that signals related to the SF and cell proliferation were significantly enhanced in Type 2 compared to the other group, which consisted of Types 1 and 3.

CONCLUSION

The nonleukocyte SF in the tumor microenvironment contributed greatly to HCC oncogenesis. We can use these HCC classification criteria to stratify patients into subtypes for personalized treatment.

MIR22HG As A Tumor Suppressive lncRNA In HCC: A Comprehensive Analysis Integrating RT-qPCR, mRNA-Seq, And Microarrays

Introduction

MIR22HG has a reported involvement in the tumorigenesis of a variety of cancers, including hepatocellular carcinoma (HCC). However, the exact molecular mechanism of MIR22HG in HCC has not been clarified.

Methods

In the present study, we integrated data from in-house RT-qPCR, RNA-sequencing, microarray, and literature studies to conduct a comprehensive evaluation of the clinico-pathological and prognostic significance of MIR22HG in an extremely large group of HCC samples. We also explored the potential mechanism of MIR22HG in HCC by analyzing the alteration profiles of MIR22HG in HCC to predict transcription factors (TFs) that may interact with MIR22HG and to annotate the biological functions of genes co-expressed with MIR22HG. MIR22HG expression was also compared in HCC nude mice xenografts before and after a treatment with nitidine chloride.

Results

We found that MIR22HG was downregulated in HCC and that this downregulation correlated with the malignant phenotype of HCC. Comprehensive analysis of the prognostic impact of MIR22HG in HCC revealed a beneficial effect of MIR22HG on the survival outcome of HCC patients. Seven cases of MIR22HG deep deletion occurred in 360 of the cancer genome atlas (TCGA) provisional HCC samples. A total of 22 MIR22HG-TF-mRNA triplets in HCC were predicted by the lncRNAmap. Co-expressed genes of MIR22HG, identified by weighted correlation network analysis (WGCNA), mainly participated in the pathways involving osteoclast differentiation, chemokine signaling pathways, and hematopoietic cell lineage. In vivo experiments demonstrated that nitidine chloride could stimulate MIR22HG expression in HCC xenografts.

Conclusion

In summary, MIR22HG may play a tumor-suppressive role in HCC by coordinating with predicted TFs and co-expressed genes, such as NLRP3, CSF1R, SIGLEC10, and ZEB2, or by being controlled by nitidine chloride.

Up-Regulation of hsa_circ_0000517 Predicts Adverse Prognosis of Hepatocellular Carcinoma

Although huge progress has been made in therapeutics against hepatocellular carcinoma (HCC) over the decades, the prognosis of this lethal disease remains poor. To find out risk factors for HCC-related outcome and better predict the prognosis, there is an unmet need to identify novel biomarkers of HCC. Accumulating evidence suggests that circRNAs play pivotal roles in carcinogenesis of several malignancies. In this study, we analyzed two datasets (GSE 94508 and GSE 97332) to examine differentially expressed circRNAs markedly related to HCC pathogenesis. Using Limma package in R and WGCNA analysis, hsa_circ_0000517 was significantly up-regulated in HCC (adjusted P < 0.01). Thereafter, a hsa_circ_0000517-related regulatory network was built based on application of databases including CSCD, TargetScan, miRDB, and miRTarBase. We uncovered the potential function of hsa_circ_0000517 through bioinformatics approaches, such as PPI network, GO, and KEGG pathway analyses. Specifically, functional analysis unveiled that hsa_circ_0000517 was likely to regulate the MAPK and Ras pathway through sponging several miRNAs and having an impact on the expression of TP53, MYC, and AKT1. To verify our initial finding, the expression of hsa_circ_0000517 in 60 HCC patients was detected by qRT-PCR and the expression in cancer tissues was higher compared with the paracarcinoma tissues. Survival analysis suggests high hsa_circ_0000517 expression was associated with adverse prognosis in HCC patients. Furthermore, this circRNA was significantly up-regulated in worse TNM stage, consistent with the progressive-stage-specific characteristic of circRNAs. A prognostic nomogram built on AFP and has_circ_0000517 showed significant diagnostic value. In all, we concluded that hsa_circ_0000517, a promising molecular in underlying mechanism of HCC, is a potent valuable biomarker for prognosis prediction.

Telomere-dependent and telomere-independent roles of RAP1 in regulating human stem cell homeostasis

RAP1 is a well-known telomere-binding protein, but its functions in human stem cells have remained unclear. Here we generated RAP1-deficient human embryonic stem cells (hESCs) by using CRISPR/Cas9 technique and obtained RAP1-deficient human mesenchymal stem cells (hMSCs) and neural stem cells (hNSCs) via directed differentiation. In both hMSCs and hNSCs, RAP1 not only negatively regulated telomere length but also acted as a transcriptional regulator of RELN by tuning the methylation status of its gene promoter. RAP1 deficiency enhanced self-renewal and delayed senescence in hMSCs, but not in hNSCs, suggesting complicated lineage-specific effects of RAP1 in adult stem cells. Altogether, these results demonstrate for the first time that RAP1 plays both telomeric and nontelomeric roles in regulating human stem cell homeostasis.

A five-gene signature may predict sunitinib sensitivity and serve as prognostic biomarkers for renal cell carcinoma

Sunitinib resistance is, nowadays, the major challenge for advanced renal cell carcinoma patients. Illuminating the potential mechanisms and exploring effective strategies to overcome sunitinib resistance are highly desired. We constructed a reliable gene signature which may function as biomarkers for prediction of sunitinib sensitivity and clinical prognosis. The gene expression profiles were obtained from The Cancer Genome Atlas database. By performing GEO2R analysis, numerous differentially expressed genes (DEGs) were found to be associated with sunitinib resistance. To acquire more precise DEGs, we integrated three different microarray datasets. Functional analysis revealed that these DEGs were mainly involved in Rap1 signaling pathway, p53 signaling pathway and Ras signaling pathway. Then, top five hub genes, BIRC5, CD44, MUC1, TF, CCL5, were identified from protein-protein interaction (PPI) network. Sub-network analysis carried out by MCODE plugin revealed that key DEGs were related with PI3K-Akt signaling pathway, Rap1 signaling pathway and VEGF signaling pathway. Next, we established sunitinib-resistant OS-RC-2 and 786-O cell lines and validated the expression of five hub genes in cell lines. To further evaluate the potentials of five-gene signature for predicting clinical prognosis, we analyzed RCC patients with gene expressions and overall survival information from two independent patient datasets. The Kaplan-Meier estimated the OS of RCC patients in the low- and high-risk groups according to gene expression signature. Multivariate Cox regression analysis indicated that the prognostic power of five-gene signature was independent of clinical features. In conclusion, we developed a five-gene signature which can predict sunitinib sensitivity and OS for advanced RCC patients, providing novel insights into understanding of sunitinib-resistant mechanisms and identification of RCC patients with poor prognosis.

Individualized predictive signatures for 5-fluorouracil-based chemotherapy in right- and left-sided colon cancer

5‐Fluorouracil (5‐FU)‐based adjuvant chemotherapy (ACT) is widely used for the treatment of colon cancer. Colon cancers with different primary tumor locations are clinically and molecularly distinct, implied through their response to 5‐FU‐based ACT. In this work, using 69 and 133 samples of patients with stage II‐III right‐sided and left‐sided colon cancer (RCC and LCC) treated with post‐surgery 5‐FU‐based ACT, we preselected gene pairs whose relative expression orderings were significantly correlated with the disease‐free survival of patients by univariate Cox proportional hazards model. Then, from the identified prognostic‐related gene pairs, a forward‐stepwise selection algorithm was formulated to search for an optimal subset of gene pairs that resulted in the highest concordance index, referred to as the gene pair signature (GPS). We identified prognostic signatures, 3‐GPS and 5‐GPS, for predicting response to 5‐FU‐based ACT of patients with RCC and LCC, respectively, which were validated in independent datasets of GSE14333 and GSE72970. With the aid of the signatures, the transcriptional and genomic characteristics between the predicted responders and non‐responders were explored. Notably, both in RCC and LCC, the predicted responders to 5‐FU‐based ACT were characterized by hypermutation, whereas the predicted non‐responders were characterized by frequent copy number alternations. Finally, in comparison with the established relative expression ordering‐based signature, which was developed without considering the differences between RCC and LCC, the newly proposed signatures had a better predictive performance. In conclusion, 3‐GPS or 5‐GPS can robustly predict response to 5‐FU‐based ACT for patients with RCC or LCC, respectively, in an individual level.

LncRNA HOXA11-AS promotes hepatocellular carcinoma progression by repressing miR-214-3p

Accumulating studies supported that lncRNAs played important roles in tumorigenesis. LncRNA HOXA11‐AS was a novel lncRNA that has been proved to involved in several tumours. However, the role of HOXA11‐AS in the development of hepatocellular carcinoma (HCC) remains to be explained. In our study, we showed that HOXA11‐AS expression was up‐regulated in the HCC tissues, and the higher expression of HOXA11‐AS was associated with the advanced stage in the HCC samples. In addition, we indicated that the expression of HOXA11‐AS was up‐regulated in HCC cell lines (Hep3B, SMMC‐7721, MHCC97‐H and BEL‐7402) compared with normal liver cell lines (HL‐7702). Overexpression of HOXA11‐AS promoted HCC proliferation and invasion and induced the epithelial‐mesenchymal transition (EMT) and knockdown of HOXA11‐AS suppressed the HCC cell proliferation and invasion. However, we showed that miR‐214‐3p expression was down‐regulated in the HCC tissues and cell lines. Ectopic expression of miR‐214‐3p suppressed HCC cell proliferation and invasion. Furthermore, we indicated that overexpression of HOXA11‐AS decreased the miR‐214‐3p expression and the expression of miR‐214‐3p was negatively related with the HOXA11‐AS expression in HCC samples. Ectopic expression of HOXA11‐AS increased HCC proliferation and invasion and induced EMT through inhibiting miR‐214‐3p expression. These data suggested that HOXA11‐AS/miR‐214‐3p axis was responsible for development of HCC.

Myosin phosphatase and RhoA-activated kinase modulate arginine methylation by the regulation of protein arginine methyltransferase 5 in hepatocellular carcinoma cells

Myosin phosphatase (MP) holoenzyme is a protein phosphatase-1 (PP1) type Ser/Thr specific enzyme that consists of a PP1 catalytic (PP1c) and a myosin phosphatase target subunit-1 (MYPT1). MYPT1 is an ubiquitously expressed isoform and it targets PP1c to its substrates. We identified the protein arginine methyltransferase 5 (PRMT5) enzyme of the methylosome complex as a MYPT1-binding protein uncovering the nuclear MYPT1-interactome of hepatocellular carcinoma cells. It is shown that PRMT5 is regulated by phosphorylation at Thr80 by RhoA-associated protein kinase and MP. Silencing of MYPT1 increased the level of the PRMT5-specific symmetric dimethylation on arginine residues of histone 2 A/4, a repressing gene expression mark, and it resulted in a global change in the expression of genes affecting cellular processes like growth, proliferation and cell death, also affecting the expression of the retinoblastoma protein and c-Myc. The phosphorylation of the MP inhibitory MYPT1^T850 and the regulatory PRMT5^T80 residues as well as the symmetric dimethylation of H2A/4 were elevated in human hepatocellular carcinoma and in other types of cancers. These changes correlated positively with the grade and state of the tumors. Our results suggest the tumor suppressor role of MP via inhibition of PRMT5 thereby regulating gene expression through histone arginine dimethylation.

Multi-omics landscapes of colorectal cancer subtypes discriminated by an individualized prognostic signature for 5-fluorouracil-based chemotherapy

Until recently, few prognostic signatures for colorectal cancer (CRC) patients receiving 5-fluorouracil (5-FU)-based chemotherapy could be used in clinical practice. Here, using transcriptional profiles for a panel of cancer cell lines and three cohorts of CRC patients, we developed a prognostic signature based on within-sample relative expression orderings (REOs) of six gene pairs for stage II-III CRC patients receiving 5-FU-based chemotherapy. This REO-based signature had the unique advantage of being insensitive to experimental batch effects and free of the impractical data normalization requirement. After stratifying 184 CRC samples with multi-omics data from The Cancer Genome Atlas into two prognostic groups using the REO-based signature, we further revealed that patients with high recurrence risk were characterized by frequent gene copy number aberrations reducing 5-FU efficacy and DNA methylation aberrations inducing distinct transcriptional alternations to confer 5-FU resistance. In contrast, patients with low recurrence risk exhibited deficient mismatch repair and carried frequent gene mutations suppressing cell adhesion. These results reveal the multi-omics landscapes determining prognoses of stage II-III CRC patients receiving 5-FU-based chemotherapy.

dbPHCC: a database of prognostic biomarkers for hepatocellular carcinoma that provides online prognostic modeling

BACKGROUND

Hepatocellular carcinoma (HCC) is one of the most common malignant cancers with a poor prognosis. For decades, more and more biomarkers were found to effect on HCC prognosis, but these studies were scattered and there were no unified identifiers. Therefore, we built the database of prognostic biomarkers and models for hepatocellular carcinoma (dbPHCC).

METHODS

dbPHCC focuses on biomarkers which were related to HCC prognosis by traditional experiments rather than high-throughput technology. All of the prognostic biomarkers came from literatures issued during 2002 to 2014 in PubMed and were manually selected. dbPHCC collects comprehensive information of candidate biomarkers and HCC prognosis.

RESULTS

dbPHCC mainly contains 567 biomarkers: 323 proteins, 154 genes, and 90 microRNAs. For each biomarker, the reference information, experimental conditions, and prognostic information are shown. Based on two available patient cohort data sets, an exemplified prognostic model was constructed using 15 phosphotransferases in dbPHCC. The web interface does not only provide a full range of browsing and searching, but also provides online analysis tools. dbPHCC is available at http://lifecenter.sgst.cn/dbphcc/

CONCLUSIONS

dbPHCC provides a comprehensive and convenient search and analysis platform for HCC prognosis research.

GENERAL SIGNIFICANCE

dbPHCC is the first database to focus on experimentally verified individual biomarkers, which are related to HCC prognosis. Prognostic markers in dbPHCC have the potential to be therapeutic drug targets and may help in designing new treatments to improve survival of HCC patients. This article is part of a Special Issue entitled "System Genetics" Guest Editor: Dr. Yudong Cai and Dr. Tao Huang.

Role of microRNAs in inflammation-associated liver cancer

Liver cancer, primarily hepatocellular carcinoma (HCC), is a major cause of cancer-related death worldwide. HCC is a suitable model of inflammation-induced cancer because more than 90% of HCC cases are caused by liver damage and chronic inflammation. Several inflammatory response pathways, such as NF-κB and JAK/STAT3 signaling pathways, play roles in the crosstalk between inflammation and HCC. MicroRNAs (miRNAs) are evolutionarily conserved, short endogenous, non-coding single-stranded RNAs that are involved in various biological and pathological processes by regulating gene expression and protein translation. Evidence showed that miRNAs play a pivotal role in hepatitis virus infection and serve as promoters or inhibitors of inflammatory response. Aberrant miRNA was observed during liver inflammation and HCC. Many dysregulated miRNAs modulate the initiation and progression of inflammation-induced HCC. This review summarizes the role and functions of miRNAs in inflammation-associated HCC, as well as the designed therapeutics targeting miRNAs to treat liver inflammation and HCC.