Prognosis Of Liver Cancer Patients Research Articles

Establishment and verification of a prognostic model of liver cancer by RNA-binding proteins based on the TCGA database.

BackgroundGlobally, liver cancer is one of the most common malignant tumors and is the third leading cause of cancer deaths. RNA-binding protein (RBP) is a general term for a class of proteins that bind to RNA to regulate metabolic processes. The expression of RNA-binding proteins is related to the prognosis of liver cancer patients.MethodsThe RBP gene expression data of liver cancer were extracted from the TCGA database. First, the differentially expressed RBPs (DE RBPs) were selected through enrichment analysis and volcano mapping. Then, the prognosis-related RBP genes were selected through single-factor Cox regression analysis. The key prognosis-related RBPs were further screened by multifactor Cox regression analysis, and a formula for the patient’s risk coefficient was obtained. Finally, based on the patient’s risk score, a nomogram was established and verified.ResultsWe extracted 374 cancer tissue samples and 50 normal tissue samples with the clinical information from each sample. Through enrichment analysis, we screened 208 upregulated RBPs and 122 downregulated RBPs. Prognosis-related high-risk genes were EEF1E1, NOP56, UPF3B, SF3B4, SMG5, CD3EAP, BRCA1, BARD1, XPO5, CSTF2, EZH2, EXO1, RRP12, PRIM1, LIN28B, NROB1 and TCOF1, and the low-risk genes were MRPL46, RCL1, MRPL54, CPEB3, IFIT5, PPARGC1A, EIF2AK4, SEPSECS, ACO1, SECISBP2 L and ZCCHC24. Further multivariate Cox regression analysis was performed on the prognosis-related RBPs, and the three key prognosis-related RBPs were screened out, which were BARD1, NR0B1 and EIF2AK4. A patient risk coefficient calculation formula was obtained: risk score = (1.207×BARD1 Exp) + (0.483×NR0B1 Exp) + (-0.720×EIF2AK4 Exp). Finally, a nomogram was established based on the risk score to predict the survival time of patients from 1 to 5 years.ConclusionsThe nomogram has good predictive value for the survival time of liver cancer patients.

Dihydroartemisinin promoted FXR expression independent of YAP1 in hepatocellular carcinoma.

Loss of FXR, one of bile acid receptors, enlarged livers. Yes-associated protein 1 (YAP1), a dominant oncogene, promotes hepatocellular carcinoma (HCC). However, the relationship between FXR and YAP1 was unspecified in bile acid homeostasis in HCC. Here, we used TIMER2.0, the Cancer Genome Atlas (TCGA) Database, and Kaplan-Meier Plotter Database and discovered that FXR was positively correlated with better prognosis in liver cancer patients. Our previous research showed that dihydroartemisinin (DHA) inhibited cell proliferation in HepG2 and HepG22215 cells. However, the relationship of YAP1 and the bile acid receptor FXR remains elusive during DHA treatment. Furthermore, we showed that DHA improved FXR and reduced YAP1 in the liver cancer cells and mice. Additionally, the expression of nucleus protein FXR was enhanced in Yap1LKO mice with liver cancer. DHA promoted the expression level of whole and nuclear protein FXR independent of YAP1 in Yap1LKO mice with liver cancer. DHA declined cholesterol 7α-hydroxylase, but not sterol 27-hydroxylase, and depressed cholic acid and chenodeoxycholic acid of liver tissue in Yap1LKO mice with liver cancer. Generally, our results suggested that DHA improved FXR and declined YAP1 to suppress bile acid metabolism. Thus, we suggested that FXR acted as a potential therapeutic target in HCC.

Sphingomyelin Phodiesterase Acid-Like 3A Promotes Hepatocellular Carcinoma Growth Through the Enhancer of Rudimentary Homolog.

BackgroundHepatocellular carcinoma (HCC) is one of the most common malignant tumors worldwide, with unclear pathogenesis. Sphingomyelin phodiesterase acid-like 3A (SMPDL3A) affects cell differentiation and participates in immune regulation. However, its molecular biological function in HCC has not yet been elucidated.MethodsData from 180 HCC patients were analyzed the relationship between the expression of SMPDL3A in liver cancer tissues and the prognosis of liver cancer patients. Crispr-Cas9 dual vector lentivirus was used to knock out SMPDL3A in HCC cell lines. The effects of SMPDL3A on cell viability were determined by CCK8 assay, clone formation experiment, cell cycle assay, cell scratch, TUNEL experiment and flow cytometry. Xenograft tumor assays in BALB/c nude mice confirmed that SMPDL3A promoted tumor growth and in vivo. Preliminary exploration of SMPDL3A interacting protein by mass spectrometry analysis and co-immunoprecipitation.ResultsThis study showed that the expression of SMPDL3A in HCC tissue differed from that in tumor-adjacent tissues. Moreover, the overall survival rate and tumor-free survival rate of patients with high-SMPDL3A expression were significantly lower than those with low-SMPDL3A expression. SMPDL3A expression was closely related to the level of protein induced by PIVKA-II, liver cirrhosis, tumor diameter, microvascular invasion, and Barcelona clinic liver cancer staging. Thus, SMPDL3A is an independent risk factor that affects the tumor-free survival rate and overall survival rate of HCC patients. In vitro study using Crispr-Cas9 genome editing technology revealed the knockout effect of SMPDL3A on cell proliferation, apoptosis, and migration. Cell counting kit-8 assay and clone formation experiment showed that sgSMPDL3A inhibited tumor cell proliferation and migration. Flow cytometry and TUNEL assay showed that sgSMPDL3A promoted apoptosis in tumors. Moreover, sgSMPDL3A inhibited tumor growth during subcutaneous tumor formation in nude mice. Immunohistochemistry of Ki67 and PNCA also indicated that sgSMPDL3A inhibited subcutaneous tumor proliferation in tumor-bearing nude mice. Further experiments showed that SMPDL3A interacts with the enhancer of rudimentary homolog (ERH).ConclusionsHigh-SMPDL3A expression was related to poor prognosis of patients with HCC. Knockout of SMPDL3A inhibited the proliferation and migration and accelerated the migration of HCC cells. SMPDL3A interacted with ERH to affect the tumorigenesis and progression of HCC.

Novel Prognostic Signatures of Hepatocellular Carcinoma Based on Metabolic Pathway Phenotypes.

Hepatocellular carcinoma is a disastrous cancer with an aberrant metabolism. In this study, we aimed to assess the role of metabolism in the prognosis of hepatocellular carcinoma. Ten metabolism-related pathways were identified to classify the hepatocellular carcinoma into two clusters: Metabolism_H and Metabolism_L. Compared with Metabolism_L, patients in Metabolism_H had lower survival rates with more mutated TP53 genes and more immune infiltration. Moreover, risk scores for predicting overall survival based on eleven differentially expressed metabolic genes were developed by the least absolute shrinkage and selection operator (LASSO)-Cox regression model in The Cancer Genome Atlas (TCGA) dataset, which was validated in the International Cancer Genome Consortium (ICGC) dataset. The immunohistochemistry staining of liver cancer patient specimens also identified that the 11 genes were associated with the prognosis of liver cancer patients. Multivariate Cox regression analyses indicated that the differentially expressed metabolic gene-based risk score was also an independent prognostic factor for overall survival. Furthermore, the risk score (AUC = 0.767) outperformed other clinical variables in predicting overall survival. Therefore, the metabolism-related survival-predictor model may predict overall survival excellently for HCC patients.

Identification of Energy Metabolism-Related Gene Signatures From scRNA-Seq Data to Predict the Prognosis of Liver Cancer Patients.

The increasingly common usage of single-cell sequencing in cancer research enables analysis of tumor development mechanisms from a wider range of perspectives. Metabolic disorders are closely associated with liver cancer development. In recent years, liver cancer has been evaluated from different perspectives and classified into different subtypes to improve targeted treatment strategies. Here, we performed an analysis of liver cancer from the perspective of energy metabolism based on single-cell sequencing data. Single-cell and bulk sequencing data of liver cancer patients were obtained from GEO and TCGA/ICGC databases, respectively. Using the Seurat R package and protocols such as consensus clustering analysis, genes associated with energy metabolism in liver cancer were identified and validated. An energy metabolism-related score (EM score) was established based on five identified genes. Finally, the sensitivity of patients in different scoring groups to different chemotherapeutic agents and immune checkpoint inhibitors was analyzed. Tumor cells from liver cancer patients were found to divide into nine clusters, with cluster 4 having the highest energy metabolism score. Based on the marker genes of this cluster and TCGA database data, the five most stable key genes (ADH4, AKR1B10, CEBPZOS, ENO1, and FOXN2) were identified as energy metabolism-related genes in liver cancer. In addition, drug sensitivity analysis showed that patients in the low EM score group were more sensitive to immune checkpoint inhibitors and chemotherapeutic agents AICAR, metformin, and methotrexate.

High expression of H2A histone family member Y promotes the proliferation and autophagy of hepatocellular carcinoma cells

ABSTRACT Hepatocellular carcinoma is a common malignant tumor and the third most common cause of cancer-related deaths. In this study, we selected H2AFY as a potential oncogene from three online databases, and verified differential expression between normal and liver cancer tissues. Moreover, H2AFY expression was significantly correlated with the clinical characteristics and the survival of liver cancer patients. H2AFY expression was correlated with poor prognosis of liver cancer patients. H2AFY expression was also significantly higher in liver cancer cells. Knockdown and overexpression of H2AFY in liver cancer cells showed that H2AFY promoted the proliferation and clone formation of liver cancer cells but had no significant effects on the migration and invasion ability of liver cancer cells. Western blot analysis, immunohistochemistry, and immunofluorescence double staining confirmed that H2AFY upregulated LC3 and p62 expression in liver cancer tissues and cells. In conclusion, H2AFY is highly expressed in liver cancer cells and tissues, and promotes the proliferation and autophagy of liver cancer cells. H2AFY is a potential target for liver cancer therapy. Abbreviations: APLF: aprataxin pnk-like factor; HCC: Hepatocellular carcinoma; H2AFY: H2A histone family member Y

Analysis of the expression and prognosis for leukocyte immunoglobulin-like receptor subfamily B in human liver cancer

BackgroundLeukocyte immunoglobulin-like receptor subfamily B (LILRB), including 5 subtypes, is a group of inhibitory receptors in the immune system. The LILRB family is known to be involved in the tumor progression of various cancer types, especially liver cancer. However, the expression patterns and prognostic values of LILRB family members in liver cancer tissues remain unclear.MethodsWe used the Oncomine database, GEPIA database, Kaplan–Meier Plotter, Timer, and TISIDB to assess the expression and prognostic value of the LILRB family in liver cancer patients. We also verified the expression of the LILRB family in tumor tissues and tumor-free liver tissues at the protein level by using immunohistochemistry. The STRING website was used to explore the interaction between the LILRB family and their related genes. The DAVID database was used to perform the gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. Flow cytometry was used to assess the infiltrated NK cells in liver cancer tissues.ResultsOur study revealed that the mRNA expression of LILRB1, LILRB2, LILRB3, and LILRB5 was downregulated, while compared with normal tissues, the mRNA expression of LILRB4 was upregulated in liver cancer tissues. Survival analysis revealed that LILRB2 and LILRB5 mRNA expression levels were significantly positively associated with overall survival (OS) and disease-free survival (DSS) and that the mRNA expression of all LILRB family members was significantly positively correlated with recurrence-free survival (RFS) and progression-free survival (PFS). Next, we further found that the mRNA expression of all LILRB family members was significantly associated with the infiltration of B cells, CD8+ T cells, CD4+ T cells, macrophages, neutrophils, and dendritic cells in liver cancer. Finally, GO and KEGG analyses found that the LILRB family and its related genes were involved in antigen processing and presentation and natural killer cell-mediated cytotoxicity pathways.ConclusionsOur study suggested that LILRB family expression was associated with the prognosis of liver cancer patients and infiltrated immune cells. The LILRB family might be involved in antigen processing and presentation and natural killer cell-mediated cytotoxicity pathways.

Exposure to aristolochic acid I is associated with poor prognosis of liver cancer patients.

The aristolochic acids (AAs), derived from Aristolochia and Asarum species used widely in herbal medicines, are closely associated with liver cancer. The major AA derivatives are aristolochic acid I (AAI) and II (AAII), which can bind DNA covalently to form AA-DNA adducts after metabolic activation in vivo. Among all these AA-DNA adducts, 7-(deoxyadenosine-N6-yl) aristolactam I (dA-AL-I) is the most abundant and persistent DNA lesion in patients. However, the direct evidence indicating AA exposure in human liver cancer is still missing. Here, we analyzed dA-AL-I adduct, the direct biomarker of AAI exposure, by ultra-performance liquid chromatography coupled with triple quadrupole mass spectrometry (UPLC-TQ/MS) in 209 liver cancer patients. Also, DNA samples from mice treated with/without AAI were used as positive and negative controls. dA-AL-I adduct was present in 110 of 209 (52.6%) patients, indicating that these patients were exposed to AAI prior to their clinical investigations and also had a worse prognosis. The relative high AA exposure rate and worse prognosis in our cohort of patients emphasize the significance to increase public awareness to avoid the use of herbal medicine containing AAs or their derivatives.

Clinical Value of PPM1G Gene in Survival Prognosis and Immune Infiltration of Hepatocellular Carcinoma.

Objective Liver cancer is one of the most common malignancies, but its prognosis is still poor. Exploring potential biomarkers is an important direction of tumor research. We intend to use bioinformatics methods to explore potential biomarkers related to survival and prognosis of HCC. Methods The mRNA and protein expressions of PPM1G in liver cancer were analyzed by HPA, TIMER, and UALCAN databases, and the effects of PPM1G on the prognosis of liver cancer patients were explored by the GEPIA database. We also explored the correlation between PPM1G expression and liver cancer immune infiltration through the TIMER database and further explored the potential protein interaction network of PPM1G through the STRING database. Results The mRNA and protein expression of PPM1G gene in hepatocellular carcinoma tissues was lower than that in normal adjacent tissues. Liver cancer patients with high expression of PPM1G have a better prognosis than those with low expression of PPM1G. The expression of PPM1G is positively or negatively correlated with different immune cells of liver cancer, such as CD4+ T lymphocytes, CD8+ T lymphocytes, B cells, macrophages, and neutrophils. Conclusion The liver cancer patients with high expression of PPM1G have a good prognosis, and PPM1G gene may be a potential immunotherapy target and prognostic marker of liver cancer.

Regulatory effect of small nuclear ribonucleoprotein-associated protein B on proliferation and metastasis of liver cancer cells

Objective: To study the expression and effect of small nuclear ribonucleoprotein-associated protein B (SNRPB) on proliferation and metastasis of liver cancer tissues and cells. Methods: The bioinformatics database starBase v3.0 and GEPIA were used to analyze the expression of SNRPB in liver cancer tissue and normal liver tissue, as well as the survival and prognosis of liver cancer patients. The expression of SNRPB mRNA and protein in liver cancer cell lines were analyzed by qRT-PCR and Western blot. RNA interference technique (siRNA) was used to determine SNRPB protein expression down-regulation. The proliferation effect on hepatocellular carcinoma cells was observed by MTT assay. Transwell invasion and migration assay was used to detect the changes in the metastatic ability of liver cancer cells after SNRPB down-regulation. Western blot was used to detect the changes of epithelial mesenchymal transition (EMT) markers in liver cancer cells after down-regulation of SNRPB expression. Data were compared between two groups and multiple groups using t-test and analysis of variance. Results: The expression of SNRPB was significantly higher in liver cancer tissue than normal liver tissue, and its expression level was correlated with the prognosis of liver cancer patients. Compared with the immortalized hepatocyte LO(2), the expression of SNRPB was significantly increased in the liver cancer cells (P < 0.01). siRNA-SNRPB had significantly inhibited the expression of SNRPB mRNA and protein in liver cancer cells. MTT results showed that the absorbance value was lower in SNRPB knockdown group than negative control group, and the difference at 96 h after transfection was most significant (P < 0.01). Transwell assay results showed that compared with the negative control group, the SNRPB knockdown group (MHCC-97H: 121.27 ± 8.12 vs. 46.38 ± 7.54; Huh7: 126.50 ± 6.98 vs. 41.10 ± 8.01) invasion and migration (MHCC-97H: 125.20 ± 4.77 vs. 43.18 ± 7.32; Huh7: 132.22 ± 8.21 vs. 38.00 ± 6.78) ability was significantly reduced (P < 0.01) in liver cancer cells. Western blot showed that the expression level of epithelial phenotype marker E-cadherin was decreased after down-regulation of SNRPB, while the expression levels of mesenchymal phenotype markers N-cadherin and vimentin was increased, suggesting that down-regulation of SNRPB inhibited EMT in liver cancer cells. Conclusion: SNRPB expression is significantly increased in liver cancer tissues and cells, and it is involved in regulating the proliferation, metastasis and EMT of liver cancer cells.

Prediction of Microvascular Invasion and Its M2 Classification in Hepatocellular Carcinoma Based on Nomogram Analyses.

Background and AimsAs a key pathological factor, microvascular invasion (MVI), especially its M2 grade, greatly affects the prognosis of liver cancer patients. Accurate preoperative prediction of MVI and its M2 classification can help clinicians to make the best treatment decision. Therefore, we aimed to establish effective nomograms to predict MVI and its M2 grade.MethodsA total of 111 patients who underwent radical resection of hepatocellular carcinoma (HCC) from January 2017 to December 2019 were retrospectively collected. We utilized logistic regression and least absolute shrinkage and selection operator (LASSO) regression to identify the independent predictive factors of MVI and its M2 classification. Integrated discrimination improvement (IDI) and net reclassification improvement (NRI) were calculated to select the potential predictive factors from the results of LASSO and logistic regression. Nomograms for predicting MVI and its M2 grade were then developed by incorporating these factors. Area under the curve (AUC), calibration curve, and decision curve analysis (DCA) were respectively used to evaluate the efficacy, accuracy, and clinical utility of the nomograms.ResultsCombined with the results of LASSO regression, logistic regression, and IDI and NRI analyses, we founded that clinical tumor-node-metastasis (TNM) stage, tumor size, Edmondson–Steiner classification, α-fetoprotein (AFP), tumor capsule, tumor margin, and tumor number were independent risk factors for MVI. Among the MVI-positive patients, only clinical TNM stage, tumor capsule, tumor margin, and tumor number were highly correlated with M2 grade. The nomograms established by incorporating the above variables had a good performance in predicting MVI (AUCMVI = 0.926) and its M2 classification (AUCM2 = 0.803). The calibration curve confirmed that predictions and actual observations were in good agreement. Significant clinical utility of our nomograms was demonstrated by DCA.ConclusionsThe nomograms of this study make it possible to do individualized predictions of MVI and its M2 classification, which may help us select an appropriate treatment plan.

(20S) Ginsenoside Rh2 Exerts Its Anti-Tumor Effect by Disrupting the HSP90A-Cdc37 System in Human Liver Cancer Cells.

(20S) ginsenoside Rh2 (G-Rh2), a major bioactive metabolite of ginseng, effectively inhibits the survival and proliferation of human liver cancer cells. However, its molecular targets and working mechanism remain largely unknown. Excitingly, we screened out heat shock protein 90 alpha (HSP90A), a key regulatory protein associated with liver cancer, as a potential target of (20S) G-Rh2 by phage display analysis and mass spectrometry. The molecular docking and thermal shift analyses demonstrated that (20S) G-Rh2 directly bound to HSP90A, and this binding was confirmed to inhibit the interaction between HSP90A and its co-chaperone, cell division cycle control protein 37 (Cdc37). It is well-known that the HSP90A-Cdc37 system aids in the folding and maturation of cyclin-dependent kinases (CDKs). As expected, CDK4 and CDK6, the two G0-G1 phase promoting kinases as well as CDK2, a key G1-S phase transition promoting kinase, were significantly downregulated with (20S) G-Rh2 treatment, and these downregulations were mediated by the proteasome pathway. In the same condition, the cell cycle was arrested at the G0-G1 phase and cell growth was inhibited significantly by (20S) G-Rh2 treatment. Taken together, this study for the first time reveals that (20S) G-Rh2 exerts its anti-tumor effect by targeting HSP90A and consequently disturbing the HSP90A-Cdc37 chaperone system. HSP90A is frequently overexpressed in human hepatoma cells and the higher expression is closely correlated to the poor prognosis of liver cancer patients. Thus, (20S) G-Rh2 might become a promising alternative drug for liver cancer therapy.

Predicting the prognosis of liver cancer patients based on cell differentiation trajectory and application of nanomaterials in treatment.

article: Predicting the prognosis of liver cancer patients based on cell differentiation trajectory and application of nanomaterials in treatment - Minerva Surgery 2021 Dec 10 - Minerva Medica - Journals

A Starvation-Based 9-mRNA Signature Correlates With Prognosis in Patients With Hepatocellular Carcinoma.

BackgroundHepatocellular carcinoma (HCC) is one of the world’s most prevalent and lethal cancers. Notably, the microenvironment of tumor starvation is closely related to cancer malignancy. Our study constructed a signature of starvation-related genes to predict the prognosis of liver cancer patients.MethodsThe mRNA expression matrix and corresponding clinical information of HCC patients were obtained from the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). Gene set enrichment analysis (GSEA) was used to distinguish different genes in the hunger metabolism gene in liver cancer and adjacent tissues. Gene Set Enrichment Analysis (GSEA) was used to identify biological differences between high- and low-risk samples. Univariate and multivariate analyses were used to construct prognostic models for hunger-related genes. Kaplan-Meier (KM) and receiver-operating characteristic (ROC) were used to assess the model accuracy. The model and relevant clinical information were used to construct a nomogram, protein expression was detected by western blot (WB), and transwell assay was used to evaluate the invasive and metastatic ability of cells.ResultsFirst, we used univariate analysis to identify 35 prognostic genes, which were further demonstrated to be associated with starvation metabolism through Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO). We then used multivariate analysis to build a model with nine genes. Finally, we divided the sample into low- and high-risk groups according to the median of the risk score. KM can be used to conclude that the prognosis of high- and low-risk samples is significantly different, and the prognosis of high-risk samples is worse. The prognostic accuracy of the 9-mRNA signature was also tested in the validation data set. GSEA was used to identify typical pathways and biological processes related to 9-mRNA, cell cycle, hypoxia, p53 pathway, and PI3K/AKT/mTOR pathway, as well as biological processes related to the model. As evidenced by WB, EIF2S1 expression was increased after starvation. Overall, EIF2S1 plays an important role in the invasion and metastasis of liver cancer.ConclusionsThe 9-mRNA model can serve as an accurate signature to predict the prognosis of liver cancer patients. However, its mechanism of action warrants further investigation.

Constitutive TDO2 expression promotes liver cancer progression by an autocrine IL-6 signaling pathway

BackgroundIncreased tryptophan (Trp) metabolism by indoleamine 2,3-dioxygenase (IDO)/tryptophan 2,3-dioxygenase (TDO) represents one of the most studied pathways for immunosuppression in tumor tissues. However, the pro-tumor effects induced by Trp metabolism remain controversial.MethodsThe paraffin sections of tumor tissues were obtained from patients with liver cancer and examined by immunohistochemical staining to investigate the role of Trp metabolic enzymes. To further confirm the pro-tumor effects induced by TDO2, we established TDO2 overexpression SMC-7721 and HepG2 liver cancer cell lines, and western blotting, cell proliferation, and colony formation were evaluated. Meanwhile, liver cancer subcutaneous mice models were established, and the tumorigenic rates of SMC-7721 cells, tumor volume and survival of bearing mice were calculated. In addition, the survival data of liver cancer patients from The Cancer Genome Atlas (TCGA) database were downloaded to analyze the effect of TDO2 expression on the survival of patients with liver cancer.ResultsHere, we showed that constitutive TDO2 expression gave rise to liver cancer through upregulation of Trp metabolism. And the TDO2 expression was positively correlated with the poor prognosis in liver cancer patients. TDO2 expression in tumor cells accounted for the release of kynurenine (Kyn), which activated aryl hydrocarbon receptor (AhR) to promote liver cancer cells proliferation. Mechanistically, we found that AhR expression contributed to the secretion of Interleukin-6 (IL-6), thereby promoting tumor cells proliferation through the STAT3 and NF-kB/TIM4 signals. Interrupt of AhR signals by PDM2 revealed improved outcomes in subcutaneous tumor-bearing mice.ConclusionsTogether, our study showed that the TDO2/Kyn/AhR/IL-6 signaling pathway was a novel mechanism underlying the malignancy of liver cancer, and suggested that AhR signals might be a valuable therapeutic target for tumor therapy.

Role of N6-Methyladenosine (m6A) Methylation Regulators in Hepatocellular Carcinoma.

Liver cancer is the fifth most common malignant tumor in terms of incidence and the third leading cause of cancer-related mortality globally. Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer. Although great progress has been made in surgical techniques, hepatic artery chemoembolization, molecular targeting and immunotherapy, the prognosis of liver cancer patients remains very poor. N6-methyladenosine (m6A) is the most abundant internal RNA modification in eukaryotic cells and regulates various stages of the RNA life cycle. Many studies have reported that the abnormal expression of m6A-related regulators in HCC represent diagnostic and prognostic markers and potential therapeutic targets. In this review, firstly, we introduce the latest research on m6A-related regulators in detail. Next, we summarize the mechanism of each regulator in the pathogenesis and progression of HCC. Finally, we summarize the potential diagnostic, prognostic and therapeutic value of the regulators currently reported in HCC.

A novel RNA binding protein-associated prognostic model to predict overall survival in hepatocellular carcinoma patients.

Hepatocellular carcinoma (HCC) is 1 of the deadliest malignancies worldwide. Despite significant advances in diagnosis and treatment, the mortality rate from HCC persists at a substantial level. Construction of a prognostic model that can reliably predict HCC patients’ overall survival is urgently needed.Two RNA-seq dataset (the Cancer Genome Atlas and International Cancer Genome Consortium) and 1 microarray dataset (GSE14520) were included in our study. RNA-binding proteins (RBPs) in HCC patients was examined by differentially expressed genes analysis, functional enrichment analysis and protein-protein interaction network analysis. Subsequently, the Cancer Genome Atlas dataset was randomly divided into training and testing cohort with a prognostic model developed in the training cohort. In order to evaluate the prognostic value of the model, a comprehensive survival assessment was conducted.Five RBPs (ribosomal protein L10-like, enhancer of zeste homolog 2 (EZH2), peroxisome proliferator-activated receptor gamma coactivator 1 alpha (PPARGC1A), zinc finger protein 239, interferon-induced protein with tetratricopeptide repeats 1) were used to construct the model. The model accurately predicted the prognosis of liver cancer patients in both the training cohort and validation cohort. HCC patients could be assigned into a high-risk group and a low-risk group by this model, and the overall survival of these 2 groups was significantly different (P < .05). Furthermore, the risk scores obtained by this model were highly correlated with immune cell infiltration.The prognostic model helps to identify HCC patients at high risk of mortality, which optimizes decision-making for individualized treatment.

Computational analysis for identification of early diagnostic biomarkers and prognostic biomarkers of liver cancer based on GEO and TCGA databases and studies on pathways and biological functions affecting the survival time of liver cancer

BackgroundLiver cancer is the sixth most commonly diagnosed cancer and the fourth most common cause of cancer death. The purpose of this work is to find new diagnostic biomarkers or prognostic biomarkers and explore the biological functions related to the prognosis of liver cancer.MethodsGSE25097 datasets were firstly obtained and compared with TCGA LICA datasets and an analysis of the overlapping differentially expressed genes (DEGs) was conducted. Cytoscape was used to screen out the Hub Genes among the DEGs. ROC curve analysis was used to screen the Hub Genes to determine the genes that could be used as diagnostic biomarkers. Kaplan-Meier analysis and Cox proportional hazards model screened genes associated with prognosis biomarkers, and further Gene Set Enrichment Analysis was performed on the prognosis genes to explore the mechanism affecting the survival and prognosis of liver cancer patients.Results790 DEGs and 2162 DEGs were obtained respectively from the GSE25097 and TCGA LIHC data sets, and 102 Common DEGs were identified by overlapping the two DEGs. Further screening identified 22 Hub Genes from 102 Common DEGs. ROC and survival curves were used to analyze these 22 Hub Genes and it was found that there were 16 genes with a value of AUC > 90%. Among these, the expression levels of ESR1,SPP1 and FOSB genes were closely related to the survival time of liver cancer patients. Three common pathways of ESR1, FOBS and SPP1 genes were identified along with seven common pathways of ESR1 and SPP1 genes and four common pathways of ESR1 and FOSB genes.ConclusionsSPP1, AURKA, NUSAP1, TOP2A, UBE2C, AFP, GMNN, PTTG1, RRM2, SPARCL1, CXCL12, FOS, DCN, SOCS3, FOSB and PCK1 can be used as diagnostic biomarkers for liver cancer, among which FOBS and SPP1 genes can also be used as prognostic biomarkers. Activation of the cell cycle-related pathway, pancreas beta cells pathway, and the estrogen signaling pathway, while on the other hand inhibition of the hallmark heme metabolism pathway, hallmark coagulation pathway, and the fat metabolism pathway may promote prognosis in liver cancer patients.

Construction and Validation of Prognostic Markers of Liver Cancer Based on Autophagy Genes.

Liver cancer is one of the most common diseases in the world. At present, the mechanism of autophagy genes in liver cancer is not very clear. Therefore, it is meaningful to study the role and the prognostic value of autophagy genes in liver cancer. The purpose of this study is to conduct a bioinformatics analysis of autophagy genes related to primary liver cancer for establishing a prognostic model of primary liver cancer based on autophagy genes. We identified autophagy genes related to the prognosis of liver cancer through bioinformatics methods. Through difference analysis, 31 differential autophagy genes were screened out and then analyzed by GO and KEGG analysis. At the same time, we built a PPI network. For optimizing the evaluation of the prognosis of liver cancer patients, we integrated multiple autophagy genes, after which a prognostic model was established. By using univariate cox regression analysis, 15 autophagy genes related to prognosis were screened out. Then we included these 15 genes into the Least Absolute Shrinkage and Selection Operator (LASSO) and performed a multi-factor cox regression analysis on the 9 selected genes for constructing a prognostic model. The risk score of each patient, who participated in the establishing of the model, was calculated based on 4 genes (BIRC5, HSP8, SQSTM1, and TMEM74). Then the patients were divided into high-risk groups and low-risk groups. In the multivariate cox regression analysis, the risk score was assessed by the independent prognostic factors (HR = 1.872, 95% CI = 1.544 - 2.196, p < 0.001). Survival analysis showed that the survival time of the low-risk group was significantly longer than that of the high-risk group. By combining clinical characteristics and autophagy genes, we constructed a nomogram for predicting the prognosis. The external dataset GSE14520 proved that the nomogram has a good prediction for individual patients with primary liver cancer. This study provided potential autophagy-related markers for liver cancer patients to predict their prognosis and reveal part of the molecular mechanism of liver cancer autophagy. At the same time, certain gene pathways and protein pathways related to autophagy may provide some inspiration for the development of anticancer drugs.

Impact of marital status on the prognosis of liver cancer patients without surgery and the critical window.

Liver cancer (LC) is the second leading cause of cancer-associated mortality. However, the critical time window during the marital status may influence the prognosis of LC is still unknown. Information on a total of 4,933 patients diagnosed with primary LC who had not undergone surgery was collected from the Surveillance, Epidemiology, and End Results (SEER) database to analyze the impact of marital status on the risk of cancer-specific mortality (CSM). All confirmed patients were monitored from January 1, 2010 until December 31, 2015 for the occurrence of death. We performed 1:1 propensity score matching among the married and non-married groups to eliminate dissimilarities in age, sex, race and clinical characteristics. Cox proportional hazards regression model was adopted to investigate the associations between marital status and the risk of CSM. Married patients were significantly negatively associated with the risk of CSM among patients compared to non-married status, with a hazard ratio (HR) [95% confidence interval (CI)] of 1.15 (1.07-1.23). The strongest associations were observed for patients with Grade II, American Joint Committee on Cancer (AJCC) I and III. Furthermore, the protective effect of marriage on the prognosis of LC was independent of sex, age, race, grade, AJCC and SEER stage. Unmarried or separated patients may have a worse prognosis. Marriage was strongly associated with a positive prognosis among patients with LC, especially in the critical window of Grade II, AJCC I and III. This study highlights the important impact of marriage on cancer prognosis.