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Simple Summary: Currently, there is no effective method to detect the prognosis for hepatocellular carcinoma (HCC). This study used bioinformatics techniques to determine HCC molecular subtypes and prognosis-related biomarkers. A total of 3330 intersectional differentially expressed genes (DEGs) with the same differential direction in four datasets were identified by differential expression analysis. Intersectional DEGs were involved in the cell cycle, FOXO signaling pathway, and complement and coagulation cascades. Then, two subtypes were identified using a non-negative matrix decomposition method. Subtype C2 displayed better overall survival than subtype C1. Moreover, 217 prognostic related-genes were identified using the Cox regression and Kaplan-Meier curves. The area under the curve >0.80 of prognostic relate-genes were selected to construct random survival forest and the least absolute shrinkage and selection operator model and obtained seven feature genes (SORBS2, DHRS1, SLC16A2, RCL1, IGFALS, GNA14 and FANCI). Risk score model and recurrence model were constructed based on feature genes, and FANCI was inferred as a key gene by univariate Cox model. High expression of FANCI was mainly involved in cell cycle, DNA replication and mismatch repair. Interestingly, Single Sample Gene Set Enrichment Analysis was used to quantify immune infiltration and showed that Th2 cells and T helper cells were significantly up regulated in HCC compared to controls. Furthermore, we found the presence of two mutation sites as well as methylation modifications occurred in FANCI. Overall, we identified two types of HCC and identified that FANCI will serve as a potential biomarker for HCC prognosis and be important to the diagnosis and treatment of HCC. Bioinformatics tools were used to identify prognosis-related molecular subtypes and biomarkers of hepatocellular carcinoma (HCC). Differential expression analysis of four datasets identified 3330 overlapping differentially expressed genes (DEGs) in the same direction in all four datasets. Those genes were involved in the cell cycle, FOXO signaling pathway, as well as complement and coagulation cascades. Based on non-negative matrix decomposition, two molecular subtypes of HCC with different prognoses were identified, with subtype C2 showing better overall survival than subtype C1. Cox regression and Kaplan-Meier analysis showed that 217 of the overlapping DEGs were closely associated with HCC prognosis. The subset of those genes showing an area under the curve >0.80 was used to construct random survival forest and least absolute shrinkage and selection operator models, which identified seven feature genes (SORBS2, DHRS1, SLC16A2, RCL1, IGFALS, GNA14, and FANCI) that may be involved in HCC occurrence and prognosis. Based on the feature genes, risk score and recurrence models were constructed, while a univariate Cox model identified FANCI as a key gene involved mainly in the cell cycle, DNA replication, and mismatch repair. Further analysis showed that FANCI had two mutation sites and that its gene may undergo methylation. Single-sample gene set enrichment analysis showed that Th2 and T helper cells are significantly upregulated in HCC patients compared to controls. Our results identify FANCI as a potential prognostic biomarker for HCC. [ABSTRACT FROM AUTHOR]

Context: Identifying the pathological diagnosis for patients with primary hepatocellular carcinoma (HCC) depends on recognizing the microscopic cytological morphology and pathological molecular marker expressions. However, there are nearly 100 markers of primary HCC, most of which are discretely distributed. Thus, the diagnostical process lacks certainty.Aims: Settings and Design: A preliminary study.Methods and Material: A total of 37,012 pathological molecular markers were selected in this study from 1,034 randomly selected patients with primary HCC from January 2014 to June 2019. Patient information included demographic and pathological characteristics, immunohistochemical and blood biochemical indicators, and other biological laboratory data.Statistical Analysis Used: The discriminant analysis method (parametric and non-parametric) was used in two-thirds of the dataset to quantitatively establish the discriminant equation of gender, age, and positive variables determined by the Cochran-Armitage trend test for pathologic grading. The remaining one-third dataset was used to verify the discriminative ability.Results: According to the fitted discriminant equation, only CD34, CD68, Glypican-3, HepPar-1, and Ki-67 (%) exhibited high sensitivity for the diagnosis of primary HCC. Among these five indicators, glypican-3 demonstrated a relatively high correlation with Ki-67 (%). CK19 and CK7 were highly correlated. Glypican-3 demonstrated a higher positive rate in poorly differentiated tumors, whereas HepPar-1 exhibited a higher positive rate in well-differentiated tumors.Conclusions: Gender, age, HepPar-1, Ki-67 (%), and Glypican-3 demonstrated higher accuracy in discriminating the pathological grades of I/II, but the ability to discriminate pathological grades III/IV was insufficient. Additionally, other factors were found to affect pathological grading. [ABSTRACT FROM AUTHOR]

The interaction between Axin and DVL2 is critical for the breaking down of the beta‐catenin destruction complex and the activation of the Wnt/beta‐catenin cascade. However, this biological process remains poorly understood. In the present study, TM4SF1 was identified as the interacting partner of DVL2 and positively regulated as Wnt/beta‐catenin signalling by strengthening the DVL2‐Axin interaction. The expression levels of TM4SF1 were elevated in hepatocellular carcinoma (HCC) and were induced by Kras signalling. The overexpression of TM4SF1 promoted the growth and motility of HCC cells, and up‐regulated the target genes (Axin2 and cyclin D1). The down‐regulation of TM4SF1 impaired the capability of HCC cells for growth, migration and metastasis. In addition, the down‐regulation of TM4SF1 promoted the ubiquitination of beta‐catenin. In summary, these results reveal the oncogenic functions of TM4SF1 in HCC progression and suggest that TM4SF1 might be a target for treatment. [ABSTRACT FROM AUTHOR]

RNA-binding motif protein 8A (RBM8A) is abnormally overexpressed in hepatocellular carcinoma (HCC) and involved in the epithelial-mesenchymal transition (EMT). The EMT plays an important role in the development of drug resistance, suggesting that RBM8A may be involved in the regulation of oxaliplatin (OXA) resistance in HCC. Here we examined the potential involvement of RBM8A and its downstream pathways in OXA resistance using in vitro and in vivo models. RBM8A overexpression induced the EMT in OXA-resistant HCC cells, altering cell proliferation, apoptosis, migration, and invasion. Moreover, whole-genome microarrays combined with bioinformatics analysis revealed that RBM8A has a wide range of transcriptional regulatory capabilities in OXA-resistant HCC, including the ability to regulate several important tumor-related signaling pathways. In particular, histone deacetylase 9 (HDAC9) emerged as an important mediator of RBM8A activity related to OXA resistance. These data suggest that RBM8A and its related regulatory pathways represent potential markers of OXA resistance and therapeutic targets in HCC. [ABSTRACT FROM AUTHOR]

Wnt/beta-catenin signaling is frequently activated in hepatocellular carcinoma (HCC). Better understanding the mechanism for its over-activation would help the therapy. In this study, we have shown that the stress-induced phosphoprotein 1 (STIP1) is up-regulated in the HCC tissues. Functional studies showed that STIP1 promoted the growth, colony formation and migration of cancer cells. However, knocking down the expression of STIP1 inhibited the growth, colony formation and migration of cancer cells. Molecular mechanism study showed that STIP1 interacted with Axin, enhanced the interaction between Axin and DVL2, thus activated beta-catenin/TCF signaling. Taken together, our study demonstrated the oncogenic roles of STIP1 in the progression of HCC, and suggested that STIP1 might be a therapeutic target. [ABSTRACT FROM AUTHOR]

Over-activation of beta-catenin/TCF signaling has been frequently observed in hepatocellular carcinoma (HCC). Better understanding the molecular mechanism for the aberrant activation of beta-catenin/TCF signaling would provide novel insights into the treatment of this malignancy. In this study, we have shown that the expression of PKMYT1 was up-regulated in HCC. PKMYT1 positively regulated the growth, migration, colony formation, metastasis and epithelia mesenchymal transition (EMT) of HCC cells. Mechanically, PKMTY1 activated the beta-catenin/TCF signaling by binding and inactivating GSK3beta. Taken together, our study demonstrated the oncogenic activity of PKMYT1 in the progression of HCC and suggested that PKMYT1 might be a therapeutic target. [ABSTRACT FROM AUTHOR]