Hepatocellular carcinoma (HCC) is one of the most prevalent malignancies worldwide because of rapid progression and high incidence of metastasis or recurrence. Accumulating evidence shows that CD73-expressing tumor cell is implicated in development of several types of cancer. However, the role of CD73 in HCC cell has not been systematically investigated and its underlying mechanism remains elusive. CD73 expression in HCC cell was determined by RT-PCR, Western blot, and immunohistochemistry staining. Clinical significance of CD73 was evaluated by Cox regression analysis. Cell counting kit-8 and colony formation assays were used for proliferation evaluation. Transwell assays were used for motility evaluations. Co-immunoprecipitation, cytosolic and plasma membrane fractionation separation, and ELISA were applied for evaluating membrane localization of P110β and its catalytic activity. NOD/SCID/γc(null) (NOG) mice model was used to investigate the in vivo functions of CD73. In the present study, we demonstrate that CD73 was crucial for epithelial-mesenchymal transition (EMT), progression and metastasis in HCC. CD73 expression is increased in HCC cells and correlated with aggressive clinicopathological characteristics. Clinically, CD73 is identified as an independent poor prognostic indicator for both time to recurrence and overall survival. CD73 knockdown dramatically inhibits HCC cells proliferation, migration, invasion, and EMT in vitro and hinders tumor growth and metastasis in vivo. Opposite results could be observed when CD73 is overexpressed. Mechanistically, adenosine produced by CD73 binds to adenosine A2A receptor (A2AR) and activates Rap1, which recruits P110β to the plasma membrane and triggers PIP3 production, thereby promoting AKT phosphorylation in HCC cells. Notably, a combination of anti-CD73 and anti-A2AR achieves synergistic depression effects on HCC growth and metastasis than single agent alone. CD73 promotes progression and metastasis through activating PI3K/AKT signaling, indicating a novel prognostic biomarker for HCC. Our data demonstrate the importance of CD73 in HCC in addition to its immunosuppressive functions and revealed that co-targeting CD73 and A2AR strategy may be a promising novel therapeutic strategy for future HCC management.

The role of sphere-forming culture in enriching subpopulations with stem-cell properties in hepatocellular carcinoma (HCC) is unclear. The present study investigates its value in enriching cancer stem cells (CSCs) subpopulations and the mechanism by which HCC CSCs are maintained. HCC cell lines and fresh primary tumor cells were cultured in serum-free and ultra-low attachment conditions to allow formation of HCC spheres. In vitro and in vivo experiments were performed to evaluate CSC characteristics. Expression levels of CSC-related genes were assessed by qRT-PCR and the correlation between sphere formation and clinical characteristics was investigated. Finally, gene expression profiling was performed to explore the molecular mechanism underlying HCC CSC maintenance. We found that both cell lines and primary tumor cells formed spheres. HCC spheres possessed the capacity for self-renewal, proliferation, drug resistance, and contained different subpopulations of CSCs. Of interest, 500 sphere-forming Huh7 cells or 200 primary tumor cells could generate tumors in immunodeficient animals. Sphere formation correlated with size, multiple tumors, satellite lesions, and advanced stage. Further investigation identified that the PPARα-SCD1 axis plays an important role in maintenance of the CSC properties of HCC sphere cells by promoting nuclear accumulation of β-Catenin. Inhibition of SCD1 interfered with sphere formation, down-regulated expression of CSC-related markers, and reduced β-Catenin nuclear accumulation. Sphere-forming culture can effectively enrich subpopulations with stem-cell properties, which are maintained through activation of the PPARα-SCD1 axis. Therefore, we suggest that targeting the SCD1-related CSC machinery might provide a novel insight into HCC treatment.

The aim of this study was to identify novel prognostic mRNA and microRNA (miRNA) biomarkers for hepatocellular carcinoma (HCC) using methods in systems biology. Differentially expressed mRNAs, miRNAs, and long non-coding RNAs (lncRNAs) were compared between HCC tumor tissues and normal liver tissues in The Cancer Genome Atlas (TCGA) database. Subsequently, a prognosis-associated mRNA co-expression network, an mRNA–miRNA regulatory network, and an mRNA–miRNA–lncRNA regulatory network were constructed to identify prognostic biomarkers for HCC through Cox survival analysis. Seven prognosis-associated mRNA co-expression modules were obtained by analyzing these differentially expressed mRNAs. An expression module including 120 mRNAs was significantly correlated with HCC patient survival. Combined with patient survival data, several mRNAs and miRNAs, including CHST4, SLC22A8, STC2, hsa-miR-326, and hsa-miR-21 were identified from the network to predict HCC patient prognosis. Clinical significance was investigated using tissue microarray analysis of samples from 258 patients with HCC. Functional annotation of hsa-miR-326 and hsa-miR-21-5p indicated specific associations with several cancer-related pathways. The present study provides a bioinformatics method for biomarker screening, leading to the identification of an integrated mRNA–miRNA–lncRNA regulatory network and their co-expression patterns in relation to predicting HCC patient survival.

Background: Sustained activation of hepatocyte growth factor (HGF)/c-MET signaling is a major driver of hepatocellular carcinoma (HCC) progression, but underlying mechanism is unclear. ArfGAP With SH3 Domain, Ankyrin Repeat And PH Domain 2 (ASAP2) can reportedly activate GTPases and promote receptor tyrosine kinase signaling. However, the exact role of ASAP2 in HCC, especially for c-MET activation, also remains elusive. Methods: ASAP2 expression levels in HCC tissues and cells were quantified using qRT-PCR, western blot (WB) analysis, and immunohistochemistry staining. Cell counting kit-8 (CCK-8) and colony formation assays were performed to evaluate cell proliferation rates. Flow cytometry assays were conducted to assess apoptosis rates. Wound healing and Transwell assays were performed to determine cell migration and invasion capacities. Epithelial-mesenchymal transition (EMT)-related marker expression levels were also examined. Subcutaneous implantation and tail vein injection models were applied for in vivo growth and metastasis evaluations, respectively. Bioinformatics analyses of The Cancer Genome Atlas and STRING datasets were performed to explore ASAP2 downstream signaling. Co-immunoprecipitation and Cycloheximide chasing experiments were performed to assess protein–protein interactions and protein half-life, respectively. Results: ASAP2 had higher expression levels in HCC tissues than in normal liver, and also predicted poor prognosis. Knocking down ASAP2 significantly impaired cell proliferation, migration, and invasion capacities, but promoted apoptosis in HCC cells in vitro. However, overexpression of ASAP2 achieved the opposite effects. In vivo experiments confirmed that ASAP2 could promote HCC cell growth and facilitate lung metastasis. Interestingly, ASAP2 was essential for triggering EMT. Gene Set Enrichment Analysis demonstrated that c-MET signaling was greatly enriched in ASAP2-high HCC cases. Additionally, c-MET signaling activity was significantly decreased following ASAP knockdown, evidenced by reduced c-MET, p-AKT, and p-ERK1/2 protein levels. Importantly, ASAP2 knockdown effectively attenuated HGF/c-MET signaling-induced malignant phenotypes. c-MET and ASAP2 expression levels were positively correlated in our cohort. Mechanistically, ASAP2 can directly bind to CIN85, thereby disrupting its interaction with c-MET, and can thus antagonize CIN85-induced c-MET internalization and lysosome-mediated degradation. Notably, knocking down CIN85 can rescue the observed inhibitory effects caused by ASAP2 knockdown. Conclusions: This study highlights the importance of ASAP2 in sustaining c-MET signaling, which can facilitate HCC progression.

This study aimed to establish a prognosis-prediction model based on serological indicators in patients with epithelial ovarian cancer (EOC). Patients initially diagnosed as ovarian cancer and surgically treated in Fudan University Shanghai Cancer Center from 2014 to 2018 were consecutively enrolled. Serological indicators preoperatively were collected. A risk model score (RMS) was constructed based on the levels of serological indicators determined by receiver operating characteristic curves. We correlated this RMS with EOC patients’ overall survival (OS). Finally, 635 patients were identified. Pearson’s χ² results showed that RMS was significantly related to clinical parameters. Kaplan–Meier analysis demonstrated that an RMS less than 3 correlated with a longer OS (p < 0.0001). Specifically, significant differences were perceived in the survival curves of different subgroups. Multivariate Cox analysis revealed that age (p = 0.015), FIGO stage (p = 0.006), ascites (p = 0.015) and RMS (p = 0.005) were independent risk factors for OS. Moreover, RMS combined with age, FIGO and ascites could better evaluate for patients’ prognosis in DCA analyses. Our novel RMS-guided classification preoperatively identified the prognostic subgroups of patients with EOC and showed higher accuracy than the conventional method, meaning that it could be a useful and economical tool for tailored monitoring and/or therapy.

Background: Ovarian cancer (OC) stands as the leading cause of cancer‐related deaths among women, globally, owing to metastasis and acquired chemoresistance. Cancer stem cells (CSCs) are accountable for tumor initiation and exhibit resistance to chemotherapy and radiotherapy. Identifying stemness‐related biomarkers that can aid in the stratification of risk and the response to chemotherapy for OC is feasible and critical. Methods: Gene expression and clinical data of patients with OC were downloaded from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) database. Four thousand three hundred seventeen stemness‐related genes (SRGs) were acquired from the StemChecker database. TCGA was used as the training dataset, while GSE30161 served as validation dataset. Univariate Cox regression analysis was used to identify overall survival (OS)‐related SRGs, and multivariate Cox regression analysis and random survival forest analysis were used for generating stemness‐relevant prognostic model. Kaplan–Meier plots were used to visualize survival functions. Receiver operating characteristic (ROC) curves were used to assess the prognostic predictive ability of SRG–based features. Associations between signature score, tumor immune phenotype, and response to chemotherapy were analyzed via TIMER 2.0 and oncoPredict R package, respectively. A cohort of Shanghai Cancer Center was employed to verify the predictive robustness of the signature with respect to chemotherapy response. Results: Seven SRGs (actin‐binding Rho activating C‐terminal like (ABRACL), growth factor receptor bound protein 7 (GRB7), Lin‐28 homolog B (LIN28B), lipolysis stimulated lipoprotein receptor (LSR), neuromedin U (NMU), Solute Carrier Family 4 Member 11 (SLC4A11), and thymocyte selection associated family member 2 (THEMIS2)) were found to have excellent predictive potential for patient survival. Patients in the high stemness risk group presented a poorer prognosis ( p < 0.0001), and patients with lower stemness scores were more likely to benefit from chemotherapy. Several tumorigenesis pathways, such as mitotic spindle and glycolysis, were enriched in the high stemness risk group. Tumor with high‐risk scores tended to be in a status of relatively high tumor infiltration of CD4+ T cells, neutrophils, and macrophages, while tumor with low‐risk scores tended to be in a status of relatively high tumor infiltration of CD8+ T cells. Conclusions: The stemness‐relevant prognostic gene signature has the potential to serve as a clinically helpful biomarker for guiding the management of OC patients.