SMYD4 monomethylates PRMT5 and forms a positive feedback loop to promote hepatocellular carcinoma progression.

Both lysine and arginine methyltransferases are thought to be promising therapeutic targets for malignant tumors, yet how these methyltransferases function in malignant tumors, especially hepatocellular carcinoma (HCC), has not been fully elucidated. Here, we reported that SMYD4, a lysine methyltransferase, acts as an oncogene in HCC. SMYD4 was highly upregulated in HCC and promoted HCC cell proliferation and metastasis. Mechanistically, PRMT5, a well-known arginine methyltransferase, was identified as a SMYD4-binding protein. SMYD4 monomethylated PRMT5 and enhanced the interaction between PRMT5 and MEP50, thereby promoting the symmetrical dimethylation of H3R2 and H4R3 on the PRMT5 target gene promoter and subsequently activating DVL3 expression and inhibiting expression of E-cadherin, RBL2, and miR-29b-1-5p. Moreover, miR-29b-1-5p was found to inversely regulate SMYD4 expression in HCC cells, thus forming a positive feedback loop. Furthermore, we found that the oncogenic effect of SMYD4 could be effectively suppressed by PRMT5 inhibitor in vitro and in vivo. Clinically, high coexpression of SMYD4 and PRMT5 was associated with poor prognosis of HCC patients. In summary, our study provides a model of crosstalk between lysine and arginine methyltransferases in HCC and highlights the SMYD4-PRMT5 axis as a potential therapeutic target for the treatment of HCC.

METTL3-mediated m6A modification of STEAP2 mRNA inhibits papillary thyroid cancer progress by blocking the Hedgehog signaling pathway and epithelial-to-mesenchymal transition.

Papillary thyroid cancer (PTC) is a common endocrine system malignancy all over the world. Aberrant expression of six transmembrane epithelial antigen of the prostate 2 (STEAP2) has been functionally associated with cancer progression in many cancers. Nevertheless, its biological function in PTC is still unclear. Here, we found that PTC tissues had preferentially downregulated STEAP2 as compared with noncancerous tissues. Low STEAP2 expression correlated with aggressive clinicopathological characteristics and dismal prognosis in patients with PTC. We performed gain- and loss-of-function experiments, including cell proliferation assay (Cell Counting Kit-8 assay), EdU (5-ethynyl-2'-deoxyuridine) and colony formation assays, transwell migration, and invasion assays, and constructed a nude mouse xenograft tumor model. The results demonstrated that STEAP2 overexpression inhibited PTC cell proliferation, migration, and invasion in vitro and inhibited lung metastasis and tumorigenicity in vivo. Conversely, silencing STEAP2 yielded the opposite results in vitro. Mechanistically, bioinformatics analysis combined with validation experiments identified STEAP2 as the downstream target of methyltransferase-like 3 (METTL3)-mediated N6-methyladenosine (m6A) modification. METTL3 stabilized STEAP2 mRNA and regulated STEAP2 expression positively in an m6A-dependent manner. We also showed that m6A-mediated STEAP2 mRNA translation initiation relied on a pathway dependent on the m6A reader protein YTHDF1. Rescue experiments revealed that silencing STEAP2 partially rescued the tumor-suppressive phenotype induced by METTL3 overexpression. Lastly, we verified that the METTL3-STEAP2 axis functions as an inhibitor in PTC by suppressing epithelial-mesenchymal transition and the Hedgehog signaling pathway. Taken together, these findings strongly suggest that METTL3-mediated STEAP2 m6A modification plays a critical tumor-suppressive role in PTC progression. The METTL3-STEAP2 axis may be a potential therapeutic molecular target against PTC.

INPP5F translocates into cytoplasm and interacts with ASPH to promote tumor growth in hepatocellular carcinoma.

BACKGROUND: Increasing evidence has suggested inositol polyphosphate 5-phosphatase family contributes to tumorigenesis and tumor progression. However, the role of INPP5F in hepatocellular carcinoma (HCC) and its underlying mechanisms is unclear. METHODS: The expression of INPP5F in HCC was analyzed in public databases and our clinical specimens. The biological functions of INPP5F were investigated in vitro and vivo. The molecular mechanism of INPP5F in regulating tumor growth were studied by transcriptome-sequencing analysis, mass spectrometry analysis, immunoprecipitation assay and immunofluorescence assay. RESULTS: High expression of INPP5F was found in HCC tissues and was associated with poor prognosis in HCC patients. Overexpression of INPP5F promoted HCC cell proliferation, and vice versa. Knockdown of INPP5F suppressed tumor growth in vivo. Results from transcriptome-sequencing analysis showed INPP5F not only regulated a series of cell cycle related genes expression (c-MYC and cyclin E1), but also promoted many aerobic glycolysis related genes expression. Further studies confirmed that INPP5F could enhance lactate production and glucose consumption in HCC cell. Mechanistically, INPP5F activated Notch signaling pathway and upregulated c-MYC and cyclin E1 in HCC via interacting with ASPH. Interestingly, INPP5F was commonly nuclear-located in cells of adjacent non-tumor tissues, while in HCC, cytoplasm-located was more common. LMB (nuclear export inhibitor) treatment restricted INPP5F in nucleus and was associated with inhibition of Notch signaling and cell proliferation. Sequence of nuclear localization signals (NLSs) and nuclear export signals (NESs) in INPP5F aminoacidic sequence were then identified. Alteration of the NLSs or NESs influenced the localization of INPP5F and the expression of its downstream molecules. Furthermore, we found INPP5F interacted with both exportin and importin through NESs and NLSs, respectively, but the interaction with exportin was stronger, leading to cytoplasmic localization of INPP5F in HCC. CONCLUSION: These findings indicate that INPP5F functions as an oncogene in HCC via a translocation mechanism and activating ASPH-mediated Notch signaling pathway. INPP5F may serve as a potential therapeutic target for HCC patients.

Anti-oncogene PTPN13 inactivation by hepatitis B virus X protein counteracts IGF2BP1 to promote hepatocellular carcinoma progression.

Hepatitis B x protein (HBx) affects cellular protein expression and participates in the tumorigenesis and progression of hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC). Metabolic reprogramming contributed to the HCC development, but its role in HBV-related HCC remains largely unclear. Tyrosine-protein phosphatase nonreceptor type 13 (PTPN13) is a significant regulator in tumor development, however, its specific role in hepatocarcinogenesis remains to be explored. Here, we found that decreased PTPN13 expression was associated with HBV/HBx. Patients with low PTPN13 expression showed a poor prognosis. Functional assays revealed that PTPN13 inhibited proliferation and tumorigenesis in vitro and in vivo. Further mechanistic studies indicated that HBx inhibited PTPN13 expression by upregulating the expression of DNMT3A and interacting with DNMT3A. Furthermore, we found that DNMT3A bound to the PTPN13 promoter (-343 to -313 bp) in an epigenetically controlled manner associated with elevated DNA methylation and then inhibited PTPN13 transcription. In addition, we identified IGF2BP1 as a novel PTPN13-interacting gene and demonstrated that PTPN13 influences c-Myc expression by directly and competitively binding to IGF2BP1 to decrease the intracellular concentration of functional IGF2BP1. Overexpressing PTPN13 promoted c-Myc mRNA degradation independent of the protein tyrosine phosphatase (PTP) activity of PTPN13. Importantly, we discovered that the PTPN13-IGF2BP1-c-Myc axis was important for cancer cell growth through promoting metabolic reprogramming. We verified the significant negative correlations between PTPN13 expression and c-Myc, PSPH, and SLC7A1 expression in clinical HCC tissue samples. In summary, our findings demonstrate that PTPN13 is a novel regulator of HBV-related hepatocarcinogenesis and may play an important role in HCC. PTPN13 may serve as a prognostic marker and therapeutic target in HBV-related HCC patients.

PRL-3 facilitates Hepatocellular Carcinoma progression by co-amplifying with and activating FAK.

Background: In addition to protein tyrosine kinases, accumulating evidence has shown that protein tyrosine phosphatases (PTPs) are suitable therapeutic targets in cancer. PRL-3 is a PTP member that has been well studied in many malignant tumours. The goal of the present study was to elucidate the role of PRL-3 in hepatocellular carcinoma (HCC), which remains largely unknown. Methods: Bioinformatic and immunohistochemical analyses were performed to analyse PRL-3 expression in HCC tissue samples and determine its clinical relevance. PRL-3 gene copy number variations were evaluated by bioinformatic analysis and quantitative-genomic polymerase chain reaction. The biological functions of PRL-3 were investigated in vivo and vitro. Gene microarray assays, RT-qPCR, western blotting and luciferase experiments were performed to identify the downstream effectors of PRL-3 that mediate its functions in HCC. Results: PRL-3 expression was upregulated in HCC samples from public databases and in cohort samples from our centre. High PRL-3 expression was associated with poor prognosis. Copy number gains and amplification of chromosome 8q24.3 in HCC were determined to be positively correlated with the PRL-3 overexpression. PRL-3 overexpression promoted HCC cell proliferation, migration and adhesion, while its loss had the opposite effects. Further study showed that focal adhesion kinase (FAK) was co-amplified and co-expressed with PRL-3 in HCC. Interestingly, PRL-3 also promoted the phosphorylation of FAK, which subsequently mediated the oncogenic functions of PRL-3 in HCC cells. Moreover, TGFB1 was identified as a downstream molecule of PRL-3. TGF-ß signalling was shown to mediate the PRL-3-induced activation of FAK. Furthermore, the p38 and PI3K/AKT pathways were observed to mediate the PRL-3-induced expression of TGFB1 and the subsequent activation of FAK, while the activation of FAK in turn stimulated activation of the p38 and PI3K/AKT pathways, forming a PRL-3-triggered AKT/p38/TGFB1/FAK positive feedback loop. Conclusion: Collectively, our findings indicate that the PTP PRL-3 plays a crucial role in the progression of HCC and provides an example of how co-amplified genes work together in HCC.

A Novel Staging System to Forecast the Cancer-Specific Survival of Patients With Resected Gallbladder Cancer.

Objective: Gallbladder cancer (GBC) is one of the most aggressive malignant tumors, and there is no effective and convenient method for predicting cancer-specific survival (CSS). We aim to develop a novel nomogram staging system based on the positive lymph node ratio (pLNR) for GBC patients. Methods:A total of 1,356 patients enrolled in the study. We evaluated the prognostic value of the pLNR and built a prognostic nomogram staging system based on the pLNR in the training cohort. The concordance index and calibration plots were used to evaluate model discrimination. The predictive accuracy and clinical value of the nomograms were measured by decision curve analysis (DCA). The CSS nomogram was further validated in an internal validation cohort. Results:The pLNR was an independent prognostic factor for CSS based on Cox regression analyses. A prognostic nomogram that combined T classification, pLNR, M classification, histologic grade, live metastasis, and tumor size was formulated with a c-index of 0.763 (95% CI, 0.728-0.798), while the c-indexes for the staging system of AJCC 8th, 7th, and 6th for CSS prediction were 0.718, 0.718, and 0.717, respectively. The calibration curves showed perfect agreement. The DCA showed that the nomogram provided substantial clinical value. The nomogram (the AUCs for 1, 3, and 5 years were 0.693, 0.716, and 0.726, respectively,) showed high prognostic accuracy. Conclusion:We have developed a formulated nomogram staging system based on the pLNR that allows more accurate individualized predictions of CSS for resected GBC patients than the AJCC staging systems.

Integrated Nomograms for Preoperative Prediction of Microvascular Invasion and Lymph Node Metastasis Risk in Hepatocellular Carcinoma Patients.

BACKGROUND: The aim of the present work is to develop and validate accurate preoperative nomograms to predict microvascular invasion (MVI) and lymph node metastasis (LNM) in hepatocellular carcinoma. PATIENTS AND METHODS: A total of 268 patients with resected hepatocellular carcinoma (HCC) were divided into a training set (n = 180), in an earlier period, and a validation set (n = 88), thereafter. Risk factors for MVI and LNM were assessed based on logistic regression. Blood signatures were established using the least absolute shrinkage and selection operator algorithm. Nomograms were constructed by combining risk factors and blood signatures. Performance was evaluated using the training set and validated using the validation set. The clinical values of the nomograms were measured by decision curve analysis. RESULTS: The risk factors for MVI were hepatitis B virus (HBV) DNA loading, portal hypertension, Barcelona liver clinic (BCLC) stage, and three computerized tomography (CT) imaging features, namely tumor number, size, and encapsulation, while only BCLC stage, Child-Pugh classification, and tumor encapsulation were associated with LNM. The nomogram incorporating both risk factors and blood signatures achieved better performance in predicting MVI in the training and validation sets (C-indexes of 0.828 and 0.804) than the LNM nomogram (C-indexes of 0.765 and 0.717). Calibration curves also demonstrated a good fit. The decision curves indicate significant clinical usefulness. CONCLUSIONS: The novel validated nomograms for HCC patients presented herein are noninvasive preoperative tools that can effectively predict the individualized risk of MVI and LNM, and this predictive power can aid doctors in explaining the illness for patient counseling.

Identification and validation of a prognostic four-genes signature for hepatocellular carcinoma: integrated ceRNA network analysis.

BACKGROUND: Hepatocellular carcinoma (HCC) is one of the most aggressive malignant tumors, with a poor long-term prognosis worldwide. The functional deregulations of global transcriptome were associated with the genesis and development of HCC, but lacks systematic research and validation. METHODS: A total of 519 postoperative HCC patients were included. We built an interactive and visual competing endogenous RNA network. The prognostic signature was established with the least absolute shrinkage and selection operator algorithm. Multivariate Cox regression analysis was used to screen for independent prognostic factors for HCC overall survival. RESULTS: In the training set, we identified a four-gene signature (PBK, CBX2, CLSPN, and CPEB3) and effectively predicted the overall survival. The survival times of patients in the high-score group were worse than those in the low-score group (p = 0.0004), and death was also more likely in the high-score group (HR 2.444, p < 0.001). The results were validated in internal validation set (p = 0.0057) and two external validation cohorts (HR 2.467 and 2.6). The signature (AUCs of 1, 2, 3 years were 0.716, 0.726, 0.714, respectively) showed high prognostic accuracy in the complete TCGA cohort. CONCLUSIONS: In conclusion, we successfully built a more extensive ceRNA network for HCC and then identified a four-gene-based signature, enabling prediction of the overall survival of patients with HCC.

Novel nomograms to predict lymph node metastasis and liver metastasis in patients with early colon carcinoma.

BACKGROUND: Lymph node status and liver metastasis (LIM) are important in determining the prognosis of early colon carcinoma. We attempted to develop and validate nomograms to predict lymph node metastasis (LNM) and LIM in patients with early colon carcinoma. METHODS: A total of 32,819 patients who underwent surgery for pT1 or pT2 colon carcinoma were enrolled in the study based on their records in the SEER database. Risk factors for LNM and LIM were assessed based on univariate and multivariate binary logistic regression. The C-index and calibration plots were used to evaluate LNM and LIM model discrimination. The predictive accuracy and clinical values of the nomograms were measured by decision curve analysis. The predictive nomograms were further validated in the internal testing set. RESULTS: The LNM nomogram, consisting of seven features, achieved the same favorable prediction efficacy as the five-feature LIM nomogram. The calibration curves showed perfect agreement between nomogram predictions and actual observations. The decision curves indicated the clinical usefulness of the prediction nomograms. Receiver operating characteristic curves indicated good discrimination in the training set (area under the curve [AUC] = 0.667, 95% CI 0.661-0.673) and the testing set (AUC = 0.658, 95% CI 0.649-0.667) for the LNM nomogram and encouraging performance in the training set (AUC = 0.766, 95% CI 0.760-0.771) and the testing set (AUC = 0.825, 95% CI 0.818-0.832) for the LIM nomogram. CONCLUSION: Novel validated nomograms for patients with early colon carcinoma can effectively predict the individualized risk of LNM and LIM, and this predictive power may help doctors formulate suitable individual treatments.

Development and external validation of prognostic nomograms in hepatocellular carcinoma patients: a population based study.

Background: We attempted to construct and validate novel nomograms to predict overall survival (OS) and cancer-specific survival (CSS) in patients with hepatocellular carcinoma (HCC). Methods: Models were established using a discovery set (n=10,262) obtained from the Surveillance, Epidemiology, and End Results (SEER) database. Based on univariate and multivariate Cox regression analyses, we identified independent risk factors for OS and CSS. Concordance indexes (c-indexes) and calibration plots were used to evaluate model discrimination. The predictive accuracy and clinical values of the nomograms were measured by decision curve analysis (DCA). Results: Our OS nomogram with a c-index of 0.753 (95% confidence interval (CI), 0.745-0.761) was based on age, sex, race, marital status, histological grade, TNM stage, tumor size, and surgery performed, and it performed better than TNM stage. Our CSS nomogram had a c-index of 0.748 (95% CI, 0.740-0.756). The calibration curves fit well. DCA showed that the two nomograms provided substantial clinical value. Internal validation produced c-indexes of 0.758 and 0.752 for OS and CSS, respectively, while external validation in the Sun Yat-sen Memorial Hospital (SYMH) cohort produced a c-indexes of 0.702 and 0.686 for OS and CSS, respectively. Conclusions: We have developed nomograms that enable more accurate individualized predictions of OS and CSS to help doctors better formulate individual treatment and follow-up management strategies.