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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-β 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.

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.

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. 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. 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. 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.

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. 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. 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

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.

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 study confirmed that INPP5F could enhance lactate production and glucose consumption in HCC cells. Mechanistically, INPP5F interacted with ASPH through which INPP5F activated Notch signaling and subsequently promoted the expression of c-MYC and cyclin E1. Interestingly, INPP5F was commonly nuclear-located in cells of adjacent tissues, while cytoplasmic-located was more common in HCC cells. LMB (nuclear export inhibitor) treatment restricted INPP5F in nucleus and was associated with inhibition of Notch signaling and cell proliferation. Furthermore, sequence of nuclear localization signals (NLSs) and nuclear export signals (NESs) in INPP5F aminoacidic sequence were identified. Alteration of the NLSs or NESs influenced the localization of INPP5F and the expression of its downstream molecules. 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.

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.

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. 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. 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. 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. Funding Statement: This work was supported by the National Natural Science Foundation of China (No. 81572407, 81602112, 81672405, 81702404 ); Key project of Natural Science Foundation of Guangdong Province, China (No. 4210016041); Science and Technology Program of Guangdong Province, China (No.2015A030313096, 2016A030313184, 2017A030313536); Natural Science Foundation of Guangzhou, China (No. 4250016043). Declaration of Interests: We declare that we have no conflicts of interest. Ethics Approval Statement: The ethics committee board of Sun Yat-sen Memorial Hospital, Sun Yat-sen University, approved the use of patients with early colon carcinoma for this study.

Background: To develop and validate accurate preoperative nomograms to predict microvascular invasion (MVI) and lymph node metastasis (LNM) in hepatocellular carcinoma. Methods: A total of 302 patients with resected HCC were divided into a training set (n=202) in an earlier period and a validation set (n=100) thereafter. Risk factors for MVI and LNM were assessed based on logistic regression. The blood signatures were established with the least absolute shrinkage and selection operator algorithm. Nomograms were constructed by combining risk factors and blood signatures. Performance was evaluated in the training set and validated in the validation set. The clinical values of the nomograms were measured by decision curve analysis. Findings: The risk factors for MVI were hepatitis B virus history and three CT imaging features, namely, tumor number, size and encapsulation, while only tumor number and size were associated with LNM. The blood signatures achieved favorable prediction efficacy with C-indexes of 0.725 and 0.709 in MVI and LNM nomograms. The nomograms incorporating the risk factors and the blood signatures also achieved good C-indexes of 0.792 and 0.771 in predicting MVI in the training and validation sets, while 0.784 and 0.844 of the LNM nomogram. Calibration curves demonstrated good fit. The decision curves indicated significant clinical usefulness. Interpretation: Our novel validated nomograms for HCC patients are noninvasive preoperative prediction tools that can effectively predict the individualized risk of MVI and LNM, and this predictive power can help doctors formulate rational individual treatments. Funding Statement: This work was supported in part by the National Natural Science Foundation of China (No. 81572407, 81602112, 81672405, 81702404 ); Key project of Natural Science Foundation of Guangdong Province, China (No. 4210016041); Science and Technology Program of Guangdong Province, China (No.2015A030313096, 2016A030313184, 2017A030313536); Natural Science Foundation of Guangzhou, China (No. 4250016043). Declaration of Interests: The authors declare that they have no conflicts of interest. Ethics Approval Statement: The retrospective study with anonymous data was approved by the institutional Ethics Committee of Sun Yat-sen Memorial Hospital, Sun Yat-sen University.

Hepatocellular carcinoma (HCC) is one of the most aggressive malignant tumors, with a poor long-term prognosis worldwide. The functional deregulations of global transcriptome have been found to be associated with the genesis and development of HCC. A total of 519 postoperative HCC patients from independent centers were included in our study. We performed an integrative analysis that found 39 DEmRNAs, 83 DElncRNAs and 20 DEmiRNAs, then we built an interactive and visual competing endogenous RNA (ceRNA) network from TCGA database including 354 HCC samples. In the TCGA training set, we identified a 4-gene signature (PBK, CBX2, CLSPN and CPEB3) and effectively predicted the OS using a LASSO penalized regression. The survival times of patients in the high-risk group were worse than those in the low-risk group according to log-rank testing (P = 0.0004), and death was also more likely in the high-risk group (HR = 2.444, 95% CI = 1.800-3.088, P < 0.001). The results were validated using a TCGA internal validation set (HR = 1.855, 95% CI = 1.310-2.400, P = 0.0057) and two external validation cohorts (HR = 1.305, 95% CI = 0.867-1.744; P = 0.29 and HR = 2.626, 95% CI = 2.188-3.064; P = 0.04). The signature (AUCs of one, two, three years were 0.716, 0.726, 0.714, respectively) showed high prognostic accuracy in the complete TCGA cohort. In summary, we successfully built a more extensive ceRNA network for HCC and then identified a 4-gene-based signature, enabling prediction of the overall survival of patients with HCC. Funding Statement: This work was supported by the National Natural Science Foundation of China (No. 81572407, 81602112, 81672405, 81702404 ); Key project of Natural Science Foundation of Guangdong Province, China (No. 4210016041); Science and Technology Program of Guangdong Province, China (No.2015A030313096, 2016A030313184, 2017A030313536); Natural Science Foundation of Guangzhou, China (No. 4250016043); These funding sources had no role in the data collection, analysis or interpretation; in the study design; in the writing of the manuscript; or in the decision to submit the paper for publication. Declaration of Interests: The authors declare that they have no conflicts of interest. Ethics Approval Statement: The data from the TCGA, the GEO database and Sun Yat-sen Memorial Hospital were anonymous. The institutional review boards of SYMH approved the study and the need to obtain informed consent was waived.