Search

Graphical abstract, Introduction The development and prognosis of HCC involve complex molecular mechanisms, which affect the effectiveness of its treatment strategies. Tumor mutational burden (TMB) is related to the efficacy of immunotherapy, but the prognostic role of TMB-related genes in HCC has not yet been determined clearly. Objectives In this study, we identified TMB-specific genes with good prognostic value to build diagnostic and prognostic models and provide guidance for the treatment of HCC patients. Methods Weighted gene co-expression network analysis (WGCNA) was applied to identify the TMB-specific genes. And LASSO method and Cox regression were used in establishing the prognostic model. Results The prognostic model based on SMG5 and MRPL9 showed patients with higher prognostic risk had a remarkedly poorer survival probability than their counterparts with lower prognostic risk in both a TCGA cohort (P

Cadmium (Cd) is a widely distributed toxic heavy metal that enters the environment via anthropogenic mobilization and accumulates in plants and animals, causing metabolic abnormalities even mortality. Although the toxic effects and stress damage of cadmium have been investigated extensively over the past few decades, research on its ability to trigger ferroptosis, growth retardation, and behavioral abnormalities is insufficient. As a result, the effects of CdCl

Purpose To develop and validate a radiomic nomogram based on arterial phase of CT to discriminate the primary ovarian cancers (POCs) and secondary ovarian cancers (SOCs). Methods A total of 110 ovarian cancer patients in our hospital were reviewed from January 2010 to December 2018. Radiomic features based on the arterial phase of CT were extracted by Artificial Intelligence Kit software (A.K. software). The least absolute shrinkage and selection operation regression (LASSO) was employed to select features and construct the radiomics score (Rad-score) for further radiomics signature calculation. Multivariable logistic regression analysis was used to develop the predicting model. The predictive nomogram model was composed of rad-score and clinical data. Nomogram discrimination and calibration were evaluated. Results Two radiomic features were selected to build the radiomics signature. The radiomics nomogram that incorporated 2 radiomics signature and 2 clinical factors (CA125 and CEA) showed good discrimination in training cohort (AUC 0.854), yielding the sensitivity of 78.8% and specificity of 90.7%, which outperformed the prediction model based on radiomics signature or clinical data alone. A visualized differential nomogram based on the radiomic score, CEA, and CA125 level was established. The calibration curve demonstrated the clinical usefulness of the proposed nomogram. Conclusion The presented nomogram, which incorporated radiomic features of arterial phase of CT with clinical features, could be useful for differentiating the primary and secondary ovarian cancers.

Type 2 diabetes mellitus (T2DM) patients may develop into mild cognitive impairment (MCI) or even dementia. However, there is lack of reliable machine learning model for detection MCI in T2DM patients based on machine learning method. In addition, the brain network changes associated with MCI have not been studied. The aim of this study is to develop a machine learning based algorithm to help detect MCI in T2DM. There are 164 participants were included in this study. They were divided into T2DM-MCI (n = 56), T2DM-nonMCI (n = 49), and normal controls (n = 59) according to the neuropsychological evaluation. Functional connectivity of each participant was constructed based on resting-state magnetic resonance imaging (rs-fMRI). Feature selection was used to reduce the feature dimension. Then the selected features were set into the cascaded multi-column random vector functional link network (RVFL) classifier model using privileged information. Finally, the optimal model was trained and the classification performance was obtained using the testing data. The results show that the proposed algorithm has outstanding performance compared with classic methods. The classification accuracy of 73.18 % (T2DM-MCI vs NC) and 79.42 % (T2DM-MCI vs T2DM-nonMCI) were achieved. The functional connectivity related to T2DM-MCI mainly distribute in the frontal lobe, temporal lobe, and central region (motor cortex), which could be used as neuroimaging biomarkers to recognize MCI in T2DM patients. This study provides a machine learning model for diagnosis of MCI in T2DM patients and has potential clinical significance for timely intervention and treatment to delay the development of MCI.

Case Presentation A 55-year-old Chinese man without significant medical history presented with progressive chest discomfort and night sweats for the past 2 months. He experienced nonexertional chest tightness and palpitation at night, not associated with dyspnea. These symptoms usually lasted for a few minutes and resolved spontaneously. He also reported night sweats but denied fever, chills, or weight change. He had never smoked and denied recent contact with anyone known to be ill.

In clinic, metastasis is still the main reason for death for cancer patients. Therefore, it is necessary to track cancer metastases accurately, kill cancer cells effectively, and then improve the prognosis of patients with advanced cancer. Therefore, we designed a liposome-based pretargeted system modified with single-stranded DNA and targeting peptide injected in sequence and then assembled

Hepatic cancer is a serious disease with high morbidity and mortality. Theranostic agents with effective diagnostic and therapeutic capability are highly needed for the treatment of hepatic cancer. Herein, we aimed to develop a novel mesoporous polydopamine (MPDA)-based theranostic agent for T1/T2 dual magnetic resonance imaging (MRI)-guided cancer chemo-photothermal therapy. Superparamagnetic iron oxide (SPIO)-loaded MPDA NPs (MPDA@SPIO) was firstly prepared, followed by modifying with a targeted molecule of sialic acid (SA) and chelating with Fe3+ (SA-MPDA@SPIO/Fe3+ NPs). After that, doxorubicin (DOX)-loaded SA-MPDA@SPIO/Fe3+ NPs (SA-MPDA@SPIO/DOX/Fe3+) was prepared for tumor theranostics. The prepared SAPEG-MPDA@SPIO/Fe3+ NPs were water-dispersible and biocompatible as evidenced by MTT assay. In vitro photothermal and relaxivity property suggested that the novel theranostic agent possessed excellent photothermal conversion capability and photostability, with relaxivity of being r1 = 4.29 mM−1s−1 and r2 = 105.53 mM−1s−1, respectively. SAPEG-MPDA@SPIO/Fe3+ NPs could effectively encapsulate the DOX, showing dual pH- and thermal-triggered drug release behavior. In vitro and in vivo studies revealed that SA-MPDA@SPIO/DOX/Fe3+ NPs could effectively target to the hepatic tumor tissue, which was possibly due to the specific interaction between SA and the overexpressed E-selectin. This behavior also endowed SA-MPDA@SPIO/DOX/Fe3+ NPs with a more precise T1-T2 dual mode contrast imaging effect than the one without SA modification. In addition, SAPEG-MPDA@SPIO/DOX/Fe3+ NPs displayed a superior therapeutic effect, which was due to its active targeting ability and combined effects of chemotherapy and photothermal therapy. These results demonstrated that SAPEG-MPDA@SPIO/DOX/Fe3+ NPs is an effective targeted nanoplatform for tumor theranostics, having potential value in the effective treatment of hepatic cancer., Graphical abstract Image 1, Highlights • Sialic acid (SA)-modified SPIO-loaded mesoporous polydopamine (MPDA) was prepared. • SAPEG-MPDA@SPIO NPs was effective at dual loading Fe3+ ion and DOX. • SAPEG-MPDA@SPIO/DOX/Fe3+ NPs showed pH- and NIR-responsible drug release behaviors. • SAPEG-MPDA@SPIO/DOX/Fe3+ NPs could actively target to the hepatic tumor sites. • The novel theranostic achieved dual-mode MRI guided chemo-photothermal therapy.

Background Cancer cells primarily utilize aerobic glycolysis for energy production, a phenomenon known as the Warburg effect. Increased aerobic glycolysis supports cancer cell survival and rapid proliferation and predicts a poor prognosis in cancer patients. Methods Molecular profiles from The Cancer Genome Atlas (TCGA) cohort were used to analyze the prognostic value of glycolysis gene signature in human cancers. Gain- and loss-of-function studies were performed to key drivers implicated in hepatocellular carcinoma (HCC) glycolysis. The molecular mechanisms underlying Osteopontin (OPN)-mediated glycolysis were investigated by real-time qPCR, western blotting, immunohistochemistry, luciferase reporter assay, and xenograft and diethyl-nitrosamine (DEN)-induced HCC mouse models. Results Increased glycolysis predicts adverse clinical outcome in many types of human cancers, especially HCC. Then, we identified a handful of differentially expressed genes related to HCC glycolysis. Gain- and loss-of-function studies showed that OPN promotes, while SPP2, LECT2, SLC10A1, CYP3A4, HSD17B13, and IYD inhibit HCC cell glycolysis as revealed by glucose utilization, lactate production, and extracellular acidification ratio. These glycolysis-related genes exhibited significant tumor-promoting or tumor suppressive effect on HCC cells and these effects were glycolysis-dependent. Mechanistically, OPN enhanced HCC glycolysis by activating the αvβ3-NF-κB signaling. Genetic or pharmacological blockade of OPN-αvβ3 axis suppressed HCC glycolysis in xenograft tumor model and hepatocarcinogenesis induced by DEN. Conclusions Our findings reveal crucial determinants for controlling the Warburg metabolism in HCC cells and provide a new insight into the oncogenic roles of OPN in HCC.

MiR‐155‐5p is a key oncogenic microRNA that maintains immune homeostasis and mediates cross‐talk between inflammation and tumorigenesis. High expression of programmed death ligand‐1 (PD‐L1) also plays an important role in immune tolerance in tumors. The present study aimed to explore the relationship between miR‐155‐5p and PD‐L1 in lung adenocarcinoma (LUAD) cells A549 and H1650. The expression levels of miR‐155‐5p and PD‐L1 in LUAD patients were detected by a quantitative reverse transcriptase‐polymerase chain reaction (qRT‐PCR) and mimics of miR‐155‐5p were used to model increased expression in A549 or H1650 cells. After 24 h, we measured levels of PD‐L1 by qRT‐PCR, western blotting and flow cytometry. In addition, we identified two sites in the PD‐L1 3′‐UTR (5′‐AGCAUUA‐3′ and 5′‐GCAUUAA‐3′) that can be bound by miR‐155‐5p using TargetScan (http://www.targetscan.org). Compared to normal tissue, miR‐155‐5p was overexpressed in tumor tissue (P = 0.0456), whereas the expression of PD‐L1 was not significantly different (P = 0.1349). The expression levels of miR‐155‐5p and PD‐L1 were negatively correlated (r = −0.6409, P = 0.0459 and r = −0.7544, P = 0.0117). Exogenous overexpression of miR‐155‐5p decreased the mRNA, total protein and membrane protein expression levels of PD‐L1 both in A549 and H1650 cells (P, The present study aimed to verify the regulation of programmed death ligand‐1 (PD‐L1) expression by miR155‐5p in lung adenocarcinoma. We conducted experiments at tissue and cell levels, and analyzed the potential mechanism through bioinformatics. The results show that miR‐155‐5p overexpression can inhibit PD‐L1 mRNA and protein expression. The mechanism may be that miR‐155‐5p affects PD‐L1 translation by binding to 3′‐UTR.

Prebiotics, such as algal polysaccharides, can be used to manage metabolic diseases by modulating gut microbiota. However, the effect of Pyropia yezoensis porphyran (PYP), a red algal polysaccharide, on gut microbiota has not been reported. Thus, the objective of this study was to determine effects of PYP on metabolic disorders caused by high sucrose (HS) and underlying mechanisms involved in such effects.Biochemical analysis demonstrated that an HS diet increased triglyceride and circulating sugar contents (metabolic abnormalities) in Drosophila larvae. It also increased the relative abundance of harmful microbiota within the larvae as identified by 16S ribosomal DNA analysis. PYP supplementation at 25 and 50 g kgPYP exhibits anti-metabolic disorder activity by modulating gut microbiota, thereby supporting the development of PYP as a functional prebiotic derived from red algae food. Copyright © 2022 John WileySons, Ltd. © 2022 Society of Chemical Industry.

The polarization of macrophages often leads to severe calcification and necrosis in aged atherosclerotic plaques, which eventually leads to poor prognosis of ischaemic cardiovascular and cerebrovascular diseases. More reliable diagnostic methods are urgently needed to discover therapeutic targets of macrophage polarization in aged atherosclerotic plaques. Metabolomics of aged plaques (n = 20) and macrophage polarization transcriptomes (n = 30) were integrated to identify metabolic therapeutic targets of macrophage polarization associated with aged plaque. Finally, metabolic inhibitors were used to verify the reliability of the target genes. Integrated multiomics analysis revealed that 6 metabolic pathways (including 21 genes) regulate macrophage polarization in aged atherosclerosis. Targeted treatment of macrophage polarization with metabolic inhibitors can effectively reduce the adverse risk of aged atherosclerosis. The combination of transcriptomics and metabolomics approaches can identify effective therapeutic targets for macrophage polarization in arteriosclerosis.

Jinyu Zhu,1,2,&ast; Bufu Tang,1,3,&ast; Yang Gao,1,4 Suqin Xu,5 Jianfei Tu,1,4 Yajie Wang,4 Weibin Yang,1,4 Shiji Fang,4 Qiaoyou Weng,4 Zhongwei Zhao,1,4 Min Xu,1,4 Yang Yang,1,4 Minjiang Chen,1,4 Chenying Lu,1,4 Jiansong Ji1,4 1Key Laboratory of Imaging Diagnosis and Minimally Invasive Intervention Research, Lishui Hospital, School of Medicine, Zhejiang University, Lishui, 323000, People’s Republic of China; 2Department of Radiology, Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310016, People’s Republic of China; 3Department of Radiology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, 310016, People’s Republic of China; 4Department of Radiology, The Fifth Affiliated Hospital of Wenzhou Medical University, Lishui, 323000, People’s Republic of China; 5Clinical Laboratory, Fuyuan Hospital of Yiwu, Jinhua, 321000, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Jiansong Ji; Chenying Lu Email jijiansong@zju.edu.cn; luchenying@zju.edu.cnIntroduction: Hepatocellular carcinoma (HCC) is a heterogeneous molecular disease with complex molecular pathogenesis that influences the efficacy of therapies. Exosomes play a crucial role in tumorigenesis and poor disease outcomes in HCC.Objective: The aim of this study was to identify the optimal gene set derived from exosomes in HCC with substantial predictive value to construct models for determining prognosis, recurrence risk and diagnosis and to identify candidates suitable for immunotherapy and chemotherapy, thereby providing new ideas for the individualized treatment of patients and for improving prognosis.Methods: Weighted correlation network analysis (WGCNA) and univariate and multivariate Cox PH regression analyses were applied to identify exosome-related signatures in the TCGA and exoRbase databases associated with clinical relevance, immunogenic features and tumor progression in HCC. Cell experiments were performed to further confirm the oncogenic effect of MYL6B and THOC2.Results: The models for prognosis and recurrence risk prediction were built based on two exosomal genes (MYL6B and THOC2) and were confirmed to be independent predictive factors with superior predictive performance. Patients with high prognostic risk had poorer prognosis than patients with low prognostic risk in all HCC datasets, namely, the TCGA cohort (HR=2.5, P< 0.001), the ICGC cohort (HR=3.15, P< 0.001) and the GSE14520 cohort (HR=1.85, P=0.004). A higher recurrence probability was found in HCC patients with high recurrence risk than in HCC patients with low recurrence risk in the TCGA cohort (HR=2.44, P< 0.001) and the GSE14520 cohort (HR=1.54, P=0.025). High prognostic risk patients had higher expression of immune checkpoint genes, such as PD1, B7H3, B7H5, CTLA4 and TIM3 (P< 0.05). Diagnostic models based on the same two genes were able to accurately distinguish HCC patients from normal individuals and HCC from dysplastic nodules.Conclusion: Our findings lay the foundation for identifying molecular markers to increase the early detection rate of HCC, improve disease outcomes, and determine more effective individualized treatment options for patients.Keywords: exosome, hepatocellular carcinoma, HCC, immune checkpoint, prognosis

Recognizing early cardiac sarcoidosis (CS) imaging phenotypes can help identify opportunities for effective treatment before irreversible myocardial pathology occurs. We aimed to characterize regional CS myocardial remodeling features correlating with future adverse cardiac events by coupling automated image processing and data analysis on cardiac magnetic resonance (CMR) imaging datasets. A deep convolutional neural network (DCNN) was used to process a CMR database of a 10-year cohort of 117 consecutive biopsy-proven sarcoidosis patients. The maximum relevance - minimum redundancy method was used to select the best subset of all the features-24 (from manual processing) and 232 (from automated processing) left ventricular (LV) structural/functional features. Three machine learning (ML) algorithms, logistic regression (LogR), support vector machine (SVM) and multi-layer neural networks (MLP), were used to build classifiers to categorize endpoints. Over a median follow-up of 41.8 (inter-quartile range 20.4-60.5) months, 35 sarcoidosis patients experienced a total of 43 cardiac events. After manual processing, LV ejection fraction (LVEF), late gadolinium enhancement, abnormal segmental wall motion, LV mass (LVM), LVMI index (LVMI), septal wall thickness, lateral wall thickness, relative wall thickness, and wall thickness of 9 (out of 17) individual LV segments were significantly different between patients with and without endpoints. After automated processing, LVEF, end-diastolic volume, end-systolic volume, LV mass and wall thickness of 92 (out of 216) individual LV segments were significantly different between patients with and without endpoints. To achieve the best predictive performance, ML algorithms selected lateral wall thickness, abnormal segmental wall motion, septal wall thickness, and increased wall thickness of 3 individual segments after manual image processing, and selected end-diastolic volume and 7 individual segments after automated image processing. LogR, SVM and MLP based on automated image processing consistently showed better predictive accuracies than those based on manual image processing. Automated image processing with a DCNN improves data resolution and regional CS myocardial remodeling pattern recognition, suggesting that a framework coupling automated image processing with data analysis can help clinical risk stratification.

ObjectivesTo develop and validate a radiomic feature-based nomogram for preoperative discriminating the epidermal growth factor receptor (EGFR) activating mutation from wild-type EGFR in non-small cell lung cancer (NSCLC) patients.MaterialA group of 301 NSCLC patients were retrospectively reviewed. The EGFR mutation status was determined by ARMS PCR analysis. All patients underwent nonenhanced CT before surgery. Radiomic features were extracted (GE healthcare). The maximum relevance minimum redundancy (mRMR) and LASSO, were used to select features. We incorporated the independent clinical features into the radiomic feature model and formed a joint model (i.e., the radiomic feature-based nomogram). The performance of the joint model was compared with that of the other two models.ResultsIn total, 396 radiomic features were extracted. A radiomic signature model comprising 9 selected features was established for discriminating patients with EGFR-activating mutations from wild-type EGFR. The radiomic score (Radscore) in the two groups was significantly different between patients with wild-type EGFR and EGFR-activating mutations (training cohort: PConclusionsThe joint model showed favorable performance in the individualized, noninvasive prediction of EGFR-activating mutations in NSCLC patients.

Background: The regulatory loop between circular RNAs and microRNAs has a vital role in cell death. Ferroptosis is the form of iron-dependent cell death, which is distinct from necroptosis and apoptosis. Increasing evidences showed that ferroptosis is an important form of cell death in hepatocellular carcinoma.Methods: Real-time PCR were used to examine the expression level of circ_0013731 in hepatocellular carcinoma tissues. Edu and colony formation were performed to detect the cell proliferation. A luciferase reporter assay was used to determine the relationship between circ_0013731, miR-877-3p and SLC7A11. ChIP-qPCR assays were performed to examine the potential binding of E2F1 to the circ_0013731 promoter. Iron Assay Kit (Sigma Aldrich) was used to detect total iron or Fe2+. C11 BODIPY 581/591 staining and flow cytometer were used to examine the Lipid ROS. The role of circ_0013731 was examined in xenograft tumors model. Results: We revealed that the expression level of circ_0013731 was elevated in hepatocellular carcinoma. Moreover, E2F1 promote the transcription of circ_0013731. Overexpression of circ_0013731 promoted cell growth and inhibited ferroptosis in SMMC-7721 and QGY-7703 in vitro. miR-877-3p was proved as the direct target of circ_0013731. Then, inhibition of miR-877-3p enhanced cell growth and inhibited ferroptosis. Further mechanism research demonstrated that circ_0013731 upregulated the expression level of SLC7A11 by sponging miR-877-3p. Finally, circ_0013731 promoted HCC growth via miR-877-3p/ SLC7A11 axis in vivo.Conclusions: Our data reveal that circ_0013731 mediated by E2F1 facilitates cell growth and suppressed the ferroptosis via miR-877-3p/ SLC7A11 axis in hepatocellular carcinoma. Therefore, circ_0013731 could be acted as potential therapeutical target for hepatocellular carcinoma.

Background Tumor microenvironments are characterized by resistance to chemotherapeutic agents and radiotherapy. Hypoxia plays an important role in the development of tumor resistance, as well as the generation of metastatic potential. YAP also participates in the regulation of hypoxia-mediated chemoresistance, and is negatively regulated by protein tyrosine phosphatase non-receptor type 14 (PTPN14). Methods The PTPN14 expression in hepatocellular carcinoma (HCC) tissues were evaluated by qRT-PCR, western blot and tissue microarrays. The effect of PTPN14 on HCC progression was investigated in vitro and in vivo. Results Here, we report that PTPN14 expression was downregulated in HCC tissues and cell lines. Silencing PTPN14 significantly enhanced proliferation, migration, invasion of HepG2 cells in vitro and tumor growth and metastasis in vivo, whereas overexpression of PTPN14 significantly inhibited these abilities in SK-Hep1 cells. We also found that hypoxia-induced nuclear translocation and accumulation of PTPN14 led to resistance to sorafenib in HCC cells. Further mechanistic studies suggested that NPM1 regulates PTPN14 localization, and that NPM1 regulates YAP by retaining PTPN14 in the nucleus under hypoxic conditions. Conclusions These data suggest that a therapeutic strategy against chemoresistant HCC may involve disruption of NPM1-mediated regulation of YAP by retaining PTPN14 in the nucleus under hypoxic conditions.

The incidence of metabolic diseases is increasing every year, and several studies have highlighted the activity of persistent organic pollutants (POPs) in causing hyperlipidemia and diabetes, and these compounds are considered to be endocrine disrupting chemicals (EDCs). Chlordane is classified as an endocrine disruptor, but the mechanism of how it functions is still unclear. This study investigates the effects of chlordane exposure on Drosophila larvae. Drosophila was cultured in diet containing 0.01 μM, 0.1 μM, 1 μM, 5 μM, and 10 μM chlordane, and the toxicity of chlordane, the growth and development of Drosophila, the homeostasis of glucose and lipid metabolism and insulin signaling pathway, lipid peroxidation-related indicators and Nrf2 signaling pathway were evaluated. We here found that exposure to high concentrations of chlordane decreased the survival rate of Drosophila and that exposure to low concentrations of chlordane caused disruption of glucose and lipid metabolism, increased insulin secretion and impairment of insulin signaling. Notably, it also led to massive ROS production and lipid peroxidation despite of the activation of Nrf2 signaling pathway, an important pathway for maintaining redox homeostasis. Collectively, chlordane causes lipid peroxidation and disrupts redox homeostasis, which may be a potential mechanism leading to impaired insulin signaling and the metabolism of glucose and lipid, ultimately affects Drosophila development.

Background: Cholangiocarcinoma (CCA) is an aggressive malignancy with a poor prognosis, with no effective therapy other than surgical resection. Circular RNAs (circRNAs) serve as a brand-new class of transcription products among abundant cancer processes. Nevertheless, the mechanisms account for their modification in CCA remain unknown. Methods: First, microarray sequencing was applied to detect the difference of circRNAs expression between CCA and corresponding non-tumor tissues. We utilized qRT-PCR to measure circ-0006302 levels in CCA cells and specimens. Gain/loss of-function assays and animal model of CCA were performed for the purpose of revealing the functions of circ-0006302 on the invasion, migration, and proliferation of CCA. We performed dual luciferase reporter, RNA-FISH and rescue assays for clarifying the mechanism behind. Results: In CCA tissues and cell lines circ-0006302 was highly expressed relatively. In vitro, overexpression of circ-0006302 intensifies the epithelial-to-mesenchymal transition (EMT) and the invasion, migration, and growth of CCA cells; and intensifies the growth as well as metastasis of tumors in a CCA mouse model. Furthermore, it was elucidated that circ-0006302 sponged miR-1299 to upregulate PD‐L1 expression. Through the process above, circ-0006302 binds to miR-1299 and emancipates PD-L1, facilitating the invasion, migration, and proliferation in CCA cells. Momentously, the results obtained revealed that circ-0006302 silencing elevated the expression of interferon (IFN)‐γ, and interleukin (IL)‐4 but diminished the IL-10 expression, while these effects could be reversed by miR-1299 inhibitor.Conclusion: circ-0006302 silence blocked the CCA progression via intensifying miR‐1299‐targeted downregulation of PD‐L1. Our conclusion provides novel therapeutic tactics for treating this fatal disease.

Although piplartine is regarded as an anticancer agent, the relationship between long noncoding RNAs (lncRNAs), which are involved in various diseases (e.g., tumors) and piplartine in hepatocellular carcinoma (HCC) remains unclear. We identified LINC01391 using microarray analysis and validated its expression by qRT-PCR. Functional assays were applied to evaluate the biological effects of LINC01391 and inhibitory of β-catenin and T-cell factor (ICAT) on HepG2 and SMMC-7721 cells. The binding relationship between LINC01391 and ICAT was determined by RNA pull-down and RNA immunoprecipitation (RIP). Results showed that piplartine attenuated cell proliferation and invasion but promoted cell apoptosis. Upregulation of LINC01391 induced by piplartine inhibited HCC cell proliferation, invasion in vitro, and tumor growth in vivo. LINC01391 interacted with ICAT and promoted its inhibitory effect on the Wnt/β-catenin pathway, as enhanced interaction between β-catenin and ICAT, and dampened interaction of β-catenin and TCF/LEF were induced by overexpression of LINC01391. Knockdown of ICAT also promoted cell proliferation in vitro and tumor growth in vivo. Our study supported a role for piplartine and LINC01391 in HCC treatment. We found that LINC01391 inhibited the Wnt/β-catenin pathway and suppressed tumor growth via ICAT.

Introduction Hepatocellular carcinoma (HCC) is a heterogeneous molecular disease with complex molecular pathogenesis that influences the efficacy of therapies. Exosomes play a crucial role in tumorigenesis and poor disease outcomes in HCC. Objective The aim of this study was to identify the optimal gene set derived from exosomes in HCC with substantial predictive value to construct models for determining prognosis, recurrence risk and diagnosis and to identify candidates suitable for immunotherapy and chemotherapy, thereby providing new ideas for the individualized treatment of patients and for improving prognosis. Methods Weighted correlation network analysis (WGCNA) and univariate and multivariate Cox PH regression analyses were applied to identify exosome-related signatures in the TCGA and exoRbase databases associated with clinical relevance, immunogenic features and tumor progression in HCC. Cell experiments were performed to further confirm the oncogenic effect of MYL6B and THOC2. Results The models for prognosis and recurrence risk prediction were built based on two exosomal genes (MYL6B and THOC2) and were confirmed to be independent predictive factors with superior predictive performance. Patients with high prognostic risk had poorer prognosis than patients with low prognostic risk in all HCC datasets, namely, the TCGA cohort (HR=2.5, P

Transcatheter arterial chemoembolization (TACE) is widely used for the treatment of advanced hepatocellular carcinoma (HCC). However, the long-term hypoxic microenvironment caused by TACE seriously affects the therapeutic effect of TACE. HIF-2α plays a crucial role on the chronic hypoxia process, which might be an ideal target for TACE therapy. Herein, a multifunctional polyvinyl alcohol (PVA)/hyaluronic acid (HA)-based microsphere (PT/DOX-MS) co-loaded with doxorubicin (DOX) and PT-2385, an effective HIF-2α inhibitor, was developed for enhanced TACE treatment efficacy. In vitro and in vivo studies revealed that PT/DOX-MS had a superior ability to treat HCC by blocking the tumor cells in G2/M phase, prompting cell apoptosis, and inhibiting tumor angiogenesis. The antitumor mechanisms of PT/DOX-MS were possibly due to that the introduction of PT-2385 could effectively inhibit the expression level of HIF-2α in hypoxic HCC cells, thereby down-regulating the expression levels of Cyclin D1, VEGF and TGF-α. In addition, the combination of DOX and PT-2385 could jointly inhibit VEGF expression, which was another reason accounting for the combined anti-cancer effect of PT/DOX-MS. Overall, our study demonstrated that PT/DOX-MS is a promising embolic agent for enhanced HCC treatment via the combined effect of hypoxia microenvironment improvement, chemotherapy, and embolization.

Molecular imaging technology enables us to observe the physiological or pathological processes in living tissue at the molecular level to accurately diagnose diseases at an early stage. Optical imaging can be employed to achieve the dynamic monitoring of tissue and pathological processes and has promising applications in biomedicine. The traditional first near-infrared (NIR-I) window (NIR-I, range from 700 to 900 nm) imaging technique has been available for more than two decades and has been extensively utilized in clinical diagnosis, treatment and scientific research. Compared with NIR-I, the second NIR window optical imaging (NIR-II, range from 1000 to 1700 nm) technology has low autofluorescence, a high signal-to-noise ratio, a high tissue penetration depth and a large Stokes shift. Recently, this technology has attracted significant attention and has also become a heavily researched topic in biomedicine. In this study, the optical characteristics of different fluorescence nanoprobes and the latest reports regarding the application of NIR-II nanoprobes in different biological tissues will be described. Furthermore, the existing problems and future application perspectives of NIR-II optical imaging probes will also be discussed.

Cancer cells primarily utilize aerobic glycolysis for energy production, a phenomenon known as the Warburg effect. Increased aerobic glycolysis supports cancer cell survival and rapid proliferation and predicts a poor prognosis in cancer patients.Molecular profiles from The Cancer Genome Atlas (TCGA) cohort were used to analyze the prognostic value of glycolysis gene signature in human cancers. Gain- and loss-of-function studies were performed to key drivers implicated in hepatocellular carcinoma (HCC) glycolysis. The molecular mechanisms underlying Osteopontin (OPN)-mediated glycolysis were investigated by real-time qPCR, western blotting, immunohistochemistry, luciferase reporter assay, and xenograft and diethyl-nitrosamine (DEN)-induced HCC mouse models.Increased glycolysis predicts adverse clinical outcome in many types of human cancers, especially HCC. Then, we identified a handful of differentially expressed genes related to HCC glycolysis. Gain- and loss-of-function studies showed that OPN promotes, while SPP2, LECT2, SLC10A1, CYP3A4, HSD17B13, and IYD inhibit HCC cell glycolysis as revealed by glucose utilization, lactate production, and extracellular acidification ratio. These glycolysis-related genes exhibited significant tumor-promoting or tumor suppressive effect on HCC cells and these effects were glycolysis-dependent. Mechanistically, OPN enhanced HCC glycolysis by activating the αvβ3-NF-κB signaling. Genetic or pharmacological blockade of OPN-αvβ3 axis suppressed HCC glycolysis in xenograft tumor model and hepatocarcinogenesis induced by DEN.Our findings reveal crucial determinants for controlling the Warburg metabolism in HCC cells and provide a new insight into the oncogenic roles of OPN in HCC. Video Abstract.

BackgroundIn this study, we comprehensively analyzed genes related to ferroptosis and iron metabolism to construct diagnostic and prognostic models and explore the relationship with the immune microenvironment in HCC.MethodsIntegrated analysis, cox regression and the least absolute shrinkage and selection operator (LASSO) method of 104 ferroptosis- and iron metabolism-related genes and HCC-related RNA sequencing were performed to identify HCC-related ferroptosis and iron metabolism genes.ResultsFour genes (ABCB6, FLVCR1, SLC48A1 and SLC7A11) were identified to construct prognostic and diagnostic models. Poorer overall survival (OS) was exhibited in the high-risk group than that in the low-risk group in both the training cohort (P ConclusionsThe prognostic and diagnostic models based on the four genes indicated superior diagnostic and predictive performance, indicating new possibilities for individualized treatment of HCC patients.Graphical abstract

Background: In this study, we performed a comprehensive analysis to identify the optimal gene set derived from exosomes in hepatocellular carcinoma (HCC) with great prognostic value to construct prognostic, recurrence and diagnostic models and predicted therapeutic response for hepatocellular carcinoma.Methods: Differential expression analysis and Weighted Gene Co-Expression Network Analysis (WGCNA) of RNA-sequencing were used to identify differentially expressed exosome-derived genes related to HCC. Univariate and multivariate Cox regression analyses were performed to determine exosome-derived genes associated with prognosis of HCC to construct a prognostic model, and recurrence and diagnostic models were built based on the same genes. Results: MYL6B and THOC2 were determined to be closely related to prognosis in HCC. The prognostic and recurrence models built based on these two genes were confirmed to be independent predictive factors with superior predictive performance. Patients with high prognostic risk had poorer prognosis than patients with low prognostic risk in all HCC sets, namely, the TCGA cohort (HR=2.5, PConclusions: Prognostic, recurrence, and diagnostic models based on the two exosome-derived genes (MYL6B and THOC2) were proven superior predictive performance. Our findings lay the foundation for identifying molecular markers to increase the early detection rate of HCC, improve disease outcomes, and determine more effective individualized treatment options for patients.