An electrochemical biosensor based on DNA “nano-bridge” for amplified detection of exosomal microRNAs

Exosomal miRNAs, as potential biomarkers in liquid biopsy for cancer early diagnosis, have aroused widespread concern. Herein, an electrochemical biosensor based on DNA “nano-bridge” was designed and applied to detect exosomal microRNA-21 (miR-21) derived from breast cancer cells. In brief, the target miR-21 can specifically open the hairpin probe 1(HP1) labeled on the gold electrode (GE) surface through strand displacement reaction. Thus the exposed loop region of HP1 can act as an initiator sequence to activate the hybridization chain reaction (HCR) between two kinetically trapped hairpin probes: HP2 immobilized on the GE surface and biotin labeled HP3 in solution. Cascade HCR leads to the formation of DNA “nano-bridge” tethered to the GE surface with a great deal of “piers”. Upon addition of avidin-modified horseradish peroxidase (HRP), numerous HRP were bound to the formed “nano-bridge” through biotin-avidin interaction to arouse tremendous current signal. In theory, only a single miR-21 is able to trigger the continuous HCR between HP2 and HP3 until all of the HP2 are exhausted. Therefore the proposed biosensor achieved ultrahigh sensitivity toward miR-21 with the detection limit down to 168 amol/L, as well as little cross-hybridization even at the single-base-mismatched level. Successful attempts were also made in the detection of exosomal miR-21 obtained from the MCF-7 of breast cancer cell line. To our knowledge, this is the first attempt to built horizontal DNA nano-structure on the electrode surface for exosomal miRNAs detection. In a word, the high sensitivity, selectivity, low cost make the proposed method hold great potential application for early point-of-care (POC) diagnostics of cancer.     

Os(VI)bipy-based electrochemical assay for detection of specific microRNAs as potential cancer biomarkers

Recently, altered expression levels of microRNAs (miRNAs) – short noncoding RNA molecules which bind to mRNAs and thus regulate gene expression – were observed in many cancer cells. miRNA expression profiling is therefore of great interest, but current standard methods are still considered relatively laborious and expensive. Electrochemistry has a potential to become quick and inexpensive alternative. Here, we describe modification of miRNA with an electroactive complex composed of six-valent osmium and 2,2′-bipyridine, Os(VI)bipy, specifically binding to the 3′-end of the ribose, which is detectable at hanging mercury drop electrode at femtomole level due to an electrocatalytic nature of a resulting signal. By combining miRNA labeling step with magnetic beads-based hybridization assay, detection of specific miRNA sequence from a mixture of other noncomplementary miRNAs was possible.     

Identifying critical states of hepatocellular carcinoma based on landscape dynamic network biomarkers

Hepatocellular carcinoma (HCC) is the major histological form of primary liver cancer. It has usually reached the disease state once the patient is diagnosed since there are no specific symptoms in the early stages of HCC. This fact increases the difficulty of curing HCC. Recently, quantities of evidence have shown that many mathematical methods (such as dynamic network biomarkers, DNB) can be used to detect critical states or tipping points of complex diseases. However, it is difficult to apply the DNB theory to the clinic since multiple samples are generally unavailable for individual patient. This paper constructs a novel method based on landscape dynamic network biomarkers (L-DNB), which aims to detect early warning signals from cirrhosis state to very advanced HCC state in individual patient. The selected dataset contains multiple samples for each HCC state. A score that indicates the disease characteristics is calculated for each sample by RNA-seq data, and several scores constitute a distribution in the same state. Quantifying the statistical characteristics of these distributions and determining that low-grade dysplastic and high-grade dysplastic are the critical states of HCC. These results can provide scientific advice for early warning indicators and optimal treatment time for HCC.     

Utilization of metabolomics to identify serum biomarkers for hepatocellular carcinoma in patients with liver cirrhosis

Characterizing the metabolic changes pertaining to hepatocellular carcinoma (HCC) in patients with liver cirrhosis is believed to contribute towards early detection, treatment, and understanding of the molecular mechanisms of HCC. In this study, we compare metabolite levels in sera of 78 HCC cases with 184 cirrhotic controls by using ultra performance liquid chromatography coupled with a hybrid quadrupole time-of-flight mass spectrometry (UPLC–QTOF MS). Following data preprocessing, the most relevant ions in distinguishing HCC cases from patients with cirrhosis are selected by parametric and non-parametric statistical methods. Putative metabolite identifications for these ions are obtained through mass-based database search. Verification of the identities of selected metabolites is conducted by comparing their MS/MS fragmentation patterns and retention time with those from authentic compounds. Quantitation of these metabolites is performed in a subset of the serum samples (10 HCC and 10 cirrhosis) using isotope dilution by selected reaction monitoring (SRM) on triple quadrupole linear ion trap (QqQLIT) and triple quadrupole (QqQ) mass spectrometers. The results of this analysis confirm that metabolites involved in sphingolipid metabolism and phospholipid catabolism such as sphingosine-1-phosphate (S-1-P) and lysophosphatidylcholine (lysoPC 17:0) are up-regulated in sera of HCC vs. those with liver cirrhosis. Down-regulated metabolites include those involved in bile acid biosynthesis (specifically cholesterol metabolism) such as glycochenodeoxycholic acid 3-sulfate (3-sulfo-GCDCA), glycocholic acid (GCA), glycodeoxycholic acid (GDCA), taurocholic acid (TCA), and taurochenodeoxycholate (TCDCA). These results provide useful insights into HCC biomarker discovery utilizing metabolomics as an efficient and cost-effective platform. Our work shows that metabolomic profiling is a promising tool to identify candidate metabolic biomarkers for early detection of HCC cases in high risk population of cirrhotic patients.     

Serum metabolomics as a novel diagnostic approach for gastrointestinal cancer

Conventional tumor markers are unsuitable for detecting carcinoma at an early stage and lack clinical efficacy and utility. In this study, we attempted to investigate the differences in serum metabolite profiles of gastrointestinal cancers and healthy volunteers using a metabolomic approach and searched for sensitive and specific metabolomic biomarker candidates. Human serum samples were obtained esophageal (n = 15), gastric (n = 11), and colorectal (n = 12) cancer patients and healthy volunteers (n = 12). A model for evaluating metabolomic biomarker candidates was constructed using multiple classification analysis, and the results were assessed with receiver operating characteristic curves. Among the 58 metabolites, the levels of nine, five and 12 metabolites were significantly changed in the esophageal, gastric and colorectal cancer patients, respectively, compared with the healthy volunteers. Multiple classification analysis revealed that the variations in the levels of malonic acid and l ‐serine largely contributed to the separation of esophageal cancer; gastric cancer was characterized by changes in the levels of 3‐hydroxypropionic acid and pyruvic acid; and l ‐alanine, glucuronoic lactone and l ‐glutamine contributed to the separation of colorectal cancer. Our approach revealed that some metabolites are more sensitive for detecting gastrointestinal cancer than conventional biomarkers. Our study supports the potential of metabolomics as an early diagnostic tool for cancer. Copyright © 2011 John Wiley & Sons, Ltd.     

Serum N-glycan fingerprint helps to discriminate intrahepatic cholangiocarcinoma from hepatocellular carcinoma

Hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC) are two main types of primary liver cancer, and reliable discrimination is important for optimal treatment. Aberrant glycosylation was detected in HCC and ICC. Both cross-sectional and follow-up studies were performed to establish a differential diagnosis model using N-glycans. A total of 420 participants were enrolled, with 310 patients in training cohort and 110 patients in validation cohort. The follow-up cohort was used to assess the prognosis of ICC. As the results, the diagnostic efficacy of the model was superior to alpha-fetoprotein (AFP), carcinoembryonic antigen (CEA) and carbohydrate antigen 19-9 (CA 19-9) when identifying ICC from HCC (AUC of the nomogram: 0.845, 95%CI: 0.788–0.902; AFP: 0.793, 95%CI: 0.732–0.854; CEA: 0.592, 95%CI: 0.496–0.687; CA 19-9: 0.674, 95%CI: 0.582–0.767) in training cohort. In validation cohort, this model (AUC: 0.810, 95% CI: 0.728–0.891) also demonstrated high efficacy in distinguishing ICC from HCC. Furthermore, the nomogram helps to stratify ICC into two subgroups with high or low risk of survival and recurrence. Therefore, a nomogram integrating six N-glycans [NGA2FB(Peak2), NG1A2F (Peak3), NA2 (Peak5), NA2F (Peak6), NA3 (Peak8) and NA4 (Peak11)] was established for ICC and HCC differentiation, and for prognosis assessment in ICC patients.     

Chromatographic determination of some biomarkers of liver cirrhosis and hepatocellular carcinoma in Egyptian patients

Metabolomics has been shown to be an effective tool for disease diagnosis, biomarker screening and characterization of biological pathways. A total of 140 subjects were included in this study; urine metabolomes of patients with liver cirrhosis (LC, n = 40), patients with hepatocellular carcinoma (HCC; n = 55) and healthy male subjects (n = 45) as a control group were studied. Gas chromatography/mass spectrometry‐based urine metabolomics profiles were investigated for all participants. Diagnostic models were constructed with a combination of marker metabolites, using principal components analysis and receiver operator characteristic curves. A total of 57 peaks could be auto‐identified of which 13 marker metabolites (glycine, serine, threonine, proline, urea, phosphate, pyrimidine, arabinose, xylitol, hippuric acid, citric acid, xylonic acid and glycerol) were responsible for the separation of HCC group from healthy subjects. Also, eight markers metabolites (glycine, serine, threonine, proline, citric acid, urea, xylitol and arabinose) showed significant differences between the LC group and healthy subjects. No significant difference was detected between HCC and LC groups regarding all these metabolites. Metabolomic profile using GC–MS established an optimized diagnostic model to discriminate between HCC patients and healthy subjects; also it could be useful for diagnosis of LC patients. However, it failed to differentiate between HCC and LC patients.     

Erythrocyte membrane encapsulated gambogic acid nanoparticles as a therapeutic for hepatocellular carcinoma

Gambogic acid (GA) is a potential clinical anticancer drug that can exert antitumor effects via various molecular mechanisms. Notwithstanding, GA's low water solubility, poor stability, short half-life, and unavoidable toxic side effects have significantly hampered its clinical application. Erythrocyte membrane-coated nanoparticles (RBCM-NPs) improve drug's physicochemical properties, biocompatibility, and pharmacokinetic behaviors, allowing for long-term drug circulation and passive targeting. In this study, a novel biomimetic drug delivery system (DDS) against hepatocellular carcinoma was prepared by covering RBCM on GPP-NPs (GA-loaded mPEG-PLA NPs) to develop the RBC@GPP-NPs. In comparison to RBCM-free nanoparticles and free GA, RBC@GPP-NPs improved the drug's water solubility, stability, safety, and anti-tumor activity in vivo. We expect that this bionic nanoparticle composite can expand the clinical applicability of GA and provide a feasible solution for the research and development of GA's nano-formulation.     

Development of lactobionic acid conjugated-copper chelators as anticancer candidates for hepatocellular carcinoma

Hepatic copper deposition leads to metabolic disorders, rapid increase in reactive oxygen species (ROS) levels, and even the occurrence and metastasis of hepatocellular carcinoma. Copper chelation or copper transporter inhibition have already been developed into an effective method to control the canceration of hepatocytes and kill the hepatocarcinoma cells. Here, we designed three novel lactobionic acid conjugated copper chelators (GT1, 9 and 10), which have the potential to be recognized by asialoglycoprotein receptor (ASGPR), a high-capacity C-type lectin receptor selectively expressed in liver. Both GT1, 9 and 10 can selectively and efficiently coordinate with copper in solution and in the high-copper treated hepatocellular carcinomas model (HC HepG2 cells). The thiosemicarbazone-based chelator GT1 should more effectively eliminate copper and promote apoptosis of HC HepG2 cells, which might have application prospects in preventing cancerization and other pathological lesions caused by copper deposition of liver. Moreover, our results also revealed the potential of GT1 to be harnessed as preventive leading structures of the hepatocellular carcinomas.     

Network-based ranking methods for prediction of novel disease associated microRNAs

BackgroundMany studies have shown roles of microRNAs on human disease and a number of computational methods have been proposed to predict such associations by ranking candidate microRNAs according to their relevance to a disease. Among them, machine learning-based methods usually have a limitation in specifying non-disease microRNAs as negative training samples. Meanwhile, network-based methods are becoming dominant since they well exploit a “disease module” principle in microRNA functional similarity networks. Of which, random walk with restart (RWR) algorithm-based method is currently state-of-the-art. The use of this algorithm was inspired from its success in predicting disease gene because the “disease module” principle also exists in protein interaction networks. Besides, many algorithms designed for webpage ranking have been successfully applied in ranking disease candidate genes because web networks share topological properties with protein interaction networks. However, these algorithms have not yet been utilized for disease microRNA prediction.MethodsWe constructed microRNA functional similarity networks based on shared targets of microRNAs, and then we integrated them with a microRNA functional synergistic network, which was recently identified. After analyzing topological properties of these networks, in addition to RWR, we assessed the performance of (i) PRINCE (PRIoritizatioN and Complex Elucidation), which was proposed for disease gene prediction; (ii) PageRank with Priors (PRP) and K-Step Markov (KSM), which were used for studying web networks; and (iii) a neighborhood-based algorithm.ResultsAnalyses on topological properties showed that all microRNA functional similarity networks are small-worldness and scale-free. The performance of each algorithm was assessed based on average AUC values on 35 disease phenotypes and average rankings of newly discovered disease microRNAs. As a result, the performance on the integrated network was better than that on individual ones. In addition, the performance of PRINCE, PRP and KSM was comparable with that of RWR, whereas it was worst for the neighborhood-based algorithm. Moreover, all the algorithms were stable with the change of parameters. Final, using the integrated network, we predicted six novel miRNAs (i.e., hsa-miR-101, hsa-miR-181d, hsa-miR-192, hsa-miR-423-3p, hsa-miR-484 and hsa-miR-98) associated with breast cancer.ConclusionsNetwork-based ranking algorithms, which were successfully applied for either disease gene prediction or for studying social/web networks, can be also used effectively for disease microRNA prediction.     

Simultaneous and multiplex detection of exosomal microRNAs based on the asymmetric Au@Au@Ag probes with enhanced Raman signal

Simultaneous and quantitative detection of multiple exosomal micro RNAs(miRNAs) was successfully performed by a surface-enhanced Raman scattering(SERS) assay consisting of Raman probes and capture probes. In this design, the asymmetric core-shell structured Au@Au@Ag nanoparticles were first synthesized by layer-by-layer self-assembly method and modified with different Raman molecules and recognition sequences(poly A-DNA) to prepare the surface-enhanced Raman probes. Then, the streptavidinmodifie...     

Serum metabolomics as a novel diagnostic approach for disease: a systematic review

Metabolomics is a promising "omics" field in systems biology; its objective is comprehensive analysis of low-molecular-weight endogenous metabolites in a biological sample. It could enable mapping of perturbations of early biochemical changes in diseases and hence provide an opportunity to develop predictive biomarkers that could result in earlier intervention and provide valuable insights into the mechanisms of diseases. Because of the possible discovery of clinically relevant biomarkers, metabolomics has potential advantages that routine approaches to clinical diagnosis do not. Monitoring specific metabolite levels in serum, the most commonly used biofluid in metabolomics, has become an important way of detecting the early stages of a disease. Serum is a readily accessible and informative biofluid, making it ideal for early detection of a wide range of diseases, and analysis of serum has several advantages over analysis of other biofluids. Metabolite profiles of serum can be regarded as important indicators of physiological and pathological states and may aid understanding of the mechanism of disease occurrence and progression on the metabolic level, and provide information enabling identification of early and differential metabolic markers of disease. Analysis of these crucial metabolites in serum has become important in monitoring the state of biological organisms and is widely used for diagnosis of disease. Emerging metabolomics will drive serum analysis, facilitate and improve the development of disease treatments, and provide great benefits for public health in the long-term.     

Insights regarding novel biomarkers and the pathogenesis of primary colorectal carcinoma based on bioinformatic analysis

BackgroundBiomarkers are important in the study of tumor processes for early detection and precise treatment. The biomarkers that have been previously detected are not useful for clinical application for primary colorectal carcinoma (PCRC). The aim of this study was to explore clinically valuable biomarkers of PCRC based on integrated bioinformatic analysis.Material and methodsGene expression data were acquired from the GSE41258 dataset, and the differentially expressed genes were determined between PCRC and normal colorectal samples. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses were implemented via Gene Set Enrichment Analysis. A protein-protein interaction (PPI) network was constructed. The significant modules and hub genes were screened and identified in the PPI network.ResultsA total of 202 DEGs were identified, including 58 upregulated and 144 downregulated genes in PCRC samples compared to those in normal colorectal samples. Enrichment analysis demonstrated that the gene sets enriched in PCRC were significantly related to bicarbonate transport, regulation of sodium ion transport, potassium ion homeostasis, regulation of telomere maintenance, and other processes. A total of 10 hub genes was identified by cytoHubba: PYY, CXCL3, CXCL11, CXCL8, CXCL12, CCL20, MMP3, P2RY14, NPY1R, and CXCL1.ConclusionThe hub genes, such as NPY1R, P2RY14, and CXCL12, and the electrolyte disequilibrium resulting from the differential expression of genes, especially bicarbonate imbalance, may provide novel insights and evidence for the future diagnosis and targeted therapy of PCRC.     

Serum metabolomics reveals the deregulation of fatty acids metabolism in hepatocellular carcinoma and chronic liver diseases

Patients with chronic liver diseases (CLD) including chronic hepatitis B and hepatic cirrhosis (CIR) are the major high-risk population of hepatocellular carcinoma (HCC). The differential diagnosis between CLD and HCC is a challenge. This work aims to study the related metabolic deregulations in HCC and CLD to promote the discovery of the differential metabolites for distinguishing the different liver diseases. Serum metabolic profiling analysis from patients with CLD and HCC was performed using a liquid chromatography–mass spectrometry system. The acquired large amount of metabolic information was processed with the random forest–recursive feature elimination method to discover important metabolic changes. It was found that long-chain acylcarnitines accumulated, whereas free carnitine, medium and short-chain acylcarnitines decreased with the severity of the non-malignant liver diseases, accompanied with corresponding alterations of enzyme activities. However, the general changing extent was smaller in HCC than in CIR, possibly due to the special energy-consumption mechanism of tumor cells. These observations may help to understand the mechanism of HCC occurrence and progression on the metabolic level and provide information for the identification of early and differential metabolic markers for HCC.     

Analysis of urinary nucleosides as helper tumor markers in hepatocellular carcinoma diagnosis

Hepatocellular carcinoma (HCC) is a common neoplasm in Taiwan, for which early diagnosis is difficult and the prognosis is usually poor. HCC is usually diagnosed by abdominal sonography and serum alpha‐fetoprotein (AFP) detection. Modified nucleosides, regarded as indicators for the whole‐body turnover of RNAs, are excreted in abnormal amounts in the urine of patients with malignancies and can serve as tumor markers. We analyzed the excretion patterns of urinary nucleosides from 25 HCC patients and 20 healthy volunteers by high‐performance liquid chromatography/electrospray ionization tandem mass spectrometry (HPLC/ESI‐MS/MS) under optimized conditions. The HPLC/ESI‐MS/MS approach with selective reaction monitoring (SRM) allowed for the sensitive determination of nucleosides in human urine samples. The mean levels of the urinary nucleosides adenosine, cytidine, and inosine were significantly higher in HCC patients than healthy volunteers (average of 1.78‐, 2.26‐, and 1.47‐fold, respectively). However, the mean levels of urinary 1‐methyladenosine, 3‐methylcytidine, uridine, and 2′‐deoxyguanosine were not significantly different. Combined with the determination of serum AFP levels, the higher levels of urinary adenosine, cytidine, and inosine may be additional diagnosis markers for HCC in Taiwanese patients. Copyright © 2009 John Wiley & Sons, Ltd.     

Advanced radionuclides in diagnosis and therapy for hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the most common primary malignant tumor of the liver, but early diagnosis and effective treatment are still difficult. With the development of radionuclide applications in medicine, nuclear medicine is playing an increasingly important role in the diagnosis and treatment of HCC. Radionuclide-based positron emission tomography-computed tomography and single-photon emission computed tomography-computed tomography molecular imaging are indispensable for assessing progression, staging, differentiation, preoperative planning, postoperative prediction, and evaluation of HCC in clinical applications. Moreover, radionuclide-based endoradiotherapy provides an objective therapeutic strategy for patients with unresectable advanced HCC. This review highlights the application and development of radionuclides in the diagnosis and treatment of HCC. More efforts are warranted for the development of advanced radionuclides to make significant contributions in the treatment of HCC.     

Preclinical investigation of artesunate as a therapeutic agent for hepatocellular carcinoma via impairment of glucosylceramidase-mediated autophagic degradation

Artesunate (ART) has been indicated as a candidate drug for hepatocellular carcinoma (HCC). Glucosylceramidase (GBA) is required for autophagic degradation. Whether ART regulates autophagic flux by targeting GBA in HCC remains to be defined. Herein, our data demonstrated that the dramatic overexpression of GBA was significantly associated with aggressive progression and short overall survival times in HCC. Subsequent experiments revealed an association between autophagic activity and GBA expression in clinical HCC samples, tumor tissues from a rat model of inflammation-induced HCC and an orthotopic mouse model, and human HCC cell lines. Interestingly, probe labeling identified GBA as an ART target, which was further verified by both a glutathione-S-transferase pulldown assay and surface plasmon resonance analysis. The elevated protein expression of LC3B, the increased numbers of GFP-LC3B puncta and double-membrane vacuoles, and the enhanced expression of SQSTM1/p62 indicated that the degradation of autophagosomes in HCC cells was inhibited by ART treatment. Both the in vitro and in vivo data revealed that autophagosome accumulation through targeting of GBA was responsible for the anti-HCC effects of ART. In summary, this preclinical study identified GBA as one of the direct targets of ART, which may have promising potential to inhibit lysosomal autophagy for HCC therapy.Subject terms: Oncogenes, Drug development, Prognostic markers, Tumour biomarkers     

Facile preparation of 177Lu-microspheres for hepatocellular carcinoma radioisotope therapy

As one of the most common cancers in the world, hepatocellular carcinoma (HCC) has become a major threat to human health. Radioembolization is a first-line option for the treatment of HCC, especially when other conventional treatments fail or there exist some relative contraindications. Herein, we developed a facile and efficient method for preparing ¹⁷⁷Lu-microspheres potentially useful for precise radioembolization therapy of HCC. The radiolabeling efficiency of ¹⁷⁷Lu-microspheres was as high as 96.8% ± 0.5%, and the radiolabeling process did not alter the morphology of the mother microspheres. The SPECT/CT studies enabled by the unique emissions of ¹⁷⁷Lu suggested that almost no ¹⁷⁷Lu ion loaded by the microspheres was released over more than 32 d in vivo, which led to remarkable inhibition effect on the growth of HepG2 tumors subcutaneously transplanted in mice. The current approach may thus offer promising ¹⁷⁷Lu-microspheres for clinical radioembolization of HCC.     

Bladder squamous cell carcinoma biomarkers derived from proteomics

Proteomics provide powerful technology for analyzing the expression levels of thousands of proteins simultaneously both in health and disease. Here, we review proteomic strategies that we have developed to identify metaplastic lesions in bladder squamous cell carcinomas as well as biomarkers in the urine for follow-up studies of squamous cell carcinoma (SCC)-bearing patients.