Method for the extraction of circulating nucleic acids based on MOF reveals cell-free RNA signatures in liver cancer.

Cell-free RNA (cfRNA) allows assessment of health, status, and phenotype of a variety of human organs and is a potential biomarker to non-invasively diagnose numerous diseases. Nevertheless, there is a lack of highly efficient and bias-free cfRNA isolation technologies due to the low abundance and instability of cfRNA. Here, we developed a reproducible and high-efficiency isolation technology for different types of cell-free nucleic acids (containing cfRNA and viral RNA) in serum/plasma based on the inclusion of nucleic acids by metal-organic framework (MOF) materials, which greatly improved the isolation efficiency and was able to preserve RNA integrity compared with the most widely used research kit method. Importantly, the quality of cfRNA extracted by the MOF method is about 10-fold that of the kit method, and the MOF method isolates more than three times as many different RNA types as the kit method. The whole transcriptome mapping characteristics of cfRNA in serum from patients with liver cancer was described and a cfRNA signature with six cfRNAs was identified to diagnose liver cancer with high diagnostic efficiency (area under curve = 0.905 in the independent validation cohort) using this MOF method. Thus, this new MOF isolation technique will advance the field of liquid biopsy, with the potential to diagnose liver cancer.

Altered bile metabolome and its diagnostic potential for biliopancreatic malignancies.

BACKGROUND: Due to the difficulty of pathological sampling, the clinical differentiation between benign and malignant biliopancreatic diseases remains challenging. Endoscopic retrograde cholangiopancreatography (ERCP) is used to investigate biliary diseases, enabling the collection of bile. This study assessed potential metabolic alterations in biliopancreatic malignancies by exploring changes in the bile metabolome and the diagnostic potential of bile metabolome analysis. METHODS: A total of 264 bile samples were collected from patients who were divided into a discovery cohort (n = 85) and a validation cohort (n = 179). Untargeted metabolomic analysis was used in the discovery cohort, while targeted metabolomic analysis was used in the validation cohort for further investigation of the differentially abundant metabolites. RESULTS: The untargeted metabolomic analysis revealed that the metabolic changes associated with biliopancreatic malignancies occurred mainly in lipid metabolites, among which fatty acid metabolism was most significantly altered, and differentially abundant metabolites identified in the discovery cohort were mainly enriched in unsaturated fatty acid synthesis and linolenic acid synthesis pathways. Analysis of free fatty acid (FFA) metabolism in the validation cohort revealed that the FFA levels and related indicators verified the abnormal fatty acid metabolism associated with biliopancreatic malignancies. The combined model for biliopancreatic malignancies based on the fatty acid indexes and clinical test results improved the diagnostic performance of current clinical level. Then, we used machine learning to define three different FFA metabolic clusters of biliopancreatic malignancies, and survival analysis showed significant differences in prognostic outcomes among the three clusters. CONCLUSIONS: This study found metabolic alterations in biliopancreatic malignancies based on bile samples, which may provide new insights for the clinical diagnosis and prognostic assessment of biliopancreatic malignancies.

Bile liquid biopsy in biliary tract cancer.

Biliary tract cancers are heterogeneous in etiology, morphology and molecular characteristics thus impacting disease management. Diagnosis is complex and prognosis poor. The advent of liquid biopsy has provided a unique approach to more thoroughly understand tumor biology in general and biliary tract cancers specifically. Due to their minimally invasive nature, liquid biopsy can be used to serially monitor disease progression and allow real-time monitoring of tumor genetic profiles as well as therapeutic response. Due to the unique anatomic location of biliary tract cancer, bile provides a promising biologic fluid for this purpose. This review focuses on the composition of bile and the use of these various components, ie, cells, extracellular vesicles, nucleic acids, proteins and metabolites as potential biomarkers. Based on the disease characteristics and research status of biliary tract cancer, considerable effort should be made to increase understanding of this disease, promote research and development into early diagnosis, develop efficient diagnostic, therapeutic and prognostic markers.

Antibody-Free Fluorine-Assisted Metabolic Sequencing of RNA N4-Acetylcytidine.

N4-Acetylcytidine (ac4C) has been found to affect a variety of cellular and biological processes. For a mechanistic understanding of the roles of ac4C in biology and disease, we present an antibody-free, fluorine-assisted metabolic sequencing method to detect RNA ac4C, called "FAM-seq". We successfully applied FAM-seq to profile ac4C landscapes in human 293T, HeLa, and MDA cell lines in parallel with the reported acRIP-seq method. By comparison with the classic ac4C antibody sequencing method, we found that FAM-seq is a convenient and reliable method for transcriptome-wide mapping of ac4C. Because this method holds promise for detecting nascent RNA ac4C modifications, we further investigated the role of ac4C in regulating chemotherapy drug resistance in chronic myeloid leukemia. The results indicated that drug development or combination therapy could be enhanced by appreciating the key role of ac4C modification in cancer therapy.

Cuproptosis-related signature for clinical prognosis and immunotherapy sensitivity in hepatocellular carcinoma.

BACKGROUND: Copper homeostasis imbalance has been implicated in tumor progression, aggressiveness, and treatment response. However, the precise roles of cuproptosis-related genes (CRGs) in hepatocellular carcinoma (HCC) remain poorly understood. METHODS: In this study, we employed a consensus clustering algorithm to identify distinct molecular subtypes. We then performed Kaplan-Meier analysis and univariate Cox regression analysis to identify prognostic differentially expressed genes. The expression of these genes was subsequently validated using qPCR on fresh-frozen tissues obtained from HCC patients. Moreover, leveraging the TCGA-HCC cohort, we constructed a CRGs-related risk prediction model using the LASSO and multivariate Cox regression analysis. RESULTS: By analyzing the data, we successfully established a CRGs risk prognostic model for HCC patients, comprising five differential genes (CAD, SGCB, TXNRD1, KDR, and MTND4P20). Cox regression analysis revealed that the CRGs risk score could serve as an independent prognostic factor for overall survival (hazard ratio [HR] = 1.308, 95% confidence interval [CI] = 1.200 - 1.426, P < 0.001). The area under the curve (AUC) values of the CRGs-score for predicting 1-year, 3-year, and 5-year survival rates were 0.785, 0.724, and 0.723, respectively. Notably, the expression levels of immune checkpoints (including PD-1, PD-L1, and CTLA4) significantly differed between the low- and high-risk score groups. Furthermore, the low-risk score group displayed increased sensitivity to sorafenib, cisplatin, cyclopamine, nilotinib, salubrinal, and gemcitabine, whereas the high-risk score group exhibited heightened sensitivity to lapatinib, erlotinib, and gefitinib. CONCLUSIONS: Our findings highlight the potential of the CRGs risk score as an independent and promising biomarker for clinical prognosis and immunotherapy sensitivity in HCC patients.

Serum Lipoprotein(a) and High-Density Lipoprotein Cholesterol Associate with Diabetic Nephropathy: Evidence from Machine Learning Perspectives.

Purpose: Diabetic nephropathy (DN) is a common complication of type 2 diabetes mellitus (T2DM) that significantly impacts the quality of life for affected patients. Dyslipidemia is a known risk factor for developing cardiovascular complications in T2DM patients. However, the association between serum lipoprotein(a) (Lp(a)) and high-density lipoprotein cholesterol (HDL-C) with DN requires further investigation. Patients and Methods: For this cross-sectional study, we randomly selected T2DM patients with nephropathy (DN, n = 211) and T2DM patients without nephropathy (T2DM, n = 217) from a cohort of 142,611 patients based on predefined inclusion and exclusion criteria. We collected clinical data from the patients to identify potential risk factors for DN using binary logistic regression and machine learning. After obtaining the feature importance score of clinical indicators by building a random forest classifier, we examined the correlations between Lp(a), HDL-C and the top 10 indicators. Finally, we trained decision tree models with top 10 features using training data and evaluated their performance with independent testing data. Results: Compared to the T2DM group, the DN group had significantly higher serum levels of Lp(a) (p < 0.001) and lower levels of HDL-C (p = 0.028). Lp(a) was identified as a risk factor for DN, while HDL-C was found to be protective. We identified the top 10 indicators that were associated with Lp(a) and/or HDL-C, including urinary albumin (uALB), uALB to creatinine ratio (uACR), cystatin C, creatinine, urinary ɑ1-microglobulin, estimated glomerular filtration rate (eGFR), urinary ß2-microglobulin, urea nitrogen, superoxide dismutase and fibrinogen. The decision tree models trained using the top 10 features and with uALB at a cut-off value of 31.1 mg/L showed an average area under the receiver operating characteristic curve (AUC) of 0.874, with an AUC range of 0.870 to 0.890. Conclusion: Our findings indicate that serum Lp(a) and HDL-C are associated with DN and we have provided a decision tree model with uALB as a predictor for DN.

Advances in biomarker discovery using circulating cell-free DNA for early detection of hepatocellular carcinoma.

The past several decades have witnessed unprecedented progress in basic and clinical cancer research, and our understanding of the molecular mechanisms and pathogenesis of cancers have been greatly improved. More recently, with the availability of high-throughput sequencing and profiling platforms as well as sophisticated analytical tools and high-performance computing capacity, there have been tremendous advances in the development of diagnostic approaches in clinical oncology, especially the discovery of novel biomarkers for cancer early detection. Although tissue biopsy-based pathology has been the "gold standard" for cancer diagnosis, notable limitations such as the risk due to invasiveness and the bias due to intra-tumoral heterogeneity have limited its broader applications in oncology (e.g., screening, regular disease monitoring). Liquid biopsy analysis that exploits the genetic and epigenetic information contained in DNA/RNA materials from body fluids, particularly circulating cell-free DNA (cfDNA) in the blood, has been an intriguing alternative approach because of advantageous features such as sampling convenience and minimal invasiveness. Taking advantage of innovative enabling technologies, cfDNA has been demonstrated for its clinical potential in cancer early detection, including hepatocellular carcinoma (HCC), the most common liver cancer that causes serious healthcare burden globally. Hereby, we reviewed the current advances in cfDNA-based approaches for cancer biomarker discovery, with a focus on recent findings of cfDNA-based early detection of HCC. Future clinical investigations and trials are warranted to further validate these approaches for early detection of HCC, which will contribute to more effective prevention, control, and intervention strategies with the ultimate goal of reducing HCC-associated mortality. This article is categorized under: Cancer > Genetics/Genomics/Epigenetics.

Predicting N2 lymph node metastasis in presurgical stage I-II non-small cell lung cancer using multiview radiomics and deep learning method.

BACKGROUND: Accurate diagnosis of N2 lymph node status of the resectable stage I-II non-small cell lung cancer (NSCLC) before surgery is crucial, while there is lack of corresponding method clinically. PURPOSE: To develop and validate a model to quantitively predict the N2 lymph node metastasis in presurgical clinical stage I-II NSCLC using multiview radiomics and deep learning method. METHODS: In this study, 140 NSCLC patients were enrolled and randomly divided into training and test sets. Univariate and multiple analysis method were used step by step to establish the clinical model; Then a multiview radiomics modeling scheme was designed, in which the optimal input feature set was determined by subcategorizing radiomics features (C1: original; C2: LoG and C3: wavelet) and comparison of corresponding radiomics model. The minimum-redundancy maximum-relevance (mRMR) selection and the least absolute shrinkage and selection operator (LASSO) algorithm were used for the feature selection and construction of each radiomics model (Rad). Next, an end-to-end ResNet18 architecture and transfer learning techniques were designed to construct a deep learning model (DL). Subsequently, the screened clinical risk factors and constructed Rad and DL models were combined and compared and a nomogram was constructed. Finally, the diagnostic performance of all constructed models were evaluated and compared using receiver operating characteristic curve (ROC) analysis, Delong test, Calibration analysis, Hosmer-Lemeshow test, and decision curves, respectively. RESULTS: Carcinoma embryonic antigen (CEA) level and spiculation were screened to make up the Clinical model, while seven radiomics features in the optimal input feature set C2 + C3 were selected to construct the Rad. DL was constructed by training on 1.8 million natural images and small sample data of our N2 lymph node volume of interest (VOI) images. Except for the Clinical model, all other models showed good predictive accuracy and consistency in both training set and test set. DL (area under curve (AUC): 0.83) was better than Rad (AUC: 0.76) in predictive accuracy, but their difference was not significant (p = 0.45). The combined models showed better diagnostic performance than the model only clinical or image risk factors were used (AUC for Clinical, Rad + DL, Rad + Clinical, DL + Clinical, and Rad + DL + Clinical were respectively 0.66, 0.86, 0.82, 0.86, and 0.88). Finally, the Rad + DL + Clinical model with the best diagnostic performance was selected to draw the final nomogram for clinical use. CONCLUSION: This study proposes a nomogram based on multiview radiomics, deep learning, and clinical features that can be efficiently used to quantitively predict presurgical N2 diseases in patients with clinical stage I-II NSCLC.

Clinical Diagnostic and Prognostic Potential of NDRG1 and NDRG2 in Hepatocellular Carcinoma Patients.

Background: Primary liver cancer is still the most common lethal malignancy. The N-myc downstream-regulated gene family (NDRG1-4) is a group of multifunctional proteins associated with carcinogenesis. However, systematic evaluation of the diagnostic and prognostic values of NDRG1 or NDRG2 expression in liver cancer is poorly investigated. Method: The gene expression matrix of liver hepatocellular carcinoma (LIHC) was comprehensively analyzed by the "limma" and "Dseq2" R packages. The Gene Ontology (GO) and Gene Set Enrichment Analysis (GSEA) were used to identify the biological functional differences. A single-sample GSEA (ssGSEA) was conducted to quantify the extent of immune cell infiltration. Finally, the clinical and prognostic information of LIHC patients was systematically investigated using Kaplan-Meier analysis and logistic and Cox regression analysis. Results: Compared with normal tissues, NDRG1 expression was higher, whereas NDRG2 expression was lower in tumor tissues (P <0.001). The area under the receiver operator characteristic curve (AUROC) of NDRG1 and NDRG2 for LIHC was 0.715 and 0.799, respectively. Kaplan-Meier analysis revealed that NDRG1 and NDRG2 were independent clinical prognostic biomarkers for the overall survival (OS, P = 0.001 and 2.9e-06), progression-free interval (PFI, P = 0.028 and 0.005) and disease-specific survival (DSS, P = 0.027 and P <0.001). The C-indexes and calibration plots of the nomogram suggest that NDRG1 and NDRG2 have an effective predictive performance for OS (C-index: 0.676), DSS (C-index: 0.741) and PFI (C-index: 0.630) of liver cancer patients. The mutation rate of NDRG1 in liver cancer reached up to 14%, and DNA methylation levels of NDRG1 and NDRG2 promoters correlated significantly with clinical prognosis. Conclusions: The mRNA expression and DNA methylation of NDRG superfamily members have the potential for LIHC diagnosis and prognosis via integrative analysis from multiple cohorts.

The diagnostic and prognostic implications of PRKRA expression in HBV-related hepatocellular carcinoma.

BACKGROUND: Hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) accounts for more than half of total HCC patients in developing countries. Currently, HBV-related HCC diagnosis and prognosis still lack specific biomarkers. Here, we investigated if PRKRA expression in peripheral blood could be a potential biomarker for the diagnosis/prognosis of HBV-related HCC. METHODS: The expression of PRKRA in HBV-related HCC was firstly analyzed using TCGA and GEO databases. The results were confirmed in a validation cohort including 152 blood samples from 77 healthy controls and 75 HCC patients, 60 of which were infected with HBV. The potential diagnostic and prognostic values of PRKRA were also evaluated by the area under the receiver operator characteristic curve (AUROC) and Kaplan-Meier method, respectively. RESULTS: PRKRA was significantly upregulated in HCC patients, especially in those with HBV infections. In addition, the combination of PRKRA expression in peripheral blood with serum AFP and CEA levels displayed a better diagnostic performance (AUROC = 0.908, 95% CI 0.844-0.972; p < 0.001). Notably, when serum AFP is less than 200 ng/mL, PRKRA expression demonstrated better diagnostic capability. Furthermore, PRKRA expression levels were associated with expression of EIF2AK2 and inflammatory cytokine genes. CONCLUSIONS: Triple combination testing of blood PRKRA expression, serum AFP and CEA levels could be a noninvasive strategy for diagnosis; and the elevation of PRKRA expression could predicate poor prognosis for HBV-related HCC.

CT-Guided Percutaneous Core Needle Biopsy in Typing and Subtyping Lung Cancer: A Comparison to Surgery.

Background: Lung cancer histologic types and subtypes are closely associated with treatment selection and prognosis prediction. In this study, we aim to evaluate the suitability of computed tomography-guided percutaneous core needle biopsy (CT-guided PCNB) in typing and subtyping lung cancer. Methods: From August 2007 to December 2015, the patients who underwent CT-guided PCNB and lung lesion resection were retrospectively collected and analyzed. All pathological sections were reassessed in consensus by 2 junior pathologists (group A) and 2 senior pathologists (group B), respectively. All cases were diagnosed on 3 levels: first, malignant and benign diagnosis; second, histologic types diagnosis; and third, histologic subtypes diagnosis and compared with surgery results. Pearson chi-square test was used to compare the differences of diagnostic accuracy between pathologists in group A and group B. Results: A cohort of 160 patients was included in this study. On the first level, the diagnostic accuracy was 90.63% (group A) and 94.38% (group B), (P = .20). On the second level, the diagnostic accuracy for malignant lesions, adenocarcinoma (ADC), and squamous cell carcinoma (SQC) were, respectively, 72.66%, 84.72%, and 69.05% (group A) and 76.98%, 90.28%, and 71.43% (group B) (P > .05). On the third level, the diagnostic accuracy for ADC subtypes were 26.39% (group A) and 55.56% (group B) (P < 0.01); for SQC subtypes were 28.57% (group A) and 38.10% (group B) (P = 0.36). Conclusion: Small specimens obtained by CT-guided PCNB were suitable for the diagnosis of lung cancer histologic types, which may contribute to the selection of a suitable treatment strategy for the unresectable lung cancers. While for the diagnosis of subtypes, discussion with experienced pathologists was recommended.

Ablation of Plasma Prekallikrein Decreases Low-Density Lipoprotein Cholesterol by Stabilizing Low-Density Lipoprotein Receptor and Protects Against Atherosclerosis.

BACKGROUND: High blood cholesterol accelerates the progression of atherosclerosis, which is an asymptomatic process lasting for decades. Rupture of atherosclerotic plaques induces thrombosis, which results in myocardial infarction or stroke. Lowering cholesterol levels is beneficial for preventing atherosclerotic cardiovascular disease. METHODS: Low-density lipoprotein (LDL) receptor (LDLR) was used as bait to identify its binding proteins in the plasma, and the coagulation factor prekallikrein (PK; encoded by the KLKB1 gene) was revealed. The correlation between serum PK protein content and lipid levels in young Chinese Han people was then analyzed. To investigate the effects of PK ablation on LDLR and lipid levels in vivo, we genetically deleted Klkb1 in hamsters and heterozygous Ldlr knockout mice and knocked down Klkb1 using adeno-associated virus-mediated shRNA in rats. The additive effect of PK and proprotein convertase subtilisin/kexin 9 inhibition also was evaluated. In addition, we applied the anti-PK neutralizing antibody that blocked the PK and LDLR interaction in mice. Mice lacking both PK and apolipoprotein e (Klkb1-/-Apoe-/-) were generated to assess the role of PK in atherosclerosis. RESULTS: PK directly bound LDLR and induced its lysosomal degradation. The serum PK concentrations positively correlated with LDL cholesterol levels in 198 young Chinese Han adults. Genetic depletion of Klkb1 increased hepatic LDLR and decreased circulating cholesterol in multiple rodent models. Inhibition of proprotein convertase subtilisin/kexin 9 with evolocumab further decreased plasma LDL cholesterol levels in Klkb1-deficient hamsters. The anti-PK neutralizing antibody could similarly lower plasma lipids through upregulating hepatic LDLR. Ablation of Klkb1 slowed the progression of atherosclerosis in mice on Apoe-deficient background. CONCLUSIONS: PK regulates circulating cholesterol levels through binding to LDLR and inducing its lysosomal degradation. Ablation of PK stabilizes LDLR, decreases LDL cholesterol, and prevents atherosclerotic plaque development. This study suggests that PK is a promising therapeutic target to treat atherosclerotic cardiovascular disease.

Corrigendum: Loss of TARBP2 Drives the Progression of Hepatocellular Carcinoma via miR-145-SERPINE1 Axis.

[This corrects the article DOI: 10.3389/fonc.2021.620912.].

Loss of TARBP2 Drives the Progression of Hepatocellular Carcinoma via miR-145-SERPINE1 Axis.

The clinical outcomes of hepatocellular carcinoma (HCC) remain dismal. Elucidating the molecular mechanisms for the progression of aggressive HCC holds the promise for developing novel intervention strategies. The transactivation response element RNA-binding protein (TRBP/TARBP2), a key component of microRNA (miRNA) processing and maturation machinery has been shown to play conflicting roles in tumor development and progression. We sought to investigate the expression of TARBP2 in HCC using well-characterized HCC cell lines, patient-derived tissues and blood samples. Additionally, the potential prognostic and diagnostic value of TARBP2 in HCC were analyzed using Kaplan-Meier plots and ROC curve. Cell counting kit-8 (CCK-8), wound healing and transwell assays examined the ability of TARBP2 to induce cell proliferation, migration, and invasion in HCC cell lines. RNA sequencing was applied to identify the downstream elements of TARBP2. The interaction of potential targets of TARBP2, miR-145 and serpin family E member 1 (SERPINE1), was assessed using luciferase reporter assay. TARBP2 expression was down-regulated in HCC cell lines relative to normal hepatocyte cells, with a similar pattern further confirmed in tissue and blood samples. Notably, the loss of TARBP2 was demonstrated to promote proliferation, migration, and invasion in HCC cell lines. Interestingly, the reduction of TARBP2 was shown to result in the upregulation of SERPINE1, also known as plasminogen activator inhibitor (PAI-1), which is a vital gene of the HIF-1 signaling pathway. Knockdown of SERPINE1 rescued the TARBP2-lost phenotype. Moreover, TARBP2 depletion induced the upregulation of SERPINE1 through reducing the processing of miR-145, which directly targets SERPINE1. Finally, overexpression of miR-145 repressed SERPINE1 and rescued the functions in sh-TARBP2 HCC cells. Our findings underscore a linear TARBP2-miR-145-SERPINE1 pathway that drives HCC progression, with the potential as a novel intervention target for aggressive HCC.

Maternal Folic Acid Supplementation Mediates Offspring Health via DNA Methylation.

The clinical significance of periconceptional folic acid supplementation (FAS) in the prevention of neonatal neural tube defects (NTDs) has been recognized for decades. Epidemiological data and experimental findings have consistently been indicating an association between folate deficiency in the first trimester of pregnancy and poor fetal development as well as offspring health (i.e., NTDs, isolated orofacial clefts, neurodevelopmental disorders). Moreover, compelling evidence has suggested adverse effects of folate overload during perinatal period on offspring health (i.e., immune diseases, autism, lipid disorders). In addition to several single-nucleotide polymorphisms (SNPs) in genes related to folate one-carbon metabolism (FOCM), folate concentrations in maternal serum/plasma/red blood cells must be considered when counseling FAS. Epigenetic information encoded by 5-methylcytosines (5mC) plays a critical role in fetal development and offspring health. S-adenosylmethionine (SAM), a methyl donor for 5mC, could be derived from FOCM. As such, folic acid plays a double-edged sword role in offspring health via mediating DNA methylation. However, the underlying epigenetic mechanism is still largely unclear. In this review, we summarized the link across DNA methylation, maternal FAS, and offspring health to provide more evidence for clinical guidance in terms of precise FAS dosage and time point. Future studies are, therefore, required to set up the reference intervals of folate concentrations at different trimesters of pregnancy for different populations and to clarify the epigenetic mechanism for specific offspring diseases.

Direct detection of circRNA in real samples using reverse transcription-rolling circle amplification.

Circular RNA is a novel class of endogenous non-coding RNA that has a well-conserved sequence. Emerging evidence has shown that circRNA is implicated in various biological processes, therefore, the ability to quantify circRNA in real samples facilitates the elucidation of circRNA related regulatory circuits and its disease associations. Here, a reverse transcription mediated rolling circle amplification process was proposed to achieve selective amplification of the target circRNA. This assay, termed reverse transcription-rolling circle amplification (RT-RCA), can be used to identify circRNA with high selectivity within only a few hours. RT-RCA is a competitive candidate technique for circRNA detection and may help us to understand the role of circRNA in cellular processes and human diseases in more detail.

Hyperglycemia affects global 5-methylcytosine and 5-hydroxymethylcytosine in blood genomic DNA through upregulation of SIRT6 and TETs.

BACKGROUND: Accumulating evidence suggests that epigenetic changes play key roles in the pathogenesis of type 2 diabetes mellitus (T2DM). However, the dynamic regulation of 5-methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC) in diabetic peripheral blood DNA remains to be elucidated. RESULTS: We collected fasting blood samples (104 patients and 108 healthy controls) and glucose-stimulated blood samples at different time points (11 patients and 5 healthy controls underwent oral glucose tolerance test (OGTT)), as well as blood samples from six couples of diabetic and control rats. A HPLC-MS/MS system was used for quantifying global 5mC and 5hmC in genomic DNA from white blood cells (WBCs), and qPCR was performed for detecting mRNA expression of SIRT6 and TETs. We found that global 5mC decreased, while global 5hmC increased in both patients and diabetic rats, with lower 5mC being a risk factor of T2DM (OR = 0.524, 95%CI 0.402-0.683, p = 1.64 × 10-6). The OGTT data from patients showed that 5mC declined within 1 h and then returned to the fasting status at 2 h, while 5hmC rose from 0.5 h to 3 h with increasing glucose. However, the similar patterns were not found in the controls. The mRNA expression of TET2, TET3, and SIRT6 was upregulated in patients (p = 0.012, p = 0.026, and p = 0.035, respectively). The similar results were observed in diabetic OGTT and rats. Correlation analysis indicated that SIRT6 was positively correlated with TET2 in humans (r = 0.277, p < 0.001) and rats (r = 0.942, p < 0.001), in addition to a correlation between glucose and SIRT6 (r = 0.162, p = 0.045) and TET2 (r = 0.174, p = 0.036). CONCLUSIONS: Hyperglycemia appeared to promote the mRNA expression of SIRT6 and TETs, which in turn might cause the dynamic changes of 5mC and 5hmC in WBCs from T2DM patients.

Insulin/IGF-1R, SIRT1, and FOXOs Pathways-An Intriguing Interaction Platform for Bone and Osteosarcoma.

Aging is a substantial risk factor for the development of osteoarthritis (OA) and, probably, an essential substrate for the development of neoplastic disease of the bone, such as osteosarcoma, which is the most common malignant mesenchymal primary bone tumor. Genetic studies have established that the insulin/insulin-like growth factor 1 (IGF-1)/phosphatidylinositol-3 kinase (PI3K)/AKT (Protein Kinase B) signal transduction pathway is involved across species, including nematodes, fruit flies, and mammals. SIRT1, a phylogenetically-conserved family of deacetylases, seems to play pleiotropic effects in epithelial malignancies of the liver and interact with the IGF-1/PI3K/AKT signal transduction pathway. Some of the most critical processes in degenerative conditions may indeed include the insulin/IGF1R and SIRT1 signaling pathways as well as some specific transcription factors. The Forkhead box O (FOXO) transcription factors (FOXOs) control diverse cellular functions, such as metabolism, longevity, and cell death. FOXOs play a critical role in the IGF-1/PI3K/AKT signal transduction pathway. FOXOs can indeed be modulated to reduce age-related diseases. FOXOs have advantageous inhibitory effects on fibroblast and myofibroblast activation, which are accompanied by a subsequent excessive production of extracellular matrix. FOXOs can block or decrease the fibrosis levels in numerous organs. Previously, we observed a correlation between nuclear FOXO3 and high caspase-8 expression, which induces cellular apoptosis in response to harmful external stimuli. In this perspective, we emphasize the current advances and interactions involving the insulin/IGF1R, SIRT1, and FOXOs pathways in the bone and osteosarcoma for a better understanding of the mechanisms potentially underpinning tissue degeneration and tumorigenesis.

Clinical significance of exosomal miRNAs and proteins in three human cancers with high mortality in China.

Cancer is the second leading cause of mortality worldwide. More importantly, the mortality rates for cancer are increasing. In China, lung cancer, liver cancer and gastric cancer are the top three leading causes of mortality in males, whereas lung cancer, gastric cancer and liver cancer are ranked the top three causes of mortality in females. Exosomes are extracellular vesicles that are produced and released by many different cells; these vesicles have a size range between 30 and 100 nm in diameter, and contain a lipid bilayer. Exosomes exist in various bodily fluids, contain plentiful amounts of nucleic acids and proteins, and shuttle these materials between cells to mediate the development of cancers. The present review summarizes the composition of exosomes and methods for their isolation and then intensively highlights the latest findings on the contributions of exosomal microRNAs (miRNAs) and proteins to lung cancer, liver cancer and gastric cancer. Taken together, exosomal miRNAs and proteins may be used as noninvasive, novel biomarkers for cancer diagnosis, prognosis or precision treatment owing to their ability to promote tumor progression and metastasis, and their ability to regulate the immune response and tumor cell sensitivity to chemotherapy drugs.

Glucose Is Involved in the Dynamic Regulation of m6A in Patients With Type 2 Diabetes.

Context: N6-methyladenosine (m6A) in mRNA is the most abundant and reversible modification. However, the mechanism behind the decrease in m6A in patients with type 2 diabetes (T2D) has not yet been thoroughly investigated. Objective: To clarify whether glucose is involved in the dynamic regulation of m6A in T2D and to identify a possible underlying mechanism. Methods: Liquid chromatography/electrospray ionization/tandem mass spectrometry and quantitative PCR were performed to determine the m6A content and the mRNA expression of target genes in 102 patients with T2D and 107 controls. An additional 12 patients with normal fasting blood glucose, emergency hyperglycemia, or emergency hypoglycemia, as well as HepG2 cells with high-glucose treatment and FTO knockout or overexpression were used to confirm the initial observations in patients. Results: In patients with T2D, the m6A content was decreased, and mRNA expression levels of FTO, METTL3, METTL14, and WTAP were increased. Interestingly, the m6A content was negatively associated with mRNA expression levels of METTL3, METTL14, and FTO. Moreover, FTO was positively correlated with serum glucose. In HepG2 cells, high glucose upregulated FTO protein, whereas it had no significant effect on METTL3 or METTL14. Additionally, mRNA expression levels of FOXO1, G6PC, and DGAT2 were significantly increased and positively correlated with FTO and serum glucose in patients. Conclusions: Our data revealed that in patients with T2D, high-glucose-enhanced FTO mRNA expression resulted in a decrease in m6A. The lower m6A content might be responsible for the upregulation of methyltransferases. Additionally, FTO induced mRNA expression of FOXO1, G6PC, and DGAT2 and was closely associated with glucose metabolism.