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Metabolic markers, offering sensitive information on biological dysfunction, play important roles in diagnosing and treating cancers. However, the discovery of effective markers is limited by the lack of well-established metabolite selection approaches. Here, we propose a network-based strategy to uncover the metabolic markers with potential clinical availability for non-small cell lung cancer (NSCLC). First, an integrated mass spectrometry-based untargeted metabolomics was used to profile the plasma samples from 43 NSCLC patients and 43 healthy controls. We found that a series of 39 metabolites were altered significantly. Relying on the human metabolic network assembled from Kyoto Encyclopedia of Genes and Genomes (KEGG) database, we mapped these differential metabolites to the network and constructed an NSCLC-related disease module containing 23 putative metabolic markers. By measuring the PageRank centrality of molecules in this module, we computationally evaluated the network-based importance of the 23 metabolites and demonstrated that the metabolism pathways of aromatic amino acids and long-chain fatty acids provided potential molecular targets of NSCLC (i.e., IL4l1 and ACOT2). Combining network-based ranking and support-vector machine modeling, we further found a panel of eight metabolites (i.e., pyruvate, tryptophan, and palmitic acid) that showed a high capability to differentiate patients from controls (accuracy > 97.7%). In summary, we present a meaningful network method for metabolic marker discovery and have identified eight strong candidate metabolites for NSCLC diagnosis.

Background The performance of previously published glomerular filtration rate (GFR) estimation equations degrades when directly used in Chinese population. We incorporated more independent variables and using complicated non-linear modeling technology (artificial neural network, ANN) to develop a more accurate GFR estimation model for Chinese population. Methods The enrolled participants came from the Third Affiliated Hospital of Sun Yat-sen University, China from Jan 2012 to Jun 2016. Participants with age Results Compared with the 4-variable equation, the 9-variable equation could not achieve superior performance in the internal validation data (mean of difference: 5.00 [3.82, 6.54] vs 4.67 [3.55, 5.90], P = 0.5; interquartile range (IQR) of difference: 18.91 [17.43, 20.48] vs 20.11 [18.46, 21.80], P = 0.05; P30: 76.6% [73.7%, 79.5%] vs 75.8% [72.9%, 78.6%], P = 0.4), but the 9-variable ANN model significantly improve bias and P30 accuracy (mean of difference: 2.77 [1.82, 4.10], P = 0.007; IQR: 19.33 [17.77, 21.17], P = 0.3; P30: 80.0% [77.4%, 82.7%], P Conclusions It is suggested that using complicated non-linear models like ANN could fully utilize the predictive ability of the independent variables, and then finally achieve a superior GFR estimation model.

Background/Aims: Chronic cerebral hypoperfusion (CCH) is a high-risk factor for vascular dementia and Alzheimer’s disease. Autophagy plays a critical role in the initiation and progression of CCH. However, the underlying mechanisms remain unclear. In this study, we identified the effect of a microRNA (miR) on autophagy under CCH. Methods: A CCH rat model was established by two-vessel occlusion (2VO). Learning and memory abilities were assessed by the Morris water maze. The protein levels of LC3, beclin-1, and mTOR were detected by western blotting and immunofluorescence assays, miR-96 expression was assessed by real-time PCR, luciferase assays were used to determine the effect of miR-96 on the 3′ untranslated region (UTR) of mTOR, and the number of autophagosomes was examined by electron microscopy. Results: The level of miR-96 was significantly increased in 2VO rats, and inhibition of miR-96 ameliorated the cognitive impairment induced by 2VO. Furthermore, the number of LC3- and beclin-1-positive autophagosomes was increased in 2VO rats, and was decreased after miR-96 antagomir injection. However, the protein level of mTOR was reduced in 2VO rats, and it was down-regulated by miR-96 overexpression and up-regulated by miR-96 inhibition in 2VO rats and primary culture cells. Moreover, the luciferase activity of the 3′-UTR of mTOR was suppressed by miR-96, which was relieved by mutation of the miR-96 binding sites. Conclusion: Our study demonstrated that miR-96 may play a key role in autophagy under CCH by regulating mTOR; therefore, miR-96 may represent a potential therapeutic target for CCH.

Stroke remains a major public health problem worldwide; it causes severe disability and is associated with high mortality rates. However, early diagnosis of stroke is difficult, and no reliable biomarkers are currently established. In this study, mass-spectrometry-based metabolomics was utilized to characterize the metabolic features of the serum of patients with acute ischemic stroke (AIS) to identify novel sensitive biomarkers for diagnosis and progression. First, global metabolic profiling was performed on a training set of 80 human serum samples (40 cases and 40 controls). The metabolic profiling identified significant alterations in a series of 26 metabolites with related metabolic pathways involving amino acid, fatty acid, phospholipid, and choline metabolism. Subsequently, multiple algorithms were run on a test set consisting of 49 serum samples (26 cases and 23 controls) to develop different classifiers for verifying and evaluating potential biomarkers. Finally, a panel of five differential metabolites, including serine, isoleucine, betaine, PC(5:0/5:0), and LysoPE(18:2), exhibited potential to differentiate AIS samples from healthy control samples, with area under the receiver operating characteristic curve values of 0.988 and 0.971 in the training and test sets, respectively. These findings provided insights for the development of new diagnostic tests and therapeutic approaches for AIS.

Background: Venous thromboembolism (VTE) is an important complication in patients with malignant tumors. Its exact diagnosis and treatment are still lacking. We used a high-sensitive chemiluminescence method to detect thrombin–antithrombin III complex (TAT), plasmin-α2-plasmininhibitor complex (PIC), thrombomodulin (TM), and tissue plasminogen activator–inhibitor complex(t-PAIC) in combination with D-dimer and fibrin degradation product (FDP) to analyze their diagnostic and prognostic value in patients with malignant tumors. Methods: In total, 870 patients with confirmed malignant tumors were included, 82 of whom had diagnosed VTE; 200 healthy individuals were classified as the control group. The TAT, PIC, TM, and t-PAIC were detected using Sysmex HISCL5000 automated analyzers, whereas FDP and D-dimer were detected using Sysmex CS5100 coagulation analyzer. Receiver operating characteristic (ROC) curves were used to evaluate the diagnostic efficiency. Survival probabilities were determined using Kaplan–Meier analysis, and multivariate analyses were performed using a Cox regression model. Results: Compared with healthy controls, patients with malignant tumors showed significantly elevated TAT, PIC, TM, t-PAIC, D-dimer, and FDP. Similarly, compared with patients in the non-thrombosis group, those in the thrombosis group showed significantly elevated levels of the above mentioned markers. Logistic regression analysis showed that TAT, PIC, TM, t-PAIC, D-Dimer, and FDP were all associated with VTE. ROC analysis showed that “TAT+PIC+TM+t-PAIC+D-dimer+FDP”showed the highest sensitivity and specificity. Patients with elevated TAT, PIC, TM, and t-PAIC had a significantly shorter survival. Multivariate Cox survival analysis showed that TM and t-PAIC were significantly associated with poor prognosis. In addition, the incidence of VTE was significantly lower in patients with malignant tumors who were treated with low-molecular-weight heparin (LMWH), and their survival period was significantly longer than that of patients with malignant tumors who were not treated with LMWH. Conclusion: TAT, PIC, TM, and t-PAIC combined with D-dimer and FDP were better than the application of a single marker in the diagnosis of VTE in patients with malignant tumors. TAT and PIC can be used as sensitive markers in the diagnosis of VTE but not as prognostic markers. TM and t-PAIC might be independent prognostic indicators in patients with malignant tumors, regardless of the state of thrombus.

Carboxypeptidase E (CPE) is one of the most important carboxypeptidases involved in biosynthesis of numerous peptide hormones and neurotransmitters and has an important role in endocrine regulation. A splice variant of CPE (CPE-ΔN) has been detected and the mechanism of CPE-ΔN action in tumorigenesis has been studied in many different cancers. The aim of this study was to examine CPE-ΔN expression in human colorectal cancer (CRC) and to evaluate its possible use as a potential prognostic marker. Two hundred nineteen primary colorectal tumors and corresponding normal tissues were included in the study. We have analyzed CPE-ΔN isoform expression by qRT-PCR and Western blot in 219 CRC patients. Correlations between CPE-ΔN mRNA expression and clinicopathological variables were determined with chi-square tests. Survival probabilities were determined using Kaplan–Meier analysis, and univariate and multivariate analyses of the prognostic factors were performed with a Cox regression model. Our results show that CPE-ΔN is overexpressed in colorectal tumor tissue and that high CPE-ΔN mRNA expression is closely correlated with tumor differentiation, pT classification, pN classification, tumor recurrence, and lymph node metastasis (P = 0.042, 0.036, 0.031, 0.006, and 0.008, respectively). However, no correlation was observed between CPE-ΔN expression and age, gender, tumor localization, gross features, and the tumor size. In addition, patients with high CPE-ΔN expression had a significantly shorter survival (P

Despite the improved ability to detect mutations in recent years, tissue specimens cannot always be procured in a clinical setting, particularly from patients with recurrence of tumors or metastasis. Therefore, the aim of this study was to investigate whether plasma is able to be used for mutation analysis instead of tissue specimens. We collected plasma from 62 patients with colorectal cancer (CRC) prior to treatment. DNA extracted from plasma and matched tumor tissues were obtained. Mutations in KRAS were amplified from the tissue specimens and sequenced by regular polymerase chain reaction (PCR) and co-amplification at lower denaturation temperature (COLD)-PCR. Plasma KRAS gene mutation on codon 12 (GGT>GAT) was detected using a nested COLD-PCR/TaqMan® -MGB probe. Mutations in plasma and matched tumors were compared. KRAS mutation on codon 12 (GGT>GAT) was found in 13 (21.0%) plasma specimens and 12 (19.4%) matched tumor tissues. The consistency of KRAS mutations between plasma and tumors was 75% (9/12), which indicated a high correlation between the mutations detected in plasma DNA and the mutations detected in the corresponding tumor DNA (P