Clinical Chemistry - Ultimo numero

Metabolic reprogramming is a hallmark of cancer. MicroRNAs (miRNAs) have been found to regulate cancer metabolism by regulating genes involved in metabolic pathways. Understanding this layer of complexity could lead to the development of novel therapeutic approaches.

miRNAs are noncoding RNAs that have been implicated as master regulators of gene expression. Studies have revealed the role of miRNAs in the metabolic reprogramming of tumor cells, with several miRNAs both positively and negatively regulating multiple metabolic genes. The tricarboxylic acid (TCA) cycle, aerobic glycolysis, de novo fatty acid synthesis, and altered autophagy allow tumor cells to survive under adverse conditions. In addition, major signaling molecules, hypoxia-inducible factor, phosphatidylinositol-3 kinase/protein kinase B/mammalian target of rapamycin/phosphatase and tensin homolog, and insulin signaling pathways facilitate metabolic adaptation in tumor cells and are all regulated by miRNAs. Accumulating evidence suggests that miRNA mimics or inhibitors could be used to modulate the activity of miRNAs that drive tumor progression via altering their metabolism. Currently, several clinical trials investigating the role of miRNA-based therapy for cancer have been launched that may lead to novel therapeutic interventions in the future.

In this review, we summarize cancer-related metabolic pathways, including glycolysis, TCA cycle, pentose phosphate pathway, fatty acid metabolism, amino acid metabolism, and other metabolism-related oncogenic signaling pathways, and their regulation by miRNAs that are known to lead to tumorigenesis. Further, we discuss the current state of miRNA therapeutics in the clinic and their future potential.

Increases in circulating LDL cholesterol (LDL-C) and high-sensitivity C-reactive protein (hsCRP) concentrations are significant risk factors for cardiovascular disease (CVD). We assessed direct LDL-C and hsCRP concentrations compared to standard risk factors in the Framingham Offspring Study.

We used stored frozen plasma samples (–80 °C) obtained after an overnight fast from 3147 male and female participants (mean age, 58 years) free of CVD at cycle 6 of the Framingham Offspring Study. Overall, 677 participants (21.5%) had a CVD end point over a median of 16.0 years of follow-up. Total cholesterol (TC), triglyceride (TG), HDL cholesterol (HDL-C), direct LDL-C (Denka Seiken and Kyowa Medex methods), and hsCRP (Dade Behring method) concentrations were measured by automated analysis. LDL-C was also calculated by both the Friedewald and Martin methods.

Considering all CVD outcomes on univariate analysis, significant factors included standard risk factors (age, hypertension, HDL-C, hypertension treatment, sex, diabetes, smoking, and TC concentration) and nonstandard risk factors (non-HDL-C, direct LDL-C and calculated LDL-C, TG, and hsCRP concentrations). On multivariate analysis, only the Denka Seiken direct LDL-C and the Dade Behring hsCRP were still significant on Cox regression analysis and improved the net risk reclassification index, but with modest effects. Discordance analysis confirmed the benefit of the Denka Seiken direct LDL-C method for prospective hard CVD endpoints (new-onset myocardial infarction, stroke, and/or CVD death).

Our data indicate that the Denka Seiken direct LDL-C and Dade Behring hsCRP measurements add significant, but modest, information about CVD risk, compared to standard risk factors and/or calculated LDL-C.

Heart failure (HF) is a leading cause of morbidity and mortality worldwide. Plasma concentrations of B-type natriuretic peptide (BNP) or its amino terminal congener (NT-proBNP) are used for HF diagnosis and risk stratification. Because BNP concentrations are inexplicably lowered in obese patients, we investigated the relationship between proBNP glycosylation, plasma NT-proBNP, and body mass index (BMI) in HF patients.

Three assays were developed to distinguish between total proBNP (glycosylated plus nonglycosylated proBNP), proBNP not glycosylated at threonine 71 (NG-T71), and proBNP not glycosylated in the central region (NG-C). Intraassay and interassay CVs were <15%; limits of detection were <21 ng/L; and samples diluted in parallel.

Applying these assays and an NT-proBNP assay to plasma samples from 106 healthy volunteers and 238 HF patients determined that concentrations [median (interquartile range)] of proBNP, NG-T71, and NT-proBNP were greater in HF patients compared with controls [300 (44–664), 114 (18–254), and 179 (880–3459) ng/L vs 36 (18–229), 36 (18–175), and 40 (17–68) ng/L, respectively; all P < 0.012]. NG-C was undetectable in most samples. ProBNP concentrations in HF patients with BMI more or less than 30 kg/m2 were not different (P = 0.85), whereas HF patients with BMI >30 kg/m2 had lower NT-proBNP and NG-T71 concentrations (P < 0.003) and higher proBNP/NT-proBNP and proBNP/NG-T71 ratios (P = 0.001 and P = 0.02, respectively) than those with BMI <30 kg/m2.

Increased BMI is associated with decreased concentrations of proBNP not glycosylated at T71. Decreased proBNP substrate amenable to processing could partially explain the lower NT-proBNP and BNP concentrations observed in obese individuals, including those presenting with HF.

Clinical decision support alerts for laboratory testing have poor compliance. Once-per-visit alerts, triggered by reorder of a test within the same admission, are highly specific for unnecessary orders and provide a means to study alert compliance.

Once-per-visit alerts for 18 laboratory orderables were analyzed over a 60-month period from September 2012 to October 2016 at a 1200-bed academic medical center. To determine correlates of alert compliance, we compared alerts by test and provider characteristics.

Overall alert compliance was 54.5%. In multivariate regression, compliance correlated with length of stay at time of alert, provider type, previous alerts in a patient visit, test ordered, total alerts experienced by ordering provider, and previous order status.

A diverse set of provider and test characteristics influences compliance with once-per-visit laboratory alerts. Future alerts should incorporate these characteristics into alert design to minimize alert overrides.

The Islet Autoantibody Standardization Program (IASP) aims to improve the performance of immunoassays measuring type 1 diabetes (T1D)-associated autoantibodies and the concordance of results among laboratories. IASP organizes international interlaboratory assay comparison studies in which blinded serum samples are distributed to participating laboratories, followed by centralized collection and analysis of results, providing participants with an unbiased comparative assessment. In this report, we describe the results of glutamic acid decarboxylase autoantibody (GADA) assays presented in the IASP 2018 workshop.

In May 2018, IASP distributed to participants uniquely coded sera from 43 new-onset T1D patients, 7 multiple autoantibody-positive nondiabetic individuals, and 90 blood donors. Results were analyzed for the following metrics: sensitivity, specificity, accuracy, area under the ROC curve (ROC-AUC), partial ROC-AUC at 95% specificity (pAUC95), and concordance of qualitative and quantitative results.

Thirty-seven laboratories submitted results from a total of 48 different GADA assays adopting 9 different formats. The median ROC-AUC and pAUC95 of all assays were 0.87 [interquartile range (IQR), 0.83–0.89] and 0.036 (IQR, 0.032–0.039), respectively. Large differences in pAUC95 (range, 0.001–0.0411) were observed across assays. Of formats widely adopted, bridge ELISAs showed the best median pAUC95 (0.039; range, 0.036–0.041).

Several novel assay formats submitted to this study showed heterogeneous performance. In 2018, the majority of the best performing GADA immunoassays consisted of novel or established nonradioactive tests that proved on a par or superior to the radiobinding assay, the previous gold standard assay format for GADA measurement.

Cellular mitochondrial DNA (mtDNA) is organized as circular, covalently closed and double-stranded DNA. Studies have demonstrated the presence of short mtDNA fragments in plasma. It is not known whether circular mtDNA might concurrently exist with linear mtDNA in plasma.

We elucidated the topology of plasma mtDNA using restriction enzyme BfaI cleavage signatures on mtDNA fragment ends to differentiate linear and circular mtDNA. mtDNA fragments with both ends carrying BfaI cleavage signatures were defined as circular-derived mtDNA, whereas those with no cleavage signature or with 1 cleavage signature were defined as linear-derived mtDNA. An independent assay using exonuclease V to remove linear DNA followed by restriction enzyme MspI digestion was used for confirming the conclusions based on BfaI cleavage analysis. We analyzed the presence of BfaI cleavage signatures on plasma DNA ends in nonhematopoietically and hematopoietically derived DNA molecules by sequencing plasma DNA of patients with liver transplantation and bone marrow transplantation.

Both linear and circular mtDNA coexisted in plasma. In patients with liver transplantation, donor-derived (i.e., liver) mtDNA molecules were mainly linear (median fraction, 91%; range, 75%–97%), whereas recipient-derived (i.e., hematopoietic) mtDNA molecules were mainly circular (median fraction, 88%; range, 77%–93%). The proportion of linear mtDNA was well correlated with liver DNA contribution in the plasma DNA pool (r = 0.83; P value = 0.0008). Consistent data were obtained from a bone marrow transplantation recipient in whom the donor-derived (i.e., hematopoietic) mtDNA molecules were predominantly circular.

Linear and circular mtDNA molecules coexist in plasma and may have different tissue origins.

Cannabis use results in impaired driving and an increased risk of motor vehicle crashes. Cannabinoid concentrations in blood and other matrices can remain high long after use, prohibiting the differentiation between acute and chronic exposure. Exhaled breath has been proposed as an alternative matrix in which concentrations may more closely correspond to the window of impairment; however, efficient capture and analytically sensitive detection methods are required for measurement.

Timed blood and breath samples were collected from 20 volunteers before and after controlled administration of smoked cannabis. Cannabinoid concentrations were measured using LC-MS/MS to determine release kinetics and correlation between the 2 matrices.

9-Tetrahydrocannabinol (THC) was detected in exhaled breath for all individuals at baseline through 3 h after cannabis use. THC concentrations in breath were highest at the 15-min timepoint (median = 17.8 pg/L) and declined to <5% of this concentration in all participants 3 h after smoking. The decay curve kinetics observed for blood and breath were highly correlated within individuals and across the population.

THC can be reliably detected throughout the presumed 3-h impairment window following controlled administration of smoked cannabis. The findings support breath THC concentrations as representing a physiological process and are correlated to blood concentrations, albeit with a shorter window of detection.