A pilot study identifying a set of microRNAs as precise diagnostic biomarkers of acute kidney injury

In the last decade, Acute Kidney Injury (AKI) diagnosis and therapy have not notably improved probably due to delay in the diagnosis, among other issues. Precocity and accuracy should be critical parameters in novel AKI biomarker discovery. microRNAs are key regulators of cell responses to many stimuli and they can be secreted to the extracellular environment. Therefore, they can be detected in body fluids and are emerging as novel disease biomarkers. We aimed to identify and validate serum miRNAs useful for AKI diagnosis and management. Using qRT-PCR arrays in serum samples, we determined miRNAs differentially expressed between AKI patients and healthy controls. Statistical and target prediction analysis allowed us to identify a panel of 10 serum miRNAs. This set was further validated, by qRT-PCR, in two independent cohorts of patients with relevant morbi-mortality related to AKI: Intensive Care Units (ICU) and Cardiac Surgery (CS). Statistical correlations with patient clinical parameter were performed. Our results demonstrated that the 10 selected miRNAs (miR-101-3p, miR-127-3p, miR-210-3p, miR-126-3p, miR-26b-5p, miR-29a-3p, miR-146a-5p, miR-27a-3p, miR-93-3p and miR-10a-5p) were diagnostic biomarkers of AKI in ICU patients, exhibiting areas under the curve close to 1 in ROC analysis. Outstandingly, serum miRNAs estimated before CS predicted AKI development later on, thus becoming biomarkers to predict AKI predisposition. Moreover, after surgery, the expression of the miRNAs was modulated days before serum creatinine increased, demonstrating early diagnostic value. In summary, we have identified a set of serum miRNAs as AKI biomarkers useful in clinical practice, since they demonstrate early detection and high diagnostic value and they recognize patients at risk.

Learning-induced gene expression in the heads of two Nasonia species that differ in long-term memory formation.

BACKGROUND: Cellular processes underlying memory formation are evolutionary conserved, but natural variation in memory dynamics between animal species or populations is common. The genetic basis of this fascinating phenomenon is poorly understood. Closely related species of Nasonia parasitic wasps differ in long-term memory (LTM) formation: N. vitripennis will form transcription-dependent LTM after a single conditioning trial, whereas the closely-related species N. giraulti will not. Genes that were differentially expressed (DE) after conditioning in N. vitripennis, but not in N. giraulti, were identified as candidate genes that may regulate LTM formation. RESULTS: RNA was collected from heads of both species before and immediately, 4 or 24 hours after conditioning, with 3 replicates per time point. It was sequenced strand-specifically, which allows distinguishing sense from antisense transcripts and improves the quality of expression analyses. We determined conditioning-induced DE compared to naïve controls for both species. These expression patterns were then analysed with GO enrichment analyses for each species and time point, which demonstrated an enrichment of signalling-related genes immediately after conditioning in N. vitripennis only. Analyses of known LTM genes and genes with an opposing expression pattern between the two species revealed additional candidate genes for the difference in LTM formation. These include genes from various signalling cascades, including several members of the Ras and PI3 kinase signalling pathways, and glutamate receptors. Interestingly, several other known LTM genes were exclusively differentially expressed in N. giraulti, which may indicate an LTM-inhibitory mechanism. Among the DE transcripts were also antisense transcripts. Furthermore, antisense transcripts aligning to a number of known memory genes were detected, which may have a role in regulating these genes. CONCLUSION: This study is the first to describe and compare expression patterns of both protein-coding and antisense transcripts, at different time points after conditioning, of two closely related animal species that differ in LTM formation. Several candidate genes that may regulate differences in LTM have been identified. This transcriptome analysis is a valuable resource for future in-depth studies to elucidate the role of candidate genes and antisense transcription in natural variation in LTM formation.

Local Salmonella immunostimulation recruits vaccine-specific CD8 T cells and increases regression of bladder tumor.

NlmCategory="UNASSIGNED">The efficacy of antitumoral responses can be increased using combinatorial vaccine strategies. We recently showed that vaccination could be optimized by local administration of diverse molecular or bacterial agents to target and augment antitumoral CD8 T cells in the genital mucosa (GM) and increase regression of cervical cancer in an animal model. Non muscle-invasive bladder cancer is another disease that is easily amenable to local therapies. In contrast to data obtained in the GM, in this study we show that intravesical (IVES) instillation of synthetic toll-like receptor (TLR) agonists only modestly induced recruitment of CD8 T cells to the bladder. However, IVES administration of Ty21a, a live bacterial vaccine against typhoid fever, was much more effective and increased the number of total and vaccine-specific CD8 T cells in the bladder approximately 10 fold. Comparison of chemokines induced in the bladder by either CpG (a TLR-9 agonist) or Ty21a highlighted the preferential increase in complement component 5a, CXCL5, CXCL2, CCL8, and CCL5 by Ty21a, suggesting their involvement in the attraction of T cells to the bladder. IVES treatment with Ty21a after vaccination also significantly increased tumor regression compared to vaccination alone, resulting in 90% survival in an orthotopic murine model of bladder cancer expressing a prototype tumor antigen. Our data demonstrate that combining vaccination with local immunostimulation may be an effective treatment strategy for different types of cancer and also highlight the great potential of the Ty21a vaccine, which is routinely used worldwide, in such combinatorial therapies.

TLR3-Mediated CD8+ Dendritic Cell Activation Is Coupled with Establishment of a Cell-Intrinsic Antiviral State.

Because of their unique capacity to cross-present Ags to CD8(+) T cells, mouse lymphoid tissue-resident CD8(+) dendritic cells (DCs) and their migratory counterparts are critical for priming antiviral T cell responses. High expression of the dsRNA sensor TLR3 is a distinctive feature of these cross-presenting DC subsets. TLR3 engagement in CD8(+) DCs promotes cross-presentation and the acquisition of effector functions required for driving antiviral T cell responses. In this study, we performed a comprehensive analysis of the TLR3-induced antiviral program and cell-autonomous immunity in CD8(+) DC lines and primary CD8(+) DCs. We found that TLR3-ligand polyinosinic-polycytidylic acid and human rhinovirus infection induced a potent antiviral protection against Sendai and vesicular stomatitis virus in a TLR3 and type I IFN receptor-dependent manner. Polyinosinic-polycytidylic acid-induced antiviral genes were identified by mass spectrometry-based proteomics and transcriptomics in the CD8(+) DC line. Nanostring nCounter experiments confirmed that these antiviral genes were induced by TLR3 engagement in primary CD8(+) DCs, and indicated that many are secondary TLR3-response genes requiring autocrine IFN-β stimulation. TLR3-activation thus establishes a type I IFN-dependent antiviral program in a DC subtype playing crucial roles in priming adaptive antiviral immune responses. This mechanism is likely to shield the priming of antiviral responses against inhibition or abrogation by the viral infection. It could be particularly relevant for viruses detected mainly by TLR3, which may not trigger type I IFN production by DCs that lack TLR3, such as plasmacytoid DCs or CD8(-) DCs.

Therapeutic drug monitoring of targeted anticancer therapy.

New oral targeted anticancer therapies are revolutionizing cancer treatment by transforming previously deadly malignancies into chronically manageable conditions. Nevertheless, drug resistance, persistence of cancer stem cells, and adverse drug effects still limit their ability to stabilize or cure malignant diseases in the long term. Response to targeted anticancer therapy is influenced by tumor genetics and by variability in drug concentrations. However, despite a significant inter-patient pharmacokinetic variability, targeted anticancer drugs are essentially licensed at fixed doses. Their therapeutic use could however be optimized by individualization of their dosage, based on blood concentration measurements via the therapeutic drug monitoring (TDM). TDM can increase the probability of therapeutic responses to targeted anticancer therapies, and would help minimize the risk of major adverse reactions.

Circulating microRNAs: The Future of Biomarkers in Anti-doping Field.

microRNAs (miRNAs) are small non-coding RNAs that regulate various biological processes. Cell-free miRNAs have been proposed as biomarkers of disease, including diagnosis, prognosis, and monitoring of treatment responses. These circulating miRNAs are highly stable in several body fluids, including plasma and serum; hence, in view of their potential use as novel, non-invasive biomarkers, the profiles of circulating miRNAs have been explored in the field of anti-doping. This chapter describes the enormous potential of circulating miRNAs as a new class of biomarkers for the detection of doping substances, and highlights the advantages of measuring these stable species over other methods that have already been implemented in anti-doping regimes. Incorporating longitudinal measurements of circulating miRNAs into the Athlete Biological Passport is proposed as an efficient strategy for the implementation of these new biomarkers. Furthermore, potential challenges related to the transition of measurements of circulating miRNAs from research settings to practical anti-doping applications are presented.

Monitoring Fatigue Status with HRV Measures in Elite Athletes : An Avenue Beyond RMSSD?

Among the tools proposed to assess the athlete's "fatigue," the analysis of heart rate variability (HRV) provides an indirect evaluation of the settings of autonomic control of heart activity. HRV analysis is performed through assessment of time-domain indices, the square root of the mean of the sum of the squares of differences between adjacent normal R-R intervals (RMSSD) measured during short (5 min) recordings in supine position upon awakening in the morning and particularly the logarithm of RMSSD (LnRMSSD) has been proposed as the most useful resting HRV indicator. However, if RMSSD can help the practitioner to identify a global "fatigue" level, it does not allow discriminating different types of fatigue. Recent results using spectral HRV analysis highlighted firstly that HRV profiles assessed in supine and standing positions are independent and complementary; and secondly that using these postural profiles allows the clustering of distinct sub-categories of "fatigue." Since, cardiovascular control settings are different in standing and lying posture, using the HRV figures of both postures to cluster fatigue state embeds information on the dynamics of control responses. Such, HRV spectral analysis appears more sensitive and enlightening than time-domain HRV indices. The wealthier information provided by this spectral analysis should improve the monitoring of the adaptive training-recovery process in athletes.

Monitoring Fatigue Status with HRV Measures in Elite Athletes: An Avenue Beyond RMSSD?

Among the tools proposed to assess the athlete's "fatigue," the analysis of heart rate variability (HRV) provides an indirect evaluation of the settings of autonomic control of heart activity. HRV analysis is performed through assessment of time-domain indices, the square root of the mean of the sum of the squares of differences between adjacent normal R-R intervals (RMSSD) measured during short (5 min) recordings in supine position upon awakening in the morning and particularly the logarithm of RMSSD (LnRMSSD) has been proposed as the most useful resting HRV indicator. However, if RMSSD can help the practitioner to identify a global "fatigue" level, it does not allow discriminating different types of fatigue. Recent results using spectral HRV analysis highlighted firstly that HRV profiles assessed in supine and standing positions are independent and complementary; and secondly that using these postural profiles allows the clustering of distinct sub-categories of "fatigue." Since, cardiovascular control settings are different in standing and lying posture, using the HRV figures of both postures to cluster fatigue state embeds information on the dynamics of control responses. Such, HRV spectral analysis appears more sensitive and enlightening than time-domain HRV indices. The wealthier information provided by this spectral analysis should improve the monitoring of the adaptive training-recovery process in athletes.