Diagnosis of Partial Body Radiation Exposure in Mice Using Peripheral Blood Gene Expression Profiles

In the event of a terrorist-mediated attack in the United States using radiological or improvised nuclear weapons, it is expected that hundreds of thousands of people could be exposed to life-threatening levels of ionizing radiation. We have recently shown that genome-wide expression analysis of the peripheral blood (PB) can generate gene expression profiles that can predict radiation exposure and distinguish the dose level of exposure following total body irradiation (TBI). However, in the event a radiation-mass casualty scenario, many victims will have heterogeneous exposure due to partial shielding and it is unknown whether PB gene expression profiles would be useful in predicting the status of partially irradiated individuals. Here, we identified gene expression profiles in the PB that were characteristic of anterior hemibody-, posterior hemibody- and single limb-irradiation at 0.5 Gy, 2 Gy and 10 Gy in C57Bl6 mice. These PB signatures predicted the radiation status of partially irradiated mice with a high level of accuracy (range 79–100%) compared to non-irradiated mice. Interestingly, PB signatures of partial body irradiation were poorly predictive of radiation status by site of injury (range 16–43%), suggesting that the PB molecular response to partial body irradiation was anatomic site specific. Importantly, PB gene signatures generated from TBI-treated mice failed completely to predict the radiation status of partially irradiated animals or non-irradiated controls. These data demonstrate that partial body irradiation, even to a single limb, generates a characteristic PB signature of radiation injury and thus may necessitate the use of multiple signatures, both partial body and total body, to accurately assess the status of an individual exposed to radiation.     

An Exploration of Molecular Correlates Relevant to Radiation Combined Skin-Burn Trauma

Background

Exposure to high dose radiation in combination with physical injuries such as burn or wound trauma can produce a more harmful set of medical complications requiring specialist interventions. Currently these interventions are unavailable as are the precise biomarkers needed to help both accurately assess and treat such conditions. In the present study, we tried to identify and explore the possible role of serum exosome microRNA (miRNA) signatures as potential biomarkers for radiation combined burn injury (RCBI).

Methodology

Female B6D2F1/J mice were assigned to four experimental groups (n = 6): sham control (SHAM), burn injury (BURN), radiation injury (RI) and combined radiation skin burn injury (CI). We performed serum multiplex cytokine analysis and serum exosome miRNA expression profiling to determine novel miRNA signatures and important biological pathways associated with radiation combined skin-burn trauma.

Principal Findings

Serum cytokines, IL-5 and MCP-1, were significantly induced only in CI mice (p<0.05). From 890 differentially expressed miRNAs identified, microarray analysis showed 47 distinct miRNA seed sequences significantly associated with CI mice compared to SHAM control mice (fold change ≥ 1.2, p<0.05). Furthermore, only two major miRNA seed sequences (miR-690 and miR-223) were validated to be differentially expressed for CI mice specifically (fold change ≥ 1.5, p<0.05).

Conclusions

Serum exosome miRNA signature data of adult mice, following RCBI, provides new insights into the molecular and biochemical pathways associated with radiation combined skin-burn trauma in vivo.     

Protein network-based Lasso regression model for the construction of disease-miRNA functional interactions

BackgroundThere is a growing body of evidence associating microRNAs (miRNAs) with human diseases. MiRNAs are new key players in the disease paradigm demonstrating roles in several human diseases. The functional association between miRNAs and diseases remains largely unclear and far from complete. With the advent of high-throughput functional genomics techniques that infer genes and biological pathways dysregulted in diseases, it is now possible to infer functional association between diseases and biological molecules by integrating disparate biological information.ResultsHere, we first used Lasso regression model to identify miRNAs associated with disease signature as a proof of concept. Then we proposed an integrated approach that uses disease-gene associations from microarray experiments and text mining, and miRNA-gene association from computational predictions and protein networks to build functional associations network between miRNAs and diseases. The findings of the proposed model were validated against gold standard datasets using ROC analysis and results were promising (AUC=0.81). Our protein network-based approach discovered 19 new functional associations between prostate cancer and miRNAs. The new 19 associations were validated using miRNA expression data and clinical profiles and showed to act as diagnostic and prognostic prostate biomarkers. The proposed integrated approach allowed us to reconstruct functional associations between miRNAs and human diseases and uncovered functional roles of newly discovered miRNAs.ConclusionsLasso regression was used to find associations between diseases and miRNAs using their gene signature. Defining miRNA gene signature by integrating the downstream effect of miRNAs demonstrated better performance than the miRNA signature alone. Integrating biological networks and multiple data to define miRNA and disease gene signature demonstrated high performance to uncover new functional associations between miRNAs and diseases.     

Distinctive microRNA expression signatures in proton-irradiated mice

Proton particles comprise the most abundant ionizing radiation (IR) in outer space. These high energy particles are known to cause frequent double- and single-stranded DNA lesions that can lead to cancer and tumor formation. Understanding the mechanism of cellular response to proton-derived IR is vital for determining health risks to astronauts during space missions. Our understanding of the consequences of these high energy charged particles on microRNA (miRNA) regulation is still in infancy. miRNAs are non-coding, single-stranded RNAs of ~22 nucleotides that constitute a novel class of gene regulators. They regulate diverse biological processes, and each miRNA can control hundreds of gene targets. To investigate the effect of proton radiation on these master regulators, we examined the miRNA expression in selected mice organs that had been exposed to whole-body proton irradiation (2 Gy), and compared this to control mice (0 Gy exposure). RNA was isolated from three tissues (testis, brain, and liver) from treated and control mice and subjected to high-throughput small RNA sequencing. Bioinformatics analysis of small RNA sequencing data revealed dysregulation of (p < 0.05; 20 up- and 10 down-regulated) 14 mouse testis, 8 liver, and 8 brain miRNAs. The statistically significant and unique miRNA expression pattern found among three different proton-treated mouse tissues indicates a tissue-specific response to proton radiation. In addition to known miRNAs, sequencing revealed differential expression of 11 miRNAs in proton-irradiated mice that have not been previously reported in association with radiation exposure and cancer. The dysregulation of miRNAs on exposure to proton radiation suggest a possible mechanism of proton particles involvement in the onset of cell tumorgenesis. In summary, we have established that specific miRNAs are vulnerable to proton radiation, that such differential expression profile may depend upon the tissue, and that there are more miRNAs affected by proton radiation than have been previously observed.     

Ionizing Radiation-Induced Oxidative Stress Alters miRNA Expression

Background

MicroRNAs (miRNAs) are small, highly conserved, non-coding RNA that alter protein expression and regulate multiple intracellular processes, including those involved in the response to cellular stress. Alterations in miRNA expression may occur following exposure to several stress-inducing anticancer agents including ionizing radiation, etoposide, and hydrogen peroxide (H₂O₂).

Methodology/Principal Findings

Normal human fibroblasts were exposed to radiation, H₂O₂, or etoposide at doses determined by clonogenic cell survival curves. Total RNA was extracted and miRNA expression was determined by microarray. Time course and radiation dose responses were determined using RT-PCR for individual miRNA species. Changes in miRNA expression were observed for 17 miRNA species following exposure to radiation, 23 after H₂O₂ treatment, and 45 after etoposide treatment. Substantial overlap between the miRNA expression changes between agents was observed suggesting a signature miRNA response to cell stress. Changes in the expression of selected miRNA species varied in response to radiation dose and time. Finally, production of reactive oxygen species (ROS) increased with increasing doses of radiation and pre-treatment with the thiol antioxidant cysteine decreased both ROS production and the miRNA response to radiation.

Conclusions

These results demonstrate a common miRNA expression signature in response to exogenous genotoxic agents including radiation, H₂O₂, and etoposide. Additionally, pre-treatment with cysteine prevented radiation-induced alterations in miRNA expression which suggests that miRNAs are responsive to oxidative stress. Taken together, these results imply that miRNAs play a role in cellular defense against exogenous stress and are involved in the generalized cellular response to genotoxic oxidative stress.     

Whole blood-derived microRNA signatures in mice exposed to lipopolysaccharides

Background

Lipopolysaccharide (LPS) is recognized as the most potent microbial mediator presaging the threat of invasion of Gram-negative bacteria that implicated in the pathogenesis of sepsis and septic shock. This study was designed to examine the microRNA (miRNA) expression in whole blood from mice injected with intraperitoneal LPS.

Methods

C57BL/6 mice received intraperitoneal injections of varying concentrations (range, 10–1000 μg) of LPS from different bacteria, including Escherichia coli, Klebsiella pneumonia, Pseudomonas aeruginosa, Salmonella enterica, and Serratia marcescens and were killed 2, 6, 24, and 72 h after LPS injection. Whole blood samples were obtained and tissues, including lung, brain, liver, and spleen, were harvested for miRNA expression analysis using an miRNA array (Phalanx miRNA OneArray® 1.0). Upregulated expression of miRNA targets in the whole blood of C57BL/6 and Tlr4^−/− mice injected with LPS was quantified using real-time RT-PCR and compared with that in the whole blood of C57BL/6 mice injected with lipoteichoic acid (LTA) from Staphylococcus aureus.

Results

Following LPS injection, a significant increase of 15 miRNAs was observed in the whole blood. Among them, only 3 miRNAs showed up-regulated expression in the lung, but no miRNAs showed a high expression level in the other examined tissues. Upregulated expression of the miRNA targets (let-7d, miR-15b, miR-16, miR-25, miR-92a, miR-103, miR-107 and miR-451) following LPS injection on real-time RT-PCR was dose- and time-dependent. miRNA induction occurred after 2 h and persisted for at least 6 h. Exposure to LPS from different bacteria did not induce significantly different expression of these miRNA targets. Additionally, significantly lower expression levels of let-7d, miR-25, miR-92a, miR-103, and miR-107 were observed in whole blood of Tlr4^−/− mice. In contrast, LTA exposure induced moderate expression of miR-451 but not of the other 7 miRNA targets.

Conclusions

We identified a specific whole blood–derived miRNA signature in mice exposed to LPS, but not to LTA, from different gram-negative bacteria. These whole blood-derived miRNAs are promising as biomarkers for LPS exposure.     

MicroRNA signature predicts survival in papillary thyroid carcinoma

Papillary thyroid cancer (PTC) accounts for the majority of malignant thyroid tumors. Recently, several microRNA (miRNA) expression profiling studies have used bioinformatics to suggest miRNA signatures as potential prognostic biomarkers in various malignancies. However, a prognostic miRNA biomarker has not yet been established for PTC. The aim of the present study was to identify miRNAs with prognostic value for the overall survival (OS) of patients with PTC by analyzing high-throughput miRNA data and their associated clinical characteristics downloaded from The Cancer Genome Atlas database. From our dataset, 150 differentially expressed miRNAs were identified between tumor and nontumor samples; of these miRNAs, 118 were upregulated and 32 were downregulated. Among the 150 differentially expressed miRNAs, a four miRNA signature was identified that reliably predicts OS in patients with PTC. This miRNA signature was able to classify patients into a high-risk group and a low-risk group with a significant difference in OS (P < .01). The prognostic value of the signature was validated in a testing set ( P < .01). The four miRNA signature was an independent prognostic predictor according to the multivariate analysis and demonstrated good performance in predicting 5-year disease survival with an area under the receiver operating characteristic curve area under the curve (AUC) score of 0.886. Thus, this signature may serve as a novel biomarker for predicting the survival of patients with PTC.     

Plasma miRNA as biomarkers for assessment of total-body radiation exposure dosimetry

The risk of radiation exposure, due to accidental or malicious release of ionizing radiation, is a major public health concern. Biomarkers that can rapidly identify severely-irradiated individuals requiring prompt medical treatment in mass-casualty incidents are urgently needed. Stable blood or plasma-based biomarkers are attractive because of the ease for sample collection. We tested the hypothesis that plasma miRNA expression profiles can accurately reflect prior radiation exposure. We demonstrated using a murine model that plasma miRNA expression signatures could distinguish mice that received total body irradiation doses of 0.5 Gy, 2 Gy, and 10 Gy (at 6 h or 24 h post radiation) with accuracy, sensitivity, and specificity of above 90%. Taken together, these data demonstrate that plasma miRNA profiles can be highly predictive of different levels of radiation exposure. Thus, plasma-based biomarkers can be used to assess radiation exposure after mass-casualty incidents, and it may provide a valuable tool in developing and implementing effective countermeasures.     

Recurrence prediction using microRNA expression in hormone receptor positive breast cancer during tamoxifen treatment

Abstract

Purpose: To identify miRNAs associated with distant recurrence during tamoxifen treatment and build a recurrence prediction model.

Materials and methods: We measured the expression of five miRNAs (miR-134, miR-125b-5P, miRNA-30a, miR-10a-5p and miR-222). A total of 176 tumour tissues from 176 patients who had hormone receptor positive breast cancer with tamoxifen treatment were used to measure miRNA expression using quantitative real-time PCR (qRT-PCR).

Results: The five miRNAs were all up-regulated in distant recurrence cases within 5?years after surgery and during tamoxifen treatment. Kaplan-Meier survival analyses based on expression cut-offs determined by receiver characteristics curves (ROC) showed that high expression of miR-134, miR-125b-5P, miRNA-30a, miR-10a-5p and miR-222 were significantly (log-rank p-value =0.006, p-value <0.0001, p-value <0.0001, p-value <0.0001 and p-value <0.0001, respectively) associated with short relapse-free time. Our results were used to build a combined 3 miRNAs expression model. It could be used to categorize high-risk subset of patients with short relapse-free survival (AUC =0.891, p-value <0.0001).

Conclusions: Distant recurrence during tamoxifen treatment of hormone positive breast cancer might be affected by tamoxifen resistance related miRNAs. Such distant recurrence can be predicted using miRNA measurement.     

Intra-individual variation of miRNA expression levels in human plasma samples

Background: Circulating miRNAs as potential non-invasive biomarkers for disease risk assessment and cancer early diagnosis have attracted increasing interest. Little information, however, is available regarding the intra-individual variation of circulating miRNA levels.

Methods: We measured expression levels of a panel of 800 miRNAs in repeated plasma samples from 51 healthy individuals that were collected 6 to 12?months apart and evaluated the intra-individual variation by the intra-class correlation coefficient (ICC).

Results: After background correction, a total of 185 miRNAs were detected in at least 10% of the plasma samples, with 69 and 28 miRNAs being detected in 50% and 90% of samples, respectively. The median ICC was 0.46 for these 185 miRNAs. Among them, 41% (75 miRNAs) had an ICC?≥?0.5, and 23% (42 miRNAs) had an ICC?≥?0.6. The ICC is higher for miRNAs with higher expression levels or higher detection rates, when compared to those with lower expression levels or lower detection rates.

Conclusions: These results suggest that common circulating miRNAs are stable over a relatively long period and can serve as reliable biomarkers for epidemiological and clinical research.     

Regulatory MicroRNA Networks:Complex Patterns of Target Pathways for Disease-related and Housekeeping MicroRNAs

Blood-based micro RNA(mi RNA) signatures as biomarkers have been reported for various pathologies, including cancer, neurological disorders, cardiovascular diseases, and also infections. The regulatory mechanism behind respective mi RNA patterns is only partially understood. Moreover, ‘‘preserved' mi RNAs, i.e., mi RNAs that are not dysregulated in any disease,and their biological impact have been explored to a very limited extent. We set out to systematically determine their role in regulatory networks by defining groups of highly-dysregulated mi RNAs that contribute to a disease signature as opposed to preserved housekeeping mi RNAs. We further determined preferential targets and pathways of both dysregulated and preserved mi RNAs by computing multi-layer networks, which were compared between housekeeping and dysregulated mi RNAs. Of 848 mi RNAs examined across 1049 blood samples, 8 potential housekeepers showed very limited expression variations, while 20 mi RNAs showed highly-dysregulated expression throughout the investigated blood samples. Our approach provides important insights into mi RNAs and their role in regulatory networks. The methodology can be applied to systematically investigate the differences in target genes and pathways of arbitrary mi RNA sets.     

Gene expression signatures of radiation response are specific, durable and accurate in mice and humans

Background

Previous work has demonstrated the potential for peripheral blood (PB) gene expression profiling for the detection of disease or environmental exposures.

Methods and Findings

We have sought to determine the impact of several variables on the PB gene expression profile of an environmental exposure, ionizing radiation, and to determine the specificity of the PB signature of radiation versus other genotoxic stresses. Neither genotype differences nor the time of PB sampling caused any lessening of the accuracy of PB signatures to predict radiation exposure, but sex difference did influence the accuracy of the prediction of radiation exposure at the lowest level (50 cGy). A PB signature of sepsis was also generated and both the PB signature of radiation and the PB signature of sepsis were found to be 100% specific at distinguishing irradiated from septic animals. We also identified human PB signatures of radiation exposure and chemotherapy treatment which distinguished irradiated patients and chemotherapy-treated individuals within a heterogeneous population with accuracies of 90% and 81%, respectively.

Conclusions

We conclude that PB gene expression profiles can be identified in mice and humans that are accurate in predicting medical conditions, are specific to each condition and remain highly accurate over time.     

Two Different Serum MiRNA Signatures Correlate with the Clinical Outcome and Histological Subtype in Pleural Malignant Mesothelioma Patients

Pleural malignant mesothelioma (MPM) is a detrimental neoplasm affecting pleural sheets and determining a high rate of mortality. In this study, we have enrolled 14 consecutive patients (13 males and 1 female) with MPM (mean age: 70.3 ± 4.6 years). We have collected serum for the determination of a miRNA profiling using a low-density microarray real time PCR system in the serum of patients and comparing it with that one of 10 control counterparts affected by not-cancer-related pleural effusions. In the patients 5 miRNAs were up-regulated (miR101, miR25, miR26b, miR335 and miR433), 2 miRNA were downregulated (miR191, miR223) and two miRNAs were expressed exclusively in patients (miR29a and miR516). Based upon the changes in the expression of the above mentioned miRNAs we detected two distinctive miRNA signatures predicting histotype and survival in these patients: I) patients with more than 3/9 upregulated miRNAs or 3/9 upregulated miRNAs and miR516 not recordable or unchanged (signature A); II) patients with at least 3/9 downregulated or unchanged miRNAs and/or miR29a downregulated (signature B). Based upon these criteria, 5 patients were stratified in signature A and the remaining 9 in signature B. Patients with signature A had a significant shorter median survival than those with signature B (7 months vs. 17 months, 95% CI: 0.098–1.72, p = 0.0021), had a sarcomatoid or mixed histological MPM subtype and were diagnosed in stage II (3/5) and stage III (2/5). In conclusion, we suggest that miRNA signature A is predictive of sarcomatoid histotype and of worse prognosis in MPM.     

Clinical implications of microRNAs in cancer

Abstract

MicroRNAs (miRNAs) are endogenously produced non-coding RNAs that serve as micromanagers by negatively regulating gene expression. MiRNAs are implicated in several biological pathways including development of neoplasia. Because altered miRNA expression is implicated in the pathobiology of various cancers, these molecules serve as potential therapeutic targets. Using miRNA mimics to restore levels of aberrantly down-regulated miRNAs or miRNA inhibitors to inactivate over-expressed miRNAs shows promise as the next generation of therapeutic strategies. Manipulation of miRNAs offers an alternative therapeutic approach for chemo- and radiation-resistant tumors. Similarly, miRNA expression patterns can be used for diagnosis and to predict prognosis and efficacy of therapy. We present here an overview of how miRNAs affect cancers, how they may be used as biomarkers, and the clinical implications of miRNAs in cancer.