Healthy Blood Samples Research Articles

Expression and prognostic relevance of long noncoding RNAs CRNDE and AOX2P in adult acute myeloid leukemia.

Several long noncoding RNAs (lncRNAs) have been demonstrated to play a critical role in the tumorigenesis of acute myeloid leukemia (AML), and altered expression of certain lncRNAs has been recognized as a potential prognostic marker in AML patients. Here, we sought to determine whether the expression of the lncRNA colorectal neoplasia differentially expressed (CRNDE) and aldehyde oxidase 2 pseudogene (AOX2P) is associated with clinicopathological features and clinical outcome of patients with AML. CRNDE and AOX2P expression levels were measured in diagnostic blood samples from 200 adult patients with de novo AML, along with 50 healthy control blood samples, using quantitative real-time polymerase chain reaction (qRT-PCR). The association of CRNDE and AOX2P expression with the clinicopathological characteristics and outcome of AML patients was analyzed. Upregulated CRNDE expression was independently associated with lower complete remission (CR) rates in the whole cohort of AML (P<.001). AOX2P overexpression was identified as an independent adverse prognostic marker for CR in the CN-AML (P=.009) and non-t (15;17) AML (P<.001) subgroups. Patients with high CRNDE expression had a significantly shorter event-free survival (EFS, whole cohort of AML: P=.017; CN-AML: P=.001; non-t (15;17) AML: P=.006) and inferior overall survival (OS, whole cohort of AML: P=.002; t(15;17) AML: P=.001) than those with low CRNDE expression. EFS and OS did not differ significantly between patients with high AOX2P expression and those with low expression. Aberrantly upregulated CRNDE expression and, to a lesser extent, AOX2P overexpression, are associated with poor prognosis in AML patients, suggesting that the determination of CRNDE and, perhaps, AOX2P, expression level at diagnosis provides valuable prognostic information, allows refinement of risk stratification, and helps clinical decision-making in AML.

Chemoresistive Nanostructured Metal-Oxide Sensors for Human Tumor Tissue and Blood Exhalations Analysis

Early-stage tumor detection is one of the most coveted goals for the world research community. An effective prevention, associated to reliable screening protocols, is crucial to favor a early diagnosis, allowing doctors and surgeons to intervene with high probabilities of success on tumor affected patients. The main purpose of this study is cancer detection, exploiting the volatile organic compounds (VOCs) produced by cancer cells as tumor biomarkers [1][2], by investigating tumor tissue and blood samples. Tumor biomarkers exhalation is attributed to two main cell involving biological mechanisms: altered metabolism and cellular membrane peroxidation [3]. This experimental work was carried on using an innovative, fast-responding and reliable patented device, named SCENT B1 [4], entirely designed and assembled in the Sensor Laboratory of the University of Ferrara. It hosts an array of four specific metal-oxide (MOX) sensors able to detect gases in low concentration (up to 10 ppm) with high stability and repeatability, chosen after many tests on different types of biological samples (feces, blood, cell cultures, etc.) [5,6]; the chosen sensors are based on different mixtures of tin, titanium, tungsten, niobium, tantalum and vanadium oxides (ST25Au, W11, STN, TiTaV). Moreover, SCENT B1 is gifted of a power supply and sensor signal transduction electronic boards, a pneumatic air system (necessary to direct the VOCs contaminated air from the sample chamber to the sensors) and an ad hoc management and data acquisition software (LSS4) [6]. The sensor output signal is a voltage directly proportional to the sensor conductance, depending on the chemical redox reactions taking place on the surface of the sensor sensing material. The sensor response is: R=Vgas/Vair , where Vgas and Vair are the sensor voltage in gas presence and in dry air after the steady state achievement respectively [6].Sensor responses were further elaborated, using different statistical approaches as principal component analysis and receiver operating characteristics methods.Measurements have been performed on colorectal cancer and healthy tissues surgically removed from the same operatory piece (directly and far enough from tumor mass respectively) (Figure 1a), and on blood samples collected from tumor affected subjects and healthy ones as controls (Figure 1b). with the future aim of extending the study to other tumor types. All four sensors gave larger responses (although with different amplitudes) to the tumor tissue with respect to the healthy one. Smaller and reproducible responses were given by the breeding ground (DMEM) only, confirming that it does not alter the measurements. The results are consistent with the stronger and altered metabolism of tumor cells, leading them to emit a larger amount of volatile biomarkers with respect to the healthy ones;.All the four sensors hosted by SCENT B1 proved to be capable of distinguishing between healthy and tumor tissue and blood samples, although with different discrimination power. The encouraging results of this feasibility study are the basis of a new in-depth study, which includes also a follow-up protocol based on post surgery blood monitoring of patients. Our future aims foresee the extension of this study to other tumor types and the obtainment of the SCENT B1 clinical validation as oncologic screening device. Figure 1

Investigation of the antimicrobial activity and hematological pattern of nano-chitosan and its nano-copper composite

Novel synthesized Chitosan–Copper oxide nanocomposite (Cs–CuO) was prepared using pomegranate peels extract as green precipitating agents to improve the biological activity of Cs-NP's, which was synthesized through the ionic gelation method. The characterization of biogenic nanoparticles Cs-NP's and Cs–CuO-NP's was investigated structurally, morphologically to determine all the significant characters of those nanoparticles. Antimicrobial activity was tested for both Cs-NP's and Cs–CuO-NP's via minimum inhibition concentration and zone analysis against fungus, gram-positive and gram-negative. The antimicrobial test results showed high sensitivity of Cs–CuO-NP's to all microorganisms tested in a concentration less than 20,000 mg/L, while the sensitivity of Cs-NP's against all microorganisms under the test started from a concentration of 20,000–40,000 mg/L except for the C. albicans species. The hematological activity was also tested via measuring the RBCs, platelet count, and clotting time against healthy, diabetic, and hypercholesteremia blood samples. The measurement showed a decrease in RBCs and platelet count by adding Cs-NP’s or Cs–CuO-NP's to the three blood samples. Cs-NP's success in decreasing the clotting time for healthy and diabetic blood acting as a procoagulant agent while adding biogenic CuO-NP’s to Cs-NP’s increased clotting time considering as an anti-coagulant agent for hypercholesteremia blood samples.

Bioinformatic analysis identifies potential biomarkers and therapeutic targets of septic-shock-associated acute kidney injury

BackgroundSepsis and septic shock are life-threatening diseases with high mortality rate in intensive care unit (ICU). Acute kidney injury (AKI) is a common complication of sepsis, and its occurrence is a poor prognostic sign to septic patients. We analyzed co-differentially expressed genes (co-DEGs) to explore relationships between septic shock and AKI and reveal potential biomarkers and therapeutic targets of septic-shock-associated AKI (SSAKI).MethodsTwo gene expression datasets (GSE30718 and GSE57065) were downloaded from the Gene Expression Omnibus (GEO). The GSE57065 dataset included 28 septic shock patients and 25 healthy volunteers and blood samples were collected within 0.5, 24 and 48 h after shock. Specimens of GSE30718 were collected from 26 patients with AKI and 11 control patents. AKI-DEGs and septic-shock-DEGs were identified using the two datasets. Subsequently, Gene Ontology (GO) functional analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, and protein-protein interaction (PPI) network analysis were performed to elucidate molecular mechanisms of DEGs. We also evaluated co-DEGs and corresponding predicted miRNAs involved in septic shock and AKI.ResultsWe identified 62 DEGs in AKI specimens and 888, 870, and 717 DEGs in septic shock blood samples within 0.5, 24 and 48 h, respectively. The hub genes of EGF and OLFM4 may be involved in AKI and QPCT, CKAP4, PRKCQ, PLAC8, PRC1, BCL9L, ATP11B, KLHL2, LDLRAP1, NDUFAF1, IFIT2, CSF1R, HGF, NRN1, GZMB, and STAT4 may be associated with septic shock. Besides, co-DEGs of VMP1, SLPI, PTX3, TIMP1, OLFM4, LCN2, and S100A9 coupled with corresponding predicted miRNAs, especially miR-29b-3p, miR-152-3p, and miR-223-3p may be regarded as promising targets for the diagnosis and treatment of SSAKI in the future.ConclusionsSeptic shock and AKI are related and VMP1, SLPI, PTX3, TIMP1, OLFM4, LCN2, and S100A9 genes are significantly associated with novel biomarkers involved in the occurrence and development of SSAKI.

IL-4, IL-17 and CD163 Immunoexpression and IL-6 Gene Polymorphism in Chronic Hepatitis C Patients and Associated Hepatocellular Carcinoma.

Objective:To assess the expression of IL-4, IL-17 and CD-163 as well as study of IL6-572 C/G gene polymorphism in chronic HCV and HCC on top of HCV. Methods:Sixty HCC specimens and 60 adjacent hepatic tissue with HCV of different grades of necro-inflammation and different stages of fibrosis. In addition to 55 HCV, 60 HCC and 50 healthy venous blood samples for evaluation of IL6-572 C/G gene polymorphism. Results:high expression of IL-4, IL-17 and CD163 in higher grades of activity, late stages of fibrosis and higher degrees of steatosis of HCV. IL-4 and CD163 showed higher expression in advanced grades of HCC, while IL-17 more expressed in lower grades. No significant difference in IL6-572 C/G gene polymorphism among studied groups regarding G/C, G/G, C/C frequencies or G and C allele’s frequencies. Conclusion: IL-4, IL-17 and CD163 were associated with HCV severity. Their expression in HCC suggests their important role in HCC development. Blocking of these proteins may be a good target to control inflammation in HCV and can hinder progression to cirrhosis then to HCC. On the other hand, IL6-572 promoter gene polymorphism is neither associated with HCV infection nor with HCC development and its progression.

TOWARDS NOVEL CIRCULATING MARKERS FOR ABDOMINAL AORTIC ANEURYSM PROGNOSIS

Objective: Abdominal aortic aneurysm (AAA) is increasing due to aging of the population and is a major cause of death among the elderly. Ultrasound screening programs are useful in early diagnosis but aneurysm size is not always a good predictor of rupture. Thus, there is an urgent need to find new potential prognostic factors. Our aim is to determine whether a battery of immune, inflammatory and oxidative stress markers, previously described to be involved in other cardiovascular diseases, may be used as potential biomarkers to provide personalized prediction of AAA progression for the clinical practice. Design and method: To address this, human abdominal aneurysmatic aortas (N = 80) and blood samples (N = 94) were obtained from patients undergoing open repair or endovascular surgery repair for AAA, whereas healthy aortas (n = 15) and blood samples (n = 46) were obtained from healthy donors. We studied the immune infiltrate in paraffin sections of human aneurysmatic tissue and quantified IgM and IgG circulating levels in our AAA patient cohort. Circulating levels of ROS, CD38, CD36, GDF15 and S100A4 were measured by ELISA and their tissue expression was studied by real Time PCR and by immunostaining. Potential correlations with the aneurysm diameter or with peak wall stress, determined by finite element analysis, were measured by the Pearson product-moment correlation. Results: Our study shows for the first time the alteration of IgM, IgG, ROS, CD38, GDF15 and S100A4 levels in plasma and in aneurysmatic tissue of AAA patients in comparison with controls. After performing the corresponding statistical analysis we could exclude age and sex as confounding factors of our current observations. Circulating levels of IgG, CD38 and GDF15 were positively correlated with abdominal aortic diameter and peak wall stress. Conclusions: Our data indicate that IgG, CD38 and GDF15 may have potential to aid AAA prognosis as indicators of the progression of the aneurysm growth.

Comprehensive Pathogen Identification, Antibiotic Resistance, and Virulence Genes Prediction Directly From Simulated Blood Samples and Positive Blood Cultures by Nanopore Metagenomic Sequencing.

Bloodstream infection is a major cause of morbidity and mortality worldwide. We explored whether MinION nanopore sequencing could accelerate diagnosis, resistance, and virulence profiling prediction in simulated blood samples and blood cultures. One milliliter of healthy blood samples each from direct spike (sample 1), anaerobic (sample 2), and aerobic (sample 3) blood cultures with initial inoculation of ∼30 CFU/ml of a clinically isolated Klebsiella pneumoniae strain was subjected to DNA extraction and nanopore sequencing. Hybrid assembly of Illumina and nanopore reads from pure colonies of the isolate (sample 4) was used as a reference for comparison. Hybrid assembly of the reference genome identified a total of 39 antibiotic resistance genes and 77 virulence genes through alignment with the CARD and VFDB databases. Nanopore correctly detected K. pneumoniae in all three blood samples. The fastest identification was achieved within 8 h from specimen to result in sample 1 without blood culture. However, direct sequencing in sample 1 only identified seven resistance genes (20.6%) but 28 genes in samples 2–4 (82.4%) compared to the reference within 2 h of sequencing time. Similarly, 11 (14.3%) and 74 (96.1%) of the virulence genes were detected in samples 1 and 2–4 within 2 h of sequencing time, respectively. Direct nanopore sequencing from positive blood cultures allowed comprehensive pathogen identification, resistance, and virulence genes prediction within 2 h, which shows its promising use in point-of-care clinical settings.

Identification of differential DNA methylation alterations of ovarian cancer in peripheral whole blood based on within-sample relative methylation orderings

ABSTRACT Leukocyte cell proportion changes affect the detection of cancer-associated aberrant DNA methylation alterations in peripheral blood samples. We aimed to detect cellular DNA methylation changes in ovarian cancer (OVC) blood samples avoiding the above-mentioned cell-composition effects. Based on the within-sample relative methylation orderings (RMOs) of CpG loci in leukocyte subtypes, we developed the Ref-RMO method to detect aberrant methylation alterations from OVC blood samples. Stable CpG pairs with consistent RMOs in different leukocyte subtypes were determined, more than 99% of which retained their RMO patterns in peripheral whole blood (PWB) in independent datasets. Based on the stable CpG pairs, significantly reversed CpG pairs were detected from OVC PWB samples, which were relative to clinical information such as age, subtype, grade, stage, or CA125 level. Results showed 439 CpG loci were determined to be significant differential DNA methylations between OVC and healthy blood samples. They were mainly enriched in KEGG pathways, such as cytokine-cytokine receptor interaction, apoptosis, proteoglycans in cancer, and immune-associated Gene Ontology terms. STRING analysis showed that they tended to have functional interactions with cancer-associated genes recorded in the COSMIC database. Leukocyte cellular differential DNA methylations could be identified by the proposed RMO-based method from OVC PWB samples, which were cancer-associated aberrant signals against cell-composition effects.

Elemental profiling of adrenal adenomas in solid tissue and blood samples by ICP-MS and ICP-OES

The elemental composition of control and pathological adrenal tissues remains to be resolved. This study aimed to provide an initial insight into the amounts of micro- (Mn, Co, Cu, Zn, As, Se, Cd, Pb, U) and macroelements (Na, K, Mg, Ca) in healthy adrenal tissue (HAT) and adenomatous adrenal tissue (AAT) samples collected from patients with adrenal adenoma (AA) using inductively coupled plasma mass spectrometry (ICP-MS) and inductively coupled plasma optical emission spectrometry (ICP-OES). The results were accompanied by a comparative determination of the same elements in healthy blood (HB) and adenomatous blood (AB) samples. This is the first study that has provided in-depth knowledge of the baseline composition of the clinically important elements of HAT samples. Furthermore, this study showed elementary changes in AA patients. The AATs had significantly higher amounts of Mn, Cu, Zn, Se, Pb, K, and Mg compared to the HATs. The opposite results were obtained for the same elements in the AB samples, indicating that the benign adrenal masses could have the ability to withdraw these elements from circulation. These results were supplemented by principal component analysis (PCA). ICP-based techniques were successfully applied to accurately provide a more comprehensive insight into the clinically important elements in the solid tissue and blood samples. The results of this study are a deep-dive into the likely future of clinical studies. Moreover, target elements should be taken into consideration as novel initiating and/or modifying factors of AA, after further research, this would include the analysis of a larger number of samples and prospective follow-up of the patient’s elemental profile.

Down-Expression of miRNA-98 and Over-Expression of miRNA-9 Can Result in Inadequate Immune System Response against Lung Cancer

Lung cancer is a disease presenting high incidence and mortality rates. Its most common type is non-small cell lung cancer (NSCLC), constituting about 80-85% of all cases. MicroRNAs (miRNAs) are the molecules playing a role in the regulation of genes. Two crucial cytokines in cancer are interleukin (IL)-10 and IFN-γ. Our objective was to investigate the expression of miRNA-9, miRNA-98, JAK, and STAT3 in patients with NSCLC and detect the cytokine level of IL-10. A total of 50 patients with NSCLC participated in this study. Besides, 50 healthy blood samples were selected as the control group. Real-time PCR determined the expression levels of miRNAs so that the RNAs extracted from the patients' peripheral mononuclear cells (PBMC) were initially synthesized, and cDNA was then extracted. Finally, the synthesized cDNA was amplified using real-time PCR, and its expression was compared to the control group. ELISA technique was used to detect IL-10 in plasma. Our result showed a low level of expression of miRNA-98, JAK, and STAT3 and a high-level expression of miRNA-9. ELISA test indicated a high cytokine level of IL-10 in the NSCLC patients' serum compared to the healthy controls. MiRNA-9 could suppress JAK and STAT3 genes in the NSCLC patients, which causes the poor immune response against the cell's proliferation. Besides, IL-10 was enhanced when miRNA-98 was reduced. Therefore, the elevation of IL-10, as an anti-inflammatory cytokine, could lead to lung cancer progression without a strong immune system response.

Gene signatures of cyclin-dependent kinases: a comparative study in naïve early and advanced stages of lung metastasis breast cancer among pre- and post-menopausal women.

The Human epidermal growth factor receptor 2 positive (HER2+) breast cancer (BC) is a more aggressive tumor with 5 years median survival rates after metastasis. Despite successful treatment, unfortunately, the majority of affected patients die. Defects in cell cycle and transcription regulation phases which are governed by cyclin-dependent kinases (CDKs) are the hallmark of many cancers that underpinning the progression of the disease. Therefore, the current study looked at the alteration of six CDKs mRNA expression levels in pre- and postmenopausal lung metastasis BC groups; the majority were HER2+. Two hundred pre-and postmenopausal lung metastasis breast cancer and healthy control blood samples were taken for RNA isolation. Quantitative PCR was done for CDKs mRNA expressions. We observed overexpression of CDK11, CDK12, CDK17, CDK18, and CDK19 in both pre- and postmenopausal groups. However, CDK20 showed progressive downregulation from early to advanced stages in both groups of patients. Collectively, this data revealed that CDKs overexpression levels may predict BC disease progression and provide further rationale for novel anticancer strategies for HER2+ BC cancers.

Identification of hsa-miR-106a-5p as an impact agent on promotion of multiple sclerosis using multi-step data analysis

Multiple sclerosis (MS) is a chronic, demyelinating disease in which the neuron myelin sheath is disrupted and leading to signal transductions disabilities. The evidence demonstrated that gene expression patterns and their related regulating factors are the most critical agents in MS demyelinating process. A miRNA is a small non-coding RNA which functions in post-transcriptional regulation of gene expression. Identification of specific miRNA dysregulation patterns in MS blood samples compared to healthy control can be used as a diagnostic and prognostic agent. Through the literature review and bioinformatics analysis, it was found that the hsa-miR-106a-5p can be considered a significant MS pathogenic factor, which seems has an abnormal expression pattern in patients' blood. Experimental validation using real-time PCR assay was carried to verifying the miR-106a-5p expression in MS and healthy control blood samples. The obtained results proved the miR-106a dysregulation in MS patients. The expression levels of miR-106a-5p were significantly downregulated (log 2 fold change = - 1.15) in patient blood samples compared to controls (p = 0.055). Our study suggested that miR-106a-5p may have a biomarker potential to the diagnosis of MS patients based on its dysregulation patterns.

Design and Clinical Application of an Integrated Microfluidic Device for Circulating Tumor Cells Isolation and Single-Cell Analysis.

Circulating tumor cells (CTCs) have been considered as an alternative to tissue biopsy for providing both germline-specific and tumor-derived genetic variations. Single-cell analysis of CTCs enables in-depth investigation of tumor heterogeneity and individualized clinical assessment. However, common CTC enrichment techniques generally have limitations of low throughput and cell damage. Herein, based on micropore-arrayed filtration membrane and microfluidic chip, we established an integrated CTC isolation platform with high-throughput, high-efficiency, and less cell damage. We observed a capture rate of around 85% and a purity of 60.4% by spiking tumor cells (PC-9) into healthy blood samples. Detection of CTCs from lung cancer patients demonstrated a positive detectable rate of 87.5%. Additionally, single CTCs, ctDNA and liver biopsy tissue of a representative advanced lung cancer patient were collected and sequenced, which revealed comprehensive genetic information of CTCs while reflected the differences in genetic profiles between different biological samples. This work provides a promising tool for CTCs isolation and further analysis at single-cell resolution with potential clinical value.

Facile PEG-based isolation and classification of cancer extracellular vesicles and particles with label-free surface-enhanced Raman scattering and pattern recognition algorithm.

Extracellular vesicles and particles (EVPs), which contain the same surface proteins as their mother cells, are promising biomarkers for cancer liquid biopsy. However, most of the isolation methods of EVPs are time-consuming and complicated, and hence, sensitive detection and classification methods are required for EVPs. Here, we report a facile polyethylene glycol (PEG)-based method for isolating and classifying EVPs with label-free surface-enhanced Raman scattering (SERS) and pattern recognition algorithm. There are only three steps in the PEG-based isolation method, and it does not require ultracentrifugation, which makes it a low-cost and easy-to-use method. Three types of common male cancer cell lines, namely leukemia (THP-1), prostate cancer (DU-145), and colorectal cancer (COLO-205), and one healthy male blood sample, were utilized to isolate EVPs. To collect the SERS spectra of EVPs, a novel planar nanomaterial, namely amino molybdenum oxide (AMO) nanoflakes, was applied, with the enhancement factor being obtained as 3.2 × 102. Based on the principal component analysis and support vector machine (PCA-SVM) algorithm, cancer and normal EVPs were classified with 97.4% accuracy. However, among the cancer EVPs, the accuracy, precision, and sensitivity were found to be 90.0%, 90.9%, and 83.3% for THP-1; 86.7%, 80.0%, and 92.3% for DU-145; 96.7%, 83.3%, and 100% for COLO-205, respectively. Thus, this work will improve the isolation, detection, and classification of EVPs and promote the development of cancer liquid biopsies.

152. rapid Ultra-high Enrichment of Bacterial Pathogens at Low Concentration from Blood for Species ID and AMR Prediction Using Nanopore Sequencing

BackgroundEach year in the United States there are over 1.7 million cases of sepsis that account for a third of hospital deaths. A key to reducing morbidity and mortality rates is early, appropriate antibiotic therapy. Most new diagnostic approaches still suffer from insufficient sensitivity to low bacterial loads in blood and limited sets of detection targets for bacterial species identification (ID) and antimicrobial resistance (AMR) determination. As such, blood culture remains the gold standard for diagnosing bacteremia despite limitations such as > 2-day turnaround time (TAT), incompatibility with fastidious organisms, and frequent inability to recover causative pathogens.Methods31 clinically relevant bacterial pathogens, made up of 17 gram-positive and 14 gram-negative bacterial species, were spiked into 2 to 4 healthy donor blood samples at 1 to 5 CFU/mL. The samples were run through our proprietary Blood2Bac™ pipeline, sequenced on a nanopore platform, and data were passed through Keynome®, our proprietary machine learning algorithm to determine species ID and AMR.ResultsBy assessing the efficiency of pathogen DNA enrichment and genome coverage post sequencing, we report high performance of 3 CFU/mL for 3 bacterial species and ≤ 2 CFU/mL for the 28 remaining species, which includes S. aureus, E. coli, and Streptococcus spp., three of the leading causes of sepsis.For all 31 bacterial species tested, Keynome called species ID with 100% accuracy. In addition, Keynome also predicted the AMR profile of pathogens with 100% accuracy for 19 drug/species AMR combinations, including ciprofloxacin for E. coli, clindamycin for S. aureus, and aztreonam for K. pneumoniae.ConclusionBlood2Bac is able to enrich a wide range of bacterial pathogens directly from blood and enable bacterial whole genome sequencing with an estimated TAT of 12 hours. When coupled with Keynome, our process provides accurate species ID and AMR calls for key BSI pathogens even at single-digit CFU/mL concentrations. Our species-agnostic and culture-free process enables detection of a diverse range of bacterial species with high sensitivity, providing a robust and comprehensive diagnostic.DisclosuresChiahao Tsui, n/a, Day Zero Diagnostics (Employee, Shareholder) Lisa S. Cunden, PhD, Day Zero Diagnostics (Shareholder) Nicole Billings, PhD, Day Zero Diagnostics (Employee) Imaly A. Nanayakkara, PhD, Day Zero Diagnostics (Employee, Shareholder) Ian Herriott, BS, Day Zero Diagnostics (Employee, Shareholder) Rachel R. Martin, n/a, Day Zero DIagnostics (Employee) Michelle Chen, MS, Day Zero Diagnostics (Employee, Shareholder) Febriana Pangestu, n/a, Day Zero Diagnostics (Employee, Shareholder) Paul Knysh, PhD, Day Zero Diagnostics (Employee) Cabell Maddux, n/a, Day Zero Diagnostics (Employee, Shareholder) Zachary Munro, n/a, Day Zero Diagnostics Inc. (Employee, Shareholder) Miriam Huntley, PhD, Day Zero Diagnostics (Employee, Shareholder)

Ab initio spillover compensation in mass cytometry data.

Signal intensity measured in a mass cytometry (CyTOF) channel can often be affected by the neighboring channels due to technological limitations. Such signal artifacts are known as spillover effects and can substantially limit the accuracy of cell population clustering. Current approaches reduce these effects by using additional beads for normalization purposes known as single-stained controls. While effective in compensating for spillover effects, incorporating single-stained controls can be costly and require customized panel design. This is especially evident when executing large-scale immune profiling studies. We present a novel statistical method, named CytoSpill that independently quantifies and compensates the spillover effects in CyTOF data without requiring the use of single-stained controls. Our method utilizes knowledge-guided modeling and statistical techniques, such as finite mixture modeling and sequential quadratic programming, to achieve optimal error correction. We evaluated our method using five publicly available CyTOF datasets obtained from human peripheral blood mononuclear cells (PBMCs), C57BL/6J mouse bone marrow, healthy human bone marrow, chronic lymphocytic leukemia patient, and healthy human cord blood samples. In the PBMCs with known ground truth, our method achieved comparable results to experiments that incorporated single-stained controls. In datasets without ground-truth, our method not only reduced spillover on likely affected markers, but also led to the discovery of potentially novel subpopulations expressing functionally meaningful, cluster-specific markers. CytoSpill (developed in R) will greatly enhance the execution of large-scale cellular profiling of tumor immune microenvironment, development of novel immunotherapy, and the discovery of immune-specific biomarkers. The implementation of our method can be found at https://github.com/KChen-lab/CytoSpill.git.

Surface enhanced Raman spectroscopy of RNA samples extracted from blood of hepatitis C patients for quantification of viral loads.

Raman spectroscopy is a promising technique to analyze the body fluids for the purpose of non-invasive disease diagnosis. To develop a surface-enhanced Raman spectroscopy (SERS) based method for qualitative and quantitative analysis of HCV from blood samples. SERS was employed to characterize the Hepatitis C viral RNA extracted from different blood samples of hepatitis C virus (HCV) infected patients with predetermined viral loads in comparison with total RNA of healthy individuals. The SERS measurements were performed on 27 extracted RNA samples including low viral loads, medium viral loads, high viral loads and healthy/negative viral load samples. For this purpose, silver nanoparticles (Ag NPs) were used as SERS substrates. Furthermore, multivariate data analysis technique, Principal Component Analysis (PCA) and Partial Least Square Regression (PLSR) were also performed on SERS spectral data. The SERS spectral features due to biochemical changes in the extracted RNA samples associated with the increasing viral loads were established which could be employed for HCV diagnostic purpose. PCA was found helpful for the differentiation between Raman spectral data of RNA extracted from hepatitis infected and healthy blood samples. PLSR model is established for the determination of viral loads in HCV positive RNA samples with 99 % accuracy. SERS can be employed for qualitative and quantitative analysis of HCV from blood samples.

Integrative Analysis of DNA Methylation and Gene Expression to Determine Specific Diagnostic Biomarkers and Prognostic Biomarkers of Breast Cancer.

Background: DNA methylation is a common event in the early development of various tumors, including breast cancer (BRCA), which has been studies as potential tumor biomarkers. Although previous studies have reported a cluster of aberrant promoter methylation changes in BRCA, none of these research groups have proved the specificity of these DNA methylation changes. Here we aimed to identify specific DNA methylation signatures in BRCA which can be used as diagnostic and prognostic markers.Methods: Differentially methylated sites were identified using the Cancer Genome Atlas (TCGA) BRCA data set. We screened for BRCA-differential methylation by comparing methylation profiles of BRCA patients, healthy breast biopsies and blood samples. These differential methylated sites were compared to nine main cancer samples to identify BRCA specific methylated sites. A BayesNet model was built to distinguish BRCA patients from healthy donors. The model was validated using three Gene Expression Omnibus (GEO) independent data sets. In addition, we also carried out the Cox regression analysis to identify DNA methylation markers which are significantly related to the overall survival (OS) rate of BRCA patients and verified them in the validation cohort.Results: We identified seven differentially methylated sites (DMSs) that were highly correlated with cell cycle as potential specific diagnostic biomarkers for BRCA patients. The combination of 7 DMSs achieved ~94% sensitivity in predicting BRCA, ~95% specificity comparing healthy vs. cancer samples, and ~88% specificity in excluding other cancers. The 7 DMSs were highly correlated with cell cycle. We also identified 6 methylation sites that are highly correlated with the OS of BRCA patients and can be used to accurately predict the survival of BRCA patients (training cohort: likelihood ratio = 70.25, p = 3.633 × 10−13, area under the curve (AUC) = 0.784; validation cohort: AUC = 0.734). Stratification analysis by age, clinical stage, Tumor types, and chemotherapy retained statistical significance.Conclusion: In summary, our study demonstrated the role of methylation profiles in the diagnosis and prognosis of BRCA. This signature is superior to currently published methylation markers for diagnosis and prognosis for BRCA patients. It can be used as promising biomarkers for early diagnosis and prognosis of BRCA.

Development and validation of Loop-Mediated Isothermal Amplification (LAMP) detection limit using blood matrix spike for Candida glabrata detection

Background: Rapid and accurate identification of yeast responsible for invasive candidiasis (IC) allows for focused and early initiation of therapy for good clinical outcome. Candida glabrata is increasingly important, and the diagnostic sensitivity of microbial culture method “gold standard” is low and could miss up to 50% of the IC patients. To develop and validate LAMP technique detection limit in comparison to microbial culture and PCR techniques using blood matrix spike for C. glabrata detection. Methods and materials: Blood spiking experiment was conducted using healthy blood sample. Candida glabrata ATCC 2001 reference strain colonies were re-suspended in phosphate-buffered saline (PBS) buffer to 0.5 McFarland standard. Ten-fold serial dilutions of yeast suspensions in 1x PBS was made from 106 to 101 cfu/mL concentrations. A 100 μL from each dilution was plated onto SDA and the resulting number of colonies was established. A 25 μL of each dilution was spiked in 225 μL of blood sample (1:10 dilution). The C. glabrata DNA was extracted from spiked blood using Qiagen yeast DNA extraction kit. The developed LAMP assay detects C. glabrata using a primer set (three pairs) (FIP/BIP, F3/B3 and LF/LB) that recognized eight distinct regions on the target internal transcribed spacer (ITS) gene, while, ITS1/4 universal primers were used in PCR analysis. The cfu/mL detection limit of the LAMP was compared to culture and PCR techniques. Results: The LAMP assay analysis of DNA from spiked blood, indicates detection limit of 101 cfu/mL (4.03 x 101 cells/25 μL) using gel electrophoresis analysis. The PCR detection limit was 105 cfu/mL (4.03 x 104 cells/25 μL) and the culture detection limit was 104 cfu/mL (1.61 x 106 cells/mL). Conclusion: The LAMP assay indicates high sensitivity of C. glabrata ITS detection from spiked blood compared to PCR and therefore, a good diagnostic tool for molecular analysis.

Identification of KRAS mutation in a patient with linear nevus sebaceous syndrome: a case report

BackgroundLinear nevus sebaceous syndrome (LNSS) is a rare genetic disease characterized by large linear sebaceous nevus typically on the face, scalp, or neck. LNSS could be accompanied by multisystem disorders including the central nervous system. Herein, we report gene mutational profile via whole exome sequencing of both lesional and non-lesional skin samples in a LNSS patient.Case presentationA 17-year-old girl presented with multisystem abnormalities, including large skin lesions, ocular disorders, abnormal bone development and neurological symptoms. A diagnosis of LNSS was established based on clinical manifestations, histopathological and imaging findings. The skin lesions were resected and no recurrence was noted at the time of drafting this report. Whole exome sequencing of genomic DNA revealed the following 3 mutations in the lesions of the index patient: KRAS (c.35G > A, p.G12D), PRKRIR (c.A1674T, p.R558S), and RRP7A (c. C670T, p.R224W), but no mutation was found in the healthy skin and peripheral blood sample of the index patient, or in the blood samples of her parents and sibling. PCR-mediated Sanger sequencing of DNA derived from lesional skin sample of the index patient verified KRAS mutation, but not PRKRIR (c.A1674T, p.R558S) and RRP7A (c. C670T, p.R224W). None of the 3 mutations was found in Sanger sequencing in skin lesions of 60 other cases of nevus sebaceous patients.ConclusionsOur findings show the relevance of KRAS mutation to LNSS, providing new clues in understanding related genetic heterogeneity which could aid genetic counselling for LNSS patients.