Gene Expression Biomarkers Research Articles

Abstract 2092: Consensus analysis of associated target-biomarker pairs in cancers

Abstract The heterogeneity of cancers limits the reproducibility of target-biomarker relationships in diverse cohorts or sample groups. Here, we carried out consensus analyses of associated data pairs to improve the consistency (reproducibility) of prognostic power of biomarkers and anticancer efficacy of targets. All of RNA expression, patient survival, CRIRSPR/shRNA screening data were integrated from TCGA, GDSC and CCLE datasets. While >90% of prognostic RNA expression found in given sample sets were not reproduced (i.e., not significant) in other test sets, those hits exhibiting consensus prognostic powers in diverse subtypes or lineages, were more significant in test sets than non-consensus hits. In the analysis of the association between CRISPR knockout and RNA expression data, the lineage consensus of the association increased the reproducibility in the validation using sh/siRNA knockdown and qPCR data. Further experimental validations reveal that ITGAV is an effective anticancer target in diverse lineages, significantly associated with prognostic RNA expression of several consensus biomarker genes. In conclusion, the consensus analysis was useful to prioritize reproducible targets and biomarkers from omics data. It has been implemented in Q-omics software (http://qomics.io) for general cancer research. Citation Format: Sumin Jeong, Yuna Park, Eunah Jeong, Sukjoon Yoon. Consensus analysis of associated target-biomarker pairs in cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2092.

Current Status of Predictive Biomarker Development in Metastatic Renal Cell Carcinoma

In this review, we analyze the current state of research in development of new biomarkers that may be useful in managing metastatic renal cell carcinoma (mRCC) setting. Combining tumor-based biomarkers (gene expression profile) and blood-based biomarkers (ctDNA, cytokines) would be helpful in acquiring information regarding RCC and might be significant in the decision-making process. Renal cell carcinoma (RCC) is the sixth most frequently diagnosed neoplasm in men and tithe in women, making it responsible for 5% and 3% of all diagnosed cancers respectively. Metastatic stage represents a non-negligible percentage at diagnosis and is characterized by poor prognosis. Despite clinical features and prognostic score could guide clinicians in therapeutic approach of this disease, biomarkers predictive of response to treatment remain an unmet need.

Sex-specific association of exposure to air pollutants and Nrf2 gene expression and inflammatory biomarkers in exhaled breath of healthy adolescents

Studies investigating the nuclear factor erythroid 2-related factor 2 (Nrf2) expression levels in the respiratory system of healthy subjects are scarce. Moreover, separate studies on the health-related outcomes of air pollution for each sex are limited. The current panel study investigated sex-specific Nrf2 expression levels and related oxidative stress and inflammatory responses among healthy adolescents exposed to PM2.5, PM10, O3, and PM2.5-bounded metals in a high traffic region. Forty-nine healthy nonsmoking subjects participated in the study for five consecutive months (Nov. 2019 to Feb. 2020). Each subject was asked to provide 1 mL of exhaled breath condensate (EBC). Data were analyzed using linear mixed-effects models. The results showed that PM10, PM2.5, O3, and PM2.5-bounded metals were negatively linked to Nrf2 expression level in EBC of females with −58.3% (95% CI: 79.5, −15.4), −32.1% (95% CI: −50.3, −7.1), −76.2% (95% CI: −92.6, −23.9), and −1.9 (95% CI: −3.4, −0.4), respectively. While our results presented no significant association between the studied pollutants and Nrf2 gene expression in males, significant associations were observed between the pollutants and total nitric oxide (NOx), interleukins 6 (IL-6), and tumor necrosis factor-alpha (TNF-α) in the EBC of females. In the case of males, only EBC cytokines showed a significant association with air pollutants. Overall, this study suggests that exposure to ambient air pollutants may affect the respiratory system with biologically different mechanisms in males and females. PM2.5 concentration had a positive correlation with exhaled TNF-α and IL6 values in females while positive correlation with TNF-α and negative correlation with IL6 values in males. O3 had a negative correlation with TNF-α in males.

Towards precision medicine for anxiety disorders: objective assessment, risk prediction, pharmacogenomics, and repurposed drugs

Anxiety disorders are increasingly prevalent, affect people’s ability to do things, and decrease quality of life. Due to lack of objective tests, they are underdiagnosed and sub-optimally treated, resulting in adverse life events and/or addictions. We endeavored to discover blood biomarkers for anxiety, using a four-step approach. First, we used a longitudinal within-subject design in individuals with psychiatric disorders to discover blood gene expression changes between self-reported low anxiety and high anxiety states. Second, we prioritized the list of candidate biomarkers with a Convergent Functional Genomics approach using other evidence in the field. Third, we validated our top biomarkers from discovery and prioritization in an independent cohort of psychiatric subjects with clinically severe anxiety. Fourth, we tested these candidate biomarkers for clinical utility, i.e. ability to predict anxiety severity state, and future clinical worsening (hospitalizations with anxiety as a contributory cause), in another independent cohort of psychiatric subjects. We showed increased accuracy of individual biomarkers with a personalized approach, by gender and diagnosis, particularly in women. The biomarkers with the best overall evidence were GAD1, NTRK3, ADRA2A, FZD10, GRK4, and SLC6A4. Finally, we identified which of our biomarkers are targets of existing drugs (such as a valproate, omega-3 fatty acids, fluoxetine, lithium, sertraline, benzodiazepines, and ketamine), and thus can be used to match patients to medications and measure response to treatment. We also used our biomarker gene expression signature to identify drugs that could be repurposed for treating anxiety, such as estradiol, pirenperone, loperamide, and disopyramide. Given the detrimental impact of untreated anxiety, the current lack of objective measures to guide treatment, and the addiction potential of existing benzodiazepines-based anxiety medications, there is a urgent need for more precise and personalized approaches like the one we developed.

Feeding graded levels of dried Sea buckthorn (Hippophaes rhamnoides) berries to broiler chickens

AbstractThe aim of this study was to assess the effects of graded levels (0, 3, 6, 9 and 12 g/kg) of dry Sea buckthorn (SB) berries on growth performance, gastrointestinal tract (GIT) development, jejunal histomorphology, bird antioxidant status and caecal short‐chain fatty acid concentration when fed to female Ross 308 broiler chickens. In addition, expression of cytokine biomarker genes in the jejunum was evaluated. The five experimental diets were fed from 7 to 21 days age to 8 pens (two birds in each) following randomisation. Feeding SB did not influence bird growth performance (p > .05). There was a linear decrease in butyric, acetic and valeric acid concentrations in caecal digesta (p < .05) and a decrease (p < .05) in crypt depth. The expression of IFNG and CD40LG responded quadratically (p < .05), peaking at 6–9 g/kg dietary inclusion of SB, respectively. Other studied variables were not affected by dietary SB inclusion (p > .05). Feeding dry SB berries up to 12 g/kg of diet did not improve the zootechnical variables of healthy commercial‐strain broilers in this study.

Advanced Glycation End Products and Bone Metabolism in Patients with Chronic Kidney Disease.

Advanced glycation end products (AGEs) accumulation may be involved in the progression of CKD-bone disorders. We sought to determine the relationship between AGEs measured in the blood, skin, and bone with histomorphometry parameters, bone protein, gene expression, and serum biomarkers ofbone metabolism in patients with CKD stages 3 to 5D patients. Serum levels of AGEs were estimated by pentosidine, glycated hemoglobin (A1c), and N-carboxymethyl lysine (CML). The accumulation of AGEs in the skin was estimated from skin autofluorescence (SAF). Bone AGEs accumulation and multiligand receptor for AGEs (RAGEs) expression were evaluated by immunohistochemistry; bone samples were used to evaluate protein and gene expression and histomorphometric analysis. Data are from 86 patients (age: 51 ± 13 years; 60 [70%] on dialysis). Median serum levels of pentosidine, CML, A1c, and SAF were 71.6pmol/mL, 15.2ng/mL, 5.4%, and 3.05 arbitrary units, respectively. AGEs covered 3.92% of trabecular bone and 5.42% of the cortical bone surface, whereas RAGEs were expressed in 0.7% and 0.83% of trabecular and cortical bone surfaces, respectively. AGEs accumulation in bone was inversely related to serum receptor activator of NF-κB ligand/parathyroid hormone (PTH) ratio (R=-0.25; p=0.03), and RAGE expression was negatively related to serum tartrate-resistant acid phosphatase-5b/PTH (R=-0.31; p=0.01). Patients with higher AGEs accumulation presented decreased bone protein expression (sclerostin [1.96 (0.11-40.3) vs. 89.3 (2.88-401) ng/mg; p=0.004]; Dickkopf-related protein 1 [0.064 (0.03-0.46) vs. 1.36 (0.39-5.87) ng/mg; p=0.0001]; FGF-23 [1.07 (0.4-32.6) vs. 44.1 (6-162) ng/mg; p=0.01]; and osteoprotegerin [0.16 (0.08-2.4) vs. 6.5 (1.1-23.7) ng/mg; p=0.001]), upregulation of the p53 gene, and downregulation of Dickkopf-1 gene expression. Patients with high serum A1c levels presented greater cortical porosity and Mlt and reduced osteoblast surface/bone surface, eroded surface/bone surface, osteoclast surface/bone surface, mineral apposition rate, and adjusted area. Cortical thickness was negatively correlated with serum A1c (R=-0.28; p=0.02) and pentosidine levels (R=-0.27; p=0.02). AGEs accumulation in the bone of CKD patients was related to decreased bone protein expression, gene expression changes, and increased skeletal resistance to PTH; A1c and pentosidine levels were related to decreased cortical thickness; and A1c levels were related to increased cortical porosity and Mlt. © 2023 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.

Identification of potential biomarkers for colorectal cancer by clinical database analysis and Kaplan-Meier curves analysis.

This study aimed to explore critical genes as potential biomarkers for the diagnosis and prognosis of colorectal cancer (CRC) for clinical utility. To identify and screen candidate genes involved in CRC carcinogenesis and disease progression, we downloaded microarray datasets GSE89076, GSE73360, and GSE32323 from the GEO database identified differentially expressed genes (DEGs), and performed a functional enrichment analysis. A protein-protein interaction network was constructed, and correlated module analysis was performed using STRING and Cytoscape. The Kaplan-Meier survival curve shows the survival of the hub genes. The expression of cyclin-dependent kinase (CDK1), cyclin B1 (CCNB1), and PCNA in tissues and changes in tumor grade were analyzed. A total of 329 DEGs were identified, including 264 upregulated and 65 downregulated genes. The functions and pathways of DEGs include the mitotic cell cycle, poly(A) RNA binding replication, ATP binding, DNA replication, ribosome biogenesis in eukaryotes, and RNA transport. Forty-seven Hub genes were identified, and biological process analysis showed that these genes were mainly enriched in cell cycle and DNA replication. Patients with mutations in CDK1, PCNA, and CCNB1 had poorer survival rates. CDK1, PCNA, and CCNB1 were significantly overexpressed in the tumor tissues. The expression of CDK1 and CCNB1 gradually decreased with increasing tumor grade. CDK1, CCNB1, and PCNA can be used as potential markers for the diagnosis and prognosis of CRC. These genes are overexpressed in colon cancer tissues and are associated with low survival rates in CRC patients.

Abstract TMP37: Gene Expression May Predict Symptom Onset Time In Acute Ischemic Stroke

Introduction: Imprecise timing of symptom onset (SO) in patients with acute ischemic stroke (AIS) may impact eligibility for reperfusion therapy. Unreliable “last-known-well” (LKW) estimates may reduce the use of thrombolytic or endovascular treatments. A blood biomarker that serves as a “stroke clock” could minimize uncertainty and augment treatment rates. Methods: The single-center VuEssence Stroke Trial (VEST) evaluated gene expression biomarkers in adult ED patients with suspected AIS, a LKW time < 24hrs, and timing of SO accurate within a 0-3 hour time frame. At ED presentation and before reperfusion treatment, whole blood was collected in PAXgene RNA tubes for RNA-sequencing and gene expression analysis. Researchers blinded to molecular results adjudicated final diagnosis (AIS vs stroke mimic) and estimated time of SO based on times of witnessed onset (WO), LKW, and symptom discovery (SD). The confirmed AIS subgroup with WO timing, or ≤60 minutes between LKW and SD, was analyzed. Results: Of AIS patients, 56 met criteria (52% men, mean age 71.6). The average time from SO was 148 minutes (range 48-490). After RNA-sequencing, linear regression showed 684 genes with a significant linear time-related expression change in reference to time from SO (<0.2 Benjamini-Hochberg p-adjusted). A subgroup of 210 genes with <0.004 p-values and linear coefficients >0.25 were used to generate multiple classifiers of up to 12 genes that identified AIS <2.5 hrs from SO. Each gene is used in at least one classifier with other genes selected to maximize a measure of accuracy. The top panels showed both high sensitivity and specificity ( table ). Conclusion: Using a biological “stroke clock” biomarker instead of SO timing may streamline evaluations of suspected AIS, augment reperfusion therapy rates, and improve outcomes. VEST identified time-related gene expression changes that may accurately classify AIS <2.5 hrs from SO. These gene panels will require further validation.

ANALYSIS OF THE GENETIC EXPRESSION OF COLON CANCER GENETIC BIOMARKERS ON INFLAMMATORY BOWEL DISEASE ON BLOOD AND BIOPSY SAMPLES

Abstract INTRODUCTION Inflammatory bowel disease (IBD) is an immune-mediated inflammatory condition of the gastrointestinal tract. Its incidence rose steadily in the last century and the estimated incidence is approximately 2.5 million in Europe and 1.5 million in North America [1]. This condition can be associated with an increased risk of cardiovascular diseases, infections, and cancer [2] The risk of colorectal cancer (CRC) is approximately 2- to 3-fold higher for IBD patients than in the general population. [2] Malignancies are the second most common cause of mortality after cardiovascular disease in patients with IBD. [3] Several genetic biomarkers have been studied as prognostic factors, such as BRAF, CEACAM5, SMAD4, APC, MLH1 (part of the Microsatellite instability prognosis factors), and KRAS. OBJECTIVE The aim of this study was to determine the gene expression of CRC genetic biomarkers in IBD patients' peripheral blood and biopsy samples. METHODOLOGY The gene expression data was retrieved from the Gene Expression Omnibus (peripheral blood: GSE186507 and colon biopsies: GSE193677). This data was submitted by Argmann et al, a study that included healthy control patients (n=243), UC (n=421), and CD (n=243). The biopsy samples were obtained from the ileum, colon, and rectum. Several CRC biomarkers were retrieved from the literature. We compared the expression of these biomarkers between the groups in both, blood samples and the different sites of biopsies using T-test (UC vs control, CD vs control, and UC vs CD). RESULTS The analysis showed a significant difference in some CRC gene biomarkers between IBD patients and the control group in peripheral blood and the different locations where the biopsies were obtained. MLH1 was more expressed in IBD patients compared with healthy patients in the cecum (CD vs control p=8e-06; CD vs UC p= 0.00046), left colon (CD vs UC p= 0.02), right colon (UC vs control p=0.022; CD vs UC p=0.0053), sigmoid colon (UC vs control p=0.037; CD vs UC p=0.028), and rectum (CD vs control p=5e-10, CD vs UC p= 1.2e-13). In the case of the blood samples, the gene expression of SMAD4 (p = 0.03) CEACAM5 (p= 0.02), KRAS (p= 0.0005), and MLH1 (p= 0.0002) was significantly higher in IBD patients compared with control group.

Deciphering genetic causes for sex differences in human health through drug metabolism and transporter genes

Sex differences have been widely observed in human health. However, little is known about the underlying mechanism behind these observed sex differences. We hypothesize that sex-differentiated genetic effects are contributors of these phenotypic differences. Focusing on a collection of drug metabolism enzymes and transporters (DMET) genes, we discover sex-differentiated genetic regulatory mechanisms between these genes and human complex traits. Here, we show that sex-differentiated genetic effects were present at genome-level and at DMET gene regions for many human complex traits. These sex-differentiated regulatory mechanisms are reflected in the levels of gene expression and endogenous serum biomarkers. Through Mendelian Randomization analysis, we identify putative sex-differentiated causal effects in each sex separately. Furthermore, we identify and validate sex differential gene expression of a subset of DMET genes in human liver samples. We observe higher protein abundance and enzyme activity of CYP1A2 in male-derived liver microsomes, which leads to higher level of an active metabolite formation of clozapine, a commonly prescribed antipsychotic drug. Taken together, our results demonstrate the presence of sex-differentiated genetic effects on DMET gene regulation, which manifest in various phenotypic traits including disease risks and drug responses.

Uma abordagem de multibiomarcadores para investigar os efeitos do paracetamol no eixo de regulação da reprodução de machos do bagre Neotropical Rhamdia quelen

Abstract: Aim Paracetamol (PCM), or acetaminophen, is one of the most used drugs for human treatment of pain and fever. Since it has often been found in the aquatic environment, the aim of this study was to investigate the effects of PCM on the reproductive axis of male Rhamdia quelen catfish. Methods Different biomarkers were evaluated in hypothalamus, liver and gonads, as well as the plasma sexual hormone quantification. The fish were exposed to three PCM concentrations: 0.25, 2.5 and 25 µg.L-1 and to a control group (solvent acetone 0.0003%). After 14 days of exposure, fish were anesthetized, for blood sampling and biometrics, and after euthanasia, the tissues were sampled. Plasma was used for 11- keto testosterone and 17β - estradiol quantification. The hypothalamus was collected for brain aromatase (cyp19a1b) gene expression; the liver for the vitellogenin (vtg) gene expression and biochemical biomarkers; and gonad for the biochemical and histological biomarkers analyses. Results No alterations were observed in the hormone’s levels, sexual maturation level or in cyp19a1b and vtg gene expression. In the liver the non-protein thiols concentration increased at 2.5 µg.L-1 of PCM, and the superoxide dismutase (SOD) activity was reduced at 0.25 µg.L-1 of PCM. In gonads, glutathione S-transferase (GST) activity decreased and SOD activity increased at 25 µg.L-1 of PCM, while the glutathione peroxidase (GPx) activity reduced after exposure to both PCM concentrations. Conclusion The results showed that environmental concentrations of PCM can cause alterations in the antioxidant system, mainly in the gonads of R. quelen males. However, without significant change in the hormones levels or in the expression of genes related to the reproduction axis. These alterations occurred at concentrations already found in aquatic environment, including in Brazil.

Biomarkers in IgA nephropathy; an update to recent data

Biomarkers are molecules that can be measured in the body and can reflect disease activity or progression. They can be used to diagnose and monitor disease, predict treatment response, and identify potential therapeutic targets. Several types of biomarkers have been studied in the context of IgA nephropathy, including protein, gene expression, epigenetic, and microRNA biomarkers. Biomarkers have the potential to improve the accuracy and specificity of the diagnosis of IgA nephropathy and predict the disease progression and response to treatment. However, further studies are needed to validate their diagnostic value in larger cohorts of patients and to integrate them into clinical practice. The development of multi-omics approaches that combine different types of biomarkers may provide a more comprehensive understanding of the disease pathogenesis and potential treatments.

Comprehensive identification of gene expression fingerprints and biomarkers of sexual endocrine disruption in zebrafish embryo

Endocrine disruptors (EDs), capable of modulating the sex hormone system of an organism, can exert long-lasting negative effects on reproduction in both humans and the environment. For these reasons, the properties of EDs prevent a substance from being approved for marketing. However, regulatory testing to evaluate endocrine disruption is time-consuming, costly, and animal-intensive. Here, we combined sublethal zebrafish embryo assays with transcriptomics and proteomics for well-characterized endocrine disrupting reference compounds to identify predictive biomarkers for sexual endocrine disruption in this model. Using RNA and protein gene expression fingerprints from two different sublethal exposure concentrations, we identified specific signatures and impaired biological processes induced by ethinylestradiol, tamoxifen, methyltestosterone and flutamide 96 h post fertilization (hpf). Our study promotes vtg1 as well as cyp19a1b, fam20cl, lhb, lpin1, nr1d1, fbp1b, and agxtb as promising biomarker candidates for identifying and differentiating estrogen and androgen receptor agonism and antagonism. Evaluation of these biomarkers for pre-regulatory zebrafish embryo-based bioassays will help identify endocrine disrupting hazards of compounds at the molecular level. Such approaches additionally provide weight-of-evidence for the identification of putative EDs and may contribute significantly to a reduction in animal testing in higher tier studies.

Analysis of a Biopsy-Based Genomic Classifier in High-Risk Prostate Cancer: Meta-Analysis of the NRG Oncology/Radiation Therapy Oncology Group 9202, 9413, and 9902 Phase 3 Randomized Trials

Decipher is a genomic classifier (GC) prospectively validated postprostatectomy. We validated the performance of the GC in pretreatment biopsy samples within the context of 3 randomized phase 3 high-risk definitive radiation therapy trials. A prespecified analysis plan (NRG-GU-TS006) was approved to obtain formalin-fixed paraffin-embedded tissue from biopsy specimens from the NRG biobank from patients enrolled in the NRG/Radiation Therapy Oncology Group (RTOG) 9202, 9413, and 9902 phase 3 randomized trials. After central review, the highest-grade tumors were profiled on clinical-grade whole-transcriptome arrays and GC scores were obtained. The primary objective was to validate the independent prognostic ability for the GC for distant metastases (DM), and secondary for prostate cancer-specific mortality (PCSM) and overall survival (OS) with Cox univariable and multivariable analyses. GC scores were obtained on 385 samples, of which 265 passed microarray quality control (69%) and had a median follow-up of 11 years (interquartile range, 9-13). In the pooled cohort, on univariable analysis, the GC was shown to be a prognostic factor for DM (per 0.1 unit; subdistribution hazard ratio [sHR], 1.29; 95% confidence interval [CI], 1.18-1.41; P < .001), PCSM (sHR, 1.28; 95% CI, 1.16-1.41; P < .001), and OS (hazard ratio [HR], 1.16; 95% CI, 1.08-1.22; P < .001). On multivariable analyses, the GC (per 0.1 unit) was independently associated with DM (sHR, 1.22; 95% CI, 1.09-1.36), PCSM (sHR, 1.23; 95% CI, 1.09-1.39), and OS (HR, 1.12; 95% CI, 1.05-1.20) after adjusting for age, Prostate Specific Antigen, Gleason score, cT stage, trial, and randomized treatment arm. GC had similar prognostic ability in patients receiving short-term or long-term androgen-deprivation therapy, but the absolute improvement in outcome varied by GC risk. This is the first validation of a gene expression biomarker on pretreatment prostate cancer biopsy samples from prospective randomized trials and demonstrates an independent association of GC score with DM, PCSM, and OS. High-risk prostate cancer is a heterogeneous disease state, and GC can improve risk stratification to help personalize shared decision making.

Transcriptional profiling of drug-induced liver injury biomarkers: association of hepatic Srebf1/Pparα signaling and crosstalk of thrombin, alcohol dehydrogenase, MDR and DNA damage regulators.

Cell stress transcribing genes provide a diverse platform of molecular mediators that vary in response to toxicity. Common drug-induced liver injury (DILI) biomarkers are usually expressed in mild toxicity and limited to confirming it rather than categorizing its intensity. Thus, new parametric biomarkers are needed to be explored. Classifying the toxicological response based on the dose-level and severity of stimuli will aid in the evaluation and approach against drug exposure. The present research explored the involvement of gene expression of potential biomarkers as a severity-specific hallmark in different acetaminophen (APAP)-induced hepatotoxicity levels in C57BL/6 mice. The differentially expressed genes were annotated and analyzed using bioinformatics tools to predict canonical pathways altered by DILI. The results revealed alteration in genes encoding for antioxidant enhancement; Slc7a11, bile efflux; MDR4, fatty acid metabolism and transcriptional factors namely Srebf1 and Pparα. Potential APAP toxicity biomarkers included Adh1 and thrombin, and other DNA damage and stress chaperones which were changed at least fourfold between control and the three tested severity models. The current investigation demonstrates a dose-mediated association of several hallmark genes in APAP-induced liver damage and addressed the involvement of uncommonly studied molecular responses. Such biomarkers can be further developed into predictive models, translated for risk assessment against drug exposure and guide in building theragnostic targets.

Reproducible method for assessing the effects of blue light using in vitro human skin tissues.

High-intensity visible light (HEV), also referred to as blue light, has a wavelength of 400-500 nm and accounts for approximately one-third of the visible light. Blue light is also emitted from electronic devices and artificial indoor lighting. Studies have shown that exposure of human skin cells to light emitted from electronic devices, even as short as 1 h, can cause an increase in reactive oxygen species (ROS), apoptosis and necrosis. Despite comprising a significant portion of the light spectrum, the effects of HEV light have not been studied as extensively. This is in part due to a lack of suitable in vitro testing methods. This work was conducted in order to develop a reproducible testing method for assessing the effects of blue light on the skin. Testing was performed using a full thickness, 3D in vitro skin tissue model. Different exposure protocols were tested to (1) determine the biological effects of blue light on the skin and (2) to identify an appropriate exposure for routine testing of cosmetic materials that may protect the skin from blue light damage. Gene expression and protein biomarkers were measured using qPCR, ELISA and immunohistochemical (IHC) methods. Our work demonstrates that daily exposure to blue light produced dose-and-time-dependent changes in biomarkers associated with skin damage. Exposure to blue light for 6 h for 5 consecutive days (total intensity of 30 J/cm2 ) increased the expression of genes that regulate inflammation and oxidative stress pathways and decreased the expression of genes that maintain skin barrier and tissue integrity. Exposure to blue light significantly increased protein biomarkers associated with ageing, inflammation and tissue damage. IHC staining confirmed changes in collagen, filaggrin and NQO1 protein expression. Treatment with ascorbic acid inhibited the effects of blue light, demonstrating a role in protection from blue light. Our results showed that consistent blue light exposure produced skin damage via alterations in biological pathways that are associated with skin ageing. This work provides a new, reproducible in vitro testing method for assessing the effects of blue light on human skin using gene expression, protein ELISA and IHC staining.

A knowledge integration strategy for the selection of a robust multi-stress biomarkers panel for Bacillus subtilis

One challenge in the engineering of biological systems is to be able to recognise the cellular stress states of bacterial hosts, as these stress states can lead to suboptimal growth and lower yields of target products. To enable the design of genetic circuits for reporting or mitigating the stress states, it is important to identify a relatively reduced set of gene biomarkers that can reliably indicate relevant cellular growth states in bacteria. Recent advances in high-throughput omics technologies have enhanced the identification of molecular biomarkers specific states in bacteria, motivating computational methods that can identify robust biomarkers for experimental characterisation and verification. Focused on identifying gene expression biomarkers to sense various stress states in Bacillus subtilis, this study aimed to design a knowledge integration strategy for the selection of a robust biomarker panel that generalises on external datasets and experiments. We developed a recommendation system that ranks the candidate biomarker panels based on complementary information from machine learning model, gene regulatory network and co-expression network. We identified a recommended biomarker panel showing high stress sensing power for a variety of conditions both in the dataset used for biomarker identification (mean f1-score achieved at 0.99), as well as in a range of independent datasets (mean f1-score achieved at 0.98). We discovered a significant correlation between stress sensing power and evaluation metrics such as the number of associated regulators in a B. subtilis gene regulatory network (GRN) and the number of associated modules in a B. subtilis co-expression network (CEN). GRNs and CENs provide information relevant to the diversity of biological processes encoded by biomarker genes. We demonstrate that quantitatively relating meaningful evaluation metrics with stress sensing power has the potential for recognising biomarkers that show better sensitivity and robustness to an extended set of stress conditions and enable a more reliable biomarker panel selection.

EE256 Budget Impact Analysis of the Introduction of a Novel Gene Expression Biomarker Test for Early-Stage Breast Cancer Patients in Cyprus

EE256 Budget Impact Analysis of the Introduction of a Novel Gene Expression Biomarker Test for Early-Stage Breast Cancer Patients in Cyprus

Genome and transcriptome of Chinese medaka (Oryzias sinensis) and its uses as a model fish for evaluating estrogenicity of surface water

Ecological toxicity assessments of contaminants in aquatic environments are of great concern. However, a dilemma in ecological toxicity assessments often arises when linking the effects found in model animals in the laboratory and the phenomena observed in wild fishes in the field due to species differences. Chinese medaka (Oryzias sinensis), widely distributed in East Asia, is a satisfactory model animal to assess aquatic environment in China. Here, we domesticated this species and assembled its genome (814 Mb) using next-generation sequencing (NGS). A total of 21,922 high-confidence genes with 41,306 transcripts were obtained and annotated, and their expression patterns in tissues were determined by RNA-sequencing. Six mostly sensitive biomarker genes, including vtg1, vtg3, vtg6, zp3a.2, zp2l1, and zp2.3 to estrogen exposure were screened and validated in the fish exposed to concentrations of estrone (E1), 17β-estradiol (E2), and estriol (E3) under laboratory condition. Field investigations were then performed to evaluating the gene expression of biomarkers in wild Chinese medaka and levels of E1, E2, and E3 in the fish habitats. It was found that in 40 sampling sites, the biomarker genes were obviously highly expressed in the wild fish from about half sites, and the detection frequencies of E1, E2, and E3, were 97.5%, 42.5%, and 45% with mean concentrations of 82.48, 43.17, 52.69 ng/L, respectively. Correlation analyses of the biomarker gene expressions in the fish with the estrogens levels which were converted to EEQs showed good correlation, indicating that the environmental estrogens and estrogenicity of the surface water might adversely affect wild fishes. Finally, histologic examination of gonads in male wild Chinese medaka was performed and found the presence of intersex in the fish. This study facilitated the uses of Chinese medaka as a model animal for ecotoxicological studies.

BIOM-54. ANALYTICAL VALIDATION OF A TARGETED GENE EXPRESSION BIOMARKER PREDICTING MENINGIOMA OUTCOMES AND RADIOTHERAPY RESPONSES

Abstract BACKGROUND Improvements in meningioma risk stratification are needed to guide postoperative management. We previously developed and externally validated a targeted gene expression biomarker predicting meningioma outcomes and radiotherapy response using fresh frozen meningiomas. Here, we present the analytical validity, test-retest and cross-platform reproducibility, intra-tumor heterogeneity, and formalin fixed paraffin embedded (FFPE) concordance for this biomarker. METHODS Matched FFPE and fresh frozen samples from 50 meningiomas underwent RNA extraction for concordance testing using a custom Nanostring gene expression panel comprised of 34 meningioma genes and 7 housekeeping genes. Matched Nanostring gene expression profiling and RNA-sequencing was available from 173 fresh frozen meningiomas. Nanostring batch, machine, and technician variability was tested on 10 FFPE meningiomas using 2 independent batches of biomarker reagents that were processed at 2 independent laboratories. To study intra-tumor heterogeneity, 68 spatially distinct meningioma biopsies obtained under stereotactic guidance from 13 tumors were analyzed using the Nanostring gene expression biomarker. RESULTS Matched FFPE and fresh frozen meningioma samples (N=50) demonstrated high gene expression concordance (Pearson R=0.89, F-test P&amp;lt; 2.2e-16) and risk score concordance (R=0.78, F-test P&amp;lt; 1.8e-11, residual standard error 0.12). The biomarker achieved high performance on FFPE samples (local freedom from recurrence [LFFR] c-index 0.75±SEM 0.05, 5y LFFR AUC 0.84, 95% interval 0.67-0.96). Test-retest concordance on FFPE samples (N=10) across independent reagent batches, machines, and technicians was high (gene expression concordance: R=0.97; risk score concordance R=0.94). Transcript counts were concordant across Nanostring and RNA sequencing approaches (N=173 frozen samples, R=0.90). Stereotactic intra-operative sampling (N=68 samples from 13 patients) revealed low levels of intra-tumor heterogeneity (median inter-quartile risk score within tumor: 0.10±0.01). CONCLUSIONS We demonstrate analytical reproducibility and robustness of a gene expression biomarker predicting meningioma outcomes and radiotherapy responses in FFPE and frozen samples across multiple conditions and platforms.