Biomarkers In Conjunction Research Articles

Spatial Patterns of Thalassia testudinum Immune Status and Labyrinthula spp. Load Implicate Environmental Quality and History as Modulators of Defense Strategies and Wasting Disease in Florida Bay, United States.

Seagrass wasting disease, caused by protists of the genus Labyrinthula, is an important stressor of the dominant macrophyte in Florida Bay (FB), United States, Thalassia testudinum. FB exhibits countervailing gradients in plant morphology and resource availability. A synoptic picture of the Thalassia-Labyrinthula relationship was obtained by assessing the activity of four immune biomarkers in conjunction with pathogen prevalence and load [via quantitative PCR (qPCR)] at 15 sites across FB. We found downregulated immune status paired with moderate pathogen load among larger-bodied host phenotypes in western FB and upregulated immunity for smaller-bodied phenotypes in eastern FB. Among the highest immune response sites, a distinct inshore-offshore loading pattern was observed, where coastal basins exposed to freshwater runoff and riverine inputs had the highest pathogen loads, while adjacent offshore locations had the lowest. To explain this, we propose a simple, conceptual model that defines a framework for testable hypotheses based on recent advances in resistance-tolerance theory. We suggest that resource availability has the potential to drive not only plant size, but also tolerance to pathogen load by reducing investment in immunity. Where resources are more scarce, plants may adopt a resistance strategy, upregulating immunity; however, when physiologically challenged, this strategy appears to fail, resulting in high pathogen load. While evidence remains correlative, we argue that hyposalinity stress, at one or more temporal scales, may represent one of many potential drivers of disease dynamics in FB. Together, these data highlight the complexity of the wasting disease pathosystem and raise questions about how climate change and ongoing Everglades restoration might impact this foundational seagrass species.

Added value of cerebrospinal fluid multimarker analysis in diagnosis and progression of dementia.

Recently, some emerging cerebrospinal fluid (CSF) markers have been proposed as diagnostic tools for Alzheimer disease (AD) that can have an effect on disease progression. We analyze the accuracy of these CSF markers for diagnosis of AD in reference to brain amyloid positron emission tomography (PET). We also investigated whether they help in differentiating AD from other dementias and examined their influence in tracing the progression to dementia. Amyloid-β (Aβ) 1-42, total tau (t-tau), phosphorylated tau, Aβ40 , Aβ38 , beta-site amyloid precursor protein cleaving enzyme 1 (BACE-1), neurogranin (ng), phosphorylated neurofilament heavy-chain, and α-synuclein (α-syn) CSF levels were analyzed in 319 subjects, among whom 57 also underwent an amyloid PET scan. We also analyzed longitudinal clinical data from 239 subjects. Emerging CSF markers, especially ng/BACE-1 ratio (area under the curve = 0.77) and their combinations with core AD CSF markers (all AUCs >0.85), showed high accuracy to discriminate amyloid PET positivity. Subjects with AD had higher CSF BACE-1, ng, and α-syn levels than those with non-AD dementia. CSF t-tau/α-syn ratio was higher in subjects with dementia with Lewy bodies than in those with frontotemporal dementia. Most emerging/core AD ratios predicted a faster conversion from mild cognitive impairment (MCI) stage to AD and appeared to be helpful when core AD CSF markers were discordant. In addition, the rate of cognitive decline was associated with all CSF core AD markers, several emerging/core AD two-marker ratios, and CSF ng levels. These results suggest that emerging biomarkers in conjunction with core AD markers improve diagnosis of AD, are associated with the conversion from MCI into AD, and predict a faster progression of dementia.

Biomarkers of Neurological Outcome After Aneurysmal Subarachnoid Hemorrhage as Early Predictors at Discharge from an Intensive Care Unit

BackgroundSubarachnoid bleeding is associated with brain injuries and ranges from almost negligible to acute and life threatening. The main objectives were to study changes in brain-specific biomarker levels in patients after an aneurysmal subarachnoid hemorrhage (aSAH) in relation to early clinical findings, severity scores, and intensive care unit (ICU) outcome. Analysis was done to identify specific biomarkers as predictors of a bad outcome in the acute treatment phase.MethodsAnalysis was performed for the proteins of neurofilament, neuron-specific enolase (NSE), microtubule-associated protein tau (MAPT), and for the proteins of glial cells, S100B, and glial fibrillary acidic protein (GFAP). Outcomes were assessed at discharge from the ICU and analyzed based on the grade in the Glasgow Outcome Scale (GOS). Patients were classified into two groups: with a good outcome (Group 1: GOS IV–V, n = 24) and with a bad outcome (Group 2: GOS I–III, n = 31). Blood samples were taken upon admission to the ICU and afterward daily for up to 6 days.ResultsIn Group 1, the level of S100B (1.0, 0.9, 0.7, 2.0, 1.0, 0.3 ng/mL) and NSE (1.5, 2.0, 1.6, 1.2, 16.6, 2.2 ng/mL) was significantly lower than in Group 2 (S100B: 4.7, 4.8, 4.4, 4.5, 6.6, 6.8 ng/mL; NSE: 4.0, 4.1, 4.3, 3.8, 4.4, 2.5 1.1 ng/mL) on day 1–6, respectively. MAPT was significantly lower only on the first and second day (83.2 ± 25.1, 132.7 ± 88.1 pg/mL in Group 1 vs. 625.0 ± 250.7, 616.4 ± 391.6 pg/mL in Group 2). GFAP was elevated in both groups from day 1 to 6. In the ROC analysis, S100B showed the highest ability to predict bad ICU outcome of the four biomarkers measured on admission [area under the curve (AUC) 0.81; 95% CI 0.67–0.94, p < 0.001]. NSE and MAPT also had significant predictive value (AUC 0.71; 95% CI 0.54–0.87, p = 0.01; AUC 0.74; 95% CI 0.55–0.92, p = 0.01, respectively). A strong negative correlation between the GOS and S100B and the GOS and NSE was recorded on days 1–5, and between the GOS and MAPT on day 1.ConclusionOur findings provide evidence that brain biomarkers such as S100B, NSE, GFAP, and MAPT increase significantly in patients following aSAH. There is a direct relationship between the neurological outcome in the acute treatment phase and the levels of S100B, NSE, and MAPT. The detection of brain-specific biomarkers in conjunction with clinical data may constitute a valuable diagnostic and prognostic tool in the early phase of aSAH treatment.

Predicting Local Failure after Stereotactic Radiation Therapy in Brain Metastasis using Quantitative CT and Machine Learning.

Despite recent advances in cancer treatment, the prognosis of patients diagnosed with brain metastasis is still poor. The median survival is limited to months even for patients undergoing treatment. Radiation therapy is a main component of treatment for brain metastasis. However, radiotherapy cannot control local progression in up to 20% of the metastatic brain tumours. An early prediction of radiotherapy outcome for individual patients could facilitate therapy adjustments to improve its efficacy. This study investigated the potential of quantitative CT biomarkers in conjunction with machine learning methods to predict local failure after radiotherapy in brain metastasis. Volumetric CT images were acquired for radiation treatment planning from 120 patients undergoing stereotactic radiotherapy. Quantitative features characterizing the morphology and texture were extracted from different regions of each lesion. A feature reduction/selection framework was adapted to define a quantitative CT biomarker of radiotherapy outcome. Different machine learning methods were applied and evaluated to predict the local failure outcome at pre-treatment. The optimum biomarker consisting of two features in conjunction with an AdaBoost with decision tree could predict the local failure outcome with 71% accuracy on an independent test set (20 patients, 31 lesions). This study is a step forward towards prediction of radiotherapy outcome in brain metastasis using quantitative imaging and machine learning.

Review of SWOG S1314: Lessons from a Randomized Phase II Study of Co-Expression Extrapolation (COXEN) with Neoadjuvant Chemotherapy for Localized, Muscle-Invasive Bladder Cancer.

SWOG1314 is a randomized phase II study of co-expression extrapolation (COXEN) with neoadjuvant chemotherapy for localized, muscle-invasive bladder cancer. COXEN is a biomarker approach in which predictive biomarkers are developed using in vitro data, which may then be applied directly into a clinical testing application. Two separate Gene Expression Models (GEMs), one for the Methotrexate, Vinblastine, Doxorubicin, Cisplatin (MVAC) regimen and another for gemcitabine plus cisplatin (GC) were tested in S1314. The lessons learned from the development and operationalization of the S1314 clinical trial are described in detail, which may help to inform the future trials of predictive biomarkers for urothelial carcinoma in the neoadjuvant setting. Specific areas addressed include: The need for broad support from the bladder cancer community, planning for non-evaluable subjects, defining adequate neoadjuvant treatment, defining adequate tissue collection, setting expectations in phase II clinical studies of predictive biomarkers, and maximizing the impact of the samples collected in these studies for broader biomarker development. With a large number of newly available treatments in advanced urothelial carcinoma in the last few years, more investigations of these agents in the neoadjuvant setting is anticipated. There will be a great need for the development of predictive biomarkers in conjunction with the use of these agents in the preoperative setting. Insights from S1314 may provide useful information and lessons learned in this development.

Explorative study of emerging blood biomarkers in progressive multiple sclerosis (EmBioProMS): Design of a prospective observational multicentre pilot study

BackgroundDefining clinical and subclinical progression in multiple sclerosis (MS) is challenging. Patient history, expanded disability status scale (EDSS), and magnetic resonance imaging (MRI) all have shortcomings and may underestimate disease dynamics. Emerging serum biomarkers such as glial fibrillary acidic protein (GFAP) and neurofilament light chain (NfL) proved useful in many cross-sectional studies. However, longitudinal data on patients with progressive MS is scarce. ObjectivesTo assess whether the serum biomarkers GFAP and NfL might differentiate between patients with progressive vs. non-progressive disease stages and predict the disease course according to the Lublin criteria. MethodsEmBioProMS is a pilot, observational, prospective, multicentric study funded by the German Multiple Sclerosis Society (DMSG). 200 patients with MS according to the 2017 McDonald criteria and history of relapse-independent progression at any time (progressive MS, PMS), younger than 65 years, and with EDSS ≤ 6.5 will be recruited in 6 centres in Germany. At baseline, month 6, and 18, medical history, EDSS, Nine-Hole-Peg-Test (9-HPT), Timed-25-Foot-Walk-Test (T-25FW), Symbol-Digit-Modalities-Test (SDMT), serum GFAP, and NfL, MRI (at least baseline and month 18) and optional optical coherence tomography (OCT) will be performed. Disease progression before and during the study is defined by confirmed EDSS progression, increase by ≥ 20% in 9-HPT or T-25FW time. ConclusionsThis longitudinal multicentre study will reveal to what extent the prediction of disease progression in patients with PMS will be improved by the analysis of serum biomarkers in conjunction with routine clinical data and neuroimaging measures.

Identifying Lipid Metabolites Influenced by Oleic Acid Administration Using High-Performance Liquid Chromatography–Mass Spectrometry-Based Lipidomics

Oleic acid (OA), one of the most important monounsaturated fatty acids, possesses protective properties against chronic liver disease (CLD) development, but the underlying metabolic metabolism remains unknown. HPLC–MS-based lipidomics was utilized to identify and quantify the endogenously altered lipid metabolites when hepatocytes were exposed to OA administration. The identified lipids could be grouped into 22 lipid classes; of which, 10 classes were significantly influenced by the OA treatment: lysophosphatidylcholine (LPC), phosphatidylglycerol (PG), ceramides (Cer), hexosylceramides (Hex1Cer), dihexosylceramides (Hex2Cer), cholesterol ester (ChE), and coenzyme (Co) were decreased, while diglyceride (DG), triglyceride (TG), and acyl carnitine (AcCa) were increased. In addition, as the variable importance in projection (VIP) list (VIP > 1.0 and P < 0.05) showed, 478 lipid species showed significant difference with OA administration, and these molecules could be potential biomarkers in conjunction with OA administration. In summary, our results provided a novel perspective to understand the influences of OA administration by investigating endogenous altered levels of lipid metabolites via lipidomics.

Evaluation of Cardiac Biomarkers in Dengue Myocarditis in a Tertiary Care Hospital in Eastern India

Introduction: Dengue, a vector borne viral infection transmitted by Aedes mosquito has recently become a major public health concern in the tropical regions of the world. In addition to the two major life threatening complications- Dengue Haemorrhagic Fever (DHF) and Dengue Shock Syndrome (DSS), a variety of cardiac complications have been recognised, the most common being myocarditis. Aim: To study and compare the quantity of different cardiac biomarkers in patients of Dengue Fever with and without myocarditis. Materials and Methods: This was a hospital-based retrospective observational study done in a Tertiary Care Hospital, Kolkata, West Bengal, India from June 2019 to November 2019. Dengue patients with diagnosed myocarditis on day 7 of fever based on electro and echocardiogram changes of left ventricular ejection fraction less than 50% were considered as cases (n=41). Age and sex matched dengue patients with normal electro and echocardiogram changes were considered as control (n=43). After obtaining Institutional Ethics Committee Clearance, laboratory data were collected from samples coded and assayed for markers of acute cardiac myocyte damage such as total Creatine Kinase (CK), CK-Muscle Brain (CK-MB), Troponin T (Trop T) and cardiac failure biomarker N-Terminal pro Brain Natriuretic Peptide (NT-proBNP). Statistical analysis of the data was performed using Statistical Package for Social Sciences (SPSS 20). Results: Cardiac biomarkers CK, CK-MB, Trop T and NT-proBNP levels in cases were higher compared to controls (p-value &lt;0.05). Trop T and NT-proBNP were positively correlated to each other (r-value: 0.44). Trop T changes could also predict significantly the rise in NT-proBNP in circulation (p&lt;0.05). Conclusion: It reconfirmed the need of routine monitoring of cardiac biomarkers in conjunction with other cardiac function tests in early diagnosis and or management of myocarditis, a severe complication of Dengue Viral Infection (DENV).

Role of NT-proBNP in the prediction of moderate to severe Bronchopulmonary Dysplasia in preterm infants.

The objective of the study was to determine the clinical utility of brain natriuretic peptide (NT-proBNP) for prediction of moderate to severe bronchopulmonary dysplasia (BPD). We hypothesized that elevated NT-proBNP levels at 4 weeks of postnatal age may predict the severity of BPD in preterm infants. The study design was a prospective observational study. The research team enrolled and followed a cohort of 70 infants with gestational age less than or equal to 30 weeks. The plasma NT-proBNP levels were measured at the postnatal day 28th. We further followed and categorized infants into two groups. Infants with no or mild BPD (Group 1) and infants with moderate or severe BPD (Group 2). We compared plasma NT-proBNP levels at 28th day of postnatal life between Groups 1 and 2. The difference in NT-proBNP levels on day 28th between groups was used to predict the severity of BPD. Plasma NT-proBNP was significantly elevated in Group 2 compared with Group 1, median (IQR) of 845 pg/mL (553, 1632) compared with 726 pg/mL (391, 923), P = 0.02. NT-proBNP had a fair predictive accuracy (C statistics of 0.68) to determine moderate to severe BPD. NT-proBNP may be a useful biomarker in conjunction with clinical factors as a predictor of severe BPD. For future directions, the trend of NT-proBNP in infants with BPD may have clinical significance in monitoring of the disease.

TGx-DDI, a Transcriptomic Biomarker for Genotoxicity Hazard Assessment of Pharmaceuticals and Environmental Chemicals.

Genotoxicity testing is an essential component of the safety assessment paradigm required by regulatory agencies world-wide for analysis of drug candidates, and environmental and industrial chemicals. Current genotoxicity testing batteries feature a high incidence of irrelevant positive findings—particularly for in vitro chromosomal damage (CD) assays. The risk management of compounds with positive in vitro findings is a major challenge and requires complex, time consuming, and costly follow-up strategies including animal testing. Thus, regulators are urgently in need of new testing approaches to meet legislated mandates. Using machine learning, we identified a set of transcripts that responds predictably to DNA-damage in human cells that we refer to as the TGx-DDI biomarker, which was originally referred to as TGx-28.65. We proposed to use this biomarker in conjunction with current genotoxicity testing batteries to differentiate compounds with irrelevant “false” positive findings in the in vitro CD assays from true DNA damaging agents (i.e., for de-risking agents that are clastogenic in vitro but not in vivo). We validated the performance of the TGx-DDI biomarker to identify true DNA damaging agents, assessed intra- and inter- laboratory reproducibility, and cross-platform performance. Recently, to augment the application of this biomarker, we developed a high-throughput cell-based genotoxicity testing system using the NanoString nCounter® technology. Here, we review the status of TGx-DDI development, its integration in the genotoxicity testing paradigm, and progress to date in its qualification at the US Food and Drug Administration (FDA) as a drug development tool. If successfully validated and implemented, the TGx-DDI biomarker assay is expected to significantly augment the current strategy for the assessment of genotoxic hazards for drugs and chemicals.

Abstract 2583: DNA-linked gold nanoprobe assay: An efficient technology for direct and high-sensitive quantification of serum microRNAs in prostate cancer

Abstract Background: Serum-based biomarkers in conjunction with advanced biosensing techniques for early detection or screening of indolent vs. aggressive prostate cancer (PCa) can improve patient care and outcmomes. Recent discoveries have identified miRNAs (miRs) as promising biomarkers and opened potential avenues for earliest diagnosis and examining aggressiveness of PCa. However, quantitation of ultra-low levels of miRs in sera or tissue of patient remains challenging with traditional techniques. The present study describes the development and application of the DNA-linked gold nanoprobe (DNA-AuNPr)-based fluorescence assay for quantification of target miRs in serum with high sensitivity. Methodology: Thorough meta-analysis followed by global in-silico analyses were performed to evaluate the differential expression of miRs among PCa studies. Further, the identified miRs were validated using TaqMan assay in human and mouse PCa serum. Thereafter, we synthesized DNA-AuNPr specific to target miRs, by conjugating FAM-tagged DNA-probes to the PEG-coated gold nanoparticle (AuNP) via cross-linker chemistry and fully characterized with UV, DLS and TEM. Sensitivity and target specificity of nanoprobe-based assay were determined using the Synergy-H1 multimode reader. As a proof of principle, a real-time evolution of fluorescence signal upon enzymatic digestion of DNA-probe in DNA-RNA heteroduplexes was tested. Finally, we utilized human (PCa n=44, control n=43) and Pten conditional knockout mouse (PCa n=8, control n=8) sera for our training and blank validation sets to determine the diagnostic significance of miRs in PCa. Results: TaqMan assays detected a significantly higher level of both miR-21 and miR-375 in the PCa compared to normal control. Analyses of DNA-AuNPr shown uniform-sized, highly stable AuNP core tagged with multiple target-specific DNA-probes (~150±21 per NP). Additional assay validation indicated an excellent sequence specificity of DNA-AuNPr in discriminating the single-base mutation (mismatch) in miRs sequence. The uniqueness of proposed assay was its capability to quantitate miR targets in the range 50 pM to 10 nM with a lower detection limit of ~5 pM (0.3 fmol) in just ~4 h of total assay time and using ~10 μL of total RNA isolated from serum. Finally, the assay performance was validated in serum for both miR-21 and miR-375. The two miRs efficiently differentiated PCa from the healthy control in training sets (AUC=0.94) as well as in independent validation sets (AUC=0.90), which reconfirmed their diagnostic potential. Conclusion: We developed a direct (without converting target miR into cDNA), highly sensitive and technologically efficient miR-quantitation strategy for diagnosis of PCa. Citation Format: Prakash Kshirsagar, Satyanarayana Rachagani, Parthasarathy Seshacharyulu, Sakthivel Muniyan, Sunandini Sharma, Ram Mahato, Surinder K. Batra, Maneesh Jain. DNA-linked gold nanoprobe assay: An efficient technology for direct and high-sensitive quantification of serum microRNAs in prostate cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 2583.

Identification of key transcription factors in endometrial cancer by systems bioinformatics analysis.

Endometrial cancer (EC) is one of the most common malignant diseases worldwide. Although many studies have been performed on EC, a systems analysis between transcription factors (TFs) and EC relationship remains poorly characterized. Here, we present a systems bioinformatics analysis of TFs in EC patient samples to identify key TFs in EC. First, dysregulated and survival-related TFs were identified in EC using data from The Cancer Genome Atlas database and Gene Expression Omnibus. Second, we investigated the mechanisms of dysregulated TFs and tested whether their expression is correlated with prognosis of EC. Finally, we addressed new perspectives in EC biomarker research, including comprehensive knowledge of previously suggested candidate biomarkers in conjunction with novel mass spectrometry-based proteomic technologies with enhanced sensitivity and specificity not yet applied to EC studies, enabling a directed clinical perspective of the study design. Our study identified three promising TFs, E2F1, HMGA1, and PGR, which closely correlate with EC. Although treatments targeting TFs are not always efficient, these TFs may be useful as biomarkers for the diagnosis and prognosis of EC. Furthermore, we found that these dysregulated TFs and their target genes are primarily involved in the cell cycle and may promote endometrial carcinoma occurrence and development. Using integrated bioinformatic analysis, we identified candidate genes and pathways in EC, which could improve our understanding of the etiology and underlying molecular events of EC. Furthermore, these candidate genes and pathways could be therapeutic targets for EC.

Impact of High-Molecular-Risk Mutations on Transplantation Outcomes in Patients with Myelofibrosis

Mutational profiling has demonstrated utility in predicting the likelihood of disease progression in patients with myelofibrosis (MF). However, there is limited data regarding the prognostic utility of genetic profiling in MF patients undergoing allogeneic hematopoietic stem cell transplantation (allo-HCT). We performed high-throughput sequencing of 585 genes on pre-transplant samples from 101 patients with MF who underwent allo-HCT and evaluated the association of mutations and clinical variables with transplantation outcomes. Overall survival (OS) at 5 years post-transplantation was 52%, and relapse-free survival (RFS) was 51.1 % for this cohort. Nonrelapse mortality (NRM) accounted for most deaths. Patient's age, donor's age, donor type, and Dynamic International Prognostic Scoring System score at diagnosis did not predict for outcomes. Mutations known to be associated with increased risk of disease progression, such as ASXL1, SRSF2, IDH1/2, EZH2, and TP53, did not impact OS or RFS. The presence of U2AF1 (P = .007) or DNMT3A (P = .034) mutations was associated with worse OS. A Mutation-Enhanced International Prognostic Scoring System 70 score was available for 80 patients (79%), and there were no differences in outcomes between patients with high risk scores and those with intermediate and low risk scores. Collectively, these data identify mutational predictors of outcome in MF patients undergoing allo-HCT. These genetic biomarkers in conjunction with clinical variables may have important utility in guiding transplantation decision making.

Biomarkers of Pineal Region Tumors: A Review.

Background: The pineal gland, a small, pinecone-shaped organ deep within the brain, is responsible for producing melatonin. The gland consists of pineal parenchymal cells and glial cells that can form neoplasms. Pineal region neoplasms can also arise from germ cells and adjacent structures. This review focuses on detection of serum and cerebrospinal fluid (CSF) biomarkers of germ cell tumors and pineal parenchymal cell tumors, as these types comprise most neoplasms specific to the pineal region. Methods: For this review, we searched PubMed using the following keywords: biomarkers, germ cell tumor, germinoma, melatonin, pineal, pineal gland, pineal neoplasm, pinealoma, pineal parenchymal cell tumor, pineal region, and pineal tumor. We limited our search to full-text English articles and identified other relevant sources from the reference lists of identified articles. Results: Serum and CSF biomarker assays have a role in cases of suspected pineal germ cell or parenchymal neoplasms. Biomarkers including alpha-fetoprotein, beta-human chorionic gonadotropin, and placental alkaline phosphatase inform diagnosis and treatment and are important for monitoring germ cell tumor response to treatment. No biomarkers are currently available that inform diagnosis or treatment of pineal parenchymal tumors, although melatonin assays may have a role in monitoring response to treatment. Conclusion: Serum and CSF biomarkers in conjunction with clinical and radiographic evidence of a pineal region mass can inform the decision whether to undertake stereotactic biopsy or surgical excision or whether to proceed straight to medical treatment.

Correlation of securin and Ki67 in invasive breast carcinoma.

To identify the role of securin (PTTG) as a prognostic marker in invasive breast carcinoma and its possible relation to ki67 and to evaluate the use of ImmunoRatio® as a tool for calculating ki67 and securin labelling indices. Securin and ki67 immunohistochemical staining were performed on tissue microarray sections representative of 118 patients diagnosed with invasive breast carcinoma from 2005 to 2011. Assessment of immunohistochemical staining was carried out using both visual counting and ImmunoRatio®. The 118 cases were categorized into 2 groups according to their clinical outcome; the first group (G1) (n=77) comprised patients who were disease-free while the second group (G2) (n=41) included patients who developed either recurrence and/or metastasis at the end of 24 months follow-up duration. Both securin and ki67 labelling indices (LIs) obtained by visual counting were significantly higher in G2, while only securin LIs acquired by ImmunoRatio® were significantly higher in G2. Securin assessment by visual counting was the most accurate (AUC=0.775) in identifying patients who will likely suffer from recurrence and/or distant metastasis. Pearson correlation showed r=0.638, p<0.001 for Ki67 and r=0.671, p<0.001 for securin. Linear regression analysis showed a significant correlation between ki67 and securin, B=1.75, p<0.001. The present results suggest that securin may add to the prognostic value of ki67 in highlighting intra-tumoural heterogeneity in invasive breast carcinoma patients with poor clinical outcome. In addition, the study showed that since securin has a visual counting cutoff with more than 1%, making it easier to use as a breast cancer biomarker in conjunction with ki67 to predict the outcome of the cases more accurately than using only ki67. However, a multivariate analysis on a larger cohort of patients is mandatory to test its potential prognostic value.

Detection of Matrix Metallopeptidase 13 for Monitoring Stem Cell Differentiation and Early Diagnosis of Osteoarthritis by Fluorescent Light‐Up Probes with Aggregation‐Induced Emission Characteristics

AbstractOsteoarthritis (OA) is the leading cause of chronic disability affecting the elderly. There is an acute demand for novel approaches to sensitively and specifically detect OA biomarkers in conjunction with traditional radiographic outcomes to facilitate early diagnosis and allow timely treatment. In this study, a novel strategy is introduced to detect the activity of matrix metallopeptidase 13 (MMP‐13)—a key enzyme responsible for cartilage matrix degradation in OA with a synthesized molecular probe containing a hydrophilic MMP‐13‐sensitive peptide conjugated to an aggregation induced emission fluorogen (AIEgen). The MMP‐13 cleaves the MMP‐13 sensitive peptide and induces aggregation of the hydrophogic AIEgen residues resulting in the activation of a fluorescent signal. The results demonstrate that this probe can detect increasing MMP‐13 activity, which is an important marker of osteogenic differentiation in living and differentiating stem cells. This allows easy and semi‐quantitative assessment of the extent of stem cell differentiation. Furthermore, by administering this probe to diseased joints of rats with induced OA, the real‐time detection of MMP‐13 activity is demonstrated in the osteoarthritic knee joints of living animals. It is believed that the molecular probe is a promising tool for real‐time detection of disease markers with high fluorescence contrast to aid the early diagnosis of OA.

Abstract A30: PELP1 and AIB1 cooperate to promote breast cancer progression in ER+ breast cancer models

Abstract Luminal breast cancers account for ~75% of newly diagnosed cases and express estrogen receptor (ER) and a range of progesterone receptor (PR)-positive cells. Although adjuvant hormone therapies that target ER actions (e.g., tamoxifen or aromatase inhibitors) have improved overall patient survival, up to ~40% of luminal breast tumors eventually progress to ER+, but endocrine-resistant disease. Therefore, there is a critical need to delineate the processes driving ER+ breast cancer progression and identify new biomarkers that can be targeted in combination with ER-targeted therapies. An emerging biomarker of increased breast cancer risk and aggressive tumor behavior is oncogenic PELP1 (i.e., partially localized to the cytoplasm; cyto PELP1). PELP1 is typically located in the nucleus in normal breast tissue; however, partial to complete localization of PELP1 to the cytoplasm has been observed in up to 50% of PELP1+ breast tumors. Although a number of studies have implicated oncogenic PELP1 in luminal breast cancer biology, the mechanisms underlying oncogenic PELP1 actions in cancer remain poorly defined. To elucidate the impact of oncogenic PELP1 on steroid hormone receptor (SR) signaling pathways and transcription programs, we generated SR+ breast cancer cell models expressing vector control, wild-type (nuclear) PELP1, and oncogenic (cyto) PELP1. Herein, we identified AIB1 (amplified in breast cancer 1; ER coactivator) as a preferential binding partner of oncogenic PELP1. In particular, our data demonstrate that oncogenic PELP1 overexpression increases activation (i.e., phosphorylation) of AIB1, enhances tumorsphere formation in SR+ breast cancer models, and upregulates specific target genes identified through RNA-Seq analysis that are related to cell survival, breast cancer progression, and stem/progenitor formation independent of hormone stimulation. Knockdown of AIB1 inhibits oncogenic PELP1-induced tumorsphere formation and downregulates oncogenic PELP1 target genes. Moreover, knockdown of PELP1 in AIB1-mouse derived tumor cells results in decreased tumor growth in vivo. To our knowledge, our findings are the first to directly link oncogenic PELP1-induced phenotypes to AIB1 in breast cancer. Our studies suggest that directly targeting PELP1 may halt tumor progression, particularly in the context of AIB1-mediated tumorigenesis. Taken together, our data highlight the oncogenic PELP1/AIB1 interaction as an important hormone-independent mechanism of increased breast tumor cell survival and altered cell fate, and as an important mediator of disease progression. In sum, we conclude that oncogenic PELP1 and AIB1 could be used as biomarkers in conjunction with each other to identify breast cancer patients likely to respond to therapeutic strategies designed to selectively target PELP1, AIB1, or the oncogenic PELP1/AIB1 signaling and transcriptional complex. Citation Format: Thu H. Truong, Hsiangyu Hu, Julie H. Ostrander, Carol A. Lange. PELP1 and AIB1 cooperate to promote breast cancer progression in ER+ breast cancer models [abstract]. In: Proceedings of the AACR Special Conference: Advances in Breast Cancer Research; 2017 Oct 7-10; Hollywood, CA. Philadelphia (PA): AACR; Mol Cancer Res 2018;16(8_Suppl):Abstract nr A30.

Pro-apoptotic and Inflammatory Markers Enhance the Ability of MDA-LDL in Circulating Immune Complex to Predict Acute Myocardial Infarction in the VADT Study

There is considerable interest in identifying biomarkers indicative of plaque instability and acute events. Previously we reported that MDA-LDL in circulating immune complex predicted acute myocardial infarction (MI) in the VADT study. Interleukin (IL)-6, Fas Ligand, tissue inhibitor of MMP (TIMP)-1 and monocyte chemotactic protein (MCP)-1 have been identified as potentially clinically relevant biomarkers related to plaque instability. Therefore, our objective was to examine the role of these biomarkers in conjunction with MDA-LDL in circulating immune complex as predictors of acute MI in type 2 diabetes. Biomarker levels were measured in 833 VADT patients, a median of 2.0 years after study entry and participants were subsequently followed a median of 3.7 years. Biomarkers were examined individually and as composite scores created by summing z scores across biomarkers. Hazard ratios (HRs) for acute MI were calculated by Cox proportional hazard models. During follow-up, 5.2% had an MI. After adjustment for conventional risk factors, results of composite biomarkers scores were promising with a hazard ratio for acute MI of 4.65 (95% CI: 1.56, 13.9) comparing the fourth to first quartile of our summary composite score which included MDA-LDL-IC, IL-6, Fas Ligand,TIMP-1 and MCP-1 (Table). Disclosure M.F.L. Lopes-Virella: None. K.J. Hunt: None. R. Agarwal: None. N.L. Baker: Research Support; Self; Bristol-Myers Squibb Company. G. Virella: None.

The A/T/N biomarker scheme and patterns of brain atrophy assessed in mild cognitive impairment

The objective of this study was to evaluate the A/T/N biomarker scheme in relation with brain atrophy patterns in individuals with mild cognitive impairment (MCI). Of the 154 participants with MCI, 74 progressed to AD within 36-months, and 80 remained stable. In addition, 101 cognitively healthy participants and 102 participants with AD were included. The A/T/N classification was assessed with cerebrospinal fluid markers. Each individual was rated as either positive (abnormal) or negative (normal) on each biomarker. Brain atrophy was assessed with visual ratings from magnetic resonance imaging. None of the individuals with MCI progressed to AD if they had a negative “A” biomarker in conjunction with minimal atrophy. In contrary, several individuals with MCI progressed to AD if they had a positive “A” biomarker in conjunction with minimal atrophy. Numerous individuals with MCI showed inconsistency in the neurodegeneration domain (“N”) regarding t-tau and atrophy. The assessment of the A/T/N classification scheme in addition with brain atrophy patterns in MCI, increases the knowledge of the clinical trajectories and the variability within the neurodegeneration domain. This emphasises that individuals with MCI display heterogeneous longitudinal patterns closely connected to their biomarker profiles, which could have important clinical implications.

Abstract LB-331: Advanced DNA-gold nanoprobe-based direct and sensitive quantification of novel microRNAs in prostate cancer

Abstract Background: There is an urgent need for a novel, non-invasive and serum-based biomarker in conjunction with a highly sensitive technique to differentiate indolent vs. aggressive prostate cancer (PCa). Emerging evidence suggests that several micro RNAs (miRs) are differentially expressed in tumor tissue and sera of PCa patients and can potentially serve as biomarkers for disease progression and aggressiveness. However, quantification of ultra-low levels of serum miRNAs remains difficult with conventional quantification methods. Hence, the present study was aimed at developing, optimizing and testing a novel fluorescence-based DNA-gold nanoprobe (DNA-AuNPr) ‘OFF-to-ON’ assay for direct, highly sensitive and precise quantification of miRNAs in serum samples. Methodology: To identify miRs associated with disease progression, TaqMan assays were performed to analyze the differential expression of miRs in PCa tissues excised from PTEN conditional knockout mice and in human PCa patient serum samples along with their respective controls. We synthesized a DNA-AuNPr specific to miR-21 by conjugating FAM-tagged probe DNA on PEGylated Au nanoparticles (AuNPs). The nanoprobe was characterized using UV, DLS, TEM, zeta potential, ICP-MS and gel electrophoretic analyses. Sensitivity and specificity of the nanoprobe were determined using Biotek Synergy H1 multimode reader. As a proof-of-concept, a kinetic evolution of fluorescence via DSN-catalyzed digestion of probe DNA in heteroduplexes was tested in the PCa serum/tissue samples. Results: TaqMan assays revealed significant upregulation of miR-21 in both mouse PCa tissue and human PCa patient serum samples. Detailed analyses of DNA-AuNPr displayed uniform spherical shape, 40 nm core size (ϕ), ζ-potential −35±3 mV, and 150±21 coupled probe DNAs/AuNP. Efficient quenching of tagged-fluorophore and clearly reduced electrophoretic mobility of DNA−AuNPr compare to bare AuNP validated successful conjugation. Our initial analyses determined 75 pM of probe DNA (≈11 nM AuNPs) as optimal concentrations for miRNA quantification. Our real-time fluorescence assay allowed absolute quantification of as little as 5 pM of synthetic (syn) miR-21 with a very good linear response curve (R2 = 0.99) of fold change vs. syn-miR-21 concentrations. Assay results also demonstrated excellent sequence specificity that was verified using seed region mutated syn-miR-21 as well as miR-1 mimic, resulting in the abolishment of fluorescence compare to miR-21. Finally, DSN-mediated kinetic release of FAM gave significantly higher signal output from PCa patient samples compared to normal controls. Conclusion: Our efforts successfully established a DNA-AuNPr-based kinetic assay for direct (without converting miR to cDNA), highly sensitive, and specific quantification of miRs in PCa patient samples. Citation Format: Prakash Kshirsagar, Satyanarayana Rachagani, Parthasarathy Seshacharyulu, Sakthivel Muniyan, Ram Mahato, Surinder K. Batra, Maneesh Jain. Advanced DNA-gold nanoprobe-based direct and sensitive quantification of novel microRNAs in prostate cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr LB-331. doi:10.1158/1538-7445.AM2017-LB-331