Blood-based Biomarker Panel Research Articles

Glial fibrillary acidic protein elevations relate to neuroimaging abnormalities after mild TBI.

To determine whether a panel of blood-based biomarkers can discriminate between patients with suspected mild traumatic brain injury (mTBI) with and without neuroimaging findings (CT and MRI). Study participants presented to the emergency department with suspected mTBI (n = 277) with a CT and MRI scan and healthy controls (n = 49). Plasma concentrations of tau, glial fibrillary acidic protein (GFAP), ubiquitin carboxyl-terminal hydrolase L1, and neurofilament light chain (NFL) were measured using the single-molecule array technology. Concentrations of GFAP, tau, and NFL were higher in patients with mTBI, compared with those of controls (p's < 0.01). GFAP yielded an area under the curve (AUC) of 0.93 (95% confidence interval [CI] 0.90-0.96), confirming its discriminatory power for distinguishing mTBI from controls. Levels of GFAP, tau, and NFL were higher in patients with trauma-related intracranial findings on CT compared with those with normal CT, with the only significant predictor being GFAP (AUC 0.77, 95% CI 0.70-0.84). Among patients with mTBI, tau, NFL, and GFAP differentiated subjects with and without MRI abnormalities with an AUC of 0.83, with GFAP being the strongest predictor. Combining tau, NFL, and GFAP showed a good discriminatory power (AUC 0.80, 95% CI 0.69-0.90) for detecting MRI abnormalities, even in patients with mTBI with a normal CT. Our study confirms GFAP as a promising marker of brain injury in patients with acute mTBI. A combination of various biomarkers linked to different pathophysiologic mechanisms increases diagnostic subgroup accuracy. This multimarker strategy may guide medical decision making, facilitate the use of MRI scanning, and prove valuable in the stratification of patients with brain injuries in future clinical trials. Class I evidence that blood concentrations of GFAP, tau, and NFL discriminate patients with mTBI with and without neuroimaging findings.

Prostate Cancer Diagnostics Using a Combination of the Stockholm3 Blood Test and Multiparametric Magnetic Resonance Imaging

BackgroundMore specific diagnostic for prostate cancer is needed to decrease overdetection and number of diagnostic procedures. ObjectiveTo assess the performance of combining a blood-based biomarker panel and magnetic resonance imaging (MRI)-targeted biopsies for prostate cancer detection. Design, setting, and participantsWe used a prospective, multicenter, paired diagnostic study design. A total of 532 men aged 45–74 yr referred for prostate cancer workup were included during 2016–2017. InterventionParticipants underwent blood sampling for analysis of the Stockholm3 test including protein biomarkers, genetic polymorphisms, and clinical variables; 1.5 T MRI; systematic prostate biopsies; and MRI-targeted biopsies to lesions with Prostate Imaging Reporting and Data System version 2 ≥3. Outcome measurements and statistical analysisThe main outcome was numbers of detected prostate cancer characterized by grade group (GG) and the number of performed biopsies using relative sensitivity (RS). Results and limitationsMedian prostate-specific antigen was 6.3 ng/ml, and mean age was 63.9 yr. Targeted and systematic biopsies detected 170 and 162 GG ≥2 tumors, respectively (RS 1.05; 95% confidence interval [CI] 0.96–1.14). Compared with performing systematic biopsies on all men, performing targeted and systematic biopsies only on men with >10% risk of GG ≥2 cancer, as predicted by the Stockholm3 test, required 62% (95% CI 58–66) of the biopsy procedures and detected 58% (95% CI 48–70) of GG 1 disease, with increased sensitivity for GG ≥2 detection (RS 1.10; 95% CI 1.02–1.17). Performing only targeted biopsies in men with elevated Stockholm3 test altered these results only slightly. Compared with performing systematic and targeted biopsies on all men, performing this only for men with an elevated Stockholm3 test decreased detection of GG ≥2 cancer slightly (RS 0.92; 95% CI 0.88–0.95). Limitations include lacking knowledge of true disease prevalence. ConclusionsThese findings provide evidence that strategies combining the blood-based Stockholm3 test and MRI-targeted biopsies can be used to inform biopsy decision making. Patient summaryIn this study, 532 men coming for prostate cancer workup underwent blood sampling, and both traditional and magnetic resonance imaging/fusion-guided prostate biopsies. We report that performing targeted biopsies only in men with an elevated risk as assessed by the Stockholm3 test saved biopsies, decreased overdetection, and maintained the number of detected high-grade cancers.

MiRNA Profiling of Magnetic Nanopore-Isolated Extracellular Vesicles for the Diagnosis of Pancreatic Cancer.

Improved diagnostics for pancreatic ductal adenocarcinoma (PDAC) to detect the disease at earlier, curative stages and to guide treatments is crucial to progress against this disease. The development of a liquid biopsy for PDAC has proven challenging due to the sparsity and variable phenotypic expression of circulating biomarkers. Here we report methods we developed for isolating specific subsets of extracellular vesicles (EV) from plasma using a novel magnetic nanopore capture technique. In addition, we present a workflow for identifying EV miRNA biomarkers using RNA sequencing and machine-learning algorithms, which we used in combination to classify distinct cancer states. Applying this approach to a mouse model of PDAC, we identified a biomarker panel of 11 EV miRNAs that could distinguish mice with PDAC from either healthy mice or those with precancerous lesions in a training set of n = 27 mice and a user-blinded validation set of n = 57 mice (88% accuracy in a three-way classification). These results provide strong proof-of-concept support for the feasibility of using EV miRNA profiling and machine learning for liquid biopsy.Significance: These findings present a panel of extracellular vesicle miRNA blood-based biomarkers that can detect pancreatic cancer at a precancerous stage in a transgenic mouse model. Cancer Res; 78(13); 3688-97. ©2018 AACR.

Identification of Optimum Panel of Blood-based Biomarkers for Alzheimer's Disease Diagnosis Using Machine Learning.

With the increasing number of people living with Alzheimer's disease (AD), there is a need for low-cost and easy to use methods to detect AD early to facilitate access to appropriate care pathways. Neuroimaging biomarkers (such as those based on PET and MRI) and biochemical biomarkers (such as those based on CSF) are recommended by international guidelines to facilitate diagnosis. However, neuroimaging is expensive and may not be widely available and CSF testing is invasive. Bloodbased biomarkers offer the potential for the development of a low-cost and more time efficient tool to detect AD to complement CSF and neuroimaging as blood is much easier to obtain. Although no single blood biomarker is yet able to detect AD, combinations of biomarkers (also called panels) have shown good results. However, a large number of biomarkers are often needed to achieve a satisfactory detection performance. In addition, it is difficult to reproduce reported results within and across different study cohorts because of data overfitting and lack of access to the datasets used in the studies. In this study, our focus is to identify an optimum panel (in terms of the least number of blood biomarkers to meet the specified diagnostic performance of 80% sensitivity and specificity) based on a widely accessible data set, and to demonstrate a testing methodology that reinforces reproducibility of results. Realizing a panel with reduced number of markers will have significant impact on the complexity and cost of diagnosis and potential development of cost-effective point of care devices.

Clinical Validation of a Protein Biomarker Panel for Non-Small Cell Lung Cancer.

We validated the diagnostic performance of a previously developed blood-based 7-protein biomarker panel, AptoDetect™-Lung (Aptamer Sciences Inc., Pohang, Korea) using modified aptamer-based proteomic technology for lung cancer detection. Non-small cell lung cancer (NSCLC), 200 patients and benign nodule controls, 200 participants were enrolled. In a high-risk population corresponding to ≥ 55 years of age and ≥ 30 pack-years, the diagnostic performance was improved, showing 73.3% sensitivity and 90.5% specificity with an area under the curve of 0.88. AptoDetect™-Lung (Aptamer Sciences Inc.) offers the best validated performance to discriminate NSCLC from benign nodule controls in a high-risk population and could play a complementary role in lung cancer screening.

Novel Blood-based Transcriptional Biomarker Panels Predict the Late-Phase Asthmatic Response.

The allergen inhalation challenge is used in clinical trials to test the efficacy of new treatments in attenuating the late-phase asthmatic response (LAR) and associated airway inflammation in subjects with allergic asthma. However, not all subjects with allergic asthma develop the LAR after allergen inhalation. Blood-based transcriptional biomarkers that can identify such individuals may help in subject recruitment for clinical trials as well as provide novel molecular insights. To identify blood-based transcriptional biomarker panels that can predict an individual's response to allergen inhalation challenge. We applied RNA sequencing to total RNA from whole blood (n = 36) collected before and after allergen challenge and generated both genome-guided and de novo datasets: genes, gene-isoforms (University of California, Santa Cruz, UCSC Genome Browser), Ensembl, and Trinity. Candidate biomarker panels were validated using the NanoString platform in an independent cohort of 33 subjects. The Trinity biomarker panel consisting of known and novel biomarker transcripts had an area under the receiver operating characteristic curve of greater than 0.70 in both the discovery and validation cohorts. The Trinity biomarker panel was useful in predicting the response of subjects that elicited different responses (accuracy between 0.65 and 0.71) and subjects that elicit a dual response (accuracy between 0.70 and 0.75) upon repeated allergen inhalation challenges. Interestingly, the biomarker panel containing novel transcripts successfully validated compared with panels with known, well-characterized genes. These biomarker-blood tests may be used to identify subjects with asthma who develop the LAR, and may also represent members of novel molecular mechanisms that can be targeted for therapy.

A blood-based biomarker panel indicates IL-10 and IL-12/23p40 are jointly associated as predictors of \u03b2-amyloid load in an AD cohort

Alzheimer’s Disease (AD) is the most common form of dementia, characterised by extracellular amyloid deposition as plaques and intracellular neurofibrillary tangles of tau protein. As no current clinical test can diagnose individuals at risk of developing AD, the aim of this project is to evaluate a blood-based biomarker panel to identify individuals who carry this risk. We analysed the levels of 22 biomarkers in clinically classified healthy controls (HC), mild cognitive impairment (MCI) and Alzheimer’s participants from the well characterised Australian Imaging, Biomarker and Lifestyle (AIBL) study of aging. High levels of IL-10 and IL-12/23p40 were significantly associated with amyloid deposition in HC, suggesting that these two biomarkers might be used to detect at risk individuals. Additionally, other biomarkers (Eotaxin-3, Leptin, PYY) exhibited altered levels in AD participants possessing the APOE ε4 allele. This suggests that the physiology of some potential biomarkers may be altered in AD due to the APOE ε4 allele, a major risk factor for AD. Taken together, these data highlight several potential biomarkers that can be used in a blood-based panel to allow earlier identification of individuals at risk of developing AD and/or early stage AD for which current therapies may be more beneficial.

Prognostic prediction of pemetrexed-platinum chemotherapeutic regimen for NSCLC by serum metabolomics.

e20603 Background: Pemetrexed-platinum chemotherapeutic doublet has become a standard schedule as the first-line treatment for advanced non-squamous NSCLC due to its promising efficacy and a favorable toxicity profile. However, chemotherapy resistance inevitably limits the therapeutic effect of this preferred chemotherapeutic regimen, especially for these intrinsically resistant patients. Development of predictive biomarkers to identify those patients who can benefit from this pemetrexed-based regimen has great significance for personalized chemotherapy. Methods: Total 354 patients who were diagnosed with inoperable stage IIIB or IV lung adenocarcinoma (LADC), assigned to receive pemetrexed-platinum doublet chemotherapy as the first-line treatment were enrolled into this prospective study, including 251 cases diagnosed ahead as training set for predictive model establishment and the subsequently diagnosed 103 cases into validation set. Ultraperformance liquid chromatography coupled to mass spectrometry (UPLC-MS) analytical platform were applied to perform the metabolic profiling studies of pre-treatment serum samples. Results: In the training set, eight potential biomarkers, comprising of hypotaurine, taurine, choline, betaine, dimethylglycine, uridine, dodecanoylcarnitine and L-palmitoylcarnitine, were discovered to be differentially expressed between the patients in disease progressive group (PD, n = 53) and disease control group (including CR, PR and SD, n = 198). In the validation set (PD vs non-PD: 23 vs 80), targeted quantitative analysis of these metabolic biomarkers revealed similar levels as that observed in the training set. Logistic regression model was accordingly established based on this eight-metabolic biomarker panel, to discriminate patients who might benefit from this chemotherapy regimen with over 90% accuracy. Conclusions: This prospective study identified blood-based biomarker panel by metabonomics analysis could predict the clinical outcome of pemetrexed-platinum chemotherapy prior to treatment for LADC patients, which needed to be validated by clinical trials of large samples.

A blood-based biomarker panel to risk-stratify mild traumatic brain injury.

Mild traumatic brain injury (TBI) accounts for the vast majority of the nearly two million brain injuries suffered in the United States each year. Mild TBI is commonly classified as complicated (radiographic evidence of intracranial injury) or uncomplicated (radiographically negative). Such a distinction is important because it helps to determine the need for further neuroimaging, potential admission, or neurosurgical intervention. Unfortunately, imaging modalities such as computed tomography (CT) and magnetic resonance imaging (MRI) are costly and not without some risk. The purpose of this study was to screen 87 serum biomarkers to identify a select panel of biomarkers that would predict the presence of intracranial injury as determined by initial brain CT. Serum was collected from 110 patients who sustained a mild TBI within 24 hours of blood draw. Two models were created. In the broad inclusive model, 72kDa type IV collagenase (MMP-2), C-reactive protein (CRP), creatine kinase B type (CKBB), fatty acid binding protein—heart (hFABP), granulocyte-macrophage colony-stimulating factor (GM-CSF) and malondialdehyde modified low density lipoprotein (MDA-LDL) significantly predicted injury visualized on CT, yielding an overall c-statistic of 0.975 and a negative predictive value (NPV) of 98.6. In the parsimonious model, MMP-2, CRP, and CKBB type significantly predicted injury visualized on CT, yielding an overall c-statistic of 0.964 and a negative predictive value (NPV) of 97.2. These results suggest that a serum based biomarker panel can accurately differentiate patients with complicated mild TBI from those with uncomplicated mild TBI. Such a panel could be useful to guide early triage decisions, including the need for further evaluation or admission, especially in those environments in which resources are limited.

Novel blood-based microRNA biomarker panel for early diagnosis of chronic pancreatitis

Chronic pancreatitis (CP) is an inflammatory disease characterized by progressive fibrosis of pancreas. Early diagnosis will improve the prognosis of patients. This study aimed to obtain serum miRNA biomarkers for early diagnosis of CP. In the current study, we analyzed the differentially expressed miRNAs (DEmiRs) of CP patients from Gene Expression Omnibus (GEO), and the DEmiRs in plasma of early CP patients (n = 10) from clinic by miRNA microarrays. Expression levels of DEmiRs were further tested in clinical samples including early CP patients (n = 20), late CP patients (n = 20) and healthy controls (n = 18). The primary endpoints were area under curve (AUC) and expression levels of DEmiRs. Four DEmiRs (hsa-miR-320a-d) were obtained from GEO CP, meanwhile two (hsa-miR-221 and hsa-miR-130a) were identified as distinct biomarkers of early CP by miRNA microarrays. When applied on clinical serum samples, hsa-miR-320a-d were accurate in predicting late CP, while hsa-miR-221 and hsa-miR-130a were accurate in predicting early CP with AUC of 100.0% and 87.5%. Our study indicates that miRNA expression profile is different in early and late CP. Hsa-miR-221 and hsa-miR-130a are biomarkers of early CP, and the panel of the above 6 serum miRNAs has the potential to be applied clinically for early diagnosis of CP.

Altered levels of blood proteins in Alzheimer's disease longitudinal study: Results from Australian Imaging Biomarkers Lifestyle Study of Ageing cohort

IntroductionA blood-based biomarker panel to identify individuals with preclinical Alzheimer's disease (AD) would be an inexpensive and accessible first step for routine testing. MethodsWe analyzed 14 biomarkers that have previously been linked to AD in the Australian Imaging Biomarkers lifestyle longitudinal study of aging cohort. ResultsLevels of apolipoprotein J (apoJ) were higher in AD individuals compared with healthy controls at baseline and 18 months (P = .0003) and chemokine-309 (I-309) were increased in AD patients compared to mild cognitive impaired individuals over 36 months (P = .0008). DiscussionThese data suggest that apoJ may have potential in the context of use (COU) of AD diagnostics, I-309 may be specifically useful in the COU of identifying individuals at greatest risk for progressing toward AD. This work takes an initial step toward identifying blood biomarkers with potential use in the diagnosis and prognosis of AD and should be validated across other prospective cohorts.

Abstract 4920: Evaluation of a diagnostic blood test for colorectal cancer screening and as a triage tool to stratify patients for colonoscopy

Abstract Worldwide, colorectal cancer (CRC) is the third most common cancer and the second leading cause of cancer death, with an annual incidence in 2012 of 1.4 million CRC cases and an annual mortality around 700,000 [1]. Fortunately the majority of colorectal cancer (CRC) cases are preventable by early detection and removal by colonoscopy or surgery. Currently in Australia, the only widely used non-invasive screening test for CRC is the immunological faecal occult blood test (iFOBT), which has been shown to reduce CRC incidence and mortality by 15-25% [2]. There are however significant issues that limit its effectiveness as a diagnostic screening tool, such as a poor positive predictive value of 5.3% for suspected cancer and low participation rate of approximately 33.5% in 2013, as seen in the Australian National Bowel Cancer Screening Program (NBCSP)[2]. Evidence indicates a robust, blood-based, diagnostic assay would increase screening participation and compliance. In our systematic analysis of 68 individual biomarkers using logistic regression strategies, we have identified a unique 3 protein biomarker panel blood test consisting of Insulin like growth factor binding protein 2 (IGFBP2), Dickkopf-3 (DKK3), and Pyruvate kinase M2(PKM2)[3]. This panel not only differentiates between CRC and normal patient sera with 95% specificity and 73% sensitivity in a single measurement (c.f. FOBT: 35-50 sensitivity [4]) but early stage disease. Currently, we are prospectively collecting a new cohort of over 1,000 blood samples from volunteers that have undergone colonoscopy, that include CRC patients, controls and other pathologies (IBD, other cancers) to specifically determine the performance of this blood test in asymptomatic and surveillance screening populations. We will also evaluate directly the accuracy and performance of our biomarker panel, as a diagnostic test suitable for CRC screening versus the iFOBT used in the NBCSP, as an intermediary test in the triage of individuals with positive iFOBT result for need and urgency to have a colonoscopy. 1. Ferlay J, Soerjomataram I, Ervik M, Dikshit R, Eser S, Mathers C, Rebelo M, Parkin DM, Forman D, Bray, F. GLOBOCAN 2012 v1.1, Cancer Incidence and Mortality Worldwide: IARC CancerBase No. 11 2. National Bowel Cancer Screening Program: monitoring report 2012-2013. AIHW &amp; Australian Government Department of Health and Ageing, 2014. 3. Fung KYC et al 2015. Blood-based protein biomarker panel for the detection of colorectal cancer. PloS one. 2015;10(3):e0120425. 4. Morikawa, T et al., A comparison of the immunochemical fecal occult blood test and total colonoscopy in the asymptomatic population. Gastroenterology, 2005. 129(2): p. 422-8. Citation Format: Leah J. Cosgrove, Kathy Surinya, Kim YC Fung, Ilka Priebe, Mike Buckley, Tim Adams, Bruce Tabor, Leanne Purins, Trevor Lockett, Hugo Leroux, Peter Gibbs, Jiangqin Wei, Ed Nice, Tony Burgess, Michelle Thomas, James Moore, Raj Singh, Andrew Ruszkiewicz. Evaluation of a diagnostic blood test for colorectal cancer screening and as a triage tool to stratify patients for colonoscopy. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 4920.

Abstract A32: NISCH promoter hypermethylation, smoking and lung cancer: A case control study

Abstract Lung cancer is the most common cancer worldwide, both in terms of incidence and mortality. The high mortality of lung cancer is attributable to the presence of metastatic disease in nearly two thirds of patients at diagnosis. Detection of early stage lung cancer amenable to curative resection could potentially result in a manifold increase in survival rates. Epigenetic alterations seemingly contribute to cancer initiation and progression. Cancer specific methylation patterns of tumor suppressor genes, which precede precursor lesions, could possibly herald earlier diagnosis of lung cancer and may even have important preventive or therapeutic implications. Our aim was to evaluate the promoter hypermethylation of tumor suppressor gene NISCH in cfDNA from plasma of lung cancer patients and its possible correlation with smoking status and various clinicopathological parameters. NISCH codes for a nonadrenergic imidazoline-1 receptor protein nischarin that anchors to the inner layer of the plasma membrane. The orthologous mouse protein has been shown to bind alpha-5 beta-1 integrin and influence cytoskeletal organization. Forty histopathologically confirmed lung cancer cases were enrolled along with thirty smoker and thirty nonsmoker controls. Plasma cfDNA was extracted and subjected to bisulfite treatment followed by conventional methylation specific PCR. DNA methylated using CpG methylase by the whole genome methylation protocol, was used as positive control and Nuclease free PCR grade water was used as negative control. The serum nischarin levels were estimated using commercially available ELISA kits. Statistical analysis was performed using SPSS 22.0 software. We observed that frequency of promoter hypermethylation of tumor suppressor NISCH was significantly higher in lung cancer patients and in non-cancerous smokers as compared to lifelong nonsmoker controls. This difference in methylation status of NISCH between lung cancer cases, smoker and nonsmoker controls was found to be significant (P&amp;lt;0.05). There was no significant association between methylation status of tumor suppressor gene NISCH and clinicopathologic variables- staging, tumor size, lymph node status, metastasis and histopathological grading. We observed a higher frequency of NISCH methylation in adenocarcinoma as compared to Squamous Cell Carcinoma. Methylation status of tumor suppressor gene NISCH was found to be significantly higher among smokers as compared to nonsmokers. But there was no significant difference in the frequency of NISCH methylation between smoker lung cancer patients and nonsmoker lung cancer patients. There was no significant difference in methylation status of NISCH with type or duration of smoking. The pack years and packs per day were significantly higher in those with methylated NISCH as compared to the unmethylated group. There was no significant association of serum nischarin levels with methylation status of NISCH, demographic variables or any clinicopathological parameters. Our findings suggest that NISCH methylation occurs in high frequencies in cfDNA from plasma of lung cancer patients. Though it was not found to correlate with stage, tumor size, lymph node status, metastases or histological grade, it was found to be significantly associated with adenocarcinomas in our study. Hence, NISCH methylation could serve as a part of blood based biomarker panel for early diagnosis of lung cancer. In addition, since NISCH is found to be highly methylated in both high risk heavy smoker controls as well as lung cancer cases irrespective of smoking status, it can be hypothesized that NISCH methylation may be the common primogenitor at which varied etiologies for lung cancer converge. Hence, in the future, it may be investigated as a universal therapeutic target for lung cancers regardless of clinicopathological heterogeneity. Citation Format: Kritika Krishnamurthy, TK Mishra, Alpana Saxena, MK Daga, Nita Khurana, Masroor Mirza. NISCH promoter hypermethylation, smoking and lung cancer: A case control study. [abstract]. In: Proceedings of the Fourth AACR International Conference on Frontiers in Basic Cancer Research; 2015 Oct 23-26; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2016;76(3 Suppl):Abstract nr A32.

Abstract 1562: Proteomic changes observed in colon cancer tumors by label-free differential profiling of paired tumor versus normal FFPE samples

Abstract Colorectal cancer (CRC) is the third most common cancer and if caught early enough has a good prognosis. Mass screening of the adult population is advisable to reduce CRC mortality rate as well as reduce the cost of treating advanced CRC cases. A blood-based biomarker panel with the ability to diagnose CRC as well as determine prognosis and predict the response to drug therapy is desired. However, blood biomarker discovery is hampered by problems of complexity and dynamic range of protein abundance. Formalin-fixed and paraffin-embedded (FFPE) tissue is an ideal sample type for cancer biomarker analysis due to its ubiquitous use in cancer diagnosis in the clinic and consequent availability in oncology hospitals and clinics as well as biobanks. Biomarker discovery to date using FFPE have used only very few patient samples, making clinically relevant biomarker discovery difficult due to large patient-to-patient variation. As a part of our Biospecimen Research Network (BRN) program we funded a proteomic biomarker study of a large number of colorectal cancer and adjacent normal tissue samples. The investigators employed two platforms for biomarker discovery: label-free intensity based discovery using high resolution tandem mass spectrometry and targeted quantitation using multiple reaction monitoring. These two techniques allowed them to dig deeper into the proteome and to profile phosphopeptides. Paired tissue from 40 patients was profiled and of the 2875 proteins quantified, 367 proteins changed significantly in patients whose tumor size was greater than 50%. Large changes in secreted proteins were observed and many of these proteins were also observed in blood, offering promise for a potential blood-based biomarker for colorectal cancer. A blood-based biomarker assay for colorectal cancer could ultimately reduce the number of colonoscopies required, reducing cost and discomfort. Citation Format: Lokesh Agrawal, Fiona McAlister, Sushmita Roy, Florian Unger, Kerstin David, Harmut Juhl, Daniel Chelsky, Helen Moore. Proteomic changes observed in colon cancer tumors by label-free differential profiling of paired tumor versus normal FFPE samples. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 1562. doi:10.1158/1538-7445.AM2015-1562

Abstract 1570: Early Detection Research Network (EDRN) validation of circulating ovarian cancer biomarkers

Abstract Developing non-invasive blood-based tests is extremely appealing for early detection of cancers through screening asymptomatic subjects. This is particularly true for epithelial ovarian cancer in which the majority of women are diagnosed at a late stage when frontline therapy is less effective. To date there are no FDA approved biomarkers for ovarian cancer screening. To address this limitation, 165 proteins and 14 autoantibodies, identified as candidate circulating ovarian cancer biomarkers in previous studies at participating EDRN sites, were evaluated for their ability to discriminate ovarian cancer patient samples from those associated with benign ovarian disease. First, an in silico approach was used to prioritize candidate biomarkers likely to be over-expressed in ovarian cancer and predicted to be secreted. In parallel, high performance quantitative tandem mass spectrometry analyses of pooled plasma from serous ovarian cancer cases and serous benign ovarian disease controls were used to confirm candidate detectability in plasma and triage candidates by differential expression. A total of 61 proteins had sufficient evidence from one or more approaches to warrant further evaluation. 32 of the 61 proteins were evaluated using antibody-free selected reaction monitoring mass spectrometry (SRM-MS) assays. 29 of the 61 proteins could only be detected using high-pressure high-resolution separations with intelligent selection and multiplexing (PRISM)-SRM, due to the required analytical sensitivity. Because of its low prevalence, early detection of ovarian cancer requires very high specificity (≥99.6%), achievable when a blood test at 98% specificity is followed by trans-vaginal ultrasound. Therefore, sensitivity was estimated at 98% specificity for all candidates by quantifying candidates in serum from serous ovarian cancer cases (n = 20) and serous benign ovarian disease controls (n = 20). All 14 autoantibody candidates were similarly evaluated by ELISA using an expanded set of 50 serous ovarian cancer cases and 50 serous benign ovarian disease controls. The use of benign ovarian disease controls ensured similar conditions of blood sample acquisition and avoided selection of candidates that are elevated in the presence of benign disease. Candidates with 5% or greater sensitivity were identified as potential members of a panel of ovarian cancer biomarkers. These included WFDC2, SPON1, CBPA4, IBP2, and A2GL proteins, and autoantibodies CTAG2, p53, CTAG1A, and PTPRA. In summary, a multi-pronged approach identified five circulating proteins and four autoantibodies that warrant further evaluation in longitudinal pre-diagnostic plasma or sera from cases detected in screening studies and matched controls. Candidates successful in this future validation may provide the foundation for a new blood-based biomarker panel for the early detection of ovarian cancer. Citation Format: Steven J. Skates, Karen S. Anderson, Tao Liu, Vathany Kulasingam, Dustin Rabideau, Chaochao Wu, Michael Gillette, Andrew K. Godwin, Nicole Urban, Anna Lokshin, Jeffrey Marks, Eleftherios Diamandis, Zhen Zhang, Sudhir Srivastava, Jacob Kagan, Christos Patriotis, Karin Rodland. Early Detection Research Network (EDRN) validation of circulating ovarian cancer biomarkers. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 1570. doi:10.1158/1538-7445.AM2015-1570

Blood gene signature for early hepatocellular carcinoma detection in patients with chronic hepatitis B.

Up to 25% of chronic hepatitis B (CHB) patients eventually develop hepatocellular carcinoma (HCC), a disease with poor prognosis unless detected early. This study identifies a blood-based RNA biomarker panel for early HCC detection in CHB. A genome-wide RNA expression study was performed using RNA extracted from blood samples from Malaysian patients (matched HCC, CHB, controls). Genes differentiating HCC from controls were selected for further testing using quantitative real-time polymerase chain reaction. Finally, a 6-gene biomarker panel was identified and characterized using a training set (cohort I = 126), and tested against 2 test sets (cohort II = 222; cohort III = 174). The total number of samples used for each group is: HCC + CHB = 143, CHB = 211, control = 168. Our gene panel displays a consistent trend distinguishing HCC from controls in our test sets, with an area under receiver-operating characteristic curve of 0.9 in cohort III. Our independent test set (cohort III) showed that the gene panel had a sensitivity of 70% with a specificity of 92%. The biomarker profile for HCC was consistently detected in a small subgroup of CHB patients, thus potentially predicting early, preclinical cases of cancer that should be screened more intensively. The biomarkers identified in this study can be used as the basis of a blood-based test for the detection of early HCC in CHB.

Blood transcriptomic biomarkers in adult primary care patients with major depressive disorder undergoing cognitive behavioral therapy.

An objective, laboratory-based diagnostic tool could increase the diagnostic accuracy of major depressive disorders (MDDs), identify factors that characterize patients and promote individualized therapy. The goal of this study was to assess a blood-based biomarker panel, which showed promise in adolescents with MDD, in adult primary care patients with MDD and age-, gender- and race-matched nondepressed (ND) controls. Patients with MDD received cognitive behavioral therapy (CBT) and clinical assessment using self-reported depression with the Patient Health Questionnaire–9 (PHQ-9). The measures, including blood RNA collection, were obtained before and after 18 weeks of CBT. Blood transcript levels of nine markers of ADCY3, DGKA, FAM46A, IGSF4A/CADM1, KIAA1539, MARCKS, PSME1, RAPH1 and TLR7, differed significantly between participants with MDD (N=32) and ND controls (N=32) at baseline (q< 0.05). Abundance of the DGKA, KIAA1539 and RAPH1 transcripts remained significantly different between subjects with MDD and ND controls even after post-CBT remission (defined as PHQ-9 <5). The ROC area under the curve for these transcripts demonstrated high discriminative ability between MDD and ND participants, regardless of their current clinical status. Before CBT, significant co-expression network of specific transcripts existed in MDD subjects who subsequently remitted in response to CBT, but not in those who remained depressed. Thus, blood levels of different transcript panels may identify the depressed from the nondepressed among primary care patients, during a depressive episode or in remission, or follow and predict response to CBT in depressed individuals.

Biomarker responses to weaning stress in beef calves

The study objective was to investigate the physiological effects of weaning on beef calves and identify a panel of blood-based welfare biomarkers. On the day (d) of weaning (d 0), 16 spring-born, single-suckled, beef bull calves that previously grazed with their dams at pasture, were assigned to one of two treatments: (1) control (n = 8), calves were loose-housed with their dam, (2) weaned (n = 8), calves were abruptly separated from their dam and loose-housed. Jugular blood was collected on d −4, 0, 1, 2, 3, 7, and 14 relative to weaning (d 0) and assayed for inflammatory and steroid variables. Total leukocyte counts were measured in whole blood. It is concluded that neutrophil number is a robust biomarker of stress and that plasma CXCL8 is a sensitive indicator of stress in weaned and control calves. In future studies, these two biomarkers should be central to the characterisation of stress responses.

An Association of Virus Infection with Type 2 Diabetes and Alzheimer’s Disease

Diabetes mellitus type 2 is a metabolic disorder characterized by high blood glucose due to insulin deficiency or resistance. Alzheimer's disease (AD) is a complex neurodegenerative disease leading to irreversible loss of neurons, intellectual abilities, memory and reasoning. The worldwide prevalence of diabetes and AD in elderly population is a major public health concern. Interestingly, both health issues are unraveling the puzzling links. The clinico-pathological relationship between diabetes and AD has been reported at genomic and proteomic levels. The association of virus infection in type 2 diabetes mellitus and AD has been reported in few recent studies, some have shown direct evidence of virus infection in diabetes and AD while other have shown that diabetes increases the risk of developing AD. This review aims to summarize the association of few common viruses like Hepatitis C Virus and Herpes Simplex Virus-1 which affects both these two age-related devastating diseases. We also discuss the pathological links of Influenza virus, Cytomegalovirus, West Nile virus, Enterovirus, Herpes Simplex Virus-2, Hepatitis viruses in diabetes and Influenza virus, Picornavirus and Borna disease virus in AD. Establishing such relationships and defining their common pathogenesis and patho-physiological mechanisms may lead to new concepts and paths for developing novel preventive strategies and pharmacological treatment options for diabetes and AD. This study may aid in future for the identification of a single or a panel of likely blood-based viral biomarkers for early diagnosis of diabetes and AD with high sensitivity and specificity.

Proteomics Approaches to Understand Linkage Between Alzheimer’s Disease and Type 2 Diabetes Mellitus

Alzheimer's disease (AD) is a progressive neurological disease of the brain leading to the irreversible loss of neurons and intellectual abilities. Diabetes mellitus type 2 (T2DM) is a metabolic disorder that is characterized by high blood glucose in the context of insulin resistance and relative insulin deficiency. The prevalence of AD and T2DM is increasing at an alarming rate and has become a major public health concern worldwide. The clinico-pathological relationship between AD and T2DM has been debated for more than a decade. Recent epidemiological studies have provided direct evidence that T2DM is a strong risk factor for AD and numerous studies have demonstrated that patients with diabetes have an increased risk of developing AD as compared with healthy individuals. The underlying biological mechanisms that link the development of diabetes with AD are not fully understood and therefore are worth intensive research. The existence of proteomic links between AD and diabetes is an important topic currently under active debate. An understanding of the complex association between diabetes and AD is necessary for the development of novel drug therapies and lifestyle guidelines aimed at the treatment and/or prevention of these diseases. This review aims to summarize what is currently known about the biological and especially proteomic relationships and similarities between these two age-related devastating diseases of modern day life. This study may also aid in future for the identification of a single or a panel of potential blood-based protein biomarkers for early diagnosis of AD and T2DM with high sensitivity and specificity.