Multiplex Biomarker Research Articles

Immunological Biomarkers of COVID-19.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the cause of the COVID-19 pandemic, has become a global health emergency. The damage and threat posed by this virus to nearly every country in the world have far exceeded those of the other six previous coronaviruses, including Middle East respiratory syndrome coronavirus (MERS-CoV) and severe acute respiratory syndrome (SARS-CoV) combined. A comprehensive profile of the hematological and inflammatory biomarkers of COVID-19 is covered in this review. Significant hematological changes that have been reported in infected patients include the following biomarker candidates: lymphocyte counts (LYM), neutrophil counts (NØ), neutrophil to lymphocyte ratio (NLR), neutrophil to CD8+ T-cell ratio (N8R), eosinophil counts (EØ), platelet counts (PLT), and platelet to lymphocyte ratio (PLR). Likewise, significant changes in soluble mediators include interleukin (IL)-2r, IL-2r to lymphocyte ratio (ILR), IL-6, interferon-γ-induced protein 10 (IP-10), monocyte chemoattractant protein (MCP-3), and macrophage colony-stimulating factor (M-CSF). Multiplex biomarker analyses based on hematological and cytokine changes in combination with biomedical levels of alanine aminotransferase (ALT), aspartate aminotransferase (AST), lactate dehydrogenase (LDH), N-terminal prohormone BNP (NT-proBNP), serum urea, C-reactive protein (CRP), and D-dimer have shown improved diagnostic accuracy for determining disease severity in patients compared with single biomarker analyses. Here, we provide a current review of blood/serum biomarker abnormalities associated with different levels of COVID-19 severity.

Clinical decision support tool and rapid point-of-care platform for determining disease severity in patients with COVID-19.

SARS-CoV-2 is the virus that causes coronavirus disease (COVID-19) which has reached pandemic levels resulting in significant morbidity and mortality affecting every inhabited continent. The large number of patients requiring intensive care threatens to overwhelm healthcare systems globally. Likewise, there is a compelling need for a COVID-19 disease severity test to prioritize care and resources for patients at elevated risk of mortality. Here, an integrated point-of-care COVID-19 Severity Score and clinical decision support system is presented using biomarker measurements of C-reactive protein (CRP), N-terminus pro B type natriuretic peptide (NT-proBNP), myoglobin (MYO), D-dimer, procalcitonin (PCT), creatine kinase-myocardial band (CK-MB), and cardiac troponin I (cTnI). The COVID-19 Severity Score combines multiplex biomarker measurements and risk factors in a statistical learning algorithm to predict mortality. The COVID-19 Severity Score was trained and evaluated using data from 160 hospitalized COVID-19 patients from Wuhan, China. Our analysis finds that COVID-19 Severity Scores were significantly higher for the group that died versus the group that was discharged with median (interquartile range) scores of 59 (40-83) and 9 (6-17), respectively, and area under the curve of 0.94 (95% CI 0.89-0.99). Although this analysis represents patients with cardiac comorbidities (hypertension), the inclusion of biomarkers from other pathophysiologies implicated in COVID-19 (e.g., D-dimer for thrombotic events, CRP for infection or inflammation, and PCT for bacterial co-infection and sepsis) may improve future predictions for a more general population. These promising initial models pave the way for a point-of-care COVID-19 Severity Score system to impact patient care after further validation with externally collected clinical data. Clinical decision support tools for COVID-19 have strong potential to empower healthcare providers to save lives by prioritizing critical care in patients at high risk for adverse outcomes.

A Method to Reuse Archived H&E Stained Histology Slides for a Multiplex Protein Biomarker Analysis.

Archived Hematoxylin and Eosin (H&E) stained pathology slides are routinely stored to index formalin-fixed paraffin-embedded (FFPE) sample tissue blocks. FFPE blocks are clinically annotated human tumor specimens that can be valuable in studies decades after the tissue is collected. If stored properly, they have the potential to yield a valuable number of serial sectioned slides for diagnostic or research purposes. However, some retrospective studies are limited in scope because the tissue samples have been depleted or not enough material is available in stored blocks for serial sections. The goal of these studies was to determine if archived H&E-stained slides can be directly reutilized by optimizing methods to de-stain and then re-stain the H&E stained slides to allow the detection of several biomarkers of interest using a conjugated antibody with chromogen multiplex immunohistochemistry procedure. This simple but innovative procedure, combined with image analysis techniques, demonstrates the ability to perform precise detection of relevant markers correlated to disease progression in initially identified tumor regions in tissue. This may add clinical value in retaining H&E slides for further use.

Abstract AP08: DEVELOPMENT OF A MULTI-PROTEIN CLASSIFIER FOR OVARIAN CANCER DETECTION BY SIMULTANEOUS MEASUREMENT OF 92 SERUM PROTEINS ON PROSEEK MULTIPLEX ONCOLOGY II PLATES

Abstract There are no FDA approved screening tools for detecting ovarian cancer in the general population. The two best known ovarian cancer biomarkers, CA125 and HE4, are neither adequately sensitive nor specific when used alone to screen the general population for early stage disease. By using a combination of protein biomarkers for screening, it may be possible to increase the sensitivity and specificity over CA125 alone. In this study, we used Proseek Multiplex Oncology II plates to simultaneously measure the expression of 92 cancer-related proteins in serum using proximity extension assays. This technology combines the sensitivity of the polymerase chain reaction with the specificity of antibody-based detection methods, allowing multiplex biomarker detection and high throughput quantification. We analyzed one microliter of serum from 61 women with advanced stage high grade serous ovarian cancer and compared the values obtained to 88 age-matched healthy women. Principle component analysis and unsupervised hierarchical clustering separated the ovarian cancer patients from the healthy, with minimal misclassification. Data from the Proseek plates for CA125 levels exhibited a strong correlation with previously measured clinical values for CA125 (correlation coefficient of 0.91). CA125 and HE4 were detected at low levels in samples from healthy women, while higher levels were observed in the ovarian cancer cases. We identified 52 proteins that differed significantly (p < 0.006) between ovarian cancer and healthy samples; several of which are novel serum biomarkers for ovarian cancer. In total, 40 proteins had an estimated area under the ROC curve of 0.70 or greater. CA125 alone achieved a sensitivity of 93.4% at a specificity of 98%. However, by adding five proteins to CA125, we increased the assay sensitivity to 98.4%, while holding the specificity fixed at 98%. Our data demonstrate that the Proseek technology can replicate the results established by conventional clinical assays for known biomarkers, identify new candidate biomarkers, and improve the sensitivity and specificity of CA125 alone. Citation Format: Amy P.N. Skubitz, Kristin L.M. Boylan, Kate Geschwind, Qing Cao, Timothy K. Starr, Melissa A. Geller, Joseph Celestino, Robert C. Bast Jr., Karen H. Lu, and Joseph S. Koopmeiners. DEVELOPMENT OF A MULTI-PROTEIN CLASSIFIER FOR OVARIAN CANCER DETECTION BY SIMULTANEOUS MEASUREMENT OF 92 SERUM PROTEINS ON PROSEEK MULTIPLEX ONCOLOGY II PLATES [abstract]. In: Proceedings of the 12th Biennial Ovarian Cancer Research Symposium; Sep 13-15, 2018; Seattle, WA. Philadelphia (PA): AACR; Clin Cancer Res 2019;25(22 Suppl):Abstract nr AP08.

Using SERS-based microfluidic paper-based device (μPAD) for calibration-free quantitative measurement of AMI cardiac biomarkers

Recently, surface enhanced Raman scattering (SERS) has attracted much attention in medical diagnosis applications owing to better detection sensitivity and lower limit of detection (LOD) than colorimetric detection. In this paper, a novel calibration-free SERS−based μPAD with multi-reaction zones for simultaneous quantitative detection of multiple cardiac biomarkers — GPBB, CK−MB and cTnT for early diagnosis and prognosis of acute myocardial infarction (AMI) are presented. Three distinct Raman probes were synthesised, subsequently conjugated with respective detecting antibodies and used as SERS nanotags for cardiac biomarker detection. Using a conventional calibration curve, quantitative simultaneous measurement of multiple cardiac biomarkers on SERS-based μPAD was performed based on the characteristic Raman spectral features of each reporter used in different nanotags. However, a calibration free point-of-care testing device is required for fast screening to rule-in and rule-out AMI patients. Partial least squares predictive models were developed and incorporated into the immunosensing system, to accurately quantify the three unknown cardiac biomarkers levels in serum based on the previously obtained Raman spectral data. This method allows absolute quantitative measurement when conventional calibration curve fails to provide accurate estimation of cardiac biomarkers, especially at low and high concentration ranges. Under an optimised condition, the LOD of our SERS-based μPAD was identified at 8, 10, and 1 pg mL−1, for GPBB, CK−MB and cTnT, respectively, which is well below the clinical cutoff values. Therefore, this proof-of-concept technique shows significant potential for highly sensitive quantitative detection of multiplex cardiac biomarkers in human serum to expedite medical decisions for enhanced patient care.

Advanced molecular characterization using Digital Spatial Profiling Technology on immuno-oncology targets in methylated compared with unmethylated IDH-wildtype glioblastoma

Abstract Introduction Glioblastoma (GBM) is the most common primary adult brain tumour with 12–15 months median overall survival. Molecular characterization of multiple immuno-onology targets in GBM is required to optimise immunotherapeutic strategies. Advanced molecular characterisation using Digital Spatial Profiling Technology allows assessment of multiple immuno-oncology protein targets in methylated compared with unmethylated Glioblastoma IDH-wildtype. Methods Nanostring DSP uses multiple primary antibodies conjugated to indexing DNA oligos with a UV photocleavable linker. Tissue Regions of interest (ROI) are selected with bound fluorescent antibodies, oligos are released via a UV-mediated linker and quantitated. We used DSP multiplex analysis of 31 immuno-oncology proteins and controls (PD-1, PD-L1, B7-H3, VISTA, CD45, CD45RO, CD3, MS4A1 (CD20), CD4, CD8A, CD68, STAT3, STAT3 (Phopshory705), GZMB, Beta-2-microglobulin, CD56, Beta-catenin, FOXP3, CD14, CD19, AKT, P-AKT, PTEN, Bcl-2, CD44, Histone H3, S6, IgG Rabbit Control, Mouse IgG Control, Pan-Cytokeratin, Ki67) from ROIs in a cohort of 10 Glioblastomas IDH-wildtype (5 methylated, 5 unmethylated). An nCounter platform allowed quantitative comparisons of antibodies between ROIs in MGMT methylated and unmethylated tumours. Mean protein expression counts between methylated and unmethylated GBM were compared using a linear mixed effect model for technical and biological replicates. Results GeoMx DSP showed 10/27 immuno-oncology target proteins were significantly increased in methylated versus unmethylated Glioblastoma IDH-wildtype (false discovery rate FDR <0.1 by Benjamini-Hocheberg Procedure). Conclusions Increased immuno-oncology protein target expression in methylated versus unmethylated glioblastoma IDH-wildtype using DSP platform has been identified. Advanced multiplex immuno-oncological biomarker analysis is required to identify predictive biomarkers for novel immunotherapeutic agents in GBMs.

1511P - Clinical implication of multiplex IHC and serologic biomarkers on hyperprogression in NSCLC patients receiving immune checkpoint blockers in real world

BackgroundAlthough immune checkpoint blockers (ICBs) can lead to favorable results by reinvigorating the anti-tumor immune response in some patients, many other patients experience poor prognosis and even tumor overgrowth can be seen in real practice. We aimed to assess these hyperprogressive disease (HPD). MethodsWe reviewed NSCLC patients (n=243) treated with ICBs. HPD was defined as a tumor growth kinetic ratio (TGKr)>2 and a time-to-failure of less than 2 months. We analyzed the association of Neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR) and CRP-albumin ratio (CAR) with HPD and the immune compositional change in TME by multiplex IHC(mIHC). Panel 1/2 showed CD4, CD8, FOXP3, CD45RO as T cell markers and CD3, TIM3, LAG3, PD-L1 as co-inhibitory signal markers. Panel 3/4 examined macrophages and NK cells with CD68, CD14, CD163, CD206, CCR7, CD86, CD103, CD56, CD11c and CD16. ResultsOverall, 231 patients were evaluated. 25 patients (10.8%) met the HPD. Patients with HPD (median, 5.6mo; P<0.001) were worse outcome than those for without (median, 7.4mo). We also analyzed the association of NLR, PLR and CAR with HPD. Serologic markers at the time of first response evaluation (post 6 weeks, i.e.,) showed a prognostic value for HPD (P<0.001, 0.008, 0.017). In mIHC, there was a difference in immune cell composition between the HPD, poor responder and good responder groups. High levels of CD4+ Teff cells and FOXP3+ Treg cells were associated with HPD (p<0.042, <0.017) The CD4 to CD45RO ratio suggests a predictive ability to develop HPD (p<0.042) The key point was the M2 polarized tendency in the HPD group. This suggests that changes in the AXL pathway and EMT features associated with reinvigorating anti-tumor immunity in M2 polarized cells may lead to HPD. ConclusionsDespite improved recognition of HPD, its etiology remains unclear, but it is clear that the prognosis becomes poor when it occurs. We observed that some serologic biomarkers (NLR, PLR, CAR) and mIHC can be used not only to predict HPD, but also to validate its mechanism. Furthermore, we undergo whole exon sequencing and experiment with murine model to understand mechanism of HPD. Legal entity responsible for the studyThe authors. FundingHas not received any funding. DisclosureAll authors have declared no conflicts of interest.

372 An Automated, Quantitative Multiplex Immunofluorescence Assay Accurately Risk Stratifies Barrett’s Esophagus Patients With a Community-Based Diagnosis of Low-Grade Dysplasia at a Rate Comparable to Expert Pathologists

INTRODUCTION: The majority of community-based LGD diagnoses are down-staged to non-dysplastic (ND) BE when reviewed by an expert pathologist, whereas patients with confirmed LGD have a 10% annual risk of progression to high-grade dysplasia (HGD) or cancer (Ca). Although recommended by guidelines, expert review is poorly defined, prone to observer variation, and not widely available. Recent studies suggest that an automated, quantitative multiplex immunofluorescence assay may identify NDBE patients with an increased risk of malignant progression. We investigated if this assay also allows objective risk stratification for cases with a community-based diagnosis of LGD at a rate comparable to expert pathologists. METHODS: A blinded nested case-control cohort was derived from the screening cohort of a randomized controlled trial of SUrveillance vs. RadioFrequency ablation (SURF) for BE patients with LGD. 60 patients with a community-based diagnosis of LGD of whom 30 progressed to HGD/Ca and 30 patients who did not progress were matched for age, sex and maximal BE length. All random biopsy levels of the baseline endoscopy were independently reviewed by 3 expert pathologists with an international reputation. All levels were additionally tested by a multiplex biomarker assay. The assay classifies patients into low-risk (LR), intermediate-risk (IR) and high-risk (HR) for progression to HGD/Ca within 5 years. A histological revision diagnosis of NDBE was considered as low- (LR), while indefinite for dysplasia (IND) and LGD were considered as high-risk (HR) for progression. RESULTS: 60 BE patients (52 male), mean age 63 ± 9 years, were studied. Median time between baseline endoscopy and progression was 2.5 years (1.3-5.4). Accuracy, sensitivity and specificity of the biomarker assay vs. the 3 expert pathologists were 73% vs 72-77%, 66% vs 77-80% and 80% vs 63-77%, respectively. 20/26 (78%) patients classified as IR/HR by the biomarker panel and 69-77% classified as HR (IND/LGD) by the 3 expert pathologists progressed to HGD/Ca. CONCLUSION: A quantitative multiplex immunofluorescence assay risk stratified BE patients with a community-based diagnosis of LGD with an accuracy comparable to three renowned expert pathologists. The assay allows for automated, objective risk stratification which may be a practical and effective solution to the lack of standardization of expert pathology review of LGD as advocated by all guidelines.

Pilot Study of Renal Urinary Biomarkers for Diagnosis of CKD of Uncertain Etiology

IntroductionChronic kidney disease of uncertain etiology (CKDu), an emerging chronic kidney disease (CKD) subtype, contributes to significant morbidity and mortality in certain tropical countries. Although several indicators of CKDu have been previously suggested, sensitive and specific tests to detect early disease or predict disease progression are currently unavailable. This study focused on evaluating 8 renal urinary markers, namely neutrophil gelatinase-associated lipocalin (NGAL), Kidney Injury Molecule-1 (KIM1), cystatin C (CST3), beta 2 microglobulin (B2M), osteopontin (OPN), alpha 1 microglobulin (A1M), tissue inhibitor of metalloproteinase 1 (TIMP1), and retinol binding protein 4 (RBP4), with the hypothesis that these have distinct expression patterns in patients with CKDu.MethodsA cross-sectional study was conducted with 5 study groups comprising subjects from CKDu, endemic CKD, nonendemic CKD, and endemic healthy and nonendemic healthy controls. The urinary levels of the 8 selected renal biomarkers were quantified using multiplex biomarker assay, and the data were subjected to systematic analysis using logistic regression algorithm aiming to extract the best marker combination that could distinctly identify the disease groups noninvasively from the healthy controls.ResultsA 3-marker signature panel comprising A1M, KIM1, and RBP4 was identified to represent the best minimum marker combination for differentiating all CKD categories, including CKDu, from healthy controls with an overall sensitivity of ≥0.867 and specificity ≥0.765. The marker combination comprising OPN, KIM1, and RBP4 showed high predictive performance for distinguishing patients with CKDu from patients with CKD with both sensitivity and specificity ≥0.93, which was superior to any existing noninvasive indicator.ConclusionIn all, our systematic evaluation of urinary markers previously linked to CKD, in general, allowed identification of exclusive marker panel combination for early diagnosis and confirmation of CKDu.

Identification of a Multiplex Biomarker Panel for Hypertrophic Cardiomyopathy Using Quantitative Proteomics and Machine Learning.

Hypertrophic cardiomyopathy (HCM) is defined by pathological left ventricular hypertrophy (LVH). It is the commonest inherited cardiac condition and a significant number of high risk cases still go undetected until a sudden cardiac death (SCD) event. Plasma biomarkers do not currently feature in the assessment of HCM disease progression, which is tracked by serial imaging, or in SCD risk stratification, which is based on imaging parameters and patient/family history. There is a need for new HCM plasma biomarkers to refine disease monitoring and improve patient risk stratification. To identify new plasma biomarkers for patients with HCM, we performed exploratory myocardial and plasma proteomics screens and subsequently developed a multiplexed targeted liquid chromatography-tandem/mass spectrometry-based assay to validate the 26 peptide biomarkers that were identified. The association of discovered biomarkers with clinical phenotypes was prospectively tested in plasma from 110 HCM patients with LVH (LVH+ HCM), 97 controls, and 16 HCM sarcomere gene mutation carriers before the development of LVH (subclinical HCM). Six peptides (aldolase fructose-bisphosphate A, complement C3, glutathione S-transferase omega 1, Ras suppressor protein 1, talin 1, and thrombospondin 1) were increased significantly in the plasma of LVH+ HCM compared with controls and correlated with imaging markers of phenotype severity: LV wall thickness, mass, and percentage myocardial scar on cardiovascular magnetic resonance imaging. Using supervised machine learning (ML), this six-biomarker panel differentiated between LVH+ HCM and controls, with an area under the curve of ≥ 0.87. Five of these peptides were also significantly increased in subclinical HCM compared with controls. In LVH+ HCM, the six-marker panel correlated with the presence of nonsustained ventricular tachycardia and the estimated five-year risk of sudden cardiac death. Using quantitative proteomic approaches, we have discovered six potentially useful circulating plasma biomarkers related to myocardial substrate changes in HCM, which correlate with the estimated sudden cardiac death risk.

Analytical Validation of Multiplex Biomarker Assay to Stratify Colorectal Cancer into Molecular Subtypes

Previously, we classified colorectal cancers (CRCs) into five CRCAssigner (CRCA) subtypes with different prognoses and potential treatment responses, later consolidated into four consensus molecular subtypes (CMS). Here we demonstrate the analytical development and validation of a custom NanoString nCounter platform-based biomarker assay (NanoCRCA) to stratify CRCs into subtypes. To reduce costs, we switched from the standard nCounter protocol to a custom modified protocol. The assay included a reduced 38-gene panel that was selected using an in-house machine-learning pipeline. We applied NanoCRCA to 413 samples from 355 CRC patients. From the fresh frozen samples (n = 237), a subset had matched microarray/RNAseq profiles (n = 47) or formalin-fixed paraffin-embedded (FFPE) samples (n = 58). We also analyzed a further 118 FFPE samples. We compared the assay results with the CMS classifier, different platforms (microarrays/RNAseq) and gene-set classifiers (38 and the original 786 genes). The standard and modified protocols showed high correlation (> 0.88) for gene expression. Technical replicates were highly correlated (> 0.96). NanoCRCA classified fresh frozen and FFPE samples into all five CRCA subtypes with consistent classification of selected matched fresh frozen/FFPE samples. We demonstrate high and significant subtype concordance across protocols (100%), gene sets (95%), platforms (87%) and with CMS subtypes (75%) when evaluated across multiple datasets. Overall, our NanoCRCA assay with further validation may facilitate prospective validation of CRC subtypes in clinical trials and beyond.

A highly sensitive multiplex biomarker assay for the early diagnosis of osteoarthritis

A highly sensitive multiplex biomarker assay for the early diagnosis of osteoarthritis

Somatic alterations in a seven-gene DDR gene panel predicts platinum sensitivity in advanced prostate cancer patients.

283 Background: Genomic alterations in the DNA damage response and repair (DDR) pathways are common in advanced PC. Platinum compounds are active in CRPC pts. DDR-defective PC tumors have increased sensitivity to PARP inhibitors (PARPi); the mechanisms involved in sensitivity to platinum and PARPi may be similar but not identical. This study aimed to assess the impact of somatic DDR alterations on clinical outcome of platinum-treated patients with advanced PC. Methods: We reviewed records of advanced PC patients, who received platinum-based chemotherapy with available tumor tissue specimens. We used next generation sequencing (whole exome or targeted) to assess for mutations and copy number alterations in a selected panel of DDR genes, including BRCA1, BRCA2, ATM, ERCC3, ERCC5, TP53 and RB1. We used Kaplan Meier curves to predict PFS and OS after initiation of platinum chemotherapy. Results: Our cohort included 50 men, median age 69.5 years (45-91), median PSA 0.81 (0.008-2291.25), median LDH 264 (109-6714). 39 had visceral metastases (38 liver, 15 lung, 2 adrenal, 2 peritoneal, 1 brain). The majority or pts (33/50) received carboplatin, 17 received cisplatin (2 subsequently also received carbo with initial platinum used for data analysis). Most pts received chemotherapy doublets, and platinum was most frequently combined with etoposide (N=27) and paclitaxel (N=9). 39 pts had tumors harboring at least one DDR alteration. Somatic deletions in BRCA2 gene (N=18) were associated with a significantly longer PFS compared to men with wild-type BRCA2 (median PFS: 6 versus 3 months, P=0.019). No significant associations were identified between somatic DDR alterations and OS. Presence of ≥2 concomitant DDR somatic alterations predicted a favorable PFS compared to single-gene alterations or lack thereof (6 vs 3 months, P=0.006). Conclusions: Our study suggests that presence of ≥2 concomitant DDR somatic alterations from a 7-gene DDR panel, including BRCA1, BRCA2, ATM, ERCC3, ERCC5, TP53, and RB1, may predict longer PFS in pts with advanced PC treated with platinum-based chemotherapy. Further studies are needed to clinically qualify multiplex predictive biomarkers of DDR-defective PCs.

Associated multiplex biomarker detection for colorectal cancer based on Bio-Plex platform

Background: Associated protein biomarkers are thought to be produced by the tumor or other tissues in response to the existence of cancers or associated conditions. Equally, known examples of cancer protein biomarker are used for the diagnosis of colorectal cancers (CRCs). However, these biomarkers suffer from low diagnostic specificity and sensitivity for CRC patients. Single biomarker detection is rarely useful for clinical applications due to the heterogeneity of cancer. Therefore, new sensitive and specific assays are urgently required for CRC diagnosis at an early stage. Methods: In this study, a total of 58 newly diagnosed primary CRC patients in Dianjiang People’s Hospital of Chongqing were included, while 20 controls were also included. Approximately 2 mL of venous blood samples from 58 CRC patients and 20 controls were collected. Then we detected 16 angiogenic cytokines using the Bio-Plex technology to measure multiple cytokines. Results: The results showed that serum levels of Follistatin, HGF, and Osteopontin were significantly higher in CRC patients, while Leptin and PECAM were significantly decreased. ROC curve analyses indicated that the up-regulated markers, including Follistatin, HGF, and Osteopontin, had diagnostic value for CRC. The down-regulated marker, PECAM, also presented diagnostic value for CRC. To maximize the ability to detect CRC, four biomarkers, as well as CEA, were combined and used for linear discriminant analysis. Using the regression equation, the sensitivity and specificity for CRC were calculated as 93.1% (54/58) and 60.0% (12/20). Conclusions: The study demonstrates that the combined analysis of five cytokines (follistatin, HGF, leptin, PECAM and osteopontin) is more useful for CRC diagnosis than the analysis of any individual marker. The combined detection of these five biomarkers is a valuable method for the diagnosis of CRC.

Simultaneous Measurement of 92 Serum Protein Biomarkers for the Development of a Multiprotein Classifier for Ovarian Cancer Detection.

The best known ovarian cancer biomarker, CA125, is neither adequately sensitive nor specific for screening the general population. By using a combination of proteins for screening, it may be possible to increase the sensitivity and specificity over CA125 alone. In this study, we used Proseek Multiplex Oncology II plates to simultaneously measure the expression of 92 cancer-related proteins in serum using proximity extension assays. This technology combines the sensitivity of the PCR with the specificity of antibody-based detection methods, allowing multiplex biomarker detection and high-throughput quantification. We analyzed 1 μL of sera from each of 61 women with ovarian cancer and compared the values obtained with those from 88 age-matched healthy women. Principle component analysis and unsupervised hierarchical clustering separated the ovarian cancer patients from the healthy, with minimal misclassification. Data from the Proseek plates for CA125 levels exhibited a strong correlation with clinical values for CA125. We identified 52 proteins that differed significantly (P < 0.006) between ovarian cancer and healthy samples, several of which are novel serum biomarkers for ovarian cancer. In total, 40 proteins had an estimated area under the ROC curve of 0.70 or greater, suggesting their potential to serve as biomarkers for ovarian cancer. CA125 alone achieved a sensitivity of 93.4% at a specificity of 98%. By adding the Oncology II values for five proteins to CA125 in a multiprotein classifier, we increased the assay sensitivity to 98.4% at a specificity of 98%, thereby improving the sensitivity and specificity of CA125 alone.

Immunobinding-induced alteration in the electrophoretic mobility of proteins: An approach to studying the preconcentration of an acidic protein under cationic isotachophoresis.

The objective of this study is to explore an approach for analyzing negatively charged proteins using paper-based cationic ITP. The rationale of electrophoretic focusing the target protein with negative charges under unfavorable cationic ITP condition is to modify the electrophoretic mobility of the target protein through antigen-antibody immunobinding. Cationic ITP was performed on a paper-based analytical device that was fabricated using fiberglass paper. The paper matrix was modified with (3-aminopropyl)trimethoxysilane to minimize sample attraction to the surface for cationic ITP. Negatively charged BSA was used as the model target protein for the cationic ITP experiments. No electrophoretic mobility was observed for BSA-only samples during cationic ITP experimental condition. However, the presence of a primary antibody to BSA significantly improved the electrokinetic behavior of the target protein. Adding a secondary antibody conjugated with amine-rich quantum dots to the sample further facilitated the concentrating effect of ITP, reduced experiment time, and elevated the stacking ratio. Under our optimized experimental conditions, the cationic ITP-based paper device electrophoretically stacked 94% of loaded BSA in less than 7 min. Our results demonstrate that the technique has a broad potential for rapid and cost-effective isotachphoretic analysis of multiplex protein biomarkers in serum samples at the point of care.

An Integrative Data Mining and Omics-Based Translational Model for the Identification and Validation of Oncogenic Biomarkers of Pancreatic Cancer.

Substantial alterations at the multi-omics level of pancreatic cancer (PC) impede the possibility to diagnose and treat patients in early stages. Herein, we conducted an integrative omics-based translational analysis, utilizing next-generation sequencing, transcriptome meta-analysis, and immunohistochemistry, combined with statistical learning, to validate multiplex biomarker candidates for the diagnosis, prognosis, and management of PC. Experiment-based validation was conducted and supportive evidence for the essentiality of the candidates in PC were found at gene expression or protein level by practical biochemical methods. Remarkably, the random forests (RF) model exhibited an excellent diagnostic performance and LAMC2, ANXA2, ADAM9, and APLP2 greatly influenced its decisions. An explanation approach for the RF model was successfully constructed. Moreover, protein expression of LAMC2, ANXA2, ADAM9, and APLP2 was found correlated and significantly higher in PC patients in independent cohorts. Survival analysis revealed that patients with high expression of ADAM9 (Hazard ratio (HR)OS = 2.2, p-value < 0.001), ANXA2 (HROS = 2.1, p-value < 0.001), and LAMC2 (HRDFS = 1.8, p-value = 0.012) exhibited poorer survival rates. In conclusion, we successfully explore hidden biological insights from large-scale omics data and suggest that LAMC2, ANXA2, ADAM9, and APLP2 are robust biomarkers for early diagnosis, prognosis, and management for PC.

Paper microfluidic device for early diagnosis and prognosis of acute myocardial infarction via quantitative multiplex cardiac biomarker detection

The early detection of acute myocardial infarction (AMI) upon the onset of chest pain symptoms is crucial for patient survival. However, this detection is challenging, particularly without a persistent elevation of ST-segment reflected in an electrocardiogram or in blood tests. A majority of the available point-of-care testing devices allow accurate and rapid diagnosis of AMI. However, AMI diagnosis is reliable only at intermediate and later stages, with myocardial injury (> 6 h) and MI, based on the expression of specific cardiac biomarkers including troponin I or T (cTnI or cTnT), creatine kinase-MB (CK−MB), and myoglobin. Diagnosis at the early myocardial ischemia stage is not possible. To overcome this limitation, a sensitive and rapid microfluidic paper-based device (µPAD) was developed for the simultaneous detection of multiple cardiac biomarkers for the early and late diagnosis of AMI. The glycogen phosphorylase isoenzyme BB (GPBB) was detected during early (within first 4 h) ischemic myocardial injury. On the same µPAD platform, detection of prolonged elevation of levels of cTnT and CK-MB, which are only produced 6 h after the onset of chest pain in human serum, was possible. Sandwich immunoassay performed on the µPAD achieved reproducibility (RSD approximately 10% and intra-and inter-day precision (CV 10–20%, 99th percentile), as well as consistently stable test results for 28 days, with strong correlation (r2= 0.962), using the standard Siemens Centaur XPT Immunoassay system. The present findings indicate the potential of the µPAD platform as a point-of-care device for the early diagnosis and prognosis of AMI.

Vertical flow assays based on core-shell SERS nanotags for multiplex prostate cancer biomarker detection.

Rapid, simultaneous, and sensitive quantification of multiplex prostate biomarkers plays an important role in early diagnosis, especially for obese men and patients. Herein, a surface-enhanced Raman scattering (SERS)-based vertical flow assay (VFA) is presented for simultaneous detection of multiplex prostate cancer biomarkers, such as prostate-specific antigen (PSA), carcinoembryonic antigen (CEA), and alpha-fetoprotein (AFP) on a single test spot. In practice, Raman dyes (RDs) encoded core-shell SERS nanotags instead of conventional gold colloids used in the colorimetric assay are employed in the sensing membrane of SERS based VFAs for multiplex protein detection. Because of the enhanced Raman signal of the core-shell nanostructure and the high surface area to volume ratio (SVR) of the porous sensing membrane, this proposed biosensor shows a wide linear dynamic range (LDR) with detection limits of 0.37, 0.43, and 0.26 pg mL-1 for PSA, CEA, and AFP, respectively, suggesting that this approach can be a good candidate in point of care testing (POCT) for rapid and sensitive biomarker detection and has a huge potential in multiplex analysis and cancer diagnosis.

Persistent metabolic changes in HIV-infected patients during the first year of combination antiretroviral therapy

The HIV-human metabolic relationship is a complex interaction convoluted even more by antiretroviral therapy (cART) and comorbidities. The ability of cART to undo the HIV induced metabolic dysregulation is unclear and under-investigated. Using targeted metabolomics and multiplex immune biomarker analysis, we characterized plasma samples obtained from 18 untreated HIV-1-infected adult patients and compared these to a non-HIV infected (n = 23) control population. The biogenic amine perturbations during an untreated HIV infection implicated altered tryptophan- nitrogen- and muscle metabolism. Furthermore, the lipid profiles of untreated patients were also significantly altered compared to controls. In untreated HIV infection, the sphingomyelins and phospholipids correlated negatively to markers of infection IP-10 and sIL-2R whereas a strong association was found between triglycerides and MCP-1. In a second cohort, we characterized plasma samples obtained from 28 HIV-1-infected adult patients before and 12 months after the start of cART, to investigate the immune-metabolic changes associated with cART. The identified altered immune-metabolic pathways of an untreated HIV infection showed minimal change after 12 months of cART. In conclusion, 12 months of cART impacts only mildly on the metabolic dysregulation underlying an untreated HIV infection and provide insights into the comorbidities present in virally suppressed HIV patients.