CXCL1: A new diagnostic biomarker for human tuberculosis discovered using Diversity Outbred mice

More humans have died of tuberculosis (TB) than any other infectious disease and millions still die each year. Experts advocate for blood-based, serum protein biomarkers to help diagnose TB, which afflicts millions of people in high-burden countries. However, the protein biomarker pipeline is small. Here, we used the Diversity Outbred (DO) mouse population to address this gap, identifying five protein biomarker candidates. One protein biomarker, serum CXCL1, met the World Health Organization’s Targeted Product Profile for a triage test to diagnose active TB from latent M.tb infection (LTBI), non-TB lung disease, and normal sera in HIV-negative, adults from South Africa and Vietnam. To find the biomarker candidates, we quantified seven immune cytokines and four inflammatory proteins corresponding to highly expressed genes unique to progressor DO mice. Next, we applied statistical and machine learning methods to the data, i.e., 11 proteins in lungs from 453 infected and 29 non-infected mice. After searching all combinations of five algorithms and 239 protein subsets, validating, and testing the findings on independent data, two combinations accurately diagnosed progressor DO mice: Logistic Regression using MMP8; and Gradient Tree Boosting using a panel of 4: CXCL1, CXCL2, TNF, IL-10. Of those five protein biomarker candidates, two (MMP8 and CXCL1) were crucial for classifying DO mice; were above the limit of detection in most human serum samples; and had not been widely assessed for diagnostic performance in humans before. In patient sera, CXCL1 exceeded the triage diagnostic test criteria (>90% sensitivity; >70% specificity), while MMP8 did not. Using Area Under the Curve analyses, CXCL1 averaged 94.5% sensitivity and 88.8% specificity for active pulmonary TB (ATB) vs LTBI; 90.9% sensitivity and 71.4% specificity for ATB vs non-TB; and 100.0% sensitivity and 98.4% specificity for ATB vs normal sera. Our findings overall show that the DO mouse population can discover diagnostic-quality, serum protein biomarkers of human TB.

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Identification and Evaluation of Serum Protein Biomarkers Which Differentiate Psoriatic from Rheumatoid Arthritis

10.1101/2020.06.23.20138552 ◽

2020 ◽

Author(s):

Angela Mc Ardle ◽

Anna Kwasnik ◽

Agnes Szenpetery ◽

Melissa Jones ◽

Belinda Hernandez ◽

...

Keyword(s):

Rheumatoid Arthritis ◽

Serum Protein ◽

Clinical Decision Making ◽

Multiple Reaction Monitoring ◽

Area Under The Curve ◽

Clinical Decision ◽

Additional Patient ◽

Second Phase ◽

Protein Biomarkers ◽

Protein Discovery

AbstractObjectivesTo identify serum protein biomarkers which might separate early inflammatory arthritis (EIA) patients with psoriatic arthritis (PsA) from those with rheumatoid arthritis (RA) to provide an accurate diagnosis and support appropriate early intervention.MethodsIn an initial protein discovery phase, the serum proteome of a cohort of patients with PsA and RA was interrogated using unbiased liquid chromatography mass spectrometry (LC-MS/MS) (n=64 patients), a multiplexed antibody assay (Luminex) for 48 proteins (n=64 patients) and an aptamer-based assay (SOMAscan) targeting 1,129 proteins (n=36 patients). Subsequently, analytically validated targeted multiple reaction monitoring (MRM) assays were developed to further evaluate those proteins identified as discriminatory during the discovery. During an initial verification phase, MRM assays were developed to a panel of 150 proteins (by measuring a total of 233 peptides) and used to re-evaluate the discovery cohort (n=60). During a second verification phase, the panel of proteins was expanded to include an additional 23 proteins identified in other proteomic discovery analyses of arthritis patients. The expanded panel was evaluated using a second, independent cohort of PsA and RA patients (n=167).ResultsMultivariate analysis of the protein discovery data revealed that it was possible to discriminate PsA from RA patients with an area under the curve (AUC) of 0.94 for nLC-MS/MS, 0.69 for Luminex based measurements; 0.73 for SOMAscan analysis. During the initial verification phase, random forest models confirmed that proteins measured by MRM could differentiate PsA and RA patients with an AUC of 0.79 and during the second phase of verification the expanded panel could segregate the two disease groups with an AUC of 0.85.ConclusionWe report a serum protein biomarker panel which can separate EIA patients with PsA from those with RA. We suggest that the routine use of such a panel in EIA patients will improve clinical decision making and with continued evaluation and refinement using additional patient cohorts will support the development of a diagnostic test for patients with PsA.

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Novel circulating protein biomarkers for thyroid cancer determined through data-independent acquisition mass spectrometry

PeerJ ◽

10.7717/peerj.9507 ◽

2020 ◽

Vol 8 ◽

pp. e9507

Author(s):

Dandan Li ◽

Jie Wu ◽

Zhongjuan Liu ◽

Ling Qiu ◽

Yimin Zhang

Keyword(s):

Mass Spectrometry ◽

Area Under The Curve ◽

High Sensitivity ◽

Factor H ◽

Complement Factor ◽

Protein Biomarkers ◽

Serum Samples ◽

Data Independent Acquisition ◽

Median Serum ◽

And Control

Background Distinguishing between different types of thyroid cancers (TC) remains challenging in clinical laboratories. As different tumor types require different clinical interventions, it is necessary to establish new methods for accurate diagnosis of TC. Methods Proteomic analysis of the human serum was performed through data-independent acquisition mass spectrometry for 29 patients with TC (stages I–IV): 13 cases of papillary TC (PTC), 10 cases of medullary TC (MTC), and six cases follicular TC (FTC). In addition, 15 patients with benign thyroid nodules (TNs) and 10 healthy controls (HCs) were included in this study. Subsequently, 17 differentially expressed proteins were identified in 291 patients with TC, including 247 with PTC, 38 with MTC, and six with FTC, and 69 patients with benign TNs and 176 with HC, using enzyme-linked immunosorbent assays. Results In total, 517 proteins were detected in the serum samples using an Orbitrap Q-Exactive-plus mass spectrometer. The amyloid beta A4 protein, apolipoprotein A-IV, gelsolin, contactin-1, gamma-glutamyl hydrolase, and complement factor H-related protein 1 (CFHR1) were selected for further analysis. The median serum CFHR1 levels were significantly higher in the MTC and FTC groups than in the PTC and control groups (P < 0.001). CFHR1 exhibited higher diagnostic performance in distinguishing patients with MTC from those with PTC (P < 0.001), with a sensitivity of 100.0%, specificity of 85.08%, area under the curve of 0.93, and detection cut-off of 0.92 ng/mL. Conclusion CFHR1 may serve as a novel biomarker to distinguish PTC from MTC with high sensitivity and specificity.

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Discovery and Validation of a Six-Marker Serum Protein Signature for the Diagnosis of Active Pulmonary Tuberculosis

Journal of Clinical Microbiology ◽

10.1128/jcm.00467-17 ◽

2017 ◽

Vol 55 (10) ◽

pp. 3057-3071 ◽

Cited By ~ 31

Author(s):

Mary A. De Groote ◽

David G. Sterling ◽

Thomas Hraha ◽

Theresa M. Russell ◽

Louis S. Green ◽

...

Keyword(s):

Serum Protein ◽

Protein A ◽

Performance Criteria ◽

Sputum Smear ◽

Protein Biomarkers ◽

Serum Samples ◽

Active Pulmonary Tuberculosis ◽

Hiv Coinfection ◽

Tb Diagnostics ◽

Sensitivity Specificity

ABSTRACT New non-sputum biomarker tests for active tuberculosis (TB) diagnostics are of the highest priority for global TB control. We performed in-depth proteomic analysis using the 4,000-plex SOMAscan assay on 1,470 serum samples from seven countries where TB is endemic. All samples were from patients with symptoms and signs suggestive of active pulmonary TB that were systematically confirmed or ruled out for TB by culture and clinical follow-up. HIV coinfection was present in 34% of samples, and 25% were sputum smear negative. Serum protein biomarkers were identified by stability selection using L1-regularized logistic regression and by Kolmogorov-Smirnov (KS) statistics. A naive Bayes classifier using six host response markers (HR6 model), including SYWC, kallistatin, complement C9, gelsolin, testican-2, and aldolase C, performed well in a training set (area under the sensitivity-specificity curve [AUC] of 0.94) and in a blinded verification set (AUC of 0.92) to distinguish TB and non-TB samples. Differential expression was also highly significant ( P < 10 −20 ) for previously described TB markers, such as IP-10, LBP, FCG3B, and TSP4, and for many novel proteins not previously associated with TB. Proteins with the largest median fold changes were SAA (serum amyloid protein A), NPS-PLA2 (secreted phospholipase A2), and CA6 (carbonic anhydrase 6). Target product profiles (TPPs) for a non-sputum biomarker test to diagnose active TB for treatment initiation (TPP#1) and for a community-based triage or referral test (TPP#2) have been published by the WHO. With 90% sensitivity and 80% specificity, the HR6 model fell short of TPP#1 but reached TPP#2 performance criteria. In conclusion, we identified and validated a six-marker signature for active TB that warrants diagnostic development on a patient-near platform.

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Predictors of long-term prognosis in rheumatoid arthritis-related interstitial lung disease

10.21203/rs.3.rs-707140/v2 ◽

2021 ◽

Author(s):

Juan Chen ◽

Yaqiong Chen ◽

Dehao Liu ◽

Yihua Lin ◽

Lei Zhu ◽

...

Keyword(s):

Interstitial Lung Disease ◽

Lung Disease ◽

Serum Protein ◽

Serum Proteins ◽

Pulmonary Function Tests ◽

Protein Biomarkers ◽

Serum Samples ◽

Binary Logistic Regression Model ◽

Longitudinal Outcome ◽

Over Time

Abstract The aim of the study was to identify specific clinical and serum protein biomarkers that are associated with longitudinal outcome of RA-associated interstitial lung disease（RA-ILD). 60 RA patients with clinical and serological profiles were assessed by HRCT and pulmonary function tests (PFTs) at baseline (Year 0) and 5 years post enrollment (Year 5). Progression versus non-progression was defined based on changes in Quantitative Modified HRCT scores and PFTs over time. Specific serum protein biomarkers were assessed in serum samples at baseline and Year 5 by Multiplex enzyme-linked immunosorbent assays (ELISAs). At Year 5, 32% of patients demonstrated progressive RA-ILD, 35% were stable, and 33% improved. Baseline age and rheumatoid factor (RF) were significantly different between RA-ILD outcomes of progression vs. no-progression (p< 0.05). Changes in levels of CXCL11/I-TAC and MMP13 over 5 years also distinguished pulmonary outcomes (p< 0.05). A final binary logistic regression model revealed that baseline age and changes in serum MMP13 were associated with RA-ILD progression at Year 5 (p< 0.05), with an AUC of 0.7569. Collectively, these analyses demonstrated that baseline clinical variables (age, RF) and shifts in levels of selected serum proteins (CXCL11/I-TAC, MMP13) were strongly linked to RA-ILD outcome over time.

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Exploratory analysis of multiprotein serum predictors at baseline of progression-free survival of ipilimumab or ipilimumab and nivolumab in the Checkmate-069 study.

Journal of Clinical Oncology ◽

10.1200/jco.2017.35.15_suppl.9571 ◽

2017 ◽

Vol 35 (15_suppl) ◽

pp. 9571-9571

Author(s):

Krisztian Homicsko ◽

Michel A. Cuendet ◽

Agata Mlynska ◽

Bianca Moura ◽

Christine Horak ◽

...

Keyword(s):

Serum Protein ◽

Checkpoint Inhibitors ◽

Stage Iv ◽

Progression Free Survival ◽

Exploratory Analysis ◽

Protein Markers ◽

Protein Biomarkers ◽

Serum Samples ◽

Baseline Serum ◽

Free Survival

9571 Background: Checkpoint inhibitors have revolutionized the treatment of stage IV melanoma patients. Selection of patients for PD-1 monotherapy or CTLA4/PD1 combination remains an important challenge. We set out to perform a discovery study of pretreatment serum protein biomarkers to identify predictors of progression free survival (PFS) for ipilimumab (IPI) or ipilimumab/nivolumab (IPI/NIVO). Methods: We performed an exploratory analysis of baseline serum samples from 135 treatment-naive patients with metastatic melanoma included in the randomized phase II clinical trial, CheckMate 069 (NCT01927419). We used the RayBiotech 440 human cytokine array and evaluated the relationship of serum protein levels with 44 clinical parameters. R, Prism 7.0 and TensorFlow were used for analyses. Results: We focused on correlation of serum protein markers with PFS as a predictor of long-term benefit. In the IPI arm (n = 46), high FGF4 correlated with worse PFS outcome (p = 0.0012). However, FGF4 levels alone were unable to select responsive vs. non-responsive patients. In contrast, a set of three markers consisting of FGF4 ( < 760pg/ml), CCL15 ( > 2.7 ng/ml), and TACE ( > 600pg/ml) separated non-progressing versus progressing patients. Moreover a small group of FGF4-high patients who were concomitantly TIM-3-low also had longer PFS (combined of both: p = 0.0004, HRlogrank: 0.07, 95% CI: 0.03279 to 0.1533). The same markers did not discriminate between IPI/NIVO patients (p = 0.467, HR: 15). In the IPI/NIVO arm, three different markers could select patients. Patients either with low CCL2 ( < 72 pg/ml) or alternatively with high CCL2 combined with high PDGF-AA ( > 8.2 ng/ml) and low GASP-1 ( < 1.3 ng/ml) had longer PFS (p < 0.0001, HR: 0.115, 95% CI: 0.03848 to 0.3408). Conversely, these markers did not predict benefit for IPI-monotherapy. Conclusions: In this study we identified protein signatures in baseline serum that correlate with PFS for therapies with IPI or IPI/NIVO. The markers were exclusive for IPI or IPI/NIVO but not for both. Additional research is warranted to substantiate these results and evaluate the possibility of incorporating into clinical practice.

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Mouse population-based evaluation of urinary protein and miRNA biomarker performance associated with cisplatin renal injury

Experimental Biology and Medicine ◽

10.1177/1535370217740854 ◽

2017 ◽

Vol 243 (3) ◽

pp. 237-247 ◽

Cited By ~ 5

Author(s):

Alison H Harrill ◽

Haixia Lin ◽

Julia Tobacyk ◽

John C Seely

Keyword(s):

Blood Urea Nitrogen ◽

Kidney Injury ◽

Urinary Protein ◽

Cell Necrosis ◽

Protein Biomarkers ◽

Tubule Cell ◽

Mouse Population ◽

Specificity And Sensitivity ◽

Diversity Outbred ◽

Mirna Species

Discovery and qualification of novel biomarkers with improved specificity and sensitivity for detection of xenobiotic-induced injuries is an area of active research across multiple sectors. However, the majority of efforts in this arena have used genetically limited rodent stocks that lack variability in xenobiotic responses inherent to genetically heterogeneous human populations. In this study, genetically diverse Diversity Outbred (DO) mice were used as a surrogate for human clinical populations to investigate performance of urinary kidney biomarkers against classical preclinical kidney injury biomarkers (blood urea nitrogen [BUN] and serum creatinine). In this study, cisplatin was used as a paradigm kidney toxicant, with female adult DO mice exposed to a single injection (5 mg/kg) of cisplatin or vehicle and necropsied 72 h post-exposure and 18 h following overnight urine collection. Interindividual variability in kidney toxicity was observed, with DO mice experiencing either no tubule cell necrosis or minimal-mild necrosis. A panel of urinary protein biomarkers and profiled miRNAs were assessed by receiver-operating characteristic curves as to their ability to distinguish non-responder versus responder animals, as defined by histopathological evidence of renal tubule cell necrosis. A surprising outcome of these studies was that BUN was elevated alongside of urinary miRNA and protein biomarkers in animals with grade 2 proximal tubular cell necrosis; but not elevated with grade 1 necrosis. These studies demonstrate a novel approach for using a rodent population to better assess sensitivity of candidate biomarkers, especially for proposed clinical applications. Impact statement Recent studies have indicated that several urinary proteins and miRNA species may be suitable as biomarkers for acute kidney injury. A major focus on biomarker qualification is demonstrating improved specificity and sensitivity over gold standard tests. In this study, a mouse population model, Diversity Outbred mice, was used to demonstrate that neither the urinary protein markers nor the miRNA species assayed in urine could reliably detect low severity kidney injury better than blood urea nitrogen. This study has implications for use of these biomarkers in the clinic, where interindividual heterogeneity is present within patient populations and for which the underlying tissue pathology may not be known.

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A 1024-sample serum analyzer chip for cancer diagnostics

Lab on a Chip ◽

10.1039/c3lc51153g ◽

2014 ◽

Vol 14 (15) ◽

pp. 2642-2650 ◽

Cited By ~ 32

Author(s):

Jose L. Garcia-Cordero ◽

Sebastian J. Maerkl

Keyword(s):

Blood Serum ◽

Limit Of Detection ◽

Cancer Diagnostics ◽

Protein Biomarkers ◽

Serum Samples ◽

Microfluidic Platform

A microarray/microfluidic platform measures four protein biomarkers in 1024 blood serum samples for 4096 assays per device with a limit-of-detection of ~1 pM.

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Comparison of Proteomic Technologies for Blood-Based Detection of Colorectal Cancer

International Journal of Molecular Sciences ◽

10.3390/ijms22031189 ◽

2021 ◽

Vol 22 (3) ◽

pp. 1189

Author(s):

Megha Bhardwaj ◽

Tobias Terzer ◽

Petra Schrotz-King ◽

Hermann Brenner

Keyword(s):

Colorectal Cancer ◽

Multiple Reaction Monitoring ◽

Area Under The Curve ◽

Superior Performance ◽

Blood Protein ◽

Protein Biomarkers ◽

Serum Samples ◽

Functional Protein ◽

Novel Technologies ◽

Diagnostic Potential

Blood-based protein biomarkers are increasingly being explored as supplementary or efficient alternatives for population-based screening of colorectal cancer (CRC). The objective of the current study was to compare the diagnostic potential of proteins measured with different proteomic technologies. The concentrations of protein biomarkers were measured using proximity extension assays (PEAs), liquid chromatography/multiple reaction monitoring–mass spectrometry (LC/MRM-MS) and quantibody microarrays (QMAs) in plasma samples of 56 CRC patients and 99 participants free of neoplasms. In another approach, proteins were measured in serum samples of 30 CRC cases and 30 participants free of neoplasm using immunome full-length functional protein arrays (IpAs). From all the measurements, 9, 6, 35 and 14 protein biomarkers overlapped for comparative evaluation of (a) PEA and LC/MRM-MS, (b) PEA and QMA, (c) PEA and IpA, and (d) LC/MRM-MS and IpA measurements, respectively. Correlation analysis was performed, along with calculation of the area under the curve (AUC) for assessing the diagnostic potential of each biomarker. DeLong’s test was performed to assess the differences in AUC. Evaluation of the nine biomarkers measured with PEA and LC/MRM-MS displayed correlation coefficients >+0.6, similar AUCs and DeLong’s p-values indicating no differences in AUCs for biomarkers like insulin-like growth factor binding protein 2 (IGFBP2), matrix metalloproteinase 9 (MMP9) and serum paraoxonase lactonase 3 (PON3). Comparing six proteins measured with PEA and QMA showed good correlation and similar diagnostic performance for only one protein, growth differentiation factor 15 (GDF15). The comparison of 35 proteins measured with IpA and PEA and 14 proteins analyzed with IpA and LC/MRM-MS revealed poor concordance and comparatively better AUCs when measured with PEA and LC/MRM-MS. The comparison of different proteomic technologies suggests the superior performance of novel technologies like PEA and LC/MRM-MS over the assessed array-based technologies in blood-protein-based early detection of CRC.

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Analytical assessment of Beckman Coulter Access anti-SARS-CoV-2 IgG immunoassay

10.1101/2020.11.05.20226555 ◽

2020 ◽

Author(s):

Maurizio Ruscio ◽

Elisa D’Agnolo ◽

Anna Belgrano ◽

Mario Plebani ◽

Giuseppe Lippi

Keyword(s):

Limit Of Detection ◽

Area Under The Curve ◽

Molecular Testing ◽

The Novel ◽

Serum Samples ◽

Humoral Immune ◽

Antibody Titers ◽

Chemiluminescent Immunoassay ◽

Analytical Assessment ◽

Paired Serum

AbstractBackgroundThe approach to diagnosing, treating and monitoring severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection relies strongly on laboratory resources, with serological testing representing the mainstay for studying the onset, nature and persistence of humoral immune response. This study was aimed at evaluating the analytical performance of the novel Beckman Coulter anti-SARS-CoV-2 IgG chemiluminescent immunoassay.MethodsThis analytical assessment encompassed the calculation of intra-assay, inter-assay and total imprecision, linearity, limit of blank (LOB), limit of detection (LOD), functional sensitivity, and comparison of anti-SARS-CoV-2 antibodies values obtained on paired serum samples using DiaSorin Liaison SARS-CoV-2 S1/S2 IgG and Roche Elecsys Anti-SARS-CoV-2 total antibodies. Diagnostic performance was also tested against results of molecular testing on nasopharyngeal swabs, collected over the previous 4 months.ResultsIntra-assay, inter-assay and total imprecision of Beckman Coulter anti-SARS-CoV-2 IgG were between 4.3-4.8%, 2.3-3.9% and 4.9-6.2%, respectively. The linearity of the assay was excellent between 0.11-18.8 antibody titers. The LOB, LOD and functional sensitivity were 0.02, 0.02 and 0.05, respectively. The diagnostic accuracy (area under the curve; AUC) of Beckman Coulter anti-SARS-CoV-2 IgG compared to molecular testing was 0.87 (95% CI, 0.84-0.91; p<0.001) using manufacturer’s cut-off, and increased to 0.90 (95% CI, 0.86-0.94; p<0.001) with antibody titers. The AUC was non-significantly different from that of Roche Elecsys Anti-SARS-CoV-2, but was always higher than that of DiaSorin Liaison SARS-CoV-2 S1/S2 IgG. The correlation of Beckman Coulter Access SARS-CoV-2 IgG was 0.80 (95% CI, 0.75-0.84; p<0.001) with Roche Elecsys Anti-SARS-CoV-2 and 0.72 (95% CI, 0.66-0.77; p<0.001) with DiaSorin Liaison SARS-CoV-2 S1/S2 IgG, respectively.ConclusionsThe results of this analytical evaluation of Beckman Coulter Access anti-SARS-CoV-2 IgG suggests that this fully-automated chemiluminescent immunoassay represents a valuable resource for large and accurate seroprevalence surveys.

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Provista 002 prospective randomized trial utilizing Videssa in conjunction with imaging to detect breast cancer from patients with imaging findings age 25-75.

Journal of Clinical Oncology ◽

10.1200/jco.2015.33.28_suppl.31 ◽

2015 ◽

Vol 33 (28_suppl) ◽

pp. 31-31

Author(s):

David Emery Reese ◽

Rao Mulpuri ◽

Kasey Benson ◽

Elias Letsios ◽

Christa Corn ◽

...

Keyword(s):

Breast Cancer ◽

Early Detection ◽

Serum Protein ◽

Invasive Breast Cancer ◽

Breast Biopsy ◽

Dense Breast ◽

Protein Biomarkers ◽

Serum Samples ◽

Blood Draw ◽

Specific Patient

31 Background: An approach to detection that relies on biochemical markers of breast cancer would significantly contribute to more accurate detection in women with suspicious lesions. The combination of imaging, which identifies anatomical anomalies consistent with cancer with proteomic approaches promises to provide a powerful detection paradigm. A proteomic detection approach would provide a powerful tool for the detection of breast cancer in women with dense breast, a diagnosis that is difficult utilizing imaging alone. While protein signatures for the presence of breast cancer have remained elusive, we have developed a novel approach that combines serum protein biomarkers with tumor-associated autoantibodies. We utilized prospectively collected serum samples to develop novel algorithms for use in conjunction with imaging. We tested whether the assay was able to distinguish benign from invasive breast cancers in a prospective, randomized setting. Methods: Provista-002 enrolled 509 patients from multiple sites across the US and followed for 6 months after the first blood draw under IRB approval. Patients were consented after assessment of a BIRADS 3 or 4 and considered eligible if they were between 25 and 75 years of age, no history of cancer, no prior breast biopsy within the last six months, and were assessed as BIRADS 3 or 4 within 28 days. Upon enrollment, patients were randomized to either training or validation groups. Clinical truth was considered equal to or greater than 80% sensitivity and/or specificity. Serum protein biomarkers and tumor-associated autoantibodies identified in prior proteomic screens were measured prior to biopsy in a blinded and randomized fashion. Individual biomarker concentrations, together with specific patient data were evaluated using various logistic regression models developed from prior studies. Results: Provista-002 demonstrated a clear difference between women under the age of 50 from over the age of 50 in both markers required for early detection and the algorithm (models) used to distinguish benign from invasive breast cancer/DCIS. This is the first study that demonstrates clearly that modeling of proteomic patterns differs significantly in the BIRADS 3/4 setting and in the detection of early breast cancer lesions. As demonstrated in Provista – 001, we did not observe a statistical difference between early detection in women with dense breast and those with mostly fatty breast. The ability of the Videssa assay to distinguish between invasive breast cancer/DCIS from benign breast conditions was demonstrated as 85.7% sensitivity and 82.4% specificity for women under the age of 50 (although, unfortunately all lesions were pathologically confirmed to be CIS) and in women over the age of 50, the sensitivity was 86.4% and specificity was 83%. Conclusions: As above, both age groups of women needed distinct marker sets and linear regressions to distinguish benign (non-clinically significant) lesions from those that needed further evaluation (DCIS and IBC). Clinical trial information: NCT02078570.

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