Targeted Mass Spectrometry of Longitudinal Patient Sera Reveals LTBP1 as a Potential Surveillance Biomarker for High-Grade Serous Ovarian Carcinoma

High-grade serous ovarian carcinoma (HGSC) is the most prevalent subtype of epithelial ovarian cancer. The combination of a high rate of recurrence and novel therapies in HGSC necessitates an accurate assessment of the disease. Currently, HGSC response to treatment and recurrence are monitored via immunoassay of serum levels of the glycoprotein CA125. CA125 levels predictably rise at HGSC recurrence; however, it is likely that the disease is progressing even before it is detectable through CA125. This may explain why treating solely based on CA125 increase has not been associated with improved outcomes. Thus, additional biomarkers that monitor HGSC progression and cancer recurrence are needed. For this purpose, we developed a scheduled parallel reaction monitoring mass spectrometry (PRM-MS) assay for the quantification of four previously identified HGSC-derived glycopeptides (from proteins FGL2, LGALS3BP, LTBP1, and TIMP1). We applied the assay to quantify their longitudinal expression profiles in 212 serum samples taken from 34 HGSC patients during disease progression. Analyses revealed that LTBP1 best-mirrored tumor load, dropping as a result of cancer treatment in 31 out of 34 patients and rising at HGSC recurrence in 28 patients. Additionally, LTBP1 rose earlier during remission than CA125 in 11 out of 25 platinum-sensitive patients with an average lead time of 116.4 days, making LTBP1 a promising candidate for monitoring of HGSC recurrence.

High CTLA-4 transcriptomic expression correlates with high expression of other checkpoints and with immunotherapy outcome

Background

CTLA-4 impedes the immune system's antitumor response. There are two Food and Drug Administration-approved anti-CTLA-4 agents - ipilimumab and tremelimumab - both used together with anti-PD-1/PD-L1 agents.

Objective

To assess the prognostic implications and immunologic correlates of high CTLA-4 in tumors of patients on immunotherapy and those on non-immunotherapy treatments.

Design/methods

We evaluated RNA expression levels in a clinical-grade laboratory and clinical correlates of CTLA-4 and other immune checkpoints in 514 tumors, including 489 patients with advanced/metastatic cancers and full outcome annotation. A reference population (735 tumors; 35 histologies) was used to normalize and rank transcript abundance (0-100 percentile) to internal housekeeping gene profiles.

Results

The most common tumor types were colorectal (140/514, 27%), pancreatic (55/514, 11%), breast (49/514, 10%), and ovarian cancers (43/514, 8%). Overall, 87 of 514 tumors (16.9%) had high CTLA-4 transcript expression (⩾75th percentile rank). Cancers with the largest proportion of high CTLA-4 transcripts were cervical cancer (80% of patients), small intestine cancer (33.3%), and melanoma (33.3%). High CTLA-4 RNA independently/significantly correlated with high PD-1, PD- L2, and LAG3 RNA levels (and with high PD-L1 in univariate analysis). High CTLA-4 RNA expression was not correlated with survival from the time of metastatic disease [N = 272 patients who never received immune checkpoint inhibitors (ICIs)]. However, in 217 patients treated with ICIs (mostly anti-PD-1/anti-PD- L1), progression-free survival (PFS) and overall survival (OS) were significantly longer among patients with high versus non-high CTLA-4 expression [hazard ratio, 95% confidence interval: 0.6 (0.4-0.9) p = 0.008; and 0.5 (0.3-0.8) p = 0.002, respectively]; results were unchanged when 18 patients who received anti-CTLA-4 were omitted. Patients whose tumors had high CTLA-4 and high PD-L1 did best; those with high PD-L1 but non-high CTLA-4 and/or other expression patterns had poorer outcomes for PFS (p = 0.004) and OS (p = 0.009) after immunotherapy.

Conclusion

High CTLA-4, especially when combined with high PD-L1 transcript expression, was a significant positive predictive biomarker for better outcomes (PFS and OS) in patients on immunotherapy.

Stress Keratin 17 Is a Predictive Biomarker Inversely Associated with Response to Immune Check-Point Blockade in Head and Neck Squamous Cell Carcinomas and Beyond

Low response rates in immune check-point blockade (ICB)-treated head and neck squamous cell carcinoma (HNSCC) drive a critical need for robust, clinically validated predictive biomarkers. Our group previously showed that stress keratin 17 (CK17) suppresses macrophage-mediated CXCL9/CXCL10 chemokine signaling involved in attracting activated CD8+ T cells into tumors, correlating with decreased response rate to pembrolizumab-based therapy in a pilot cohort of ICB-treated HNSCC (n = 26). Here, we performed an expanded analysis of the predictive value of CK17 in ICB-treated HNSCC according to the REMARK criteria and investigated the gene expression profiles associated with high CK17 expression. Pretreatment samples from pembrolizumab-treated HNSCC patients were stained via immunohistochemistry using a CK17 monoclonal antibody (n = 48) and subjected to spatial transcriptomic profiling (n = 8). Our findings were validated in an independent retrospective cohort (n = 22). CK17 RNA expression in pembrolizumab-treated patients with various cancer types was investigated for predictive significance. Of the 48 patients (60% male, median age of 61.5 years), 21 (44%) were CK17 high, and 27 (56%) were CK17 low. A total of 17 patients (35%, 77% CK17 low) had disease control, while 31 patients (65%, 45% CK17 low) had progressive disease. High CK17 expression was associated with a lack of disease control (p = 0.037), shorter time to treatment failure (p = 0.025), and progression-free survival (PFS, p = 0.004), but not overall survival (OS, p = 0.06). A high CK17 expression was associated with lack of disease control in an independent validation cohort (p = 0.011). PD-L1 expression did not correlate with CK17 expression or clinical outcome. CK17 RNA expression was predictive of PFS and OS in 552 pembrolizumab-treated cancer patients. Our findings indicate that high CK17 expression may predict resistance to ICB in HNSCC patients and beyond.

Clinical Proteomics for Meningioma: An Integrated Workflow for Quantitative Proteomics and Biomarker Validation in Formalin-Fixed Paraffin-Embedded Tissue Samples

Clinical proteomics is a rapidly emerging frontier in laboratory medicine. High-throughput proteomic investigations of biopsy tissues provide mechanistic insights into complex human diseases. For large-scale proteomics, formalin-fixed and paraffin-embedded (FFPE) tissue samples offer a viable alternative to fresh-frozen (FF) tissues that have restricted availability. In this context, meningioma is one of the most common primary brain tumors where innovation in diagnostics and therapeutic targets can benefit from clinical proteomics. We present here an integrated workflow for quantitative proteomics and biomarker validation of meningioma FFPE tissues. Applying label-free quantitative (LFQ) proteomics, we reproducibly (Pearson's correlation: 0.84-0.91) obtained an in-depth proteome coverage (nearly 4000 proteins per sample) from 120 min gradient of single unfractionated mass spectrometry run. Furthermore, building upon LFQ data and literature curated set of meningioma-associated proteins, we validated VIM, AHNAK, and CLU from FFPE tissues using selected reaction monitoring (SRM) assay and compared its performance with FF tissues. This study illustrates how knowledge from label-free proteomics can be integrated for selecting peptides for targeted validation and suggests that FFPE tissues are comparable to FF tissues for SRM assays. This quantitative clinical proteomics workflow is scalable for large-scale clinical diagnostics studies in the future, for example, utilizing the global repository of FFPE tissues in meningioma and possibly in other cancers.

Odd Chain Fatty Acids Are Not Robust Biomarkers for Dietary Intake of Fiber

SCOPE

Prior investigation has suggested a positive association between increased colonic propionate production and circulating odd-chain fatty acids (OCFAs; pentadecanoic acid [C15:0], heptadecanoic acid [C17:0]). As the major source of propionate in humans is the microbial fermentation of dietary fiber, OCFAs have been proposed as candidate biomarkers of dietary fiber. The objective of this study is to critically assess the plausibility, robustness, reliability, dose-response, time-response aspects of OCFAs as potential biomarkers of fermentable fibers in two independent studies using a validated analytical method.

METHODS AND RESULTS

OCFAs are first assessed in a fiber supplementation study, where 21 participants received 10 g dietary fiber supplementation for 7 days. OCFAs are then assessed in a highly controlled inpatient setting, which 19 participants consumed a high fiber (45.1 g per day) and a low fiber diet (13.6 g per day) for 4 days. Collectively in both studies, dietary intakes of fiber as fiber supplementations or having consumed a high fiber diet do not increase circulating levels of OCFAs. The dose and temporal relations are not observed.

CONCLUSION

Current study has generated new insight on the utility of OCFAs as fiber biomarkers and highlighted the importance of critical assessment of candidate biomarkers before application.

Pre-Therapeutic VEGF Level in Plasma Is a Prognostic Bio-Marker in Head and Neck Squamous Cell Carcinoma (HNSCC)

Simple Summary

In the context of a growing variety in treatment strategies for patients with cancer, especially approaches based on antiangiogenetic pathways, we aimed to identify a useful biomarker for patients with head and neck squamous cell carcinoma (HNSCC). Our experimental results detected vascular endothelial growth factor (VEGF) in patients’ pre-therapeutic plasma, and not serum, which serves as a suitable biomarker for outcome prognostication. Results were validated in an independent cohort, confirming VEGF as an independent predictor (Pi) of outcomes in HNSCC patients. Therefore, pre-therapeutic VEGF in plasma may be an attractive biomarker in future HNSCC studies.

Abstract

Vascular endothelial growth factor (VEGF) is centrally involved in cancer angiogenesis. We hypothesized that pre-therapeutic VEGF levels in serum and plasma differ in their potential as biomarkers for outcomes in head and neck squamous cell carcinoma (HNSCC) patients. As prospectively defined in the study protocols of TRANSCAN-DietINT and NICEI-CIH, we measured VEGF in pretreatment serum and plasma of 75 HNSCC test cohort (TC) patients. We analyzed the prognostic value of VEGF concentrations in serum (VEGF_Serum) and plasma (VEGF_Plasma) for event-free survival (EFS) utilizing receiver-operating characteristics (ROC). Mean VEGF concentrations in plasma (34.6, 95% CI 26.0–43.3 ng/L) were significantly lower (p = 3.35 × 10⁻¹⁸) than in serum (214.8, 95% CI 179.6–250.0 ng/L) but, based on ROC (area under the curve, AUC_Plasma = 0.707, 95% CI 0.573–0.840; p = 0.006 versus AUC_Serum = 0.665, 95% CI 0.528–0.801; p = 0.030), superiorly correlated with event-free survival (EFS) of TC patients. Youden indices revealed optimum binary classification with VEGF_Plasma 26 ng/L and VEGF_Serum 264 ng/L. Kaplan–Meier plots demonstrated superiority of VEGF_Plasma in discriminating patients regarding outcome. Patients with VEGF_Plasma < 26 ng/L had superior nodal (NC), local (LC) and loco-regional control (LRC) leading to significant prolonged progression-free survival (PFS) and EFS. We successfully validated VEGF_Plasma according the cut-off <26 ng/L as predictive for superior outcome in an independent validation cohort (iVC) of 104 HNSCC patients from the studies DeLOS-II and LIFE and found better outcomes including prolonged tumor-specific (TSS) and overall survival (OS). Outcomes in TC and iVC combined again was related to VEGF_Plasma, and multivariate Cox regression revealed that VEGF_Plasma was an independent outcome predictor. In HNSCC, pre-therapeutic VEGF_Plasma is prognostic for outcomes.

An examination of a novel multipanel of CSF biomarkers in the Alzheimer's disease clinical and pathological continuum

INTRODUCTION

This study examines the utility of a multipanel of cerebrospinal fluid (CSF) biomarkers complementing Alzheimer's disease (AD) biomarkers in a clinical research sample. We compared biomarkers across groups defined by clinical diagnosis and pTau₁₈₁ /Aβ₄₂ status (+/-) and explored their value in predicting cognition.

METHODS

CSF biomarkers amyloid beta (Aβ)₄₂ , pTau₁₈₁ , tTau, Aβ₄₀ , neurogranin, neurofilament light (NfL), α-synuclein, glial fibrillary acidic protein (GFAP), chitinase-3-like protein 1 (YKL-40), soluble triggering receptor expressed on myeloid cells 2 (sTREM2), S100 calcium binding protein B (S100B), and interleukin 6 (IL6), were measured with the NeuroToolKit (NTK) for 720 adults ages 40 to 93 years (mean age = 63.9 years, standard deviation [SD] = 9.0; 50 with dementia; 54 with mild cognitive impairment [MCI], 616 unimpaired).

RESULTS

Neurodegeneration and glial activation biomarkers were elevated in pTau₁₈₁ /Aβ₄₂ + MCI/dementia participants relative to all pTau₁₈₁ /Aβ₄₂ - participants. Neurodegeneration biomarkers increased with clinical severity among pTau₁₈₁ /Aβ₄₂ + participants and predicted worse cognitive performance. Glial activation biomarkers were unrelated to cognitive performance.

DISCUSSION

The NTK contains promising markers that improve the pathophysiological characterization of AD. Neurodegeneration biomarkers beyond tTau improved statistical prediction of cognition and disease stages.

A 17-Gene Panel Genomic Prostate Score Has Similar Predictive Accuracy for Adverse Pathology at Radical Prostatectomy in African American and European American Men

OBJECTIVE

To validate the 17-gene Oncotype DX Genomic Prostate Score (GPS) as a predictor of adverse pathology (AP) in African American (AA) men and to assess the distribution of GPS in AA and European American (EA) men with localized prostate cancer.

METHODS

The study populations were derived from 2 multi-institutional observational studies. Between February 2009 and September 2014, AA and EA men who elected immediate radical prostatectomy after a ≥10-core transrectal ultrasound biopsy were included in the study. Logistic regressions, area under the receiver operating characteristics curves (AUC), calibration curves, and predictive values were used to compare the accuracy of GPS. AP was defined as primary Gleason grade 4, presence of any Gleason pattern 5, and/or non-organ-confined disease (≥pT3aN0M0) at radical prostatectomy.

RESULTS

Overall, 96 AA and 76 EA men were selected and 46 (26.7%) had AP. GPS result was a significant predictor of AP (odds ratio per 20 GPS units [OR/20 units] in AA: 4.58; 95% confidence interval (CI) 1.8-11.5, P = .001; and EA: 4.88; 95% CI 1.8-13.5, P = .002). On multivariate analysis, there was no significant interaction between GPS and race (P >.10). GPS remained significant in models adjusted for either National Comprehensive Cancer Network (NCCN) risk group or Cancer of the Prostate Risk Assessment (CAPRA) score. In race-stratified models, area under the receiver operating characteristics curves for GPS/20 units was 0.69 for AAs vs 0.74 for EAs (P = .79). The GPS distributions were not statistically different by race (all P >.05).

CONCLUSION

In this clinical validation study, the Oncotype DX GPS is an independent predictor of AP at prostatectomy in AA and EA men with similar predictive accuracy and distributions.

Duchenne Muscular Dystrophy: recent advances in protein biomarkers and the clinical application

INTRODUCTION

Early biomarker discovery studies have praised the value of their emerging results, predicting an unprecedented impact on health care. Biomarkers are expected to provide tests with increased specificity and sensitivity compared to existing measures, improve the decision-making process, and accelerate the development of therapies. For rare disorders, like Duchenne Muscular Dystrophy (DMD) such biomarkers can assist the development of therapies, therefore also helping to find a cure for the disease.

AREA COVERED

State-of-the-art technologies have been used to identify blood biomarkers for DMD and efforts have been coordinated to develop and promote translation of biomarkers for clinical practice. Biomarker translation to clinical practice is however, adjoined by challenges related to the complexity of the disease, involving numerous biological processes, and the limited sample resources. This review highlights the current progress on the development of biomarkers, describing the proteomics technologies used, the most promising findings and the challenges encountered.

EXPERT OPINION

Strategies for effective use of samples combined with orthogonal proteomics methods for protein quantification are essential for translating biomarkers to the patient's bed side. Progress is achieved only if strong evidence is provided that the biomarker constitutes a reliable indicator of the patient's health status for a specific context of use.

Neuroinflammation PET Imaging: Current Opinion and Future Directions

Neuroinflammation is a key pathologic hallmark of numerous neurologic diseases, however, its exact role in vivo is yet to be fully understood. PET imaging enables investigation, quantification, and tracking of different neuroinflammation biomarkers in living subjects longitudinally. One such biomarker that has been imaged extensively using PET is translocator protein 18 kDa (TSPO). Although imaging TSPO has yielded valuable clinical data linking neuroinflammation to various neurodegenerative diseases, considerable limitations of TSPO PET have prompted identification of other more cell-specific and functionally relevant biomarkers. This review analyzes the clinical potential of available and emerging PET biomarkers of innate and adaptive immune responses, with mention of exciting future directions for the field.

Quality Control and Outlier Detection of Targeted Mass Spectrometry Data from Multiplex Protein Panels

Increased throughput as well as increased multiplexing of liquid chromatography coupled to selected reaction monitoring mass spectrometry (LC-SRM-MS) assays for protein quantification challenges routine data analysis. Despite the measurement of multiple transitions from multiple peptides, for clinical applications a single (quantifier) transition from one (quantifier) signature peptide is used to represent the protein quantity with most data used solely to validate the quantifier result. To support the generation of reliable protein results from multiplexed LC-SRM-MS assays with large sample numbers, we developed a data analysis process for quality control and outlier detection using data from an 11-protein multiplex LC-SRM-MS method for dried blood samples (195 492 chromatographic peaks from 1481 samples * 11 proteins * 2 peptides * 3 transitions * 2 isotopologues). The 2-tiered data analysis process detects outliers for ion transition ratio, peptide ratio, and % difference between duplicates, applying less stringent criteria to samples with a small % difference between duplicates (Tier 1) and more stringent criteria to samples with unassessed or a large % difference between duplicates (Tier 2). After manual peak review, 1127 samples (76%) were selected based on the sample quality. The data analysis process thereafter automatically selected quantifier transitions/peptides, removed quality control failures and outliers (8%), averaged duplicates, and generated a comprehensive report listing 6085 quality controlled protein-level results. The proposed data analysis process serves as a starting point toward standardized data analysis of multiplexed LC-SRM-MS protein assays.

Horizon 2020 SME-Instrument topic: clinical research for the validation of biomarkers and/or diagnostic medical devices

The European Commission released €130 million over 2014, 2015 and 2017 under the EU Framework Program for Research and Innovation, Horizon 2020, to support innovative small and medium-sized enterprises in the diagnostic area. The call topic focused on 'Clinical research for the validation of biomarkers and/or diagnostic medical devices'. It attracted 1194 applicants from all over Europe. The quality of the proposals was high and a large proportion of them were eligible for funding. In the majority, proposals were about in vitro diagnostics and tackled both clinical validation of new biomarkers and device optimization. The proposals dealt with various advanced technologies. One third of the proposers gave priority to the new and promising field of personalized medicine.

A five-CpG DNA methylation score to predict metastatic-lethal outcomes in men treated with radical prostatectomy for localized prostate cancer

BACKGROUND

Prognostic biomarkers for localized prostate cancer (PCa) could improve personalized medicine. Our group previously identified a panel of differentially methylated CpGs in primary tumor tissue that predict disease aggressiveness, and here we further validate these biomarkers.

METHODS

Pyrosequencing was used to assess CpG methylation of eight biomarkers previously identified using the HumanMethylation450 array; CpGs with strongly correlated (r >0.70) results were considered technically validated. Logistic regression incorporating the validated CpGs and Gleason sum was used to define and lock a final model to stratify men with metastatic-lethal versus non-recurrent PCa in a training dataset. Coefficients from the final model were then used to construct a DNA methylation score, which was evaluated by logistic regression and Receiver Operating Characteristic (ROC) curve analyses in an independent testing dataset.

RESULTS

Five CpGs were technically validated and all were retained (P < 0.05) in the final model. The 5-CpG and Gleason sum coefficients were used to calculate a methylation score, which was higher in men with metastatic-lethal progression (P = 6.8 × 10-6 ) in the testing dataset. For each unit increase in the score there was a four-fold increase in risk of metastatic-lethal events (odds ratio, OR = 4.0, 95%CI = 1.8-14.3). At 95% specificity, sensitivity was 74% for the score compared to 53% for Gleason sum alone. The score demonstrated better prediction performance (AUC = 0.91; pAUC = 0.037) compared to Gleason sum alone (AUC = 0.87; pAUC = 0.025).

CONCLUSIONS

The DNA methylation score improved upon Gleason sum for predicting metastatic-lethal progression and holds promise for risk stratification of men with aggressive tumors. This prognostic score warrants further evaluation as a tool for improving patient outcomes.

The 44th Congress of the International Society of Oncology and Biomarkers: Rio de Janeiro, Brazil, 7-10 September 2017

The 44th Congress of the International Society of Oncology and Biomarkers: Rio de Janeiro, Brazil, 7-10 September 2017 The 44th congress followed the previous one of  International Society of Oncology and Biomarkers (ISOBM) that took place in Chicago (USA) in 2016. The title of the 44th Annual congress was: 'Biomarkers in oncology: new horizons and challenges in the diagnosis and treatment of cancer' [ 1 ]. The congress was co-organized by ISOBM, European Group on Tumor Markers (EGTM) and Brazilian Society of Clinical Pathology SBPC/ML. The event attracted more than 180 participants from all over the world. The program offered many topics regarding discovery, validation, evaluation and use of tumor biomarkers. The presentations were split into the key note lectures, oral presentations, poster presentations and satellite symposiums sponsored by companies. The congress offered participants the opportunity to link clinical and research oncologists to discuss new tools for diagnosis and monitoring of cancer diseases. Prominent people in the field of cancer research and clinical oncology were presented and offered the unique opportunity to exchange experiences and knowledge in an international forum [ 2 ]. Compared with previous ISOBM congresses, it was held in Latin America for the first time, and due to that more participants from Latin America were present.

Evaluating a 4-marker signature of aggressive prostate cancer using time-dependent AUC

BACKGROUND

We previously identified a protein tumor signature of PTEN, SMAD4, SPP1, and CCND1 that, together with clinical features, was associated with lethal outcomes among prostate cancer patients. In the current study, we sought to validate the molecular model using time-dependent measures of AUC and predictive values for discriminating lethal from non-lethal prostate cancer.

METHODS

Using data from the initial study, we fit survival models for men with prostate cancer who were participants in the Physicians' Health Study (PHS; n = 276). Based on these models, we generated prognostic risk scores in an independent population, the Health Professionals Follow-up Study (HPFS; n = 347) to evaluate external validity. In each cohort, men were followed prospectively from cancer diagnosis through 2011 for development of distant metastasis or cancer mortality. We measured protein tumor expression of PTEN, SMAD4, SPP1, and CCND1 on tissue microarrays.

RESULTS

During a median of 11.9 and 14.3 years follow-up in the PHS and HPFS cohorts, 24 and 32 men (9%) developed lethal disease. When used as a prognostic factor in a new population, addition of the four markers to clinical variables did not improve discriminatory accuracy through 15 years of follow-up.

CONCLUSIONS

Although the four markers have been identified as key biological mediators in metastatic progression, they do not provide independent, long-term prognostic information beyond clinical factors when measured at diagnosis. This finding may underscore the broad heterogeneity in aggressive prostate tumors and highlight the challenges that may result from overfitting in discovery-based research.

A Dual-Carbon-and-Nitrogen Stable Isotope Ratio Model Is Not Superior to a Single-Carbon Stable Isotope Ratio Model for Predicting Added Sugar Intake in Southwest Virginian Adults

BACKGROUND

An objective measure of added sugar (AS) and sugar-sweetened beverage (SSB) intake is needed. The δ(13)C value of finger-stick blood is a novel validated biomarker of AS/SSB intake; however, nonsweetener corn products and animal protein also carry a δ(13)C value similar to AS sources, which may affect blood δ(13)C values. The δ(15)N value of blood has been proposed as a "correction factor" for animal protein intake.

OBJECTIVES

The objectives were to 1) identify foods associated with δ(13)C and δ(15)N blood values, 2) determine the contribution of nonsweetener corn to the diet relative to AS intake, and 3) determine if the dual-isotope model (δ(13)C and δ(15)N) is a better predictor of AS/SSB intake than δ(13)C alone.

METHODS

A cross-sectional sample of southwest Virginian adults (n = 257; aged 42 ± 15 y; 74% overweight/obese) underwent dietary intake assessments and provided finger-stick blood samples, which were analyzed for δ(13)C and δ(15)N values by using natural abundance stable isotope mass spectrometry. Statistical analyses included ANOVAs, paired-samples t tests, and multiple linear regressions.

RESULTS

The mean ± SD daily AS intake was 88 ± 59 g and nonsweetener corn intake was 13 ± 13 g. The mean δ(13)C value was -19.1 ± 0.9‰, which was significantly correlated with AS and SSB intakes (r = 0.32 and 0.39, respectively; P ≤ 0.01). The δ(13)C value and nonsweetener corn intake and the δ(15)N value and animal protein intake were not correlated. AS intake was significantly greater than nonsweetener corn intake (mean difference = 76.2 ± 57.2 g; P ≤ 0.001). The δ(13)C value was predictive of AS/SSB intake (β range: 0.28-0.35; P ≤ 0.01); however, δ(15)N was not predictive and minimal increases in R(2) values were observed when the δ(15)N value was added to the model.

CONCLUSIONS

The data do not provide evidence that the dual-isotope method is superior for predicting AS/SSB intakes within a southwest Virginian population. Our results support the potential of the δ(13)C value of finger-stick blood to serve as an objective measure of AS/SSB intake. This trial was registered at clinicaltrials.gov as NCT02193009.

Lessons for tumor biomarker trials: vicious cycles, scientific method & developing guidelines

Interview with Daniel Hayes, by Claire Raison (Commissioning Editor) Daniel F Hayes, M.D. is the Stuart A Padnos Professor of Breast Cancer Research and co-Director of the Breast Oncology Program at the University of Michigan Comprehensive Cancer Center (Ann Arbor, MI, USA). Dr Hayes has extensive experience in clinical and translational breast cancer biomarker research, and in drug development and clinical trials. Around 30 years ago, he led the discovery of the circulating breast tumor biomarker, CA15-3, which started his career into further tumor biomarker work. The main thrust of his work since then has been in clinical trials, tumor biomarkers and trying to integrate the two. Dr Hayes is Chair of the Correlative Sciences Committee of the North American Breast Cancer Group (now called the Breast Cancer Steering Committee), and co-chairs the Expert Panel for Tumor Biomarker Practice Guidelines for the American Society of Clinical Oncology.

Two-stage adaptive cutoff design for building and validating a prognostic biomarker signature

Cancer biomarkers are frequently evaluated using archived specimens collected from previously conducted therapeutic trials. Routine collection and banking of high quality specimens is an expensive and time-consuming process. Therefore, care should be taken to preserve these precious resources. Here, we propose a novel two-stage adaptive cutoff design that affords the possibility to stop the biomarker study early if an evaluation of the model performance is unsatisfactory at an early stage, thereby allowing one to preserve the remaining specimens for future research. In addition, our design integrates important elements necessary to meet statistical rigor and practical demands for developing and validating a prognostic biomarker signature, including maintaining strict separation between the datasets used to build and evaluate the model and producing a locked-down signature to facilitate future validation. We conduct simulation studies to evaluate the operating characteristics of the proposed design. We show that under the null hypothesis when the model performance is deemed undesirable, the proposed design maintains type I error at the nominal level, has high probabilities of terminating the study early, and results in substantial savings in specimens. Under the alternative hypothesis, power is generally high when the total sample size and the targeted degree of improvement in prediction accuracy are reasonably large. We illustrate the use of the procedure with a dataset in patients with diffuse large-B-cell lymphoma. The practical aspects of the proposed designs are discussed. Published 2014. This article is a U.S. Government work and is in the public domain in the USA.

Systemic sclerosis biomarkers discovered using mass-spectrometry-based proteomics: a systematic review

CONTEXT

Systemic sclerosis (SSc) is an autoimmune disease with incompletely known physiopathology. There is a great challenge to predict its course and therapeutic response using biomarkers.

OBJECTIVE

To critically review proteomic biomarkers discovered from biological specimens from systemic sclerosis patients using mass spectrometry technologies.

METHODS

Medline and Embase databases were searched in February 2014.

RESULTS

Out of the 199 records retrieved, a total of 20 records were included, identifying 116 candidate proteomic biomarkers.

CONCLUSION

Research in SSc proteomic biomarkers should focus on biomarker validation, as there are valuable mass-spectrometry proteomics studies in the literature.

Randomized reverse marker strategy design for prospective biomarker validation

We describe a novel study design for validating marker-based treatment strategies meant to select among possible therapeutic options using a biologic marker. Studying existing designs in realistic scenarios, we demonstrate that this design is more than four times more efficient for testing the interaction between a marker and its intended treatment. Our analysis employs a simple parametric framework that uncovers systematic biases in currently proposed designs and suggests how they may be accommodated or enumerated. In the context of markers for choosing a treatment for recurrent ovarian cancer, our proposal requires sample sizes on the order of recently completed phases II and III studies making validation studies for this clinical decision scenario viable.

Urinary biomarkers of smokers' exposure to tobacco smoke constituents in tobacco products assessment: a fit for purpose approach

There are established guidelines for bioanalytical assay validation and qualification of biomarkers. In this review, they were applied to a panel of urinary biomarkers of tobacco smoke exposure as part of a "fit for purpose" approach to the assessment of smoke constituents exposure in groups of tobacco product smokers. Clinical studies have allowed the identification of a group of tobacco exposure biomarkers demonstrating a good doseresponse relationship whilst others such as dihydroxybutyl mercapturic acid and 2-carboxy-1-methylethylmercapturic acid - did not reproducibly discriminate smokers and non-smokers. Furthermore, there are currently no agreed common reference standards to measure absolute concentrations and few inter-laboratory trials have been performed to establish consensus values for interim standards. Thus, we also discuss in this review additional requirements for the generation of robust data on urinary biomarkers, including toxicant metabolism and disposition, method validation and qualification for use in tobacco products comparison studies.

Assessing receptivity in the endometrium: the need for a rapid, non-invasive test

Successful implantation of an embryo into the uterus requires synchrony between the blastocyst and the endometrium. Endometrial preparedness, or receptivity, occurs only for a very short time during the mid-secretory phase of the menstrual cycle in fertile women. Failure to achieve receptivity results in infertility and is a rate-limiting step for IVF success. Frozen embryo transfer in non-stimulation cycles is already improving live birth rates. However, an important tool that is missing in the armoury of reproductive specialists is a means to rapidly assess endometrial receptivity, either during initial assessment or immediately prior to embryo transfer. The development of a wealth of omics technologies now opens the way for identifying potential receptivity markers, although validation of these is still a major issue. This review assesses the current state of the field and the requirements to proceed to a valid clinical test.

The failure of protein cancer biomarkers to reach the clinic: why, and what can be done to address the problem?

There is a plethora of published cancer biomarkers but the reality is that very few, if any, new circulating cancer biomarkers have entered the clinic in the last 30 years. I here try to explain this apparent oxymoron by classifying circulating cancer biomarkers into three categories: fraudulent reports (rare); true discoveries of biomarkers, that then fail to meet the demands of the clinic; and false discoveries, which represent artifactual biomarkers. I further provide examples of combinations of some known cancer biomarkers that can perform well in niche clinical applications, despite individually being not useful.

Selected reaction monitoring (SRM) mass spectrometry without isotope labeling can be used for rapid protein quantification

The validation of putative biomarker candidates has become the major bottle-neck in protein biomarker development. Conventional immunoaffinity methods are limited by the availability of antibodies and kits. Here we demonstrate the feasibility of using selected reaction monitoring (SRM) without isotope labeling to achieve fast and reproducible quantification of serum proteins. The SRM/MRM assays for three standard serum proteins, including ceruloplasmin (CP), serum aymloid A (SAA) and sex hormone binding globulin (SHBG), have good linear ranges, generally 10(3) to 10(4) . There are almost perfect correlations between SRM intensities and the loaded peptide amounts (R(2) is usually ~0.99). Our data suggest that SRM/MRM is able to quantify proteins within the range of 0.2-2 fmol, which is comparable to the commercial ELISA/LUMINEX kits for these proteins. Excellent correlations between SRM/MRM and ELISA/LUMINEX assays were observed for SAA and SHBG (R(2)=0.928 and 0.851, respectively). However, the correlation between SRM/MRM and ELISA for CP is less desirable (R(2)=0.565). The reproducibility for SRM/MRM assays is generally very good but may depend on the proteins/peptides being analyzed (R(2)=0.931 and 0.882 for SAA and SHBG, and 0.723 for CP). The SRM/MRM assay without isotope labeling is a rapid and useful method for protein biomarker validation in a modest number of samples and is especially useful when other assays such as ELISA or LUMINEX are not available.

Biomarkers of immunotoxicity for environmental and public health research

The immune response plays an important role in the pathophysiology of numerous diseases including asthma, autoimmunity and cancer. Application of biomarkers of immunotoxicity in epidemiology studies and human clinical trials can improve our understanding of the mechanisms that underlie the associations between environmental exposures and development of these immune-mediated diseases. Immunological biomarkers currently used in environmental health studies include detection of key components of innate and adaptive immunity (e.g., complement, immunoglobulin and cell subsets) as well as functional responses and activation of key immune cells. The use of high-throughput assays, including flow cytometry, Luminex, and Multi-spot cytokine detection methods can further provide quantitative analysis of immune effects. Due to the complexity and redundancy of the immune response, an integrated assessment of several components of the immune responses is needed. The rapidly expanding field of immunoinformatics will also aid in the synthesis of the vast amount of data being generated. This review discusses and provides examples of how the identification and development of immunological biomarkers for use in studies of environmental exposures and immune-mediated disorders can be achieved.