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Roland Matthews1, Andres Azuero2, Senait Asmellash3, Earl Brewster1, Edward E Partridge4, Chandrika J Piyathilake51Department of Obstetrics and Gynecology, The Morehouse School of Medicine, Atlanta, Georgia, USA; 2School of Nursing, 3Departments of Surgery, 4Obstetrics and Gynecology, 5Nutrition Sciences, University of Alabama at Birmingham, Birmingham, Alabama, USABackground: An early detection of precursor lesions of cervical cancer will help to eliminate the worldwide burden of cervical cancer.Methods: This exploratory study aimed to identify, by matrix-assisted laser desorption/ionization (MALDI) time-of-flight (TOF) mass spectrometry (MS), serum protein profiles that distinguish cervical intraepithelial neoplasia grades CIN 1 or lower (≤CIN 1) from CIN 2+ among 127 women infected with human papillomavirus (HPV) 16. Of these 127 women, 25 and 23 were diagnosed with CIN 2 or CIN 3, respectively (cases), and 79 were diagnosed with ≤CIN 1 (non-cases). Serum protein profiles were generated by MALDI-TOF-MS. A total of 95 m/z peaks were tested for association with case status by two racial groups, African American (AAs) and Caucasian American (CAs).Results: Overall, 2 protein peaks identified by our study demonstrated higher specificity for identifying CIN 2+ than previously published studies. An increasing intensity of [m/z 4459] was associated with a higher risk of being a case, regardless of race with a specificity of 58% for CIN 2 and a specificity of 75% for CIN 3. An increasing intensity of [m/z 4154] was not only associated with a higher risk of being a case only among CAs, but also had an opposite effect among AAs.Conclusion: Identification of specific proteins associated with the peaks detected in serum and development of antibody-based tests such as ELISA should lead to the development of race-specific, non-invasive and cost effective screening tests with higher specificity for identifying HPV 16 associated CIN 2+.Keywords: serum mass spectrometry, cervical intraepithelial neoplasia, race

Introduction: The VeriStrat® test (VS) is a blood-based assay that predicts a patient's response to therapy by analyzing eight features in a spectrum obtained from matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) analysis of human serum and plasma. In a recent analysis of the INSIGHT clinical trial (NCT03289780), it was found that the VS labels, VS Good and VS Poor, can effectively predict the responsiveness of non-small cell lung cancer (NSCLC) patients to immune checkpoint inhibitor (ICI) therapy. However, while VS measures the intensities of spectral features using MALDI-TOF analysis, the specific proteoforms underlying these features have not been comprehensively identified., Objectives: The objective of this study was to identify the proteoforms that are measured by VS., Methods: To resolve the features obtained from the low-resolution MALDI-TOF procedure used to acquire mass spectra for VS DeepMALDI® analysis of serum was employed. This technique allowed for the identification of finer peaks within these features. Additionally, a combination of reversed-phase fractionation and liquid chromatography-tandem mass spectrometry (LC-MS/MS) was then used to identify the proteoforms associated with these peaks., Results: The analysis revealed that the primary constituents of the spectrum measured by VS are serum amyloid A1, serum amyloid A2, serum amyloid A4, C-reactive protein, and beta-2 microglobulin., Conclusion: Proteoforms involved in host immunity were identified as significant components of these features. This newly acquired information improves our understanding of how VS can accurately predict patient response to therapy. It opens up additional studies that can expand our understanding even further., Competing Interests: The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: All authors are current and/or former employees of and have or had stock options in Biodesix, Inc. Heinrich Roder, Joanna Roder, and Senait Asmellash are inventors on patents describing DeepMALDI, assigned to Biodesix, Inc., (© 2023 THE AUTHORS.)

Accurate and precise measurement of the relative protein content of blood-based samples using mass spectrometry is challenging due to the large number of circulating proteins and the dynamic range of their abundances. Traditional spectral processing methods often struggle with accurately detecting overlapping peaks that are observed in these samples. In this work, we develop a novel spectral processing algorithm that effectively detects over 1650 peaks with over 3.5 orders of magnitude in intensity in the 3 to 30 kD m/z range. The algorithm utilizes a convolution of the peak shape to enhance peak detection, and accurate peak fitting to provide highly reproducible relative abundance estimates for both isolated peaks and overlapping peaks. We demonstrate a substantial increase in the reproducibility of the measurements of relative protein abundance when comparing this processing method to a traditional processing method for sample sets run on multiple matrix-assisted laser desorption/ionization-time of flight (MALDI-TOF) instruments. By utilizing protein set enrichment analysis, we find a sizable increase in the number of features associated with biological processes compared to previously reported results. The new processing method could be very beneficial when developing high-performance molecular diagnostic tests in disease indications.

Hepatocellular carcinoma (HCC) is one of the fastest growing causes of cancer-related death. Guidelines recommend obtaining a screening ultrasound with or without alpha-fetoprotein (AFP) every 6 months in at-risk adults. AFP as a screening biomarker is plagued by low sensitivity/specificity, prompting interest in discovering alternatives. Mass spectrometry-based techniques are promising in their ability to identify potential biomarkers. This study aimed to use machine learning utilizing spectral data and AFP to create a model for early detection. Serum samples were collected from three separate cohorts, and data were compiled to make Development, Internal Validation, and Independent Validation sets. AFP levels were measured, and Deep MALDI ® analysis was used to generate mass spectra. Spectral data were input into the VeriStrat ® classification algorithm. Machine learning techniques then classified each sample as "Cancer" or "No Cancer". Sensitivity and specificity of the test were >80% to detect HCC. High specificity of the test was independent of cause and severity of underlying disease. When compared to AFP, there was improved cancer detection for all tumor sizes, especially small lesions. Overall, a machine learning algorithm incorporating mass spectral data and AFP values from serum samples offers a novel approach to diagnose HCC. Given the small sample size of the Independent Validation set, a further independent, prospective study is warranted.

Introduction: Most diseases involve a complex interplay between multiple biological processes at the cellular, tissue, organ, and systemic levels. Clinical tests and biomarkers based on the measurement of a single or few analytes may not be able to capture the complexity of a patient's disease. Novel approaches for comprehensively assessing biological processes from easily obtained samples could help in the monitoring, treatment, and understanding of many conditions., Objectives: We propose a method of creating scores associated with specific biological processes from mass spectral analysis of serum samples., Methods: A score for a process of interest is created by: (i) identifying mass spectral features associated with the process using set enrichment analysis methods, and (ii) combining these features into a score using a principal component analysis-based approach. We investigate the creation of scores using cohorts of patients with non-small cell lung cancer, melanoma, and ovarian cancer. Since the circulating proteome is amenable to the study of immune responses, which play a critical role in cancer development and progression, we focus on functions related to the host response to disease., Results: We demonstrate the feasibility of generating scores, their reproducibility, and their associations with clinical outcomes. Once the scores are constructed, only 3 µL of serum is required for the assessment of multiple biological functions from the circulating proteome., Conclusion: These mass spectrometry-based scores could be useful for future multivariate biomarker or test development studies for informing treatment, disease monitoring and improving understanding of the roles of various biological functions in multiple disease settings., Competing Interests: Joanna Roder, Heinrich Roder, Julia Grigorieva, Lelia Net, Senait Asmellash, Carlos Oliveira, and Krista Meyer are or were employees of Biodesix, Inc. and have or had stock or stock options in Biodesix, Inc. Joanna Roder, Heinrich Roder and Carlos Oliveria are inventors on related patents assigned to Biodesix, Inc. Sabine Kasimir-Bauer, Harvey Pass and Jeffrey Weber declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2020 The Authors.)

The remarkable success of immune checkpoint inhibitors (ICIs) has given hope of cure for some patients with advanced cancer; however, the fraction of responding patients is 15-35%, depending on tumor type, and the proportion of durable responses is even smaller. Identification of biomarkers with strong predictive potential remains a priority. Until now most of the efforts were focused on biomarkers associated with the assumed mechanism of action of ICIs, such as levels of expression of programmed death-ligand 1 (PD-L1) and mutation load in tumor tissue, as a proxy of immunogenicity; however, their performance is unsatisfactory. Several assays designed to capture the complexity of the disease by measuring the immune response in tumor microenvironment show promise but still need validation in independent studies. The circulating proteome contains an additional layer of information characterizing tumor-host interactions that can be integrated into multivariate tests using modern machine learning techniques. Here we describe several validated serum-based proteomic tests and their utility in the context of ICIs. We discuss test performances, demonstrate their independence from currently used biomarkers, and discuss various aspects of associated biological mechanisms. We propose that serum-based multivariate proteomic tests add a missing piece to the puzzle of predicting benefit from ICIs.

Introduction: Reliable measurements of the protein content of biological fluids like serum or plasma can provide valuable input for the development of personalized medicine tests. Standard MALDI analysis typically only shows high abundance proteins, which limits its utility for test development. It also exhibits reproducibility issues with respect to quantitative measurements. In this paper we show how the sensitivity of MALDI profiling of intact proteins in unfractionated human serum can be substantially increased by exposing a sample to many more laser shots than are commonly used. Analytical reproducibility is also improved., Methods: To assess what is theoretically achievable we utilized spectra from the same samples obtained over many years and combined them to generate MALDI spectral averages of up to 100,000,000 shots for a single sample, and up to 8,000,000 shots for a set of 40 different serum samples. Spectral attributes, such as number of peaks and spectral noise of such averaged spectra were investigated together with analytical reproducibility as a function of the number of shots. We confirmed that results were similar on MALDI instruments from different manufacturers., Results: We observed an expected decrease of noise, roughly proportional to the square root of the number of shots, over the whole investigated range of the number of shots (5 orders of magnitude), resulting in an increase in the number of reliably detected peaks. The reproducibility of the amplitude of these peaks, measured by CV and concordance analysis also improves with very similar dependence on shot number, reaching median CVs below 2% for shot numbers > 4 million. Measures of analytical information content and association with biological processes increase with increasing number of shots., Conclusions: We demonstrate that substantially increasing the number of laser shots in a MALDI-TOF analysis leads to more informative and reliable data on the protein content of unfractionated serum. This approach has already been used in the development of clinical tests in oncology., Competing Interests: HR, SA and MT are inventors on patents describing Deep MALDI TOF mass spectrometry of complex biological samples, assigned to Biodesix, Inc. All authors are current employees of and have or had stock options in Biodesix, Inc. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

The therapeutic landscape in metastatic melanoma has changed dramatically in the last decade, with the success of immune checkpoint inhibitors resulting in durable responses for a large number of patients. For patients with BRAF mutations, combinations of BRAF and MEK inhibitors demonstrated response rates and benefit comparable to those from immune checkpoint inhibitors, providing the rationale for sequential treatment with targeted and immunotherapies and raising the question of optimal treatment sequencing.Biomarkers for the selection of anti-PD-1 therapy in BRAF wild type (BRAF WT) and in BRAF mutated (BRAF MUT) patients help development of alternative treatments for patients unlikely to benefit, and might lead to better understanding of the interaction of checkpoint inhibition and targeted therapy. In this paper we evaluate the performance of a previously developed serum proteomic test, BDX008, in metastatic melanoma patients treated with anti-PD-1 agents and investigate the role of BRAF mutation status. BDX008, a pre-treatment proteomic test associated with acute phase reactants, wound healing and complement activation, stratifies patients into two groups, BDX008+ and BDX008-, with better and worse outcomes on immunotherapy.Serum samples were available from 71 patients treated with anti-PD1 inhibitors; 25 patients had BRAF mutations, 39 were wild type. Overall, BDX008+ patients had significantly better overall survival (OS) (HR = 0.50, P = 0.016) and a trend for better progression-free survival (PFS) (HR = 0.61, P = 0.060) than BDX008- patients. BDX008 classification was statistically significant in the analyses adjusted for mutation status, LDH, and line of treatment (P = 0.009 for OS and 0.031 for PFS). BRAF WT BDX008+ patients had markedly long median OS of 32.5 months and 53% landmark 2 years survival, with statistically significantly superior OS as compared to BDX008- patients (HR = 0.41, P = 0.032). The difference between BDX008+ and BDX008- in PFS in BRAF WT patients and in OS and PFS in BRAF MUT patients did not reach statistical significance, though numerically was consistent with overall results. The test demonstrated significant interaction with neutrophil-to-lymphocyte ratio (NLR) (PFS P = 0.041, OS P = 0.004). BDX008 as a biomarker selecting for benefit from immune checkpoint blockade, especially in patients with wild type BRAF and in subgroups with low NLR, warrants further evaluation.

Background: The proteome varies with physiologic and disease states. Few studies have been reported that differentiate the proteome of those with pancreatic cancer., Aim: To apply proteomic-based technologies to body fluids. To differentiate pancreatic neoplasia from nonneoplastic pancreatic disease., Methods: Samples from 50 patients (15 healthy (H), 24 cancer (Ca), 11 chronic pancreatitis (CP)) were prospectively collected and underwent analysis. A high-throughput method, using high-affinity solid lipophilic extraction resins, enriched low molecular weight proteins for extraction with a high-speed 200-Hz matrix-assisted laser desorption/ionization time-of-flight mass spectrometer (MALDI-MS; Bruker Ultraflex III). Samples underwent software processing with FlexAnalysis, Clinprot, MatLab, and Statistica (baseline, align, and normalize spectra). Nonparametric pairwise statistics, multidimensional scaling, hierarchical analysis, and leave-one-out cross validation completed the analysis. Sensitivity (sn) and specificity (sp) of group comparisons were determined. Two top-down-directed protein identification approaches were combined with MALDI-MS and tandem mass spectrometry to fully characterize the most significant protein biomarker., Results: Using eight serum features, we differentiated Ca from H (sn 88%, sp 93%), Ca from CP (sn 88%, sp 30%), and Ca from both H and CP combined (sn 88%, sp 66%). In addition, nine features obtained from urine differentiated Ca from both H and CP combined with high efficiency (sn 90%, sp 90%). Interestingly, the plasma samples (considered by the Human Proteome Organization to be the preferred biological fluid) did not show significant differences. Multidimensional scaling indicated that markers from both serum and urine led to a highly effective clinical indicator of each specific disease state., Conclusions: The proteomic analysis of noninvasively acquired biological fluids provided a high level of predictability for diagnosing pancreatic cancer. While the proteomic analysis of serum was capable of screening individuals for pancreatic disease (i.e., CP and Ca vs. H), specific urine biomarkers further distinguished malignancy (Ca) from chronic inflammation (CP).

Agents that disrupt functions of the endoplasmic reticulum (ER) induce expression of ER stress-response genes including ER chaperones. Increased expression of the major ER chaperone, Grp78, protects cells, including renal epithelial cells, from chemically induced injury and death in vitro. In this study, we determined if pharmacological manipulation of the ER stress-response gene is an effective strategy to protect the kidney from chemical stress in vivo. Treatment with trans-4,5-dihydroxy-1,2-dithiane (DTTox), a novel inducer of ER stress proteins, stimulated a time-and dose-dependent increase in Grp78 expression in the kidney, but it did not cause detectable injury. Furthermore, prior treatment with DTTox protected the proximal tubular epithelium against a subsequent challenge with the nephrotoxicant S-(1,1,2,2,-tetrafluoroethyl)-L-cysteine (TFEC). In contrast, activating a heat shock response did not have a protective effect. Prior treatment with DTTox did not reduce covalent binding of radiolabeled reactive metabolites of (35)S-TFEC to renal proteins, indicating that protection was not due to an effect on the metabolic activation of TFEC to the reactive metabolite(s) responsible for renal injury. Antisense grp78 expression in the renal epithelial cell line LLC-PK1 blocked the DTTox-induced Grp78 increase and ablated the protective effect against TFEC damage, indicating that the induction of grp78 expression and the ER stress response were critical for the protective effect of DTTox. These findings suggest that increased expression of Grp78 plays a major role in the protection of renal epithelial cells from reactive intermediate-induced chemical injury in vivo and that pharmacological manipulation is an effective strategy to prevent damage by some classes of nephrotoxicants.

Environmental stress induces the synthesis of glucose-regulated proteins (Grps) in the endoplasmic reticulum (ER) and heat shock proteins (Hsps) in the cytoplasm. Iodoacetamide (IDAM), a prototypical alkyating agent, induces both Grp and Hsp synthesis in renal epithelial cells and causes necrosis which is prevented by prior activation of the ER stress response (pre-ER stress) [Liu, H., et al. (1997) J. Biol. Chem. 272, 21751-21759]. In this study, we examined the biochemical pathways leading to IDAM-induced apoptosis and investigated the role of the ER stress response in apoptotic cell death. The antioxidant N,N'-diphenyl-p-phenylenediamine (DPPD) prevented necrosis after IDAM treatment, but the cells went on to die with hallmarks of apoptosis, i.e., cell detachment, caspase-3 activation, cleavage of poly(ADP-ribose)polymerase (PARP), and DNA-ladder formation, all of which were blocked by the general caspase inhibitor zVAD. As with IDAM-induced necrosis, dithiothreitol protected against apoptosis, but cell permeable calcium chelators did not, suggesting that distinct biochemical pathways mediate these two forms of cell death. Pre-ER stress, but not heat shock, prevented IDAM-induced apoptosis. pkASgrp78 cells are deficient in Grp78 induction due to expression of a grp78 antisense RNA and are more sensitive to necrosis. However, these cells were resistant to IDAM-induced apoptosis and had increased basal levels of Grp94 and a KDEL-containing protein of about 50 kDa. Thus, the expression of grp78 antisense perturbs ER functions and activates expression of other ER stress genes accounting for the resistance to apoptosis. Taken together, the data describe functionally distinct signaling pathways through which the ER regulates apoptosis and necrosis caused by chemical toxicants.