Multiplexed Mass Spectrometry Research Articles

Plasma proteomics identify biomarkers predicting Parkinson’s disease up to 7 years before symptom onset

Parkinson’s disease is increasingly prevalent. It progresses from the pre-motor stage (characterised by non-motor symptoms like REM sleep behaviour disorder), to the disabling motor stage. We need objective biomarkers for early/pre-motor disease stages to be able to intervene and slow the underlying neurodegenerative process. Here, we validate a targeted multiplexed mass spectrometry assay for blood samples from recently diagnosed motor Parkinson’s patients (n = 99), pre-motor individuals with isolated REM sleep behaviour disorder (two cohorts: n = 18 and n = 54 longitudinally), and healthy controls (n = 36). Our machine-learning model accurately identifies all Parkinson patients and classifies 79% of the pre-motor individuals up to 7 years before motor onset by analysing the expression of eight proteins—Granulin precursor, Mannan-binding-lectin-serine-peptidase-2, Endoplasmatic-reticulum-chaperone-BiP, Prostaglaindin-H2-D-isomaerase, Interceullular-adhesion-molecule-1, Complement C3, Dickkopf-WNT-signalling pathway-inhibitor-3, and Plasma-protease-C1-inhibitor. Many of these biomarkers correlate with symptom severity. This specific blood panel indicates molecular events in early stages and could help identify at-risk participants for clinical trials aimed at slowing/preventing motor Parkinson’s disease.

Secretome of Cancer-Associated Fibroblasts (CAFs) Influences Drug Sensitivity in Cancer Cells.

Resistance is a major problem with effective cancer treatment and the stroma forms a significant portion of the tumor mass but traditional drug screens involve cancer cells alone. Cancer-associated fibroblasts (CAFs) are a major tumor stroma component and its secreted proteins may influence the function of cancer cells. The majority of secretome studies compare different cancer or CAF cell lines exclusively. Here, we present the direct characterization of the secreted protein profiles between CAFs and KRAS mutant-cancer cell lines from colorectal, lung, and pancreatic tissues using multiplexed mass spectrometry. 2573 secreted proteins were annotated, and differential analysis highlighted understudied CAF-enriched secreted proteins, including Wnt family member 5B (WNT5B), in addition to established CAF markers, such as collagens. The functional role of CAF secreted proteins was explored by assessing its effect on the response to 97 anticancer drugs since stromal cells may cause a differing cancer drug response, which may be missed on routine drug screening using cancer cells alone. CAF secreted proteins caused specific effects on each of the cancer cell lines, which highlights the complexity and challenges in cancer treatment and so the importance to consider stromal elements.

A data analysis framework for combining multiple batches increases the power of isobaric proteomics experiments.

We present a framework for the analysis of multiplexed mass spectrometry proteomics data that reduces estimation error when combining multiple isobaric batches. Variations in the number and quality of observations have long complicated the analysis of isobaric proteomics data. Here we show that the power to detect statistical associations is substantially improved by utilizing models that directly account for known sources of variation in the number and quality of observations that occur across batches.In a multibatch benchmarking experiment, our open-source software (msTrawler) increases the power to detect changes, especially in the range of less than twofold changes, while simultaneously increasing quantitative proteome coverage by utilizing more low-signal observations. Further analyses of previously published multiplexed datasets of 4 and 23 batches highlight both increased power and the ability to navigate complex missing data patterns without relying on unverifiable imputations or discarding reliable measurements.

Mass spectrometry imaging of natural carbonyl products directly from agar-based microbial interactions using 4-APEBA derivatization.

Aliphatic carboxylic acids, aldehydes, and ketones play diverse roles in microbial adaptation to their microenvironment, from excretion as toxins to adaptive metabolites for membrane fluidity. However, the spatial distribution of these molecules throughout biofilms and how microbes in these environments exchange these molecules remain elusive for many of these bioactive species due to inefficient molecular imaging strategies. Herein, we apply on-tissue chemical derivatization (OTCD) using 4-(2-((4-bromophenethyl)dimethylammonio)ethoxy)benzenaminium dibromide (4-APEBA) on a co-culture of a soil bacterium (Bacillus subtilis NCIB 3610) and fungus (Fusarium sp. DS 682) grown on agar as our model system. Using matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI), we spatially resolved more than 300 different metabolites containing carbonyl groups within this model system. Various spatial patterns are observable in these species, which indicate possible extracellular or intercellular processes of the metabolites and their up- or downregulation during microbial interaction. The unique chemistry of our approach allowed us to bring additional confidence in accurate carbonyl identification, especially when multiple isomeric candidates were possible, and this provided the ability to generate hypotheses about the potential role of some aliphatic carbonyls in this B. subtilis/Fusarium sp. interaction. The results shown here demonstrate the utility of 4-ABEBA-based OTCD MALDI-MSI in probing interkingdom interactions directly from microbial co-cultures, and these methods will enable future microbial interaction studies with expanded metabolic coverage.IMPORTANCEThe metabolic profiles within microbial biofilms and interkingdom interactions are extremely complex and serve a variety of functions, which include promoting colonization, growth, and survival within competitive and symbiotic environments. However, measuring and differentiating many of these molecules, especially in an in situ fashion, remains a significant analytical challenge. We demonstrate a chemical derivatization strategy that enabled highly sensitive, multiplexed mass spectrometry imaging of over 300 metabolites from a model microbial co-culture. Notably, this approach afforded us to visualize over two dozen classes of ketone-, aldehyde-, and carboxyl-containing molecules, which were previously undetectable from colonies grown on agar. We also demonstrate that this chemical derivatization strategy can enable the discrimination of isobaric and isomeric metabolites without the need for orthogonal separation (e.g., online chromatography or ion mobility). We anticipate that this approach will further enhance our knowledge of metabolic regulation within microbiomes and microbial systems used in bioengineering applications.

Spatial single-cell mass spectrometry defines zonation of the hepatocyte proteome

Single-cell proteomics by mass spectrometry is emerging as a powerful and unbiased method for the characterization of biological heterogeneity. So far, it has been limited to cultured cells, whereas an expansion of the method to complex tissues would greatly enhance biological insights. Here we describe single-cell Deep Visual Proteomics (scDVP), a technology that integrates high-content imaging, laser microdissection and multiplexed mass spectrometry. scDVP resolves the context-dependent, spatial proteome of murine hepatocytes at a current depth of 1,700 proteins from a cell slice. Half of the proteome was differentially regulated in a spatial manner, with protein levels changing dramatically in proximity to the central vein. We applied machine learning to proteome classes and images, which subsequently inferred the spatial proteome from imaging data alone. scDVP is applicable to healthy and diseased tissues and complements other spatial proteomics and spatial omics technologies.

Endothelial APC/PAR1 distinctly regulates cytokine-induced pro-inflammatory VCAM-1 expression.

Introduction: Dysfunction of the endothelium impairs its' protective role and promotes inflammation and progression of vascular diseases. Activated Protein C (APC) elicits endothelial cytoprotective responses including barrier stabilization, anti-inflammatory and anti-apoptotic responses through the activation of the G protein-coupled receptor (GPCR) protease-activated receptor-1 (PAR1) and is a promising therapeutic. Despite recent advancements in developing new Activated protein C variants with clinical potential, the mechanism by which APC/PAR1 promotes different cytoprotective responses remains unclear and is important to understand to advance Activated protein C and new targets as future therapeutics. Here we examined the mechanisms by which APC/PAR1 attenuates cytokine-induced pro-inflammatory vascular cell adhesion molecule (VCAM-1) expression, a key mediator of endothelial inflammatory responses. Methods: Quantitative multiplexed mass spectrometry analysis of Activated protein C treated endothelial cells, endothelial cell transcriptomics database (EndoDB) online repository queries, biochemical measurements of protein expression, quantitative real-time polymerase chain reaction (RT-qPCR) measurement of mRNA transcript abundance, pharmacological inhibitors and siRNA transfections of human cultured endothelial cells. Results: Here we report that Activated Protein C modulates phosphorylation of tumor necrosis factor (TNF)-α signaling pathway components and attenuates of TNF-α induced VCAM-1 expression independent of mRNA stability. Unexpectedly, we found a critical role for the G protein-coupled receptor co-receptor sphingosine-1 phosphate receptor-1 (S1PR1) and the G protein receptor kinase-2 (GRK2) in mediating APC/PAR1 anti-inflammatory responses in endothelial cells. Discussion: This study provides new knowledge of the mechanisms by which different APC/PAR1 cytoprotective responses are mediated through discrete β-arrestin-2-driven signaling pathways modulated by specific G protein-coupled receptor co-receptors and GRKs.

Urinary Proteomics for Discovery of Gastric Cancer Biomarkers to Enable Precision Clinical Oncology.

For precision in clinical oncology practice, detection of tumor-derived peptides and proteins in urine offers an attractive and noninvasive alternative for diagnostic or screening purposes. In this study, we report comparative quantitative proteomic profiling of urine samples from patients with gastric cancer and healthy controls using tandem mass tags-based multiplexed mass spectrometry approach. We identified 1504 proteins, of which 246 were differentially expressed in gastric cancer cases. Notably, ephrin A1 (EFNA1), pepsinogen A3 (PGA3), sortilin 1 (SORT1), and vitronectin (VTN) were among the upregulated proteins, which are known to play crucial roles in the progression of gastric cancer. We also found other overexpressed proteins, including shisa family member 5 (SHISA5), mucin like 1 (MUCL1), and leukocyte cell derived chemotaxin 2 (LECT2), which had not previously been linked to gastric cancer. Using a novel approach for targeted proteomics, SureQuant, we validated changes in abundance of a subset of proteins discovered in this study. We confirmed the overexpression of vitronectin and sortilin 1 in an independent set of urine samples. Altogether, this study provides molecular candidates for biomarker development in gastric cancer, and the findings also support the promise of urinary proteomics for noninvasive diagnostics and personalized/precision medicine in the oncology clinic.

A spatiotemporal Notch interaction map from plasma membrane to nucleus.

Notch signaling relies on ligand-induced proteolysis of the transmembrane receptor Notch to liberate a nuclear effector that drives cell fate decisions. Upon ligand binding, sequential cleavage of Notch by the transmembrane protease ADAM10 and the intracellular protease γ-secretase releases the Notch intracellular domain (NICD), which translocates to the nucleus and forms a complex that induces target gene transcription. To map the location and timing of the individual steps required for the proteolysis and movement of Notch from the plasma membrane to the nucleus, we used proximity labeling with quantitative, multiplexed mass spectrometry to monitor the interaction partners of endogenous NOTCH2 after ligand stimulation in the presence of a γ-secretase inhibitor and as a function of time after inhibitor removal. Our studies showed that γ-secretase-mediated cleavage of NOTCH2 occurred in an intracellular compartment and that formation of nuclear complexes and recruitment of chromatin-modifying enzymes occurred within 45 min of inhibitor washout. These findings provide a detailed spatiotemporal map tracking the path of Notch from the plasma membrane to the nucleus and identify signaling events that are potential targets for modulating Notch activity.

Multiplexed LC-MS/MS quantification of salivary RNA modifications in periodontitis.

To analyse the salivary epitranscriptomic profiles as periodontitis biomarkers using multiplexed mass spectrometry (MS). The field of epitranscriptomics, which relates to RNA chemical modifications, opens new perspectives in the discovery of diagnostic biomarkers, especially in periodontitis. Recently, the modified ribonucleoside N6-methyladenosine (m6A) was revealed as a crucial player in the etiopathogenesis of periodontitis. However, no epitranscriptomic biomarker has been identified in saliva to date. Twenty-four saliva samples were collected from periodontitis patients (n = 16) and from control subjects (n = 8). Periodontitis patients were stratified according to stage and grade. Salivary nucleosides were directly extracted and, in parallel, salivary RNA was digested into its constituent nucleosides. Nucleoside samples were then quantified by multiplexed MS. Twenty-seven free nucleosides were detected and an overlapping set of 12 nucleotides were detected in digested RNA. Among the free nucleosides, cytidine and three other modified nucleosides (inosine, queuosine and m6Am) were significantly altered in periodontitis patients. In digested RNA, only uridine was significantly higher in periodontitis patients. Importantly there was no correlation between free salivary nucleoside levels and the levels of those same nucleotides in digested salivary RNA, except for cytidine, m5C and uridine. This statement implies that the two detection methods are complementary. The high specificity and sensitivity of MS allowed the detection and quantification of multiple nucleosides from RNA and free nucleosides in saliva. Some ribonucleosides appear to be promising biomarkers of periodontitis. Our analytic pipeline opens new perspectives for diagnostic periodontitis biomarkers.

New Perspectives of Multiplex Mass Spectrometry Blood Protein Quantification on Microsamples in Biological Monitoring of Elderly Patients.

Blood microsampling combined with large panels of clinically relevant tests are of major interest for the development of home sampling and predictive medicine. The aim of the study was to demonstrate the practicality and medical utility of microsamples quantification using mass spectrometry (MS) in a clinical setting by comparing two types of microsamples for multiplex MS protein detection. In a clinical trial based on elderly population, we compared 2 µL of plasma to dried blood spot (DBS) with a clinical quantitative multiplex MS approach. The analysis of the microsamples allowed the quantification of 62 proteins with satisfactory analytical performances. A total of 48 proteins were significantly correlated between microsampling plasma and DBS (p < 0.0001). The quantification of 62 blood proteins allowed us to stratify patients according to their pathophysiological status. Apolipoproteins D and E were the best biomarker link to IADL (instrumental activities of daily living) score in microsampling plasma as well as in DBS. It is, thus, possible to detect multiple blood proteins from micro-samples in compliance with clinical requirements and this allows, for example, to monitor the nutritional or inflammatory status of patients. The implementation of this type of analysis opens new perspectives in the field of diagnosis, monitoring and risk assessment for personalized medicine approaches.

MetaProD: A Highly-Configurable Mass Spectrometry Analyzer for Multiplexed Proteomic and Metaproteomic Data.

The microbiome has been shown to be important for human health because of its influence on disease and the immune response. Mass spectrometry is an important tool for evaluating protein expression and species composition in the microbiome but is technically challenging and time-consuming. Multiplexing has emerged as a way to make spectrometry workflows faster while improving results. Here, we present MetaProD (MetaProteomics in Django) as a highly configurable metaproteomic data analysis pipeline supporting label-free and multiplexed mass spectrometry. The pipeline is open-source, uses fully open-source tools, and is integrated with Django to offer a web-based interface for configuration and data access. Benchmarking of MetaProD using multiple metaproteomics data sets showed that MetaProD achieved fast and efficient identification of peptides and proteins. Application of MetaProD to a multiplexed cancer data set resulted in identification of more differentially expressed human proteins in cancer tissues versus healthy tissues as compared to previous studies; in addition, MetaProD identified bacterial proteins in those samples, some of which are differentially abundant.

A targeted multiplex mass spectrometry method for quantitation of abundant matrix and cellular proteins in formalin-fixed paraffin embedded arterial tissue

Assessment of proteins in formalin-fixed paraffin-embedded (FFPE) tissue traditionally hinges on immunohistochemistry and immunoblotting. These methods are far from optimal for quantitative studies and not suitable for large-scale testing of multiple protein panels. In this study, we developed and optimised a novel targeted isotope dilution mass spectrometry (MS)-based method for FFPE samples, designed to quantitate 17 matrix and cytosolic proteins abundantly present in arterial tissue. Our new method was developed on FFPE human tissue samples of the internal thoracic artery obtained from coronary artery bypass graft (CABG) operations. The workflow has a limit of 60 samples per day. Assay precision improved by normalisation to both beta-actin and smooth muscle actin with inter-assay coefficients of variation (CV) ranging from 5.3% to 31.9%. To demonstrate clinical utility of the assay we analysed 40 FFPE artery specimens from two groups of patients with or without type 2 diabetes. We observed increased levels of collagen type IV α1 and α2 in patients with diabetes. The assay is scalable for larger cohorts and advantageous for pathophysiological studies in diabetes and the method is easily convertible to analysis of other proteins in FFPE artery samples. SignificanceThis article presents a novel robust and precise targeted mass spectrometry assay for relative quantitation of a panel of abundant matrix and cellular arterial proteins in archived formalin-fixed paraffin-embedded arterial samples. We demonstrate its utility in pathophysiological studies of cardiovascular disease in diabetes.

Relative Quantification of Proteins in Formalin-Fixed Paraffin-Embedded Breast Cancer Tissue Using Multiplexed Mass Spectrometry Assays

The identification of clinically relevant biomarkers represents an important challenge in oncology. This problem can be addressed with biomarker discovery and verification studies performed directly in tumor samples using formalin-fixed paraffin-embedded (FFPE) tissues. However, reliably measuring proteins in FFPE samples remains challenging. Here, we demonstrate the use of liquid chromatography coupled to multiple reaction monitoring mass spectrometry (LC-MRM/MS) as an effective technique for such applications. An LC-MRM/MS method was developed to simultaneously quantify hundreds of peptides extracted from FFPE samples and was applied to the targeted measurement of 200 proteins in 48 triple-negative, 19 HER2-overexpressing, and 20 luminal A breast tumors. Quantitative information was obtained for 185 proteins, including known markers of breast cancer such as HER2, hormone receptors, Ki-67, or inflammation-related proteins. LC-MRM/MS results for these proteins matched immunohistochemistry or chromogenic in situ hybridization data. In addition, comparison of our results with data from the literature showed that several proteins representing potential biomarkers were identified as differentially expressed in triple-negative breast cancer samples. These results indicate that LC-MRM/MS assays can reliably measure large sets of proteins using the analysis of surrogate peptides extracted from FFPE samples. This approach allows to simultaneously quantify the expression of target proteins from various pathways in tumor samples. LC-MRM/MS is thus a powerful tool for the relative quantification of proteins in FFPE tissues and for biomarker discovery.

Biomarkers of Endometriosis

Background: Endometriosis is an under-recognised and often misdiagnosed chronic disease that affects one in ten women. It occurs when cells similar to those that line a uterus grow in other parts of the body, usually around the pelvis. The current gold standard for diagnosis of endometriosis is direct visualisation by histological analysis which can only be achieved by an invasive laparoscopy. It is estimated 176 million women and girls around the world are living with endometriosis. The condition costs $7.7 billion a year in direct medical expenses and lost productivity in Australia alone. Aim: To analyse a series of plasma samples from patients with clinically diagnosed endometriosis, others with gynaecological symptoms without endometriosis and otherwise healthy controls to identify biomarkers to differentiate these groups and potentially aid in endometriosis diagnosis. Method: A standard proteomic discovery workflow was used to search for unique biomarkers of endometriosis. Initially, pooled plasma samples from three distinct groups of patients were tested. The first group had symptoms of endometriosis with a laparoscopic/histology confirmed diagnosis. The second group also had symptoms, but the laparoscopy confirmed no endometriosis or an alternate diagnosis. The third group were healthy matched controls. The pooled plasma samples were quantitatively profiled against each other with a triplicate experiment. A validation of the biomarkers identified as significant in the discovery phase, was then undertaken in a larger clinical cohort (n=902) using a targeted multiplex mass spectrometry assay using multiple reaction monitoring (MRM). Statistical analyses were caried out using Stata and logistical regression was used to evaluate associations of biomarkers with binary clinical outcomes. Results: Out of the 943 proteins identified with [Formula: see text] 2 significant peptides in the initial discovery workflow, 47 were determined as being differential biomarkers across the three clinical groups. The derived targeted MRM assay was tested on the clinical validation cohort, and a number of candidate biomarkers were significantly associated, thereby indicating their potential for use in the diagnosis of endometriosis.

Abstract 4099: Clinical survey of Trop2 antibody drug conjugate target and payload biomarkers in multiple cancer indications using multiplex mass spectrometry

Abstract Introduction: Trop2 is overexpressed in many cancers and currently Trop2 ADC is approved in TNBC. In ADC drug design, it is imperative to assess not only the levels of the receptor but also the payload biomarkers. We have developed a multiplex mass spectrometry method to quantitate 72 actionable proteins from FFPE samples that requires minimal tissue (2-3 sections). This panel includes chemotherapy, targeted therapy and immunotherapy agents. The test is run in our CAP, CLIA, and NYSDOH approved laboratory. For this study, we examined a subset of samples run in the clinical lab for the levels of Trop2 (target biomarker) and payload biomarkers (Topo1, TUBB3). Topo1 is a chemosensitive marker for irinotecan, while TUBB3 is a chemoresistance marker for tubulin inhibitors. Methods: FFPE tissue sections from 1140 clinical samples from a variety of cancers were examined. These include breast (n=318), colorectal (n=228), ovarian (n=199), GBM (n=69), NSCLC (n=169), HNSCC (n=91), and Gastric cancer (n=66). Two sections (10 µ) of FFPE tissue were cut on DIRECTOR slides and only the tumor areas were laser microdissected for downstream analysis which resulted in tryptic peptides. 1µg of peptides (~4000 cells) along with heavy peptides was injected into a triple quad mass spec and 72 biomarkers were quantitated concurrently. Results: Trop2 showed a wide range of expression in various cancers. Almost all (95%)breast cancer samples expressed Trop2 which exhibited a wide range (93x; 157 - 14650 amol/µg). Topo1 and TUBB3 were expressed in 93% and 60% of samples respectively. 1/4th of NSCLC does not express Trop2 and there is a 106x difference in expression of Trop2 in NSCLC. Topo1 was expressed in almost all samples while TUBB3 was expressed in 80% of NSCLC. Majority of ovarian cancer samples (85%), HNSCC (89%), Gastric cancer (88%) samples expressed Trop2 with a 113x, 134x, 47x difference in expression. Chemosensitive biomarker Topo1 was expressed in almost all ovarian (96%), HNSCC (91%) and Gastric (99%) cancer samples. Chemoresistant marker TUBB3 was expressed in 66% of ovarian cancer, 44% of HNSCC and 45% of gastric cancer samples. In contrast to above cancers, only 10% of Glioblastoma samples express Trop2 and only 3/4th of GBMs express Topo1. Discussion: In a randomly selected group of cancers, we have found Trop2 is expressed in majority of Breast, Ovarian, Lung, HNSCC and gastric cancers and minimal expression in GBM. Given the range of expression of anti-tubulin resistance marker in many solid tumors, a payload biomarker guided clinical trial is highly recommended in ADCs that employ anti-tubulin inhibitors. In contrast, wide expression of chemosensitive biomarker for Topo1 payload makes it a promising candidate for many solid tumors. Further studies are warranted to determine the level of target and payload biomarkers that will be required for a clinical response. Citation Format: Sheeno P. Thyparambil, Wei-Li Liao, Robert Heaton, Guolin Zhang, Amanda Strasbaugh, Marya Melkie, Xuefeng B. Ling. Clinical survey of Trop2 antibody drug conjugate target and payload biomarkers in multiple cancer indications using multiplex mass spectrometry [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 4099.

Abstract 5082: Proteomic analysis of extracellular vesicles from oncology donor samples purified using an alternating current electrokinetic microelectrode chip

Abstract In this study, we evaluated the ability to detect novel proteins on extracellular vesicles (EVs) following isolation using an alternating current electrokinetic (ACE) microarray. EVs circulating in blood contain a wealth of biomarkers that are thought to reflect the tumor’s proteome; however, detecting the full diversity of EV proteins may depend on choice of method to purify EVs for analysis. We compared an ACE microarray isolation method with a conventional chemical precipitation method to isolate EVs from blood plasma cancer and control samples. EVs were isolated from 1 mL each of control or pancreatic cancer patient plasma using the ExoVerita platform (Biological Dynamics) or ExoQuick Ultra kit (System Biosciences). Purified EVs were processed using tandem mass tag (TMT)-based multiplexing mass spectrometry proteomics (ThermoFisher Scientific) and the resulting peptide spectra were analyzed and quantified to determine the proteins present. Additional analyses, such as bioanalyzer measurements of contaminating plasma proteins and nanoparticle tracking analysis were performed in parallel to further characterize the isolated EVs. Cancer EVs isolated by ACE were enriched in proteins related to cancer functions when compared to non-cancer control EVs. They also showed enrichment in ontology clusters such as NABA core matrisome proteins, with depressed expression of wound healing family proteins. In contrast, EVs isolated using chemical purification demonstrated enrichment chiefly in proteins functionally grouped into immune system or blood regulation functions. After analyzing EVs isolated by ACE, a total of fifty-one (51) proteins were observed to be upregulated in the cancer donor samples. EV isolation method choice significantly impacted the proteomic profile observed. EV isolation using ACE-based technology can provide more insights into understanding the proteome by possibly reducing or removing non-specific proteins from the EVs. With better separation of EVs from blood proteins, the EV proteins identified may have greater biological significance. Citation Format: Juan P. Hinestrosa, Jean M. Lewis, David J. Searson, Heath I. Balcer, David J. Gonzalez, Rajaram Krishnan. Proteomic analysis of extracellular vesicles from oncology donor samples purified using an alternating current electrokinetic microelectrode chip [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5082.

Multiplex Mass Spectrometry for Enzymatic Activities Screening of Lysosomal Storage Diseases

Lysosomal storage diseases (LSDs) are a group of rare and inherited disorders of lysosome function and they are classified into more than 50 types (e.g., mucopolysaccharidoses, neuronal ceroid lipofuscinoses, Fabry’s Disease; Pompe Disease, etc.). The majority of LSDs result from defective lysosomal enzyme activity leading to accumulation of endogenous macromolecules in the lysosome causing severe disease symptoms and finally death. For some LSDs, treatment is available in the form of enzyme replacement therapy with good results if the therapy is started as soon as possible, making the diagnosis of crucial importance. State of art now in LSDs diagnostic employs in first stage, enzymatic determinations by fluorimetry or by mass spectrometry (in few cases).In this report, we describe a highly specific and sensitive diagnostics on dry blood spots (DBSs) for (i) molecular determinations of LSDs, particularly mucopolysaccharidoses (MPSs) and neuronal ceroid lipofuscinoses (NCLs), by simultaneous fluorimetric and mass spectrometric analysis using new types of substrate derivatives based on different alkyl‐umbelliferone; (ii) clinical diagnostics of LSDs by multiplex‐MS‐MRM analysis using new type of substrate derivatives and (iii) clinical validation of the new developed methods using DBS samples for patients with established LSDs. We have developed a high‐throughput single and multiplexing assay for rare diseases (e.g. MPS 1, MPS 2, MPS 6, NCL 2, NCL 10, Fabry Disease, etc.) in DBSs. A common substrate for the fluorimetric measurement of a lysosomal enzyme activity is a molecule with 2 different parts which are bound covalently: a group recognized by the target enzyme (e.g. sugar, lipid) and 4‐umbelliferone and the product resulted after the enzymatic reaction is always 4‐methyl umbelliferone. In our tests, the enzymatic activity levels in DBSs were determinate by fluorimetry or multiple reactions monitoring mass spectrometry in the presence of an internal standard showing a good statistical correlation in singles assays. Moreover, we developed duplex and triplex assays for the diagnosis of different LSDs from the muccopolysacharidoses family using modified substrates based on different coumarin derivates obtained through Pechman condensation. The new umbelliferone derivatives were synthesize by substituting groups in position 4 and 7 of the alpha‐ coumarin molecule with others e.g. 4‐ ethyl‐ umbelliferone, 4‐propyl‐umbelliferone, etc.In conclusion, by quantification of umbelliferone derivatives as products of enzymatic reactions either by fluorimetry or mass spectrometry, the newly proposed substrates can be easily use for clinical diagnosis of several LSDs.

Multiplexed nanomaterial-assisted laser desorption/ionization for pan-cancer diagnosis and classification

As cancer is increasingly considered a metabolic disorder, it is postulated that serum metabolite profiling can be a viable approach for detecting the presence of cancer. By multiplexing mass spectrometry fingerprints from two independent nanostructured matrixes through machine learning for highly sensitive detection and high throughput analysis, we report a laser desorption/ionization (LDI) mass spectrometry-based liquid biopsy for pan-cancer screening and classification. The Multiplexed Nanomaterial-Assisted LDI for Cancer Identification (MNALCI) is applied in 1,183 individuals that include 233 healthy controls and 950 patients with liver, lung, pancreatic, colorectal, gastric, thyroid cancers from two independent cohorts. MNALCI demonstrates 93% sensitivity at 91% specificity for distinguishing cancers from healthy controls in the internal validation cohort, and 84% sensitivity at 84% specificity in the external validation cohort, with up to eight metabolite biomarkers identified. In addition, across those six different cancers, the overall accuracy for identifying the tumor tissue of origin is 92% in the internal validation cohort and 85% in the external validation cohort. The excellent accuracy and minimum sample consumption make the high throughput assay a promising solution for non-invasive cancer diagnosis.

Quantitative proteomic profiling of esophageal adenocarcinoma tumors to assess prevalence of approved targets and elucidate novel biomarkers.

343 Background: Esophageal adenocarcinoma (EAC) continues to have extremely poor prognosis despite advances in surgical and oncological regimens. Targeted and immune therapy hold promise to improve outcomes in solid tumors including EAC. At present HER-2 and anti-PD-L1 therapies are approved by the FDA for EAC. Additionally, off-label use of EGFR directed therapy has been reported. The aim of this study is to measure expression of 80+ oncoproteins in EAC using multiplexed mass spectrometry to elucidate expression of currently approved-drug targets and explore promising new targets for drug development. Methods: After Institutional Review Board approval (Mayo Clinic and KUMC), EAC patients whose tumors were resected via esophagectomy before chemotherapy and/or radiation were identified. Normal esophageal mucosa samples with no history of EAC were also retrieved for analysis. Tissue sections were microdissected to exclude stroma from adenocarcinoma cells. Isolated EAC cells were solubilized for mass spectrometry-based quantitation of more than 80 clinically relevant tumor markers. Results: 55 EAC tissues were analyzed. HER2, PD-L1 and EGFR were overexpressed only in 16.3%, 0%, and 0% of patients, respectively. New oncoproteins #2 and #6 were noted to have high (7,634.0 and 27,222.6 attomoles/ug) and consistent (98.1% and 94.5%) overexpression in EAC samples. Expression of HER2, oncoproteins #2 and #6 were significantly higher in EAC compared to normal esophageal mucosa. There was no statistical difference in the expression of PD-L1 and EGFR between EAC and normal samples. Conclusions: Mass spectrometry revealed a very low prevalence of target oncoproteins in EAC for currently used drugs. Our study potentially reveals alternate markers which are near universally present at high levels and should be further explored for targeted treatment.[Table: see text]

Comprehensive Library Generation for Identification and Quantification of Endometrial Cancer Protein Biomarkers in Cervico-Vaginal Fluid.

Simple SummaryEndometrial cancer is the most common cancer of the female reproductive tract, and its incidence is rising. Early diagnosis has the potential to improve survival as women can receive care at the earliest possible stage when curative treatment is likely. Current tests for endometrial cancer diagnosis are sequentially invasive with low patient acceptability. A detection tool based on minimally invasive samples such as cervico-vaginal fluid would be a major advance in the field. This study focuses on the potential of detecting endometrial cancer based on the proteins and peptides expressed in cervico-vaginal fluid. Using Sequential window acquisition of all theoretical mass spectra (SWATH-MS), we present a spectral library of thousands of proteins in the cervico-vaginal fluid of women with or at risk of endometrial cancer. This important resource will enable the identification of endometrial cancer biomarkers in cervico-vaginal fluid and advances our knowledge of the role of proteomics in endometrial cancer detection.Endometrial cancer is the most common gynaecological malignancy in high-income countries and its incidence is rising. Early detection, aided by highly sensitive and specific biomarkers, has the potential to improve outcomes as treatment can be provided when it is most likely to effect a cure. Sequential window acquisition of all theoretical mass spectra (SWATH-MS), an accurate and reproducible platform for analysing biological samples, offers a technological advance for biomarker discovery due to its reproducibility, sensitivity and potential for data re-interrogation. SWATH-MS requires a spectral library in order to identify and quantify peptides from multiplexed mass spectrometry data. Here we present a bespoke spectral library of 154,206 transitions identifying 19,394 peptides and 2425 proteins in the cervico-vaginal fluid of postmenopausal women with, or at risk of, endometrial cancer. We have combined these data with a library of over 6000 proteins generated based on mass spectrometric analysis of two endometrial cancer cell lines. This unique resource enables the study of protein biomarkers for endometrial cancer detection in cervico-vaginal fluid. Data are available via ProteomeXchange with unique identifier PXD025925.