Data-independent Acquisition Mass Spectrometry Research Articles

Highly accurate detection of early-stage colorectal cancer using tumor and immune extracellular vesicles biomarkers.

262 Background: Colorectal cancer (CRC) is one of the most common cancers worldwide, and early detection is critical for successful treatment and improved survival rates. However, precancerous and early-stage CRC present significant diagnostic challenges due to the small size of lesions and the very low expression of tumor-specific biomarkers in the bloodstream. Current genomics-based diagnostic methods struggle to detect these early-stage and precancerous lesions, making it imperative to develop more sensitive and specific approaches. Circulating extracellular vesicles (EVs) are emerging as a promising solution for early-stage CRC detection. Since EVs are produced by tumor cells as well as tumor microenvironment and host immune response cells, EVs offer the means to detect and monitor small early-stage tumors through both direct detection of tumor-associated biomarkers as well as tumor specific host response and tumor microenvironment biomarkers. Methods: To identify novel early-stage CRC specific biomarkers, we performed proteomics analysis on EVs purified from patient plasma using size exclusion chromatography and a proprietary buffer system that enhances EV and corona protein recovery. TrueDiscovery Data-independent acquisition (DIA) mass spectrometry (MS) analysis was conducted on 24 pre-cancer/stage 0 and 25 stage 1 CRC patients and 75 normal patient plasma samples. An in-house developed machine learning pipeline was used to identify differentially expressed proteins and model candidate multiplexes to identify those with extremely high diagnostic accuracy (> 0.99). Results: An average of ~2,500 proteins were identified per sample and included in bioinformatics analysis. Comparative analysis between control patient EVs and either pre-cancerous/Stage 0, or Stage 1 colon cancer EVs using an in-house Machine Learning pipeline identified 336 and 493 differentially expressed proteins for each group (FDR adjusted p-value < 0.001). Of these, the best 17 pre/stage 0 proteins and 53 stage 1 proteins were trained and tested using Support Vector Machine to assess all potential 3-plexes in order to identify those with mean diagnostic accuracy > 99%. This yielded 5 3-plexes in precancer/stage 0 and 34 3-plexes in stage 1 with near perfect diagnostic accuracy. These plexes are currently being assessed in single analyte and multiplex immunoassays with the goal of translating candidate 3-plexes to the clinical. Conclusions: Key biomarkers from CRC patient EVs indicate the potential to detect and diagnose early-stage and low tumor burden cancers using our methods. Interestingly, the most accurate 3-plexes consist of proteins from immune, inflammatory and metabolic processes, suggesting that for the detection of early stage cancer it may be critical to include both tumor and host specific biomarkers.

Cross-sectional study of proteomic differences between moderate and severe psoriasis

Although an ongoing understanding of psoriasis vulgaris (PV) pathogenesis, little is known about the proteomic differences between moderate and severe psoriasis. In this cross-sectional study, we evaluated the proteomic differences between moderate and severe psoriasis using data-independent acquisition mass spectrometry (DIA-MS). 173 differentially expressed proteins (DEPs) were significantly differentially expressed between the two groups. Among them, 85 proteins were upregulated, while 88 were downregulated (FC ≥ ± 1.5, P < 0.05). Eighteen DEPs were mainly enriched in the IL − 17 signalling pathway, Neutrophil extracellular trap formation, Neutrophil degranulation and NF − kappa B signalling pathway, which were associated with psoriasis pathogenesis. Ingenuity pathway Analysis (IPA) identified TNF and TDP53 as the top upstream up-regulators, while Lipopolysaccharide and YAP1 were the top potential down-regulators. The main active pathways were antimicrobial peptides and PTEN signalling, while the inhibitory pathways were the neutrophil extracellular trap pathway, neutrophil degranulation, and IL-8 signalling. 4D-parallel reaction monitoring (4D-PRM) suggested that KRT6A were downregulated in severe psoriasis. Our data identify Eighteen DEPs as biomarkers of disease severity, and are associated with IL − 17 signalling pathway, Neutrophil extracellular trap formation, NF − kappa B signalling pathway, and defence response to the bacterium. Targeting these molecules and measures to manage infection may improve psoriasis’s severity and therapeutic efficacy.

Automated High-Throughput Affinity Capture-Mass Spectrometry Platform with Data-Independent Acquisition.

Affinity capture (AC) combined with mass spectrometry (MS)-based proteomics is highly utilized throughout the drug discovery pipeline to determine small-molecule target selectivity and engagement. However, the tedious sample preparation steps and time-consuming MS acquisition process have limited its use in a high-throughput format. Here, we report an automated workflow employing biotinylated probes and streptavidin magnetic beads for small-molecule target enrichment in the 96-well plate format, ending with direct sampling from EvoSep Solid Phase Extraction tips for liquid chromatography (LC)-tandem mass spectrometry (MS/MS) analysis. The streamlined process significantly reduced both the overall and hands-on time needed for sample preparation. Additionally, we developed a data-independent acquisition-mass spectrometry (DIA-MS) method to establish an efficient label-free quantitative chemical proteomic kinome profiling workflow. DIA-MS yielded a coverage of ∼380 kinases, a > 60% increase compared to using a data-dependent acquisition (DDA)-MS method, and provided reproducible target profiling of the kinase inhibitor dasatinib. We further showcased the applicability of this AC-MS workflow for assessing the selectivity of two clinical-stage CDK9 inhibitors against ∼250 probe-enriched kinases. Our study here provides a roadmap for efficient target engagement and selectivity profiling in native cell or tissue lysates using AC-MS.

Abstract P001: Discovery and validation of mTOR as an immune mediator of the FLASH effect

Abstract An area of particular interest in FLASH is the potential influence of the immune microenvironment in the sparing of normal tissue. After finding loss of the FLASH effect via survival studies in immunocompromised SCID mice, we examined proteomic analyses performed upon the skin of BALB/c mice for classifiers of FLASH that may be involved in the immune response. Intriguingly, one of our top hits was a known immune regulator, mTOR (mammalian target of rapamycin). Here we have validated and further explored the role of mTOR in FLASH. For these studies we exposed the pelvic region of 6-7-week-old female BALB/c mice to proton radiation at two different dose rates: FLASH (∼80Gy/s) and conventional (∼0.5Gy/s), with doses of either 0, 12, or 14 Gy, and mice were irradiated in the entrance region of a 50 MeV proton beam. After 27 days, surviving animals were euthanized, and their pelts and colons were collected for analysis. Protein extracts from skin were prepared for Data Independent Acquisition-Mass Spectrometry (DIA-MS) with protein aggregation capture. Peptide and protein levels were quantified using the Skyline software platform, with normalization performed using the limma batch correction. Through recursive feature elimination using a support vector machine, we identified tryptic peptides whose abundance distinguished between FLASH and conventional radiation treatments. Our analysis revealed significant upregulation of mTOR and Raptor (the regulatory associated protein of mTOR) in response to FLASH radiation, suggesting a pivotal role for mTOR signaling in mediating the differential effects of FLASH versus conventional radiation. mTOR is known to promote PD-L1 expression on cancer cells and enhance the infiltration of immune-suppressive lymphocytes into tumors through increased signaling of interferon and TGF-β. Based on these results, we sought to explore whether combining FLASH radiation with immune checkpoint inhibitors could enhance therapeutic efficacy in melanoma treatment. We conducted experiments treating melanoma cell lines and mice with the combination of conventional or FLASH radiation, with and without anti-PD-1, and noted an increase in overall survival of mice treated with FLASH + anti-PD-1 suggesting a potential therapeutic benefit from this combination. In addition, lysates from in vitro and in vivo studies displayed increased levels of phospho-mTOR (Ser2448), as well as downstream phosphorylated substrates signifying the role of mTOR in mediation of this response. Furthermore, immunofluorescent analyses of the normal colons harvested from the MS cohort demonstrate increased mTOR signaling in FLASH via elevated downstream phospho-S6 ribosomal protein. mTOR is a known regulator of the immune response in cancer therapies; interestingly, it may also be a regulator of FLASH radiation in normal tissue. We have validated our MS hit by western blot and IF, but further studies are aimed at the elucidation of this mechanism. Citation Format: Danielle P. Johnson Erickson, Gennie L. Parkman, Alec Morimoto, Benjamin A. Shaver, Zacharias Seitz, Ava Delonais-Dick, Sunan Cui, Ning Cao, Jing Zeng, Justin Sanders, William S. Noble, Christine C. Wu, Ramesh Rengan, Michael J. MacCoss. Discovery and validation of mTOR as an immune mediator of the FLASH effect. [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Targeted Therapies in Combination with Radiotherapy; 2025 Jan 26-29; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2025;31(2_Suppl):Abstract nr P001

Comparative Proteomic Atlas of Two Soybean Varieties with Contrasting Seed Oil and Protein Content.

As complex quantitative traits, soybean seed oil and protein contents are governed by dynamic proteome networks that remain largely unknown. Here, we investigated the dynamic changes of the proteome during seed maturation across two soybean varieties with contrasting seed oil and protein content. Through optimizing the detectability of low-abundance proteins and utilizing library-free data-independent acquisition (directDIA) mass spectrometry, we unprecedentedly identified 7414 proteins and 3975 protein groups (PGs), substantially expanding the soybean seed proteome. Among the PGs, 1391 differentially accumulated between the two varieties. By comparing the abundance of PGs between the two varieties, we identified the core and periphery proteome of soybean seeds and revealed that variations in the oil and protein content are primarily attributed to the peripheral proteome, which significantly fluctuated across seed developmental stages. Our work presents a quantitative proteomic atlas underlying the variation of seed oil and protein content in soybean varieties and provides insight into the mechanisms regulating the seed oil and protein content in soybean.

Anaplasma phagocytophilum AFAP targets the host nucleolus and inhibits induced apoptosis.

Anaplasma phagocytophilum, the etiologic agent of human granulocytic anaplasmosis (HGA), is an obligate intracellular Gram-negative bacterium. During infection, A. phagocytophilum transfers its type IV secretion system (T4SS) effector proteins into host cells to manipulate cellular processes. AFAP (an actin filament-associated Anaplasma phagocytophilum protein) was identified as a T4SS effector protein and found to interact with the host nucleolin, as described in a previous study. In this study, proteomic analysis was performed to extensively identify AFAP-interacting proteins in host cells and analyze the potential role of AFAP in modulating host cellular processes. A total of 586 host proteins were identified interacting with AFAP by data-independent acquisition mass spectrometry and annotated to 501 Gene Ontology (GO) terms, with the significantly over-represented ones related to ribosomes, nucleolus, DNA binding, and rRNA metabolic process. Given the role of the nucleolus in cellular stress response, the targeting of AFAP to the nucleolus, and the identification of dozens of AFAP-interacting proteins that were annotated to the GO term (GO:0072331, signal transduction by p53 class mediator), the role of AFAP in modulating host apoptosis was determined. AFAP was found capable of inhibiting induced apoptosis. Thus, the proteomic analysis of AFAP-interacting proteins and determination of AFAP with anti-apoptotic activity may help elucidate the role of this T4SS effector protein in HGA pathogenesis.

TMC7 is required for spermiogenesis and male fertility by regulating TGN-derived vesicles.

Infertility affects 10-12 % of couples worldwide, 50 % of which are male. Abnormal spermatogenesis is among the main causes of male infertility. We were curious about the possible role of transmembrane channel-like protein 7 (TMC7) in spermatogenesis because of its aberrant expression in several male infertility patients. In this study, we found that deletion of Tmc7, which is highly expressed during spermiogenesis, causes a human oligoasthenoteratozoospermia (OAT)-like phenotype in male mice. By histological analysis, TEM, RNA-seq and library-free data-independent acquisition mass spectrometry (DIA-MS) of TMC7-null mouse testes, we found that Tmc7 deletion caused abnormal swelling of trans-Golgi network (TGN) vesicles in elongated spermatids. Further immunofluorescence localization analysis revealed that these vesicles were defined by synaptophysin-like 1 (SYPL1). In addition, TMC7 may act as a potential chloride transport channel to regulate the size of transport vesicles. In conclusion, this study demonstrated that TMC7 is essential for male fertility and may be used as a potential protein for the identification and recognition of OAT. On the other hand, TMC7 may be a potential male contraceptive target.

Advancements in Global Phosphoproteomics Profiling: Overcoming Challenges in Sensitivity and Quantification.

Protein phosphorylation introduces post-genomic diversity to proteins, which plays a crucial role in various cellular activities. Elucidation of system-wide signaling cascades requires high-performance tools for precise identification and quantification of dynamics of site-specific phosphorylation events. Recent advances in phosphoproteomic technologies have enabled the comprehensive mapping of the dynamic phosphoproteomic landscape, which has opened new avenues for exploring cell type-specific functional networks underlying cellular functions and clinical phenotypes. Here, we provide an overview of the basics and challenges of phosphoproteomics, as well as the technological evolution and current state-of-the-art global and quantitative phosphoproteomics methodologies. With a specific focus on highly sensitive platforms, we summarize recent trends and innovations in miniaturized sample preparation strategies for micro-to-nanoscale and single-cell profiling, data-independent acquisition mass spectrometry (DIA-MS) for enhanced coverage, and quantitative phosphoproteomic pipelines for deep mapping of cell and disease biology. Each aspect of phosphoproteomic analysis presents unique challenges and opportunities for improvement and innovation. We specifically highlight evolving phosphoproteomic technologies that enable deep profiling from low-input samples. Finally, we discuss the persistent challenges in phosphoproteomic technologies, including the feasibility of nanoscale and single-cell phosphoproteomics, as well as future outlooks for biomedical applications.

Proteomic Insights into the Regulatory Role of CobQ Deacetylase in Aeromonas hydrophila.

Post-translational modifications are crucial in regulating biological functions across both prokaryotes and eukaryotes. In Aeromonas hydrophila, CobQ, a recently identified novel deacetylase, plays a significant role in lysine deacetylation, influencing bacterial metabolism and stress responses. The present study utilized quantitative proteomics to investigate the impact of cobQ deletion on the global protein expression profile in A. hydrophila. Through data-independent acquisition mass spectrometry, we identified 233 upregulated and 41 downregulated proteins in the cobQ deletion mutant (ΔahcobQ) strain compared to the wild-type (WT) strain. Key differentially expressed proteins were involved in oxidative phosphorylation, bacterial secretion, and ribosomal function. Additionally, phenotypic assays demonstrated that the ΔahcobQ strain exhibited an increased resistance to oxidative phosphorylation inhibitors, suggesting a pivotal role for AhCobQ in energy metabolism. Outer membrane proteins and efflux pumps also showed altered expression, indicating potential implications for membrane permeability and antibiotic resistance. These results suggested that AhCobQ plays a vital regulatory role in maintaining metabolic homeostasis and responding to environmental stress, highlighting its potential as a target for therapeutic interventions against A. hydrophila infections.

Multi-omic integration with human DRG proteomics highlights TNFα signalling as a relevant sexually dimorphic pathway.

The peripheral nervous system has been widely implicated in pathological conditions that exhibit distinct clinical presentations in men and women, most notably in chronic pain disorders. Here, we explored this sexual dimorphism at a molecular level. We expanded the available omics landscape in the PNS to include quantitative proteomics of the human dorsal root ganglia (hDRG) and nerve. Using data-independent acquisition mass spectrometry, we uncovered an extensive protein landscape, validated against tissue-specific differences between the nerve and hDRG. Using a combination of multi-omic analyses and in vitro functional support, we then examined sex-differences, highlighting TNFα signalling as a relevant sexually dimorphic pathway in males. These results support a functional sexually dimorphism in the periphery, which is of particular importance to sensory- and pain-related clinical translation.

Plasma proteomics for novel biomarker discovery in childhood tuberculosis.

Failure to rapidly diagnose tuberculosis disease (TB) and initiate treatment is a driving factor of TB as a leading cause of death in children. Current TB diagnostic assays have poor performance in children, and identifying novel non-sputum-based TB biomarkers to improve pediatric TB diagnosis is a global priority. We sought to develop a plasma biosignature for TB by probing the plasma proteome of 511 children stratified by TB diagnostic classification and HIV status from sites in four low- and middle-income countries, using high-throughput data-independent acquisition mass-spectrometry (DIA-PASEF-MS). We identified 47 proteins differentially regulated (BH adjusted p-values < 1%) between children with microbiologically confirmed TB and children with non-TB respiratory diseases (Unlikely TB). We further employed machine learning to derive three parsimonious biosignatures encompassing 4, 5, or 6 proteins that achieved AUCs of 0.86-0.88 all of which exceeded the minimum WHO target product profile accuracy thresholds for a TB screening test (70% specificity at 90% sensitivity, PPV 0.65-0.74, NPV 0.92-0.95). This work provides insights into the unique host response in pediatric TB disease, as well as a non-sputum biosignature that could reduce delays in TB diagnosis and improve detection and management of TB in children worldwide.

TopDIA: A Software Tool for Top-Down Data-Independent Acquisition Proteomics.

Top-down mass spectrometry is widely used for proteoform identification, characterization, and quantification owing to its ability to analyze intact proteoforms. In the past decade, top-down proteomics has been dominated by top-down data-dependent acquisition mass spectrometry (TD-DDA-MS), and top-down data-independent acquisition mass spectrometry (TD-DIA-MS) has not been well studied. While TD-DIA-MS produces complex multiplexed tandem mass spectrometry (MS/MS) spectra, which are challenging to confidently identify, it selects more precursor ions for MS/MS analysis and has the potential to increase proteoform identifications compared with TD-DDA-MS. Here we present TopDIA, the first software tool for proteoform identification by TD-DIA-MS. It generates demultiplexed pseudo MS/MS spectra from TD-DIA-MS data and then searches the pseudo MS/MS spectra against a protein sequence database for proteoform identification. We compared the performance of TD-DDA-MS and TD-DIA-MS using Escherichia coli K-12 MG1655 cells and demonstrated that TD-DIA-MS with TopDIA increased proteoform and protein identifications compared with TD-DDA-MS.

Differential proteomic expression in non-functional pituitary neuroendocrine tumours and pituitary glands.

Pituitary neuroendocrine tumours (PitNETs) are common accounting for 10 to 25 % of all intracranial tumours. This project describes the feasibility of developing a novel membrane-based biomarker that could be used for fluorescent guided surgery. The aim was to catalogue the differential expression of membrane proteins between non-functional PitNETs and pituitary glands. Ten pituitary gland tissue specimens were obtained from the National Institute of Health (NIH) NeuroBio-Bank and twenty non-functional PitNETs were obtained from the Northwestern University Nervous System Tumour Bank. Mass spectrometry analysis using an Orbitrap Fusion Lumos Tribrid Mass Spectrometer linked to a Dionex Ultimate 3000 UPLC system was undertaken. Data Dependent Acquisition Mass Spectrometry and Data Independent Acquisition Mass Spectrometry was then completed. Pathway enrichment analysis was performed using clusterProfiler v4.6.0. Functional enrichment analysis was conducted using Gene Ontology terms and Reactome pathways. Differential expression analysis between the two groups revealed a total of 2110 significant differently expressed proteins (DEPs), with 1387 of these also having a Log2 fold change either greater than 1, or less than -1. Of the 2110 DEPs, 925 were upregulated in tumours compared to control, while 1185 were downregulated. We have demonstrated a proteomic comparison between non-functional PitNETs and normal pituitary glands. These results demonstrate differences consistent with contemporary literature but shows that NOTCH3 and PTPRJ are up-regulated in non-functional PitNETs compared to pituitary glands.

Mass Spectrometry-Based Workflow for the Identification and Quantification of Alternative and Canonical Proteins in Pancreatic Cancer Cells.

The identification of small proteins and proteins produced from unannotated open reading frames (called alternative proteins or AltProts) has changed our vision of the proteome and has attracted more and more attention from the scientific community. Despite several studies investigating particular AltProts in diseases and demonstrating their importance in such context, we are still missing data on their expression and functions in many pathologies. Among these, pancreatic ductal adenocarcinoma (PDAC) is a particularly relevant case to study alternative proteins. Indeed, late detection of this disease, notably due to the lack of reliable biomarkers of early-stage PDAC, and the fact that tumors rapidly develop resistance to most of the treatments used in the clinics warrant the exploration of new repertoires of molecules. In the present article, we aim to investigate the alternative proteome of pancreatic cancer cell lines as a first attempt to decipher the expression of AltProts in PDAC. Thanks to a combined data-dependent and data-independent acquisition mass spectrometry workflow, we were able to identify tryptic peptides matching 113 AltProts in a panel of 6 cell lines. In addition, we identified AltProts differentially expressed between pancreatic cancer cell lines and other cells (HeLa and HEK293T). Finally, mining the TCGA and Gtex databases showed that the corresponding transcripts encoding several AltProts we identified are differentially expressed between PDAC tumors and normal tissues and are correlated with the patient's survival.

Proteomic Analysis of Tissue Proteins Related to Lateral Lymph Node Metastasis in Papillary Thyroid Microcarcinoma.

Patients with lateral lymph node metastasis (LLNM) may experience higher locoregional recurrence rates and poorer prognoses compared to those without LLNM, highlighting the need for effective preoperative stratification to reliably assess risk LLNM. In this study, we collected PTMC samples from Peking Union Medical College Hospital and employed data-independent acquisition mass spectrometry proteomics technique to identify protein profiles in PTMC tissues with and without LLNM. Pseudo temporal analysis and single sample gene set enrichment analysis were conducted in combination with The Cancer Genome Atlas Thyroid Carcinoma for functional coordination analysis and the construction of a prediction model based on random forest. Non-negative matrix factorization (NMF) clustering was utilized to classify molecular subtypes of PTMC. Our findings revealed that the differential activation of pathways such as MAPK and PI3K was critical in enhancing the lateral lymph node metastatic potential of PTMC. We successfully screened biomarkers via machine learning and public databases, creating an effective prediction model for metastasis. Additionally, we explored the mechanism of metastasis-associated PTMC subtypes via NMF clustering. These insights into LLNM mechanisms in PTMC may contribute to future biomarker screening and the identification of therapeutic targets.

Data-independent acquisition-based blood proteomics unveils predictive biomarkers for neonatal necrotizing enterocolitis

Necrotizing enterocolitis (NEC) is a life-threatening condition affecting preterm infants, sometimes necessitating surgical treatment. This study aimed to analyze differentially expressed proteins (DEPs) and access their biological and clinical significance in the plasma of neonates with NEC. Peripheral blood samples were collected from NEC infants at various time points, and plasma was separated. Data-independent acquisition (DIA) technology was utilized to identify DEPs among NEC patients at different stages. Bioinformatic analyses, including Gene Ontology and Kyoto Encyclopedia of Genes and Genomes, and protein-to-protein interaction analyses were performed on the DEPs. External datasets, along with receiver operating characteristic curves and gene set enrichment analysis, were used to clinically and biologically validate the findings. DEPs between the NEC and pre-NEC groups indicated reduced protein, heme, nitrogen, and purine nucleotide biosynthesis during NEC formation. In addition, enriched DEPs among the NEC groups at different time points suggested reconstructed extracellular matrix, aberrant B-lymphocyte immune responses, and decreased glycosaminoglycan levels during NEC progression. These findings were both clinically and biologically validated using external datasets. Our study highlights the clinical and biological relevance of proteomics in NEC patients. This study demonstrates key pathways involved in NEC pathogenesis and establishes DIA mass spectrometry as a powerful and noninvasive tool for evaluating and predicting NEC formation and progression.Graphical

Elevated Cerebrospinal Fluid Ubiquitin Carboxyl-Terminal Hydrolase Isozyme L1 in Asymptomatic C9orf72 Hexanucleotide Repeat Expansion Carriers.

To identify biochemical changes in individuals at higher risk of developing amyotrophic lateral sclerosis (ALS) or frontotemporal dementia (FTD) via C9orf72 hexanucleotide repeat expansion (HRE) heterozygosity. Cross-sectional observational study of 48 asymptomatic C9orf72 HRE carriers, 39 asymptomatic non-carrier controls, 19 people with sporadic ALS, 10 with C9orf72 ALS, 14 with sporadic FTD, and 10 with C9orf72 FTD. Relative abundance of 30 pre-defined cerebrospinal fluid biomarkers of ALS and FTD were compared in asymptomatic C9orf72 HRE carriers and age-matched non-carrier controls. Differential abundance of these proteins was quantified using data independent acquisition mass spectrometry or electro chemiluminescent assay for neurofilament light chain. Unbiased analysis of the entire cerebrospinal fluid proteome was then carried out. Ubiquitin carboxyl-hydrolase isozyme L1 levels were higher in asymptomatic C9orf72 HRE carriers compared with age-matched non-carriers (log2fold change 0.20, FDR-adjusted p-value = 0.034), whereas neurofilament light chain levels did not significantly differ. Ubiquitin carboxyl-hydrolase isozyme L1 levels remained elevated after matching of groups by neurofilament levels (p = 0.011), and after adjusting for age, sex, and neurofilament levels. A significant difference was also observed when restricting analysis to younger participants (<37) matched by neurofilament level (p = 0.007). Elevated cerebrospinal fluid ubiquitin carboxyl-hydrolase isozyme L1 levels in C9orf72 HRE carriers can occur in the absence of increased neurofilament levels, potentially reflecting either compensatory or pathogenic mechanisms preceding rapid neuronal loss. This brings forward the window on changes associated with the C9orf72 HRE carrier state, with potential to inform understanding of penetrance and approaches to prevention. ANN NEUROL 2024.

Abstract PR013: Highly accurate detection of early-stage colorectal cancer using tumor and immune extracellular vesicles biomarkers

Abstract Introduction: Colorectal cancer (CRC) is one of the most common cancers worldwide, and early detection is critical for successful treatment and improved survival rates. However, precancerous and early-stage CRC present significant diagnostic challenges due to the small size of lesions and the very low expression of tumor-specific biomarkers in the bloodstream. Current genomics-based diagnostic methods struggle to detect these lesions, making it imperative to develop more sensitive and specific approaches. Circulating extracellular vesicles (EVs) are emerging as a promising solution for early-stage CRC detection, since EVs are produced by tumor cells as well as the tumor microenviroment and host immune cells. Thus, EVs may offer the means to detect and monitor small early-stage tumors through both direct detection of tumor- associated biomarkers as well through tumor specific host response and tumor microenvironment biomarkers. Methods: To identify novel early-stage CRC specific biomarkers, we performed proteomics analysis on EVs purified from patient plasma using size exclusion chromatography and a proprietary buffer system that enhances EV and corona protein recovery. TrueDiscovery™ Data-independent acquisition (DIA) mass spectrometry (MS) analysis was conducted on 24 pre- cancer/stage 0 and 25 stage 1 CRC patients and 75 normal patient plasma samples. An in-house developed machine learning pipeline was used to identify differentially expressed proteins and model candidate multiplexes to identify those with extremely high diagnostic accuracy (&amp;gt; 0.99). Results: An average of ∼2,500 proteins were identified per sample and included in bioinformatics analysis. Comparative analysis between control patient EVs and either pre- cancerous/Stage 0, or Stage 1 colon cancer EVs using an in-house Machine Learning pipeline identified 336 and 493 differentially expressed proteins for each group (FDR adjusted p-value &amp;lt; 0.001). Of these, the best 17 pre/stage 0 proteins and 53 stage 1 proteins were trained and tested using Support Vector Machine to assess all potential 3-plexes in order to identify those with mean diagnostic accuracy &amp;gt; 99%. This yielded 5 3-plexes in precancer/stage 0 and 34 3-plexes in stage 1 with near perfect diagnostic accuracy. These plexes are currently being assessed in single analyte and multiplex immunoassays with the goal of translating candidate 3-plexes to the clinical. Conclusions: Key biomarkers from CRC patient EVs indicate the potential to detect and diagnose early-stage and low tumor burden cancers using our methods. Interestingly, the most accurate 3-plexes consist of proteins from immune, inflammatory and metabolic processes, suggesting that for the detection of early stage cancer it may be critical to include both tumor and host specific biomarkers. Citation Format: Poorva Mudgal, Cheryl Bandoski, Zachary Opheim, Martin Mehnert, Valesca Anschau, Issa Isaac, Alan Ezrin, Todd Hembrough. Highly accurate detection of early-stage colorectal cancer using tumor and immune extracellular vesicles biomarkers [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr PR013.

A Proteomics Pipeline for Generating Clinical Grade Biomarker Candidates from Data‐Independent Acquisition Mass Spectrometry (DIA‐MS) Discovery

AbstractClinical biomarker development has been stymied by inaccurate protein quantification from mass spectrometry (MS) discovery data and a prolonged validation process. To mitigate these issues, we created the Targeted Extraction Assessment of Quantification (TEAQ) software package that uses data‐independent acquisition analysis from a discovery cohort to select precursors, peptides, and proteins that adhere to analytical criteria required for established targeted assays. TEAQ was applied to DIA‐MS data from plasma samples acquired on a new high resolution accurate mass (HRAM) mass spectrometry platform where precursors were evaluated for linearity, specificity, repeatability, reproducibility, and intra‐protein correlation based on 8‐ or 11‐point loading curves at three throughputs. This data can be used as a general resource for developing other targeted assays. TEAQ analysis of data from a case and control cohort for inflammatory bowel disease (n=492) identified 1110 signature peptides for 326 quantifiable proteins from the 1179 identified proteins. Applying TEAQ analysis to discovery data will streamline targeted assay development and the transition to validation and clinical studies.

A Proteomics Pipeline for Generating Clinical Grade Biomarker Candidates from Data-Independent Acquisition Mass Spectrometry (DIA-MS) Discovery.

Clinical biomarker development has been stymied by inaccurate protein quantification from mass spectrometry (MS) discovery data and a prolonged validation process. To mitigate these issues, we created the Targeted Extraction Assessment of Quantification (TEAQ) software package that uses data-independent acquisition analysis from a discovery cohort to select precursors, peptides, and proteins that adhere to analytical criteria required for established targeted assays. TEAQ was applied to DIA-MS data from plasma samples acquired on a new high resolution accurate mass (HRAM) mass spectrometry platform where precursors were evaluated for linearity, specificity, repeatability, reproducibility, and intra-protein correlation based on 8- or 11-point loading curves at three throughputs. This data can be used as a general resource for developing other targeted assays. TEAQ analysis of data from a case and control cohort for inflammatory bowel disease (n=492) identified 1110 signature peptides for 326 quantifiable proteins from the 1179 identified proteins. Applying TEAQ analysis to discovery data will streamline targeted assay development and the transition to validation and clinical studies.