Differential Analysis of Cereblon Neosubstrates in Rabbit Embryos Using Targeted Proteomics.

Targeted protein degradation is the selective removal of a protein of interest through hijacking intracellular protein cleanup machinery. This rapidly growing field currently relies heavily on the use of the E3 ligase cereblon (CRBN) to target proteins for degradation, including the immunomodulatory drugs (IMiDs) thalidomide, lenalidomide, and pomalidomide which work through a molecular glue mechanism of action with CRBN. While CRBN recruitment can result in degradation of a specific protein of interest (e.g., efficacy), degradation of other proteins (called CRBN neosubstrates) also occurs. Degradation of one or more of these CRBN neosubstrates is believed to play an important role in thalidomide-related developmental toxicity observed in rabbits and primates. We identified a set of 25 proteins of interest associated with CRBN-related protein homeostasis and/or embryo/fetal development. We developed a targeted assay for these proteins combining peptide immunoaffinity enrichment and high-resolution mass spectrometry and successfully applied this assay to rabbit embryo samples from pregnant rabbits dosed with three IMiDs. We confirmed previously reported in vivo decreases in neosubstrates like SALL4, as well as provided evidence of neosubstrate changes for proteins only examined in vitro previously. While there were many proteins that were similarly decreased by all three IMiDs, no compound had the exact same neosubstrate degradation profile as another. We compared our data to previous literature reports of IMiD-induced degradation and known developmental biology associations. Based on our observations, we recommend monitoring at least a major subset of these neosubstrates in a developmental test system to improve CRBN-binding compound-specific risk assessment. A strength of our assay is that it is configurable, and the target list can be readily adapted to focus on only a subset of proteins of interest or expanded to incorporate new findings as additional information about CRBN biology is discovered.

The key role of Spain in the traffic of West Nile virus lineage 1 strains between Europe and Africa.

BACKGROUND: West Nile Virus (WNV) is a zoonotic arbovirus worldwide spread. Seasonal WNV outbreaks occur in the Mediterranean basin since the late 1990's with ever-increasing incidence. In Southern Spain WNV is endemic, as disease foci - caused by WNV lineage 1 (WNV-L1) strains - occur every year. On the contrary, WNV-L2 is the dominant lineage in Europe, so most European WNV sequences available belong to this lineage, WNV-L1 sequences being still scarce. METHODS: To fill this gap, this study reports the genetic characterisation of 27 newly described WNV-L1 strains, involved in outbreaks affecting wild birds and horses during the last decade in South-Western Spain. RESULTS: All strains except one belong to the Western Mediterranean-1 sub-cluster (WMed-1), related phylogenetically to Italian, French, Portuguese, Moroccan and, remarkably, Senegalese strains. This sub-cluster persisted, spread and evolved into three distinguishable WMed-1 phylogenetic groups that co-circulated, notably, in the same province (Cádiz). They displayed different behaviours: from long-term persistence and rapid spread to neighbouring regions within Spain, to long-distance spread to different countries, including transcontinental spread to Africa. Among the different introductions of WNV in Spain revealed in this study, some of them succeeded to get established, some extinguished from the territory shortly afterwards. Furthermore, Spain's southernmost province, Cádiz, constitutes a hotspot for virus incursion. CONCLUSION: Southern Spain seems a likely scenario for emergence of exotic pathogens of African origin. Therefore, circulation of diverse WNV-L1 variants in Spain prompts for an extensive surveillance under a One Health approach.

Koina: Democratizing machine learning for proteomics research.

Recent developments in machine-learning (ML) and deep-learning (DL) have immense potential for applications in proteomics, such as generating spectral libraries, improving peptide identification, and optimizing targeted acquisition modes. Although new ML/DL models for various applications and peptide properties are frequently published, the rate at which these models are adopted by the community is slow, which is mostly due to technical challenges. We believe that, for the community to make better use of state-of-the-art models, more attention should be spent on making models easy to use and accessible by the community. To facilitate this, we developed Koina, an open-source containerized, decentralized and online-accessible high-performance prediction service that enables ML/DL model usage in any pipeline. Using the widely used FragPipe computational platform as example, we show how Koina can be easily integrated with existing proteomics software tools and how these integrations improve data analysis.

Sodium arsenite impairs sperm quality via downregulating the ZMYND15 and ZMYND10.

Zinc finger MYND-type containing 15 (ZMYND15) has been documented to play important roles in spermatogenesis, and mutants contribute to recessive azoospermia, severe oligozoospermia, non-obstructive azoospermia, teratozoospermia, even male infertility. ZMYND10 is involved in sperm motility. Whether environmental pollutants impair male fertility via regulating the expression of ZMYND15 and ZMYND10 has not been studied. Arsenic exposure results in poor sperm quality and male infertility. In order to investigate whether arsenic-induced male reproductive toxicity is related to the expression of ZMYND15, ZMYND10 and their target genes, we established a male rat model of sodium arsenite exposure-induced reproductive injury, measured sperm quality, serum hormone levels, mRNA and protein expressions of intratesticular ZMYND15 and ZMYND10 as well as their target genes. The results showed that, in addition to the increased mRNA expression of Tnp1, sodium arsenite exposure reduced sperm quality, serum hormone levels, and mRNA and protein expression of intratesticular ZMYND15 and ZMYND10 and their target genes in male rats compared with the control group (p < .05). Therefore, our study first showed that the environmental pollutant arsenic impairs sperm quality in male rats by reducing the expression of ZMYND10 and ZMYND15 and their regulatory genes, which provides a possible diagnostic marker for environmental pollutants-induced male infertility.

Quantitative accuracy of lung function measurement using parametric response mapping: A virtual imaging study.

Parametric response mapping (PRM) is a voxel-based quantitative CT imaging biomarker that measures the severity of chronic obstructive pulmonary disease (COPD) by analyzing both inspiratory and expiratory CT scans. Although PRM-derived measurements have been shown to predict disease severity and phenotyping, their quantitative accuracy is impacted by the variability of scanner settings and patient conditions. The aim of this study was to evaluate the variability of PRM-based measurements due to the changes in the scanner types and configurations. We developed 10 human chest models with emphysema and air-trapping at end-inspiration and end-expiration states. These models were virtually imaged using a scanner-specific CT simulator (DukeSim) to create CT images at different acquisition settings for energy-integrating and photon-counting CT systems. The CT images were used to estimate PRM maps. The quantified measurements were compared with ground truth values to evaluate the deviations in the measurements. Results showed that PRM measurements varied with scanner type and configurations. The emphysema volume was overestimated by 3 ± 9.5 % (mean ± standard deviation) of the lung volume, and the functional small airway disease (fSAD) volume was underestimated by 7.5±19 % of the lung volume. PRM measurements were more accurate and precise when the acquired settings were photon-counting CT, higher dose, smoother kernel, and larger pixel size. This study demonstrates the development and utility of virtual imaging tools for systematic assessment of a quantitative biomarker accuracy.

CircANXA4 (hsa_circ_0055087) regulates the miR-1256/PRM1 axis to promote tumor progression in colorectal cancer.

Colorectal cancer (CRC) incidence ranks third among malignant cancers with a high propensity for distant metastasis. Despite continuous efforts to improve treatment, the prognosis especially in patients with advanced distant metastasis is low. The mechanism of development and progression of CRC is not fully understood. Non-coding RNAs (ncRNAs) have emerged as essential regulators in cancer progression. Here, we aim to dissect the role of one critical ncRNA, circANXA4, in CRC progression. CircANXA4 expression was analyzed by the GEO database. Differentially expressed circRNAs were identified by the Limma package R software. Expression of circANXA4 and miR-1256 was detected by qRT-PCR. The regulation of circANXA4 on cell proliferation and progression was confirmed with the cell viability assay using cell counting kit-8 (CCK-8) and transwell migration assay. RNA pull-down assay, RNA immunoprecipitation (RIP), and western blot were used to determine the interaction between circANXA4, miR-1256, and protamine1 (PRM1). CircANXA4 was upregulated in both CRC tissues and cell lines. Knockdown of circANXA4 effectively reduced cell proliferation, progression, and migration. Additionally, silencing circANXA4 remarkably increased miR-1256 expression, while reducing PRM1 expression, thereby demonstrating that circANXA4 downregulates miR-1256 expression through a complementary binding site. Rescue experiments revealed the interactions between circANXA4, miR-1256, and PRM1. Pearson correlation analysis revealed that circANXA4 expression positively correlated with PRM1 expression and miR-1256 expression inversely correlated with PRM1 expression. In sum, we demonstrated that circANXA4 promotes cancer cell proliferation and progression by sponging miR-1256 and upregulating PRM1 in CRC.

Hydrogen Sulfide Exerted a Pro-Angiogenic Role by Promoting the Phosphorylation of VEGFR2 at Tyr797 and Ser799 Sites in Hypoxia-Reoxygenation Injury.

The protective effects of hydrogen sulfide (H2S) against ischemic brain injury and its role in promoting angiogenesis have been established. However, the specific mechanism underlying these effects remains unclear. This study is designed to investigate the regulatory impact and mechanism of H2S on VEGFR2 phosphorylation. Following expression and purification, the recombinant His-VEGFR2 protein was subjected to LC-PRM/MS analysis to identify the phosphorylation sites of VEGFR2 upon NaHS treatment. Adenovirus infection was used to transfect primary rat brain artery endothelial cells (BAECs) with the Ad-VEGFR2WT, Ad-VEGFR2Y797F, and Ad-VEGFR2S799A plasmids. The expression of VEGFR2 and recombinant Flag-VEGFR2, along with Akt phosphorylation, cell proliferation, and LDH levels, was assessed. The migratory capacity and tube-forming potential of BAECs were assessed using wound healing, transwell, and tube formation assays. NaHS notably enhanced the phosphorylation of VEGFR2 at Tyr797 and Ser799 sites. These phosphorylation sites were identified as crucial for mediating the protective effects of NaHS against hypoxia-reoxygenation (H/R) injury. NaHS significantly enhanced the Akt phosphorylation, migratory capacity, and tube formation of BAECs and upregulated the expression of VEGFR2 and recombinant proteins. These findings suggest that Tyr797 and Ser799 sites of VEGFR2 serve as crucial mediators of H2S-induced pro-angiogenic effects and protection against H/R injury.

Simultaneous targeted and discovery-driven clinical proteotyping using hybrid-PRM/DIA.

BACKGROUND: Clinical samples are irreplaceable, and their transformation into searchable and reusable digital biobanks is critical for conducting statistically empowered retrospective and integrative research studies. Currently, mainly data-independent acquisition strategies are employed to digitize clinical sample cohorts comprehensively. However, the sensitivity of DIA is limited, which is why selected marker candidates are often additionally measured targeted by parallel reaction monitoring. METHODS: Here, we applied the recently co-developed hybrid-PRM/DIA technology as a new intelligent data acquisition strategy that allows for the comprehensive digitization of rare clinical samples at the proteotype level. Hybrid-PRM/DIA enables enhanced measurement sensitivity for a specific set of analytes of current clinical interest by the intelligent triggering of multiplexed parallel reaction monitoring (MSxPRM) in combination with the discovery-driven digitization of the clinical biospecimen using DIA. Heavy-labeled reference peptides were utilized as triggers for MSxPRM and monitoring of endogenous peptides. RESULTS: We first evaluated hybrid-PRM/DIA in a clinical context on a pool of 185 selected proteotypic peptides for tumor-associated antigens derived from 64 annotated human protein groups. We demonstrated improved reproducibility and sensitivity for the detection of endogenous peptides, even at lower concentrations near the detection limit. Up to 179 MSxPRM scans were shown not to affect the overall DIA performance. Next, we applied hybrid-PRM/DIA for the integrated digitization of biobanked melanoma samples using a set of 30 AQUA peptides against 28 biomarker candidates with relevance in molecular tumor board evaluations of melanoma patients. Within the DIA-detected approximately 6500 protein groups, the selected marker candidates such as UFO, CDK4, NF1, and PMEL could be monitored consistently and quantitatively using MSxPRM scans, providing additional confidence for supporting future clinical decision-making. CONCLUSIONS: Combining PRM and DIA measurements provides a new strategy for the sensitive and reproducible detection of protein markers from patients currently being discussed in molecular tumor boards in combination with the opportunity to discover new biomarker candidates.

Plasma proteomic characterization of colorectal cancer patients with FOLFOX chemotherapy by integrated proteomics technology.

BACKGROUND: Colorectal Cancer (CRC) is a prevalent form of cancer, and the effectiveness of the main postoperative chemotherapy treatment, FOLFOX, varies among patients. In this study, we aimed to identify potential biomarkers for predicting the prognosis of CRC patients treated with FOLFOX through plasma proteomic characterization. METHODS: Using a fully integrated sample preparation technology SISPROT-based proteomics workflow, we achieved deep proteome coverage and trained a machine learning model from a discovery cohort of 90 CRC patients to differentiate FOLFOX-sensitive and FOLFOX-resistant patients. The model was then validated by targeted proteomics on an independent test cohort of 26 patients. RESULTS: We achieved deep proteome coverage of 831 protein groups in total and 536 protein groups in average for non-depleted plasma from CRC patients by using a Orbitrap Exploris 240 with moderate sensitivity. Our results revealed distinct molecular changes in FOLFOX-sensitive and FOLFOX-resistant patients. We confidently identified known prognostic biomarkers for colorectal cancer, such as S100A4, LGALS1, and FABP5. The classifier based on the biomarker panel demonstrated a promised AUC value of 0.908 with 93% accuracy. Additionally, we established a protein panel to predict FOLFOX effectiveness, and several proteins within the panel were validated using targeted proteomic methods. CONCLUSIONS: Our study sheds light on the pathways affected in CRC patients treated with FOLFOX chemotherapy and identifies potential biomarkers that could be valuable for prognosis prediction. Our findings showed the potential of mass spectrometry-based proteomics and machine learning as an unbiased and systematic approach for discovering biomarkers in CRC.

Proteomics Defines Plasma Biomarkers for the Early Diagnosis of Biliary Atresia.

Early diagnosis of biliary atresia (BA) is crucial for improving the chances of survival and preserving the liver function of pediatric patients with BA. Herein, we performed proteomics analysis using data-independent acquisition (DIA) and parallel reaction monitoring (PRM) to explore potential biomarkers for the early diagnosis of BA compared to other non-BA jaundice cases. Consequently, we detected and validated differential protein expression in the plasma of patients with BA compared to the plasma of patients with intrahepatic cholestasis. Bioinformatics analysis revealed the enriched biological processes characteristic of BA by identifying the differential expression of specific proteins. Signaling pathway analysis revealed changes in the expression levels of proteins associated with an alteration in immunoglobulin levels, which is indicative of immune dysfunction in BA. The combination of polymeric immunoglobulin receptor expression and immunoglobulin lambda variable chain (IGL c2225_light_IGLV1-47_IGLJ2), as revealed via machine learning, provided a useful early diagnostic model for BA, with a sensitivity of 0.8, specificity of 1, accuracy of 0.89, and area under the curve value of 0.944. Thus, our study identified a possible effective plasma biomarker for the early diagnosis of BA and could help elucidate the underlying mechanisms of BA.

A framework for quality control in quantitative proteomics.

A thorough evaluation of the quality, reproducibility, and variability of bottom-up proteomics data is necessary at every stage of a workflow from planning to analysis. We share real-world case studies applying adaptable quality control (QC) measures to assess sample preparation, system function, and quantitative analysis. System suitability samples are repeatedly measured longitudinally with targeted methods, and we share examples where they are used on three instrument platforms to identify severe system failures and track function over months to years. Internal QCs incorporated at protein and peptide-level allow our team to assess sample preparation issues and to differentiate system failures from sample-specific issues. External QC samples prepared alongside our experimental samples are used to verify the consistency and quantitative potential of our results during batch correction and normalization before assessing biological phenotypes. We combine these controls with rapid analysis using Skyline, longitudinal QC metrics using AutoQC, and server-based data deposition using PanoramaWeb. We propose that this integrated approach to QC be used as a starting point for groups to facilitate rapid quality control assessment to ensure that valuable instrument time is used to collect the best quality data possible.

The proteome of Penicillium expansum during infection of postharvest apple is revealed using Label-Free and Parallel Reaction Monitoring(PRM)Techniques.

Penicillium expansum is the main pathogen in the postharvest storage of apples. Penicilliosis caused by P. expansum infection not only seriously affects the appearance and quality of fruits, but also the secondary metabolite Patulin (PAT) can cause harm to human health. Until now, little attention has been paid to the molecular mechanism of P. expansum infecting apples. Studying its molecular mechanism can help us better prevent and control apple postharvest blue mold. In this present investigation, we will use Label-Free technology to perform proteomic sequencing on apple samples at key time points of P. expansum infection, explore and screen key proteins and metabolic pathways during infection, and use Parallel Reaction Monitoring (PRM) technology to thoroughly validate proteomic data. The infection of P. expansum activates the MAPK signaling pathway, plant-pathogen interaction metabolic pathway and phenylpropanoid biosynthesis pathway of apple, participates in the regulation of ROS generation and oxidative stress process, promotes the synthesis of lignin and flavonoids, and the synthesis of Pathogenesis-Related Protein helps apple directly defend against P. expansum infection. This study provides the foundation for relevant postharvest control strategies, paving the way for further exploration of the proteome of pathogens infecting fruit and vegetables. SIGNIFICANCE: Proteins are macromolecules essential to the life of organisms, as they participate in the function and structure of cells. Proteomics technology is currently one of the important means to study the the response mechanism of pathogenic bacteria to plant infection, which can reveal the essence of physiological and pathological processes and help to clarify the possible relationship between protein abundance and plant stress. The present study essentially uses recent proteome analysis technology, namely label-free and PRM techniques, and lays the foundations for studying the of the infection response between P. expansum and apples. In particular, it provides a broad perspective on the molecular mechanism of P. expansum in the early stage of apple infection through detailed functional exploration and verification of associated proteins. Thus, it provides a theoretical basis for preventing and treating apple postharvest blue mold.

A peptide dataset for target analysis of human complement system proteins.

The targeted LC-MS/MS method has been widely applied for peptide quantification, offering sensibility, specificity, and reproducibility to the analysis. However, it requires the prior selection of targets, including the construction of a spectral library. Here, we present a dataset comprising peptide mass spectra for targeted LC-MS/MS method setup, applied to a set of human complement system proteins. Additionally, we selected a group of peptides and demonstrated their stability and reproducibility in quantification. This dataset is invaluable for studies aiming at the quantification of the complement system proteins by targeted LC-MS/MS, as it provides data for spectral library construction and a list of selected peptides.

Single Isotopologue for In-Sample Calibration and Absolute Quantitation by LC-MS/MS.

Targeted mass spectrometry (MS)-based absolute quantitative analysis has been increasingly used in biomarker discovery. The ability to accurately measure the masses by MS enabled the use of isotope-incorporated surrogates having virtually identical physiochemical properties with the target analytes as calibrators. Such a unique capacity allowed for accurate in-sample calibration. Current in-sample calibration uses multiple isotopologues or structural analogues for both the surrogate and the internal standard. Here, we simplified this common practice by using endogenous light peptides as the internal standards and used a mathematical deduction of "heavy matching light, HML" to directly quantify an endogenous analyte. This method provides all necessary assay performance parameters in the authentic matrix, including the lower limit of quantitation (LLOQ) and intercept of the calibration curve, by using only a single isotopologue of the analyte. This method can be applied to the quantitation of proteins, peptides, and small molecules. Using this method, we quantified the efficiency of heart tissue digestion and recovery using sodium deoxycholate as a detergent and two spiked exogenous proteins as mimics of heart proteins. The results demonstrated the robustness of the assay.

Absolute quantitation of human wild-type DNAI1 protein in lung tissue using a nanoLC-PRM-MS-based targeted proteomics approach coupled with immunoprecipitation.

BACKGROUND: Dynein axonemal intermediate chain 1 protein (DNAI1) plays an essential role in cilia structure and function, while its mutations lead to primary ciliary dyskinesia (PCD). Accurate quantitation of DNAI1 in lung tissue is crucial for comprehensive understanding of its involvement in PCD, as well as for developing the potential PCD therapies. However, the current protein quantitation method is not sensitive enough to detect the endogenous level of DNAI1 in complex biological matrix such as lung tissue. METHODS: In this study, a quantitative method combining immunoprecipitation with nanoLC-MS/MS was developed to measure the expression level of human wild-type (WT) DNAI1 protein in lung tissue. To our understanding, it is the first immunoprecipitation (IP)-MS based method for absolute quantitation of DNAI1 protein in lung tissue. The DNAI1 quantitation was achieved through constructing a standard curve with recombinant human WT DNAI1 protein spiked into lung tissue matrix. RESULTS: This method was qualified with high sensitivity and accuracy. The lower limit of quantitation of human DNAI1 was 4 pg/mg tissue. This assay was successfully applied to determine the endogenous level of WT DNAI1 in human lung tissue. CONCLUSIONS: The results clearly demonstrate that the developed assay can accurately quantitate low-abundance WT DNAI1 protein in human lung tissue with high sensitivity, indicating its high potential use in the drug development for DNAI1 mutation-caused PCD therapy.

SECRET AGENT O-GlcNAcylates Hundreds of Proteins Involved in Diverse Cellular Processes in Arabidopsis.

O-GlcNAcylation is a critical post-translational modification of proteins observed in both plants and animals and plays a key role in growth and development. While considerable knowledge exists about over 3000 substrates in animals, our understanding of this modification in plants remains limited. Unlike animals, plants possess two putative homologs: SECRET AGENT (SEC) and SPINDLY, with SPINDLY also exhibiting O-fucosylation activity. To investigate the role of SEC as a major O-GlcNAc transferase in plants, we utilized lectin-weak affinity chromatography enrichment and stable isotope labeling in Arabidopsis labeling, quantifying at both MS1 and MS2 levels. Our findings reveal a significant reduction in O-GlcNAc levels in the sec mutant, indicating the critical role of SEC in mediating O-GlcNAcylation. Through a comprehensive approach, combining higher-energy collision dissociation and electron-transfer high-energy collision dissociation fragmentation with substantial fractionations, we expanded our GlcNAc profiling, identifying 436 O-GlcNAc targets, including 227 new targets. The targets span diverse cellular processes, suggesting broad regulatory functions of O-GlcNAcylation. The expanded targets also enabled exploration of crosstalk between O-GlcNAcylation and O-fucosylation. We also examined electron-transfer high-energy collision dissociation fragmentation for site assignment. This report advances our understanding of O-GlcNAcylation in plants, facilitating further research in this field.

Targeted Glycoproteomics Analysis Using MRM/PRM Approaches.

MS-target analyses are frequently utilized to analyze and validate structural changes of biomolecules across diverse fields of study such as proteomics, glycoproteomics, glycomics, lipidomics, and metabolomics. Targeted studies are commonly conducted using multiple reaction monitoring (MRM) and parallel reaction monitoring (PRM) techniques. A reliable glycoproteomics analysis in intricate biological matrices is possible with these techniques, which streamline the analytical workflow, lower background interference, and enhance selectivity and specificity.

Targeted Analysis of Permethylated N-Glycans Using MRM/PRM Approaches.

Targeted mass spectrometric analysis is widely employed across various omics fields as a validation strategy due to its high sensitivity and accuracy. The approach has been successfully employed for the structural analysis of proteins, glycans, lipids, and metabolites. Multiple reaction monitoring (MRM) and parallel reaction monitoring (PRM) have been the methods of choice for targeted structural studies of biomolecules. These target analyses simplify the analytical workflow, reduce background interference, and increase selectivity/specificity, allowing for a reliable quantification of permethylated N-glycans in complex biological matrices.

Illuminating function of the understudied druggable kinome.

The human kinome, with more than 500 proteins, is crucial for cell signaling and disease. Yet, about one-third of kinases lack in-depth study. The Data and Resource Generating Center for Understudied Kinases has developed multiple resources to address this challenge including creation of a heavy amino acid peptide library for parallel reaction monitoring and quantitation of protein kinase expression, use of understudied kinases tagged with a miniTurbo-biotin ligase to determine interaction networks by proximity-dependent protein biotinylation, NanoBRET probe development for screening chemical tool target specificity in live cells, characterization of small molecule chemical tools inhibiting understudied kinases, and computational tools for defining kinome architecture. These resources are available through the Dark Kinase Knowledgebase, supporting further research into these understudied protein kinases.

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

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