Proteome-wide Tyrosine Phosphorylation Analysis Reveals Dysregulated Signaling Pathways in Ovarian Tumors

Advancements in protein glycosylation biomarkers for ovarian cancer through mass spectrometry-based approaches

INTRODUCTION

Ovarian cancer, characterized by metastasis and reduced 5-year survival rates, stands as a substantial factor in the mortality of gynecological malignancies worldwide. The challenge of delayed diagnosis originates from vague early symptoms and the absence of efficient screening and diagnostic biomarkers for early cancer detection. Recent studies have explored the intricate interplay between ovarian cancer and protein glycosylation, unveiling the potential significance of glycosylation-oriented biomarkers.

AREAS COVERED

This review examines the progress in glycosylation biomarker research, with particular emphasis on advances driven by mass spectrometry-based technologies. We document milestones achieved, discuss encountered limitations, and also highlight potential areas for future research and development of protein glycosylation biomarkers for ovarian cancer.

EXPERT OPINION

The association of glycosylation in ovarian cancer is well known, but current research lacks desired sensitivity and specificity for early detection. Notably, investigations into protein-specific and site-specific glycoproteomics have the potential to significantly enhance our understanding of ovarian cancer and facilitate the identification of glycosylation-based biomarkers. Furthermore, the integration of advanced mass spectrometry techniques with AI-driven analysis and glycome databases holds the promise for revolutionizing biomarker discovery for ovarian cancer, ultimately transforming diagnosis and improving patient outcomes.

Liquid Biopsy Proteomics in Ophthalmology

Minimally invasive liquid biopsies from the eye capture locally enriched fluids that contain thousands of proteins from highly specialized ocular cell types, presenting a promising alternative to solid tissue biopsies. The advantages of liquid biopsies include sampling the eye without causing irreversible functional damage, potentially better reflecting tissue heterogeneity, collecting samples in an outpatient setting, monitoring therapeutic response with sequential sampling, and even allowing examination of disease mechanisms at the cell level in living humans, an approach that we refer to as TEMPO (Tracing Expression of Multiple Protein Origins). Liquid biopsy proteomics has the potential to transform molecular diagnostics and prognostics and to assess disease mechanisms and personalized therapeutic strategies in individual patients. This review addresses opportunities, challenges, and future directions of high-resolution liquid biopsy proteomics in ophthalmology, with particular emphasis on the large-scale collection of high-quality samples, cutting edge proteomics technology, and artificial intelligence-supported data analysis.

Aneuploidy Landscape in Precursors of Ovarian Cancer

PURPOSE

Serous tubal intraepithelial carcinoma (STIC) is now recognized as the main precursor of ovarian high-grade serous carcinoma (HGSC). Other potential tubal lesions include p53 signatures and tubal intraepithelial lesions. We aimed to investigate the extent and pattern of aneuploidy in these epithelial lesions and HGSC to define the features that characterize stages of tumor initiation and progression.

EXPERIMENTAL DESIGN

We applied RealSeqS to compare genome-wide aneuploidy patterns among the precursors, HGSC (cases, n = 85), and histologically unremarkable fallopian tube epithelium (HU-FTE; control, n = 65). On the basis of a discovery set (n = 67), we developed an aneuploidy-based algorithm, REAL-FAST (Repetitive Element AneupLoidy Sequencing Fallopian Tube Aneuploidy in STIC), to correlate the molecular data with pathology diagnoses. We validated the result in an independent validation set (n = 83) to determine its performance. We correlated the molecularly defined precursor subgroups with proliferative activity and histology.

RESULTS

We found that nearly all p53 signatures lost the entire Chr17, offering a "two-hit" mechanism involving both TP53 and BRCA1 in BRCA1 germline mutation carriers. Proliferatively active STICs harbor gains of 19q12 (CCNE1), 19q13.2, 8q24 (MYC), or 8q arm, whereas proliferatively dormant STICs show 22q loss. REAL-FAST classified HU-FTE and STICs into 5 clusters and identified a STIC subgroup harboring unique aneuploidy that is associated with increased proliferation and discohesive growth. On the basis of a validation set, REAL-FAST showed 95.8% sensitivity and 97.1% specificity in detecting STIC/HGSC.

CONCLUSIONS

Morphologically similar STICs are molecularly distinct. The REAL-FAST assay identifies a potentially "aggressive" STIC subgroup harboring unique DNA aneuploidy that is associated with increased cellular proliferation and discohesive growth. REAL-FAST offers a highly reproducible adjunct technique to assist the diagnosis of STIC lesions.

Novel proteomic technologies to address gaps in pre-clinical ovarian cancer biomarker discovery efforts

INTRODUCTION

An estimated 20,000 women in the United States will receive a diagnosis of ovarian cancer in 2023. Late-stage diagnosis is associated with poor prognosis. There is a need for novel diagnostic biomarkers for ovarian cancer to improve early-stage detection and novel prognostic biomarkers to improve patient treatment.

AREAS COVERED

This review provides an overview of the clinicopathological features of ovarian cancer and the currently available biomarkers and treatment options. Two affinity-based platforms using proximity extension assays (Olink) and DNA aptamers (SomaLogic) are described in the context of highly reproducible and sensitive multiplexed assays for biomarker discovery. Recent developments in ion mobility spectrometry are presented as novel techniques to apply to the biomarker discovery pipeline. Examples are provided of how these aforementioned methods are being applied to biomarker discovery efforts in various diseases, including ovarian cancer.

EXPERT OPINION

Translating novel ovarian cancer biomarkers from candidates in the discovery phase to bona fide biomarkers with regulatory approval will have significant benefits for patients. Multiplexed affinity-based assay platforms and novel mass spectrometry methods are capable of quantifying low abundance proteins to aid biomarker discovery efforts by enabling the robust analytical interrogation of the ovarian cancer proteome.

Spatial Transcriptomic Analysis of Ovarian Cancer Precursors Reveals Reactivation of IGFBP2 during Pathogenesis

Elucidating the earliest pathogenic steps in cancer development is fundamental to improving its early detection and prevention. Ovarian high-grade serous carcinoma (HGSC), a highly aggressive cancer, mostly originates from the fallopian tube epithelium through a precursor stage, serous tubal intraepithelial carcinoma (STIC). In this study, we performed spatial transcriptomic analysis to compare STICs, carcinoma, and their matched normal fallopian tube epithelium. Several differentially expressed genes in STICs and carcinomas were involved in cancer metabolism and detected in a larger independent transcriptomic dataset of ovarian HGSCs. Among these, insulin-like growth factor binding protein-2 (IGFBP2) was found to undergo DNA hypomethylation and to be increased at the protein level in STICs. Pyrosequencing revealed an association of IGFBP2 expression with the methylation state of its proximal enhancer, and 5-azacytidine treatment increased IGFBP2 expression. In postmenopausal fallopian tubes, where most STICs are detected, IGFBP2 immunoreactivity was detected in all 38 proliferatively active STICs but was undetectable in morphologically normal tubal epithelia, including those with TP53 mutations. In premenopausal fallopian tubes, IGFBP2 expression was limited to the secretory epithelium at the proliferative phase, and estradiol treatment increased IGFBP2 expression levels. IGFBP2 knockdown suppressed the growth of IGFBP2-expressing tubal epithelial cells via inactivation of the AKT pathway. Taken together, demethylation of the proximal enhancer of IGFBP2 drives tumor development by maintaining the increased IGFBP2 required for proliferation in an otherwise estrogen-deprived, proliferation-quiescent, and postmenopausal tubal microenvironment.

SIGNIFICANCE

Molecular studies of the earliest precursor lesions of ovarian cancer reveal a role of IGFBP2 in propelling tumor initiation, providing new insights into ovarian cancer development.

Mining the Immunopeptidome for Antigenic Peptides in Cancer

Simple Summary

The immunopeptidome of cancer cells is a treasure trove of neoantigens bound to MHC molecules, thus a great source for mining immunopeptides for immunotherapy applications, including cancer vaccines. Immunopeptides may encompass post-translational modifications that are overlooked by genomic and transcriptomic tools. We review post-translational modifications that have been uncovered, and how this information could be harnessed for cancer vaccines.

Abstract

Although harnessing the immune system for cancer therapy has shown success, response to immunotherapy has been limited. The immunopeptidome of cancer cells presents an opportunity to discover novel antigens for immunotherapy applications. These neoantigens bind to MHC class I and class II molecules. Remarkably, the immunopeptidome encompasses protein post-translation modifications (PTMs) that may not be evident from genome or transcriptome profiling. A case in point is citrullination, which has been demonstrated to induce a strong immune response. In this review, we cover how the immunopeptidome, with a special focus on PTMs, can be utilized to identify cancer-specific antigens for immunotherapeutic applications.

The role of patient-derived ovarian cancer organoids in the study of PARP inhibitors sensitivity and resistance: from genomic analysis to functional testing

Epithelial ovarian cancer (EOC) harbors distinct genetic features such as homologous recombination repair (HRR) deficiency, and therefore may respond to poly ADP-ribose polymerase inhibitors (PARPi). Over the past few years, PARPi have been added to the standard of care for EOC patients in both front-line and recurrent settings. Next-generation sequencing (NGS) genomic analysis provides key information, allowing for the prediction of PARPi response in patients who are PARPi naïve. However, there are indeed some limitations in NGS analyses. A subset of patients can benefit from PARPi, despite the failed detection of the predictive biomarkers such as BRCA1/2 mutations or HRR deficiency. Moreover, in the recurrent setting, the sequencing of initial tumor does not allow for the detection of reversions or secondary mutations restoring proficient HRR and thus leading to PARPi resistance. Therefore, it becomes crucial to better screen patients who will likely benefit from PARPi treatment, especially those with prior receipt of maintenance PARPi therapy. Recently, patient-derived organoids (PDOs) have been regarded as a reliable preclinical platform with clonal heterogeneity and genetic features of original tumors. PDOs are found feasible for functional testing and interrogation of biomarkers for predicting response to PARPi in EOC. Hence, we review the strengths and limitations of various predictive biomarkers and highlight the role of patient-derived ovarian cancer organoids as functional assays in the study of PARPi response. It was found that a combination of NGS and functional assays using PDOs could enhance the efficient screening of EOC patients suitable for PARPi, thus prolonging their survival time.

Synergistic AHR Binding Pathway with EMT Effects on Serous Ovarian Tumors Recognized by Multidisciplinary Integrated Analysis

Epithelial ovarian cancers (EOCs) are fatal and obstinate among gynecological malignancies in advanced stage or relapsed status, with serous carcinomas accounting for the vast majority. Unlike EOCs, borderline ovarian tumors (BOTs), including serous BOTs, maintain a semimalignant appearance. Using gene ontology (GO)-based integrative analysis, we analyzed gene set databases of serous BOTs and serous ovarian carcinomas for dysregulated GO terms and pathways and identified multiple differentially expressed genes (DEGs) in various aspects. The SRC (SRC proto-oncogene, non-receptor tyrosine kinase) gene and dysfunctional aryl hydrocarbon receptor (AHR) binding pathway consistently influenced progression-free survival and overall survival, and immunohistochemical staining revealed elevated expression of related biomarkers (SRC, ARNT, and TBP) in serous BOT and ovarian carcinoma samples. Epithelial-mesenchymal transition (EMT) is important during tumorigenesis, and we confirmed the SNAI2 (Snail family transcriptional repressor 2, SLUG) gene showing significantly high performance by immunohistochemistry. During serous ovarian tumor formation, activated AHR in the cytoplasm could cooperate with SRC, enter cell nuclei, bind to AHR nuclear translocator (ARNT) together with TATA-Box Binding Protein (TBP), and act on DNA to initiate AHR-responsive genes to cause tumor or cancer initiation. Additionally, SNAI2 in the tumor microenvironment can facilitate EMT accompanied by tumorigenesis. Although it has not been possible to classify serous BOTs and serous ovarian carcinomas as the same EOC subtype, the key determinants of relevant DEGs (SRC, ARNT, TBP, and SNAI2) found here had a crucial role in the pathogenetic mechanism of both tumor types, implying gradual evolutionary tendencies from serous BOTs to ovarian carcinomas. In the future, targeted therapy could focus on these revealed targets together with precise detection to improve therapeutic effects and patient survival rates.

Assessing the activation/inhibition of tyrosine kinase-related pathways with a newly developed platform

The phosphorylation of cellular proteins plays a crucial role in the transduction of various signals from outside the cell into the nucleus. The signals are transduced by phosphorylation chain reactions within multiple pathways; however, determining which pathways are responsible for each defined signal has proven challenging. To estimate the activity of each pathway, we developed a phosphorylation array platform comprising a protein array with 1200 proteins belonging to 376 signalling pathways and an analytical method to estimate pathway activity based on the phosphorylation levels of proteins. The performance of our system was assessed by reconstructing kinase-substrate relationships, as well as by estimating pathway activity upon epidermal growth factor (EGF) stimulation and the pharmacological inhibition of epidermal growth factor receptor (EGFR). As a result, kinase-substrate relationships were reliably reconstructed based on the precise measurement of phosphorylation levels of constituent proteins on the array. Furthermore, the pathway activities associated with EGF stimulation and EGFR inhibition were successfully traced through the related pathways from the outer membrane to the nucleus along a time course. Thus, our phosphorylation array system can effectively assess the activity of specific signalling pathways that are perturbed by extracellular stimuli, such as various drugs.

Comprehending the Proteomic Landscape of Ovarian Cancer: A Road to the Discovery of Disease Biomarkers

Despite recent technological advancements allowing the characterization of cancers at a molecular level along with biomarkers for cancer diagnosis, the management of ovarian cancers (OC) remains challenging. Proteins assume functions encoded by the genome and the complete set of proteins, termed the proteome, reflects the health state. Comprehending the circulatory proteomic profiles for OC subtypes, therefore, has the potential to reveal biomarkers with clinical utility concerning early diagnosis or to predict response to specific therapies. Furthermore, characterization of the proteomic landscape of tumor-derived tissue, cell lines, and PDX models has led to the molecular stratification of patient groups, with implications for personalized therapy and management of drug resistance. Here, we review single and multiple marker panels that have been identified through proteomic investigations of patient sera, effusions, and other biospecimens. We discuss their clinical utility and implementation into clinical practice.

Proteomic Studies on the Management of High-Grade Serous Ovarian Cancer Patients: A Mini-Review

High-grade serous ovarian cancer (HGSC) remains the most common and deadly subtype of ovarian cancer. It is characterized by its late diagnosis and frequent relapse despite standardized treatment with cytoreductive surgery and platinum-based chemotherapy. The past decade has seen significant advances in the clinical management and molecular understanding of HGSC following the publication of the Cancer Genome Atlas (TCGA) researchers and the introduction of targeted therapies with anti-angiogenic drugs and poly(ADP-ribose) polymerase inhibitors in specific subgroups of patients. We provide a comprehensive review of HGSC, focusing on the most important molecular advances aimed at providing a better understanding of the disease and its response to treatment. We emphasize the role that proteomic technologies are now playing in these two aspects of the disease, through the identification of proteins and their post-translational modifications in ovarian cancer tumors. Finally, we highlight how the integration of proteomics with genomics, exemplified by the work performed by the Clinical Proteomic Tumor Analysis Consortium (CPTAC), can guide the development of new biomarkers and therapeutic targets.

Convergence of Plasma Metabolomics and Proteomics Analysis to Discover Signatures of High-Grade Serous Ovarian Cancer

Simple Summary

In-time diagnosing ovarian cancer, intractable cancer that has no symptoms can increase the survival of women. The aim of this study was to discover biomarkers from liquid biopsy samples using multi-omics approach, metabolomics and proteomics for the diagnosis of ovarian cancer. To verify our biomarker candidates, we conducted comparative analysis with other previous published studies. Despite the limitations of non-invasive samples, our findings are able to discover emerging properties through the interplay between metabolites and proteins and mechanism-based biomarkers through integrated protein and metabolite analysis.

Abstract

The 5-year survival rate in the early and late stages of ovarian cancer differs by 63%. In addition, a liquid biopsy is necessary because there are no symptoms in the early stage and tissue collection is difficult without using invasive methods. Therefore, there is a need for biomarkers to achieve this goal. In this study, we found blood-based metabolite or protein biomarker candidates for the diagnosis of ovarian cancer in the 20 clinical samples (10 ovarian cancer patients and 10 healthy control subjects). Plasma metabolites and proteins were measured and quantified using mass spectrometry in ovarian cancer patients and control groups. We identified the differential abundant biomolecules (34 metabolites and 197 proteins) and statistically integrated molecules of different dimensions to better understand ovarian cancer signal transduction and to identify novel biological mechanisms. In addition, the biomarker reliability was verified through comparison with existing research results. Integrated analysis of metabolome and proteome identified emerging properties difficult to grasp with the single omics approach, more reliably interpreted the cancer signaling pathway, and explored new drug targets. Especially, through this analysis, proteins (PPCS, PMP2, and TUBB) and metabolites (L-carnitine and PC-O (30:0)) related to the carnitine system involved in cancer plasticity were identified.

Developments and Applications of Functional Protein Microarrays

Protein microarrays are crucial tools in the study of proteins in an unbiased, high-throughput manner, as they allow for characterization of up to thousands of individually purified proteins in parallel. The adaptability of this technology has enabled its use in a wide variety of applications, including the study of proteome-wide molecular interactions, analysis of post-translational modifications, identification of novel drug targets, and examination of pathogen-host interactions. In addition, the technology has also been shown to be useful in profiling antibody specificity, as well as in the discovery of novel biomarkers, especially for autoimmune diseases and cancers. In this review, we will summarize the developments that have been made in protein microarray technology in both in basic and translational research over the past decade. We will also introduce a novel membrane protein array, the GPCR-VirD array, and discuss the future directions of functional protein microarrays.

Progress on Identifying and Characterizing the Human Proteome: 2019 Metrics from the HUPO Human Proteome Project

The Human Proteome Project (HPP) annually reports on progress made throughout the field in credibly identifying and characterizing the complete human protein parts list and making proteomics an integral part of multiomics studies in medicine and the life sciences. NeXtProt release 2019-01-11 contains 17 694 proteins with strong protein-level evidence (PE1), compliant with HPP Guidelines for Interpretation of MS Data v2.1; these represent 89% of all 19 823 neXtProt predicted coding genes (all PE1,2,3,4 proteins), up from 17 470 one year earlier. Conversely, the number of neXtProt PE2,3,4 proteins, termed the "missing proteins" (MPs), has been reduced from 2949 to 2129 since 2016 through efforts throughout the community, including the chromosome-centric HPP. PeptideAtlas is the source of uniformly reanalyzed raw mass spectrometry data for neXtProt; PeptideAtlas added 495 canonical proteins between 2018 and 2019, especially from studies designed to detect hard-to-identify proteins. Meanwhile, the Human Protein Atlas has released version 18.1 with immunohistochemical evidence of expression of 17 000 proteins and survival plots as part of the Pathology Atlas. Many investigators apply multiplexed SRM-targeted proteomics for quantitation of organ-specific popular proteins in studies of various human diseases. The 19 teams of the Biology and Disease-driven B/D-HPP published a total of 160 publications in 2018, bringing proteomics to a broad array of biomedical research.

Global targeting of functional tyrosines using sulfur-triazole exchange chemistry

Covalent probes serve as valuable tools for global investigation of protein function and ligand binding capacity. Despite efforts to expand coverage of residues available for chemical proteomics (e.g. cysteine and lysine), a large fraction of the proteome remains inaccessible with current activity-based probes. Here, we introduce sulfur-triazole exchange (SuTEx) chemistry as a tunable platform for developing covalent probes with broad applications for chemical proteomics. We show modifications to the triazole leaving group can furnish sulfonyl probes with ~5-fold enhanced chemoselectivity for tyrosines over other nucleophilic amino acids to investigate, for the first time, more than 10,000 tyrosine sites in lysates and live cells. We discover that tyrosines with enhanced nucleophilicity are enriched in enzymatic, protein-protein interaction, and nucleotide recognition domains. We apply SuTEx as a chemical phosphoproteomics strategy to monitor activation of phosphotyrosine sites. Collectively, we describe SuTEx as a biocompatible chemistry for chemical biology investigations of the human proteome.

Matrine inhibits the development and progression of ovarian cancer by repressing cancer associated phosphorylation signaling pathways

Ovarian cancer remains the most lethal gynecologic malignancy with late detection and acquired chemoresistance. Advanced understanding of the pathophysiology and novel treatment strategies are urgently required. A growing body of proteomic investigations suggest that phosphorylation has a pivotal role in the regulation of ovarian cancer associated signaling pathways. Matrine has been extensively studied for its potent anti-tumor activities. However, its effect on ovarian cancer cells and underlying molecular mechanisms remain unclear. Herein we showed that matrine treatment inhibited the development and progression of ovarian cancer cells by regulating proliferation, apoptosis, autophagy, invasion and angiogenesis. Matrine treatment retarded the cancer associated signaling transduction by decreasing the phosphorylation levels of ERK1/2, MEK1/2, PI3K, Akt, mTOR, FAK, RhoA, VEGFR2, and Tie2 in vitro and in vivo. Moreover, matrine showed excellent antitumor effect on chemoresistant ovarian cancer cells. No obvious toxic side effects were observed in matrine-administrated mice. As the natural agent, matrine has the potential to be the targeting drug against ovarian cancer cells with the advantages of overcoming the chemotherapy resistance and decreasing the toxic side effects.

Proteome microarray technology and application: higher, wider, and deeper

Introduction: Protein microarray is a powerful tool for both biological study and clinical research. The most useful features of protein microarrays are their miniaturized size (low reagent and sample consumption), high sensitivity and their capability for parallel/high-throughput analysis. The major focus of this review is functional proteome microarray. Areas covered: For proteome microarray, this review will discuss some recently constructed proteome microarrays and new concepts that have been used for constructing proteome microarrays and data interpretation in past few years, such as PAGES, M-NAPPA strategy, VirD technology, and the first protein microarray database. this review will summarize recent proteomic scale applications and address the limitations and future directions of proteome microarray technology. Expert opinion: Proteome microarray is a powerful tool for basic biological and clinical research. It is expected to see improvements in the currently used proteome microarrays and the construction of more proteome microarrays for other species by using traditional strategies or novel concepts. It is anticipated that the maximum number of features on a single microarray and the number of possible applications will be increased, and the information that can be obtained from proteome microarray experiments will more in-depth in the future.

Quantitative analysis of the human ovarian carcinoma mitochondrial phosphoproteome

To investigate the existence and their potential biological roles of mitochondrial phosphoproteins (mtPPs) in human ovarian carcinoma (OC), mitochondria purified from OC and control tissues were analyzed with TiO₂ enrichment-based iTRAQ quantitative proteomics. Totally 67 mtPPs with 124 phosphorylation sites were identified, which of them included 48 differential mtPPs (mtDPPs). Eighteen mtPPs were reported previously in OCs, and they were consistent in this study compared to previous literature. GO analysis revealed those mtPPs were involved in multiple cellular processes. PPI network indicated that those mtPPs were correlated mutually, and some mtPPs acted as hub molecules, such as EIF2S2, RPLP0, RPLP2, CFL1, MYH10, HSP90, HSPD1, PSMA3, TMX1, VDAC2, VDAC3, TOMM22, and TOMM20. Totally 32 mtPP-pathway systems (p<0.05) were enriched and clustered into 15 groups, including mitophagy, apoptosis, deubiquitination, signaling by VEGF, RHO-GTPase effectors, mitochondrial protein import, translation initiation, RNA transport, cellular responses to stress, and c-MYC transcriptional activation. Totally 29 mtPPs contained a certain protein domains. Upstream regulation analysis showed that TP53, TGFB1, dexamethasone, and thapsigargin might act as inhibitors, and L-dopa and forskolin might act as activators. This study provided novel insights into mitochondrial protein phosphorylations and their potential roles in OC pathogenesis and offered new biomarker resource for OCs.