Quantitative Mass Spectrometry-Based Proteomics for Biomarker Development in Ovarian Cancer

Next-generation sequencing-based analysis of homologous recombination repair gene variant in ovarian cancer

Background

Ovarian cancer is the leading cause of death from gynecological malignancies. Investigating the HRR-related gene status, notably BRCA1/2 in different regions and populations is of great significance for formulating accurate target therapy.

Methods

We collected 124 ovarian cancer cases from the Affiliated Hospital of.Qingdao University, detected the genomic alteration of 32 genes by NGS, including.19 HRR-related genes, 9 proto-oncogenes and 4 tumor suppressor genes. Clinicopathological characteristics, variants, clinical significance, and correlation with prognosis were analyzed.

Results

The incidence of HRR-related gene mutation was 59.68 % and no statistical significance was found with multiple clinicopathological characteristics. BRCA1/2 (27.42 %) were the most frequent mutated HRR genes. 23 (18.55 %) cases harbored gBRCA1/2 mutation, with all BRCA1 mutations were pathogenic/likely pathogenic and 2 cases of BRCA2 mutation was variant of uncertain significance. Somatic BRCA1/2 mutations were found in 12 (9.68 %) cases, and sBRCA1/2 had a higher frequency in less common ovarian cancer than high-grade serous carcinoma. HRR-related gene mutation status was associated with better prognosis than HRR wild-type.

Conclusions

Somatic BRCA1/2 mutation has higher incidence in less common ovarian cancer. HRR gene mutation status is an independent prognosis factor in ovarian cancer. Clarifying the HRR gene status is important for the selection of target therapy as well as the evaluation of prognosis.

Quantification of putative ovarian cancer serum protein biomarkers using a multiplexed targeted mass spectrometry assay

BACKGROUND

Ovarian cancer is the most lethal gynecologic malignancy in women, and high-grade serous ovarian cancer (HGSOC) is the most common subtype. Currently, no clinical test has been approved by the FDA to screen the general population for ovarian cancer. This underscores the critical need for the development of a robust methodology combined with novel technology to detect diagnostic biomarkers for HGSOC in the sera of women. Targeted mass spectrometry (MS) can be used to identify and quantify specific peptides/proteins in complex biological samples with high accuracy, sensitivity, and reproducibility. In this study, we sought to develop and conduct analytical validation of a multiplexed Tier 2 targeted MS parallel reaction monitoring (PRM) assay for the relative quantification of 23 putative ovarian cancer protein biomarkers in sera.

METHODS

To develop a PRM method for our target peptides in sera, we followed nationally recognized consensus guidelines for validating fit-for-purpose Tier 2 targeted MS assays. The endogenous target peptide concentrations were calculated using the calibration curves in serum for each target peptide. Receiver operating characteristic (ROC) curves were analyzed to evaluate the diagnostic performance of the biomarker candidates.

RESULTS

We describe an effort to develop and analytically validate a multiplexed Tier 2 targeted PRM MS assay to quantify candidate ovarian cancer protein biomarkers in sera. Among the 64 peptides corresponding to 23 proteins in our PRM assay, 24 peptides corresponding to 16 proteins passed the assay validation acceptability criteria. A total of 6 of these peptides from insulin-like growth factor-binding protein 2 (IBP2), sex hormone-binding globulin (SHBG), and TIMP metalloproteinase inhibitor 1 (TIMP1) were quantified in sera from a cohort of 69 patients with early-stage HGSOC, late-stage HGSOC, benign ovarian conditions, and healthy (non-cancer) controls. Confirming the results from previously published studies using orthogonal analytical approaches, IBP2 was identified as a diagnostic biomarker candidate based on its significantly increased abundance in the late-stage HGSOC patient sera compared to the healthy controls and patients with benign ovarian conditions.

CONCLUSIONS

A multiplexed targeted PRM MS assay was applied to detect candidate diagnostic biomarkers in HGSOC sera. To evaluate the clinical utility of the IBP2 PRM assay for HGSOC detection, further studies need to be performed using a larger patient cohort.

Research progress of extracellular vesicles in the treatment of ovarian diseases (Review)

The ovary is an essential reproductive organ in the female organism and its development seriously affects the physical and mental health of female patients. Ovarian diseases include ovarian cancer, premature ovarian insufficiency (POI) and polycystic ovary syndrome (PCOS). Women should pay attention to the most effective treatments for this condition because it is one of the most prevalent gynecological illnesses at present. Extracellular vesicles (EVs), which are smaller vesicles that mediate the exchange of cellular information, include the three categories of exosomes, microvesicles and apoptotic bodies. They are able to transport proteins, RNA and other substances to adjacent or distal cells, thus allowing cellular and tissue homeostasis to be maintained. Numerous previous studies have revealed that EVs are crucial for the treatment of ovarian diseases. They are known to transport its contents to ovarian cancer cells as well as other ovarian cells such as granulosa cells, affecting the development of ovarian disease processes. Therefore, this extracellular vesicle may be involved as a target in the therapeutic process of ovarian disease and may have great potential in the treatment of ovarian disease. In the present review, the role of EVs in the development of three ovarian diseases, including ovarian cancer, POI and PCOS, was mainly summarizes. It is expected that this will provide some theoretical support for the treatment of ovarian disease.

MRE11:p.K464R mutation mediates olaparib resistance by enhancing DNA damage repair in HGSOC

BACKGROUND

Although the clinical application of PARP inhibitors has brought hope to ovarian cancer, the problem of its resistance has become increasingly prominent. Therefore, clinical experts have been focused on finding specific indicators and therapeutic targets that can be used for resistance monitoring of PARP inhibitors.

RESULTS

By cfDNA detecting during Olaparib maintenance therapy in platinum-sensitive relapsed ovarian cancer, we found the presence of MRE11:p.K464R mutation was strongly associated with acquired Olaparib resistance. Structural analysis revealed that the MRE11:p.K464R mutation is situated at a critical site where the MRE11 protein interacts with other biomolecules, leading to potential structural and functional abnormalities of MRE11 protein. Functionally, MRE11:p.K464R mutation enhanced the tolerance of Olaparib by reducing the DNA damage. Mechanistically, MRE11:p.K464R mutation improved the efficiency of DNA damage repair and induce Olaparib resistance by enhancing its binding activity with the interacting proteins (including RAD50 and RPS3). Among them, the enhanced binding of MRE11:p.K464R mutation to RAD50/RPS3 facilitated non-homologous end joining (NHEJ) repair in tumor cells, thereby expanding the scope of research into acquired resistance to PARP inhibitors.

CONCLUSIONS

Our findings provide a theoretical basis for MRE11:p.K464R mutation as a specific indicator of resistance monitoring in Olaparib treatment, and the exploration of its resistance mechanism provides a novel insights for the formulation of combination ther therapies after Olaparib resistance.

Recent advances in mass spectrometry-based proteomics and metabolomics in chronic rhinosinusitis with nasal polyps

Chronic rhinosinusitis with nasal polyps (CRSwNP) is a complex and heterogeneous disease, typically diagnosed through endoscopy and computed tomography and treated with glucocorticoid or surgery. There is an urgent need to develop molecular-level diagnostic or prognostic tools to better understand the pathophysiology of CRSwNP. Proteomics and metabolomics, emerging fields, offer significant potential in elucidating the mechanisms underlying CRSwNP. Mass spectrometry, a powerful and sensitive tool for trace substance detection, is broadly applied for proteomics and metabolomics analysis in CRSwNP research. While previous literature has summarized the advancement of mass spectrometry-based CRSwNP proteomics from 2004 to 2018, recent years have seen new advances in this field, particularly about non-invasive samples and exosomes. Furthermore, mass spectrometry-based CRSwNP metabolomics research has opened new avenues for inquiry. Therefore, we present a comprehensive review of mass spectrometry-based proteomics and metabolomics studies on CRSwNP conducted between 2019 and 2022. Specifically, we highlight protein and metabolic biomarkers that have been utilized as diagnostic or prognostic markers for CRSwNP. Lastly, we conclude with potential directions for future mass spectrometry-based omics studies of CRSwNP.

Mass Spectrometry-based Proteomics of Epithelial Ovarian Cancers: a Clinical Perspective

Increasing proteomic studies focused on epithelial ovarian cancer (EOC) have attempted to identify early disease biomarkers, establish molecular stratification, and discover novel druggable targets. Here we review these recent studies from a clinical perspective. Multiple blood proteins have been used clinically as diagnostic markers. The ROMA test integrates CA125 and HE4, while the OVA1 and OVA2 tests analyze multiple proteins identified by proteomics. Targeted proteomics has been widely used to identify and validate potential diagnostic biomarkers in EOCs, but none has yet been approved for clinical adoption. Discovery proteomic characterization of bulk EOC tissue specimens has uncovered a large number of dysregulated proteins, proposed new stratification schemes, and revealed novel targets of therapeutic potential. A major hurdle facing clinical translation of these stratification schemes based on bulk proteomic profiling is intra-tumor heterogeneity, namely that single tumor specimens may harbor molecular features of multiple subtypes. We reviewed over 2500 interventional clinical trials of ovarian cancers since 1990, and cataloged 22 types of interventions adopted in these trials. Among 1418 clinical trials which have been completed or are not recruiting new patients, about 50% investigated chemotherapies. Thirty-seven clinical trials are at phase 3 or 4, of which 12 focus on PARP, 10 on VEGFR, 9 on conventional anti-cancer agents, and the remaining on sex hormones, MEK1/2, PD-L1, ERBB, and FRα. Although none of the foregoing therapeutic targets were discovered by proteomics, newer targets discovered by proteomics, including HSP90 and cancer/testis antigens, are being tested also in clinical trials. To accelerate the translation of proteomic findings to clinical practice, future studies need to be designed and executed to the stringent standards of practice-changing clinical trials. We anticipate that the rapidly evolving technology of spatial and single-cell proteomics will deconvolute the intra-tumor heterogeneity of EOCs, further facilitating their precise stratification and superior treatment outcomes.

Ovarian Cancer: A Landscape of Mitochondria with Emphasis on Mitochondrial Dynamics

Ovarian cancer (OC) represents the main cause of death from gynecological malignancies in western countries. Altered cellular and mitochondrial metabolism are considered hallmarks in cancer disease. Several mitochondrial aspects have been found altered in OC, such as the oxidative phosphorylation system, oxidative stress and mitochondrial dynamics. Mitochondrial dynamics includes cristae remodeling, fusion, and fission processes forming a dynamic mitochondrial network. Alteration of mitochondrial dynamics is associated with metabolic change in tumour development and, in particular, the mitochondrial shaping proteins appear also to be responsible for the chemosensitivity and/or chemoresistance in OC. In this review a focus on the mitochondrial dynamics in OC cells is presented.

Novel Diagnostic Biomarkers for High-Grade Serous Ovarian Cancer Uncovered by Data-Independent Acquisition Mass Spectrometry

High-grade serous ovarian cancer (HGSOC) represents the major histological type of ovarian cancer, and the lack of effective screening tools and early detection methods significantly contributes to the poor prognosis of HGSOC. Currently, there are no reliable diagnostic biomarkers for HGSOC. In this study, we performed liquid chromatography data-independent acquisition tandem mass spectrometry (MS) on depleted serum samples from 26 HGSOC cases and 24 healthy controls (HCs) to discover potential HGSOC diagnostic biomarkers. A total of 1,847 proteins were identified across all samples, among which 116 proteins showed differential expressions between HGSOC patients and HCs. Network modeling showed activations of coagulation and complement cascades, platelet activation and aggregation, neutrophil extracellular trap formation, toll-like receptor 4, insulin-like growth factor, and transforming growth factor β signaling, as well as suppression of lipoprotein assembly and Fc gamma receptor activation in HGSOC. Based on the network model, we prioritized 28 biomarker candidates and validated 18 of them using targeted MS assays in an independent cohort. Predictive modeling showed a sensitivity of 1 and a specificity of 0.91 in the validation cohort. Finally, in vitro functional assays on four potential biomarkers (FGA, VWF, ARHGDIB, and SERPINF2) suggested that they may play an important role in cancer cell proliferation and migration in HGSOC. All raw data were deposited in PRIDE (PXD033169).

Proteomic analysis reveals stage-specific reprogramed metabolism for the primary breast cancer cell lines MGSO-3 and MACL-1

Breast cancer is the most prevalent cancer in women worldwide. Its molecular subtypes are based on the presence/absence of estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor 2 (HER2). MACL-1 and MGSO-3 are cell lines derived from primary tumor sites of patients diagnosed with luminal A subtype carcinoma (ER+ / PR+ / HER2-) and ductal carcinoma in situ (ER- / PR- / HER2+), respectively. However, these cell lines lost the expression of these markers over cell culturing, and both have triple-negative phenotypes (ER- / PR- / HER2-), which has the poorest prognosis. Here, we sought to study the proteome signature of MGSO-3 and MACL-1, comparing them with the epithelial cell line MCF-10A and the well-established metastatic-derived breast cancer cell line MDA-MB-231. Our results showed that proteins associated with the tricarboxylic acid cycle (TCA) and oxidative phosphorylation (OXPHOS) were upregulated in MGSO-3 and MACL-1 cells. These cell lines also showed upregulation of pro-apoptotic proteins when compared with MDA-MB-231. The molecular differences highlighted in this study may clarify the molecular basis behind cancer cells functioning and may reveal novel signatures across the breast cancer cell models. This article is protected by copyright. All rights reserved.

Applications of Proteomics in Ovarian Cancer: Dawn of a New Era

The ability to identify ovarian cancer (OC) at its earliest stages remains a challenge. The patients present an advanced stage at diagnosis. This heterogeneous disease has distinguishable etiology and molecular biology. Next-generation sequencing changed clinical diagnostic testing, allowing assessment of multiple genes, simultaneously, in a faster and cheaper manner than sequential single gene analysis. Technologies of proteomics, such as mass spectrometry (MS) and protein array analysis, have advanced the dissection of the underlying molecular signaling events and the proteomic characterization of OC. Proteomics analysis of OC, as well as their adaptive responses to therapy, can uncover new therapeutic choices, which can reduce the emergence of drug resistance and potentially improve patient outcomes. There is an urgent need to better understand how the genomic and epigenomic heterogeneity intrinsic to OC is reflected at the protein level, and how this information could potentially lead to prolonged survival.

Proteomic Analysis Reveals Low-Dose PARP Inhibitor-Induced Differential Protein Expression in BRCA1-Mutated High-Grade Serous Ovarian Cancer Cells

High-grade serous ovarian cancer (HGSOC) is the most common form of ovarian cancer diagnosed in patients worldwide. Patients with BRCA1/2-mutated HGSOC have benefited from targeted treatments such as poly(ADP-ribose) polymerase inhibitors (PARPi). Despite the initial success of PARPi-based ovarian cancer treatment regimens, approximately 70% of patients with ovarian cancer relapse and the 5-year survival rate remains at 30%. PARPi exhibit variable treatment efficacy and toxicity profiles. Furthermore, the off-target effects of PARP inhibition have not yet been fully elucidated, warranting further study of these classes of molecules in the context of HGSOC treatment. Highly reproducible quantitative mass spectrometry-based proteomic workflows have been developed for the analysis of tumor tissues and cell lines. To detect the off-target effects of PARP inhibition, we conducted a quantitative mass spectrometry-based proteomic analysis of a BRCA1-mutated HGSOC cell line treated with low doses of two PARPi, niraparib and rucaparib. Our goal was to identify PARPi-induced protein signaling pathway alterations toward a more comprehensive elucidation of the mechanism of action of PARPi beyond the DNA damage response pathway. A significant enrichment of nuclear and nucleoplasm proteins that are involved in protein binding was observed in the rucaparib-treated cells. Shared upregulated proteins between niraparib and rucaparib treatment demonstrated RNA II pol promoter-associated pathway enrichment in transcription regulation. Pathway enrichment analyses also revealed off-target effects in the Golgi apparatus and the ER. The results from our mass spectrometry-based proteomic analysis highlights notable off-target effects produced by low-dose treatment of BRCA1-mutated HGSOC cells treated with rucaparib or niraparib.

The Molecular Landscape Influencing Prognoses of Epithelial Ovarian Cancer

Epithelial ovarian cancer (EOC) is one of the major increasing lethal malignancies of the gynecological tract, mostly due to delayed diagnosis and chemoresistance, as well as its very heterogeneous genetic makeup. Application of high-throughput molecular technologies, gene expression microarrays, and powerful preclinical models has provided a deeper understanding of the molecular characteristics of EOC. Therefore, molecular markers have become a potent tool in EOC management, including prediction of aggressiveness, prognosis, and recurrence, and identification of novel therapeutic targets. In addition, biomarkers derived from genomic/epigenomic alterations (e.g., gene mutations, copy number aberrations, and DNA methylation) enable targeted treatment of affected signaling pathways in advanced EOC, thereby improving the effectiveness of traditional treatments. This review outlines the molecular landscape and discusses the impacts of biomarkers on the detection, diagnosis, surveillance, and therapeutic targets of EOC. These findings focus on the necessity to translate these potential biomarkers into clinical practice.