Mass spectrometry as a tool for biomarkers searching in gynecological oncology

Proteomics for Biomarker Discovery in Gynecological Cancers: A Systematic Review

The present study aims to summarize the current biomarker landscape in gynecological cancers (GCs) and incorporate bioinformatics analysis to highlight specific biological processes. The literature was retrieved from PubMed, Web of Science, Embase, Scopus, Ovid Medline, and Cochrane Library. The final search was conducted on December 7, 2022. Prospective registration was completed with the PROSPERO with registration number CRD42023477145. This systematic review covered proteomic research on biomarkers for cervical, endometrial, and ovarian cancers. The PANTHER classification system was used to classify the shortlisted candidate biomarkers (CBs), and the STRING database was utilized to visualize protein-protein interaction networks. A total of 23 articles were included in this systematic review. Consistently regulated CBs in the GCs include collagen alpha-2(I) chain, collagen alpha-1(III) chain, collagen alpha-2(V) chain, calreticulin, protein disulfide-isomerase A3, heat shock protein family A (Hsp70) member 5, prolyl 4-hydroxylase, beta polypeptide, fibrinogen alpha chain, fibrinogen gamma chain, apolipoprotein B-100, apolipoprotein C-IV, and apolipoprotein M. In conclusion, collagens, fibrinogens, chaperones, and apolipoproteins were revealed to be replicated in GCs and to be regulated consistently. These CBs contribute to GC etiology and physiology by participating in collagen fibril organization, blood coagulation, protein folding in endoplasmic reticulum, and lipid transporter activity.

From Nanozymes to Multi-Purpose Nanomaterials: The Potential of Metal-Organic Frameworks for Proteomics Applications

Metal-organic frameworks (MOFs) have the potential to revolutionize the biotechnological and medical landscapes due to their easily tunable crystalline porous structure. Herein, the study presents MOFs' potential impact on proteomics, unveiling the diverse roles MOFs can play to boost it. Although MOFs are excellent catalysts in other scientific disciplines, their role as catalysts in proteomics applications remains largely underexplored, despite protein cleavage being of crucial importance in proteomics protocols. Additionally, the study discusses evolving MOF materials that are tailored for proteomics, showcasing their structural diversity and functional advantages compared to other types of materials used for similar applications. MOFs can be developed to seamlessly integrate into proteomics workflows due to their tunable features, contributing to protein separation, peptide enrichment, and ionization for mass spectrometry. This review is meant as a guide to help bridge the gap between material scientists, engineers, and MOF chemists and on the other side researchers in biology or bioinformatics working in proteomics.

Upgrading Treatment and Molecular Diagnosis in Endometrial Cancer-Driving New Tools for Endometrial Preservation?

One emerging problem for onco-gynecologists is the incidence of premenopausal patients under 40 years of age diagnosed with stage I Endometrial Cancer (EC) who want to preserve their fertility. Our review aims to define a primary risk assessment that can help fertility experts and onco-gynecologists tailor personalized treatment and fertility-preserving strategies for fertile patients wishing to have children. We confirm that risk factors such as myometrial invasion and The International Federation of Gynecology and Obstetrics (FIGO) staging should be integrated into the novel molecular classification provided by The Cancer Genome Atlas (TCGA). We also corroborate the influence of classical risk factors such as obesity, Polycystic ovarian syndrome (PCOS), and diabetes mellitus to assess fertility outcomes. The fertility preservation options are inadequately discussed with women with a diagnosis of gynecological cancer. A multidisciplinary team of gynecologists, oncologists, and fertility specialists could increase patient satisfaction and improve fertility outcomes. The incidence and death rates of endometrial cancer are rising globally. International guidelines recommend radical hysterectomy and bilateral salpingo-oophorectomy as the standard of care for this cancer; however, fertility-sparing alternatives should be tailored to motivated women of reproductive age, establishing an appropriate cost-benefit balance between childbearing desire and cancer risk. New molecular classifications such as that of TCGA provide a robust supplementary risk assessment tool that can tailor the treatment options to the patient's needs, curtail over- and under-treatment, and contribute to the spread of fertility-preserving strategies.

Analysis of carbohydrates and glycoconjugates by matrix-assisted laser desorption/ionization mass spectrometry: An update for 2017-2018

This review is the tenth update of the original article published in 1999 on the application of matrix-assisted laser desorption/ionization mass spectrometry (MALDI) mass spectrometry to the analysis of carbohydrates and glycoconjugates and brings coverage of the literature to the end of 2018. Also included are papers that describe methods appropriate to glycan and glycoprotein analysis by MALDI, such as sample preparation techniques, even though the ionization method is not MALDI. Topics covered in the first part of the review include general aspects such as theory of the MALDI process, new methods, matrices, derivatization, MALDI imaging, fragmentation and the use of arrays. The second part of the review is devoted to applications to various structural types such as oligo- and poly-saccharides, glycoproteins, glycolipids, glycosides, and biopharmaceuticals. Most of the applications are presented in tabular form. The third part of the review covers medical and industrial applications of the technique, studies of enzyme reactions, and applications to chemical synthesis. The reported work shows increasing use of combined new techniques such as ion mobility and highlights the impact that MALDI imaging is having across a range of diciplines. MALDI is still an ideal technique for carbohydrate analysis and advancements in the technique and the range of applications continue steady progress.

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

Simple Summary

Endometrial cancer is the most common cancer of the female reproductive tract, and its incidence is rising. Early diagnosis has the potential to improve survival as women can receive care at the earliest possible stage when curative treatment is likely. Current tests for endometrial cancer diagnosis are sequentially invasive with low patient acceptability. A detection tool based on minimally invasive samples such as cervico-vaginal fluid would be a major advance in the field. This study focuses on the potential of detecting endometrial cancer based on the proteins and peptides expressed in cervico-vaginal fluid. Using Sequential window acquisition of all theoretical mass spectra (SWATH-MS), we present a spectral library of thousands of proteins in the cervico-vaginal fluid of women with or at risk of endometrial cancer. This important resource will enable the identification of endometrial cancer biomarkers in cervico-vaginal fluid and advances our knowledge of the role of proteomics in endometrial cancer detection.

Abstract

Endometrial cancer is the most common gynaecological malignancy in high-income countries and its incidence is rising. Early detection, aided by highly sensitive and specific biomarkers, has the potential to improve outcomes as treatment can be provided when it is most likely to effect a cure. Sequential window acquisition of all theoretical mass spectra (SWATH-MS), an accurate and reproducible platform for analysing biological samples, offers a technological advance for biomarker discovery due to its reproducibility, sensitivity and potential for data re-interrogation. SWATH-MS requires a spectral library in order to identify and quantify peptides from multiplexed mass spectrometry data. Here we present a bespoke spectral library of 154,206 transitions identifying 19,394 peptides and 2425 proteins in the cervico-vaginal fluid of postmenopausal women with, or at risk of, endometrial cancer. We have combined these data with a library of over 6000 proteins generated based on mass spectrometric analysis of two endometrial cancer cell lines. This unique resource enables the study of protein biomarkers for endometrial cancer detection in cervico-vaginal fluid. Data are available via ProteomeXchange with unique identifier PXD025925.

Understanding Cervical Cancer through Proteomics

Cancer is one of the leading public health issues worldwide, and the number of cancer patients increases every day. Particularly, cervical cancer (CC) is still the second leading cause of cancer death in women from developing countries. Thus, it is essential to deepen our knowledge about the molecular pathogenesis of CC and propose new therapeutic targets and new methods to diagnose this disease in its early stages. Differential expression analysis using high-throughput techniques applied to biological samples allows determining the physiological state of normal cells and the changes produced by cancer development. The cluster of differential molecular profiles in the genome, the transcriptome, or the proteome is analyzed in the disease, and it is called the molecular signature of cancer. Proteomic analysis of biological samples of patients with different grades of cervical intraepithelial neoplasia (CIN) and CC has served to elucidate the pathways involved in the development and progression of cancer and identify cervical proteins associated with CC. However, several cervical carcinogenesis mechanisms are still unclear. Detecting pathologies in their earliest stages can significantly improve a patient's survival rate, prognosis, and recurrence. The present review is an update on the proteomic study of CC.

GYNOCARE Update: Modern Strategies to Improve Diagnosis and Treatment of Rare Gynecologic Tumors—Current Challenges and Future Directions

Simple Summary

More than 50% of all the tumors affecting the female genital tract can be classified as rare and usually have a poor prognosis owing to delayed diagnosis and treatment. Currently, gynecologic cancer research, due to distinct scientific and technological challenges, is lagging behind. Moreover, the overall efforts for addressing these challenges are fragmented across different countries. The European Network for Gynecological Rare Cancer Research: GYNOCARE aims to address these challenges by creating a unique network between key stakeholders covering distinct domains from basic research to cure. GYNOCARE is part of a European Collaboration in Science and Technology (COST) with the aim to focus on the development of new approaches to improve the diagnosis and treatment of rare gynecological tumors. Here, we provide a brief overview describing the goals of this COST Action and its future challenges with the aim to continue fighting against this rare cancer.

Abstract

More than 50% of all gynecologic tumors can be classified as rare (defined as an incidence of ≤6 per 100,000 women) and usually have a poor prognosis owing to delayed diagnosis and treatment. In contrast to almost all other common solid tumors, the treatment of rare gynecologic tumors (RGT) is often based on expert opinion, retrospective studies, or extrapolation from other tumor sites with similar histology, leading to difficulty in developing guidelines for clinical practice. Currently, gynecologic cancer research, due to distinct scientific and technological challenges, is lagging behind. Moreover, the overall efforts for addressing these challenges are fragmented across different European countries and indeed, worldwide. The GYNOCARE, COST Action CA18117 (European Network for Gynecological Rare Cancer Research) programme aims to address these challenges through the creation of a unique network between key stakeholders covering distinct domains from concept to cure: basic research on RGT, biobanking, bridging with industry, and setting up the legal and regulatory requirements for international innovative clinical trials. On this basis, members of this COST Action, (Working Group 1, “Basic and Translational Research on Rare Gynecological Cancer”) have decided to focus their future efforts on the development of new approaches to improve the diagnosis and treatment of RGT. Here, we provide a brief overview of the current state-of-the-art and describe the goals of this COST Action and its future challenges with the aim to stimulate discussion and promote synergy across scientists engaged in the fight against this rare cancer worldwide.

Urinary Biomarkers and Their Potential for the Non-Invasive Detection of Endometrial Cancer

Endometrial cancer is the most common malignancy of the female genital tract and its incidence is rising in parallel with the mounting prevalence of obesity. Early diagnosis has great potential to improve outcomes as treatment can be curative, especially for early stage disease. Current tests and procedures for diagnosis are limited by insufficient accuracy in some and unacceptable levels of invasiveness and discomfort in others. There has, therefore, been a growing interest in the search for sensitive and specific biomarkers for endometrial cancer detection based on non-invasive sampling methodologies. Urine, the prototype non-invasive sample, is attractive for biomarker discovery as it is easily accessible and can be collected repeatedly and in quantity. Identification of urinary biomarkers for endometrial cancer detection relies on the excretion of systemic biomarkers by the kidneys or urinary contamination by biomarkers shed from the uterus. In this review, we present the current standing of the search for endometrial cancer urinary biomarkers based on cytology, genomic, transcriptomic, proteomic, and metabolomic platforms. We summarize the biomarker candidates and highlight the challenges inherent in urinary biomarker discovery. We review the various technologies with promise for biomarker detection and assess these novel approaches for endometrial cancer biomarker research.

Metabolomic Biomarkers for Detection, Prognosis and Identifying Recurrence in Endometrial Cancer

Metabolic reprogramming is increasingly recognised as one of the defining hallmarks of tumorigenesis. There is compelling evidence to suggest that endometrial cancer develops and progresses in the context of profound metabolic dysfunction. Whilst the incidence of endometrial cancer continues to rise in parallel with the global epidemic of obesity, there are, as yet, no validated biomarkers that can aid risk prediction, early detection, prognostic evaluation or surveillance. Advances in high-throughput technologies have, in recent times, shown promise for biomarker discovery based on genomic, transcriptomic, proteomic and metabolomic platforms. Metabolomics, the large-scale study of metabolites, deals with the downstream products of the other omics technologies and thus best reflects the human phenotype. This review aims to provide a summary and critical synthesis of the existing literature with the ultimate goal of identifying the most promising metabolite biomarkers that can augment current endometrial cancer diagnostic, prognostic and recurrence surveillance strategies. Identified metabolites and their biochemical pathways are discussed in the context of what we know about endometrial carcinogenesis and their potential clinical utility is evaluated. Finally, we underscore the challenges inherent in metabolomic biomarker discovery and validation and provide fresh perspectives and directions for future endometrial cancer biomarker research.

Proteomic Biomarkers for the Detection of Endometrial Cancer

Endometrial cancer is the leading gynaecological malignancy in the western world and its incidence is rising in tandem with the global epidemic of obesity. Early diagnosis is key to improving survival, which at 5 years is less than 20% in advanced disease and over 90% in early-stage disease. As yet, there are no validated biological markers for its early detection. Advances in high-throughput technologies and machine learning techniques now offer unique and promising perspectives for biomarker discovery, especially through the integration of genomic, transcriptomic, proteomic, metabolomic and imaging data. Because the proteome closely mirrors the dynamic state of cells, tissues and organisms, proteomics has great potential to deliver clinically relevant biomarkers for cancer diagnosis. In this review, we present the current progress in endometrial cancer diagnostic biomarker discovery using proteomics. We describe the various mass spectrometry-based approaches and highlight the challenges inherent in biomarker discovery studies. We suggest novel strategies for endometrial cancer detection exploiting biologically important protein biomarkers and set the scene for future directions in endometrial cancer biomarker research.

The Relevance of Mass Spectrometry Analysis for Personalized Medicine through Its Successful Application in Cancer "Omics"

Mass spectrometry (MS) is an essential analytical technology on which the emerging omics domains; such as genomics; transcriptomics; proteomics and metabolomics; are based. This quantifiable technique allows for the identification of thousands of proteins from cell culture; bodily fluids or tissue using either global or targeted strategies; or detection of biologically active metabolites in ultra amounts. The routine performance of MS technology in the oncological field provides a better understanding of human diseases in terms of pathophysiology; prevention; diagnosis and treatment; as well as development of new biomarkers; drugs targets and therapies. In this review; we argue that the recent; successful advances in MS technologies towards cancer omics studies provides a strong rationale for its implementation in biomedicine as a whole.

MALDI-TOF-MS Analysis in the Identification of Urine Proteomic Patterns of Gestational Trophoblastic Disease

Gestational trophoblastic disease (GTD) is a group of highly aggressive, rare tumors. Human chorionic gonadotropin is a common biomarker used in the diagnosis and monitoring of GTD. To improve our knowledge of the pathology of GTD, we performed protein-peptide profiling on the urine of patients affected with gestational trophoblastic neoplasm (GTN). We analyzed urine samples from patients diagnosed with GTN (n = 26) and from healthy pregnant and non-pregnant controls (n = 17) using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS). Ions were examined in a linear mode over a m/z range of 1000–10,000. All GTN urine samples were analyzed before and after treatment and compared with those of the controls. The statistical analyses included multivariate classification algorithms as well as ROC curves. Urine sample analyses revealed there were significant differences in the composition of the ions between the evaluated groups. Comparing the pre-treatment and group with the pregnant controls, we identified two discriminatory proteins: hemoglobin subunit α (m/z = 1951.81) and complement C4A (m/z = 1895.43). Then, comparing urine samples from the post-treatment cases with those from the non-pregnant controls, we identified the peptides uromodulin fragments (m/z = 1682.34 and 1913.54) and complement C4A (m/z = 1895.43).

Proteomic Screening for Serum Biomarkers for Cervical Cancer and Their Clinical Significance

Background

The present study aimed to determine serum markers for cervical cancer (CC) and to provide valuable references for clinical diagnosis and treatment.

Material/Methods

Serum samples were collected from age-matched healthy control women, and from female CC patients before and after surgery. Serum biomarkers were selected by comparing serum peptides profiles among the 3 groups by magnetic bead-based weak cation – exchange chromatography fractionation combined with matrix-assisted laser desorption/ionization-time of flight mass spectrometry. Probable serum biomarkers for cervical cancer were then further identified by liquid chromatography-electrospray ionization-tandem mass spectrometry system and the identified proteins were verified by enzyme-linked immunosorbent assay (ELISA).

Results

Three peptide biomarkers were identified for distinguishing CC patients from normal individuals, and distinguishing preoperative CC patients from postoperative CC patients. Of these 3 identified protein peptide regions, 2 peptide regions – TKT (Peak 2, 2435.63 m/z, 499–524) and FGA (Peak 4, 2761.79 m/z, 603–629) – were identified as upregulated markers, and peptide region of APOA1 (Peak 9, 2575.3 m/z, 245–260) was identified as a downregulated biomarker in preoperative CC patients compared with healthy women.

Conclusions

The present study provides a new method for identifying potential serum biomarkers for CC patients.

Naringin inhibits ovarian tumor growth by promoting apoptosis: An in vivo study

The aim of the present study was to investigate the antitumor activities of naringin in ovarian cancer, and to assess the underlying mechanisms. Ovarian tumor cells were implanted into nude mice to produce ovarian tumors in vivo. The mice were divided into six groups: Control, low dose naringin [0.5 mg/kg, intraperitoneal (i.p.)], middle dose naringin (1 mg/kg, i.p.), high dose naringin (2 mg/kg, i.p.), positive control (cisplatin, 2 mg/kg, i.p.) and a combination of cisplatin and naringin (both 2 mg/kg). Following administration of naringin and/or cisplatin, the tumor size and weight were measured. Apoptosis of tumor cells was detected using a terminal deoxynucleotidyl transferase dUTP nick end labeling assay. Apoptosis-associated gene expression was detected using reverse transcription-polymerase chain reaction and immunohistochemistry. In the range of 0.5–2 mg/kg, naringin dose-dependently inhibited tumor growth, as demonstrated by a decrease in tumor size and weight. Naringin promoted apoptosis of the ovarian tumor cells. Additionally, naringin reduced the expression of B-cell lymphoma (Bcl)-2, Bcl-extra large (Bcl-xL), cyclin D1, c-Myc and survivin, while it increased the expression of caspase-3 and caspase-7. The data demonstrated that naringin inhibited ovarian tumor growth in vivo. Its mechanisms may be associated with caspase-7-, caspase-3-, Bcl-2- and Bcl-xL-mediated apoptosis. Nevertheless, the clinical application of naringin in the treatment of ovarian cancer requires further study.