Protein expression patterns associated with advanced stage ovarian cancer

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.

Evaluation of the Potential Diagnostic Utility of the Determination of Selected Immunological and Molecular Parameters in Patients with Ovarian Cancer

Ovarian cancer is one of the most serious challenges in modern gynaecological oncology. Due to its non-specific symptoms and the lack of an effective screening procedure to detect the disease at an early stage, ovarian cancer is still marked by a high mortality rate among women. For this reason, a great deal of research is being carried out to find new markers that can be used in the detection of ovarian cancer to improve early diagnosis and survival rates of women with ovarian cancer. Our study focuses on presenting the currently used diagnostic markers and the latest selected immunological and molecular parameters being currently investigated for their potential use in the development of new diagnostic and therapeutic strategies.

Proteome profiling of low grade serous ovarian cancer

Background

Serous carcinoma, the subtype of ovarian cancer has the highest occurrence and mortality in women. Proteomic profiling using mass spectrometry (MS) has been used to detect biomarkers in tissue s obtained from patients with ovarian cancer.

Thus, this study aimed at analyzing the interactome (protein-protein interaction (PPI)) and (MS) data to inspect PPI networks in patients with Low grade serous ovarian cancer.

Methods

For proteome profiling in Low grade serous ovarian cancer, 2DE and mass spectrometry were used. Differentially expressed proteins which had been determined in Low grade serous ovarian cancer and experimental group separately were integrated with PPI data to construct the (QQPPI) networks.

Results

Six Hub-bottlenecks proteins with significant centrality values, based on centrality parameters of the network (Degree and between), were found including Transgelin (TAGLN), Keratin (KRT14), Single peptide match to actin, cytoplasmic 1(ACTB), apolipoprotein A-I (APOA1), Peroxiredoxin-2 (PRDX2), and Haptoglobin (HP).

Discussion

This study showed these six proteins were introduced as hub-bottleneck protein. It can be concluded that regulation of gene expression can have a critical role in the pathology of Low-grade serous ovarian cancer.

Interstitial Fluid in Gynecologic Tumors and Its Possible Application in the Clinical Practice

Gynecologic cancers are an important cause of worldwide mortality. The interstitium consists of solid and fluid phases, situated between the blood vessels and cells. The interstitial fluid (IF), or fluid phase, is an extracellular fluid bathing and surrounding the tissue cells. The TIF (tumor interstitial fluid) is a dynamic fluid rich in lipids, proteins and enzyme-derived substances. The molecules found in the IF may be associated with pathological changes in tissues leading to cancer growth and metastatization. Proteomic techniques have allowed an extensive study of the composition of the TIF as a source of biomarkers for gynecologic cancers. In our review, we analyze the composition of the TIF, its formation process, the sampling methods, the consequences of its accumulation and the proteomic analyses performed, that make TIF valuable for monitoring different types of cancers.

Gaining insights into cancer biology through exploration of the cancer secretome using proteomic and bioinformatic tools

INTRODUCTION

Tumor-associated proteins released by cancer cells and by tumor stroma cells, referred as 'cancer secretome', represent a valuable resource for discovery of potential cancer biomarkers. The last decade was marked by a great increase in number of studies focused on various aspects of cancer secretome including, composition and identification of components externalized by malignant cells and by the components of tumor microenvironment. Areas covered: Here, we provide an overview of achievements in the proteomic analysis of the cancer secretome, elicited through the tumor-associated interstitial fluid recovered from malignant tissues ex vivo or the protein component of conditioned media obtained from cultured cancer cells in vitro. We summarize various bioinformatic tools and approaches and critically appraise their outcomes, focusing on problems and challenges that arise when applied for the analysis of cancer secretomic databases. Expert commentary: Recent achievements in the omics- analysis of structural and metabolic aspects of altered cancer secretome contribute greatly to the various hallmarks of cancer including the identification of clinically significant biomarkers and potential targets for therapeutic intervention.

Comparative secretome of ovarian serous carcinoma: Gelsolin in the spotlight

Ovarian cancer is one of the most common types of reproductive cancer, and has the highest mortality rate amongst gynecological cancer subtypes. The majority of ovarian cancers are diagnosed at an advanced stage, resulting in a five-year survival rate of ~30%. Early diagnosis of ovarian cancer has improved the five-year survival rate to ≥90%, thus the current imperative requirement is to identify biomarkers that would allow the early detection, diagnosis and monitoring of the progression of the disease, or of novel targets for therapy. In the present study, secreted proteins from purified ovarian control, benign and cancer cells were investigated by mass spectrometry, in order to identify novel specific markers that are easy to quantify in patients sera. A total of nine proteins revealed significant differential secretion from control and benign cells, in comparison with ovarian cancer cells. The mRNA expression levels of three of these proteins (Dickkopf protein 3, heat shock protein 10 kDa and gelsolin) were subsequently evaluated by reverse transcription-quantitative polymerase chain reaction. Combined with the protein level in serum, the present study identified that gelsolin may be a useful marker of ovarian cancer.

Tumor Interstitial Fluid Formation, Characterization, and Clinical Implications

The interstitium, situated between the blood and lymph vessels and the cells, consists of a solid or matrix phase and a fluid phase representing the tissue microenvironment. In the present review, we focus on the interstitial fluid phase of solid tumors, the tumor interstitial fluid (TIF), i.e., the fluid bathing the tumor and stroma cells, also including immune cells. This is a component of the internal milieu of a solid tumor that has attracted regained attention. Access to this space may provide important insight into tumor development and therapy response. TIF is formed by transcapillary filtration, and since this fluid is not readily available we discuss available techniques for TIF isolation, results from subsequent characterization and implications of recent findings with respect to fluid filtration and uptake of macromolecular therapeutic agents. There appear to be local gradients in signaling substances from neoplastic tissue to plasma that may provide new understanding of tumor biology. The development of sensitive proteomic technologies has made TIF a valuable source for tumor specific proteins and biomarker candidates. Potential biomarkers will appear locally in high concentrations in tumors and may eventually be found diluted in the plasma. Access to TIF that reliably reflects the local tumor microenvironment enables identification of substances that can be used in early detection and monitoring of disease.

Proteomics in cancer biomarkers discovery: challenges and applications

With the introduction of recent high-throughput technologies to various fields of science and medicine, it is becoming clear that obtaining large amounts of data is no longer a problem in modern research laboratories. However, coherent study designs, optimal conditions for obtaining high-quality data, and compelling interpretation, in accordance with the evidence-based systems biology, are critical factors in ensuring the emergence of good science out of these recent technologies. This review focuses on the proteomics field and its new perspectives on cancer research. Cornerstone publications that have tremendously helped scientists and clinicians to better understand cancer pathogenesis; to discover novel diagnostic and/or prognostic biomarkers; and to suggest novel therapeutic targets will be presented. The author of this review aims at presenting some of the relevant literature data that helped as a step forward in bridging the gap between bench work results and bedside potentials. Undeniably, this review cannot include all the work that is being produced by expert research groups all over the world.

Galectin expression in cancer diagnosis and prognosis: A systematic review

Galectins are a family of proteins that bind to specific glycans thereby deciphering the information captured within the glycome. In the last two decades, several galectin family members have emerged as versatile modulators of tumor progression. This has initiated the development and preclinical assessment of galectin-targeting compounds. With the first compounds now entering clinical trials it is pivotal to gain insight in the diagnostic and prognostic value of galectins in cancer as this will allow a more rational selection of the patients that might benefit most from galectin-targeted therapies. Here, we present a systematic review of galectin expression in human cancer patients. Malignant transformation is frequently associated with altered galectin expression, most notably of galectin-1 and galectin-3. In most cancers, increased galectin-1 expression is associated with poor prognosis while elevated galectin-9 expression is emerging as a marker of favorable disease outcome. The prognostic value of galectin-3 appears to be tumor type dependent and the other galectins require further investigation. Regarding the latter, additional studies using larger patient cohorts are essential to fully unravel the diagnostic and prognostic value of galectin expression. Furthermore, to better compare different findings, consensus should be reached on how to assess galectin expression, not only with regard to localization within the tissue and within cellular compartments but also regarding alternative splicing and genomic variations. Finally, linking galectin expression and function to aberrant glycosylation in cancer cells will improve our understanding of how these versatile proteins can be exploited for diagnostic, prognostic and even therapeutic purposes in cancer patients.

Distribution volumes of macromolecules in human ovarian and endometrial cancers--effects of extracellular matrix structure

Elements of the extracellular matrix (ECM), notably collagen and glucosaminoglycans, will restrict part of the space available for soluble macromolecules simply because the molecules cannot occupy the same space. This phenomenon may influence macromolecular drug uptake. To study the influence of steric and charge effects of the ECM on the distribution volumes of macromolecules in human healthy and malignant gynecologic tissues we used as probes 15 abundant plasma proteins quantified by high-resolution mass spectrometry. The available distribution volume (VA) of albumin was increased in ovarian carcinoma compared with healthy ovarian tissue. Furthermore, VA of plasma proteins between 40 and 190 kDa decreased with size for endometrial carcinoma and healthy ovarian tissue, but was independent of molecular weight for the ovarian carcinomas. An effect of charge on distribution volume was only found in healthy ovaries, which had lower hydration and high collagen content, indicating that a condensed interstitium increases the influence of negative charges. A number of earlier suggested biomarker candidates were detected in increased amounts in malignant tissue, e.g., stathmin and spindlin-1, showing that interstitial fluid, even when unfractionated, can be a valuable source for tissue-specific proteins. We demonstrate that the distribution of abundant plasma proteins in the interstitium can be elucidated by mass spectrometry methods and depends markedly on hydration and ECM structure. Our data can be used in modeling of drug uptake, and give indications on ECM components to be targeted to increase the uptake of macromolecular substances.

Ovarian cancer: can proteomics give new insights for therapy and diagnosis?

The study of the ovarian proteomic profile represents a new frontier in ovarian cancer research, since this approach is able to enlighten the wide variety of post-translational events (such as glycosylation and phosphorylation). Due to the possibility of analyzing thousands of proteins, which could be simultaneously altered, comparative proteomics represent a promising model of possible biomarker discovery for ovarian cancer detection and monitoring. Moreover, defining signaling pathways in ovarian cancer cells through proteomic analysis offers the opportunity to design novel drugs and to optimize the use of molecularly targeted agents against crucial and biologically active pathways. Proteomic techniques provide more information about different histological types of ovarian cancer, cell growth and progression, genes related to tumor microenvironment and specific molecular targets predictive of response to chemotherapy than sequencing or microarrays. Estimates of specificity with proteomics are less consistent, but suggest a new role for combinations of biomarkers in early ovarian cancer diagnosis, such as the OVA1 test. Finally, the definition of the proteomic profiles in ovarian cancer would be accurate and effective in identifying which pathways are differentially altered, defining the most effective therapeutic regimen and eventually improving health outcomes.

Potential tumor biomarkers identified in ovarian cyst fluid by quantitative proteomic analysis, iTRAQ

BACKGROUND

Epithelial-derived ovarian adenocarcinoma (EOC) is the most deadly gynecologic tumor, and the principle cause of the poor survival rate is diagnosis at a late stage. Screening and diagnostic biomarkers with acceptable specificity and sensitivity are lacking. Ovarian cyst fluid should harbor early ovarian cancer biomarkers because of its closeness to the tumor. We investigated ovarian cyst fluid as a source for discovering biomarkers for use in the diagnosis of EOC.

RESULTS

Using quantitative mass spectrometry, iTRAQ MS, we identified 837 proteins in cyst fluid from benign, EOC stage I, and EOC stage III. Only patients of serous histology were included in the study. Comparing the benign (n = 5) with the malignant (n = 10) group, 87 of the proteins were significantly (p < 0.05) differentially expressed. Two proteins, serum amyloid A-4 (SAA4) and astacin-like metalloendopeptidase (ASTL), were selected for verification of the iTRAQ method and external validation with immunoblot in a larger cohort with mixed histology, in plasma (n = 68), and cyst fluid (n = 68). The protein selections were based on either high significance and high fold change or abundant appearance and several peptide recognitions in the sample sets (p = 0.04, FC = 1.95) and (p < 0.001, FC = 8.48) for SAA4 and ASTL respectively. Both were found to be significantly expressed (p < 0.05), but the methods did not correlate concerning ASTL.

CONCLUSIONS

Fluid from ovarian cysts connected directly to the primary tumor harbor many possible new tumor-specific biomarkers. We have identified 87 differentially expressed proteins and validated two candidates to verify the iTRAQ method. However several of the proteins are of interest for validation in a larger setting.

Interstitial fluid-a reflection of the tumor cell microenvironment and secretome

The interstitium or interstitial space describes the space outside the blood and lymphatic vessels. It contains two phases; the interstitial fluid (IF) and the extracellular matrix. In this review we focus on the interstitial fluid phase, which is the physical and biochemical microenvironment of the cells, and more specifically that of tumors. IF is created by transcapillary filtration and cleared by lymphatic vessels, and contains substances that are either produced and secreted locally, thus denoted secretome, or brought to the organ by the circulation. The structure of the interstitium is discussed briefly and moreover techniques for IF isolation focusing on those that are relevant for studies of the secretome. Accumulated data show that tumor IF is hypoxic and acidic compared with subcutaneous IF and plasma, and that there are gradients between IF and plasma giving information on where substances are produced and thereby reflecting the local microenvironment. We review recent data on the origin of tissue specific substances, challenges related to isolating a representative secretome and the use of this as a substrate for biomarker identification. Finally we perform a comparative analysis across human tumor types and techniques and show that there is great variation in the results obtained that may at least partially be due to the isolation method used. We conclude that when care is taken in isolation of substrate, analysis of the secretome may give valuable biological insight and result in identification of biomarker candidates. This article is part of a Special Issue entitled: An Updated Secretome.