Proteomics of ovarian cancer: functional insights and clinical applications

Diagnostic biomarkers in ovarian cancer: advances beyond CA125 and HE4

Ovarian cancer (OC) is the most lethal gynaecologic malignancy, attributed to its insidious growth, non-specific symptoms and late presentation. Unfortunately, current screening modalities are inadequate at detecting OC and many lack the appropriate specificity and sensitivity that is desired from a screening test. Nearly 70% of cases are diagnosed at stage III or IV with poor 5-year overall survival. Therefore, the development of a sensitive and specific biomarker for early diagnosis and screening for OC is of utmost importance. Currently, diagnosis is guided by CA125, the patient's menopausal status and imaging features on ultrasound scan. However, emerging evidence suggests that a combination of CA125 and HE4 (another serum biomarker) and patient characteristics in a multivariate index assay may provide a higher specificity and sensitivity than either CA125 and HE4 alone in the early detection of OC. Other attempts at combining various serum biomarkers into one multivariate index assay such as OVA1, ROMA and Overa have all shown promise. However, significant barriers exist before these biomarkers can be implemented in clinical practice. This article aims to provide an up-to-date review of potential biomarkers for screening and early diagnosis of OC which may have the potential to transform its diagnostic landscape.

Circ_0078607 increases platinum drug sensitivity via miR-196b-5p/GAS7 axis in ovarian cancer

Platinum-based chemotherapy is one of the predominant strategies for treating ovarian cancer (OC), however, platinum resistance greatly influences the therapeutic effect. Circular RNAs (circRNAs) have been found to participate in the pathogenesis of platinum resistance. Our aim was to explore the involvement of circ_0078607 in OC cell cisplatin (DDP) resistance and its potential mechanisms. Circ_0078607, miR-196b-5p, and growth arrest-specific 7 (GAS7) levels were assessed by qPCR. Circ_0078607 stability was assessed by ribonuclease R digestion and actinomycin D treatment. Cell viability of various conic of DDP treatment was measured by CCK-8. The cell proliferation was determined by CCK-8 and colony formation assay. Western blotting was performed for determining GAS7, ABCB1, CyclinD1 and Bcl-2 protein levels. The direct binding between miR-196b-5p and circ_0078607 or GAS7 was validated by dual-luciferase reporter and RIP assay. DDP resistance in vivo was evaluated in nude mice. Immunohistochemistry staining for detecting Ki67 expression in xenograft tumours. Circ_0078607 and GAS7 was down-regulated, but miR-196b-5p was up-regulated in OC samples and DDP-resistant cells. Overexpression of circ_0078607 inhibited DDP resistance, cell growth and induced apoptosis in DDP-resistant OC cells. Mechanistically, circ_0078607 sequestered miR-196b-5p to up-regulate GAS7. MiR-196b-5p mimics reversed circ_0078607 or GAS7 overexpression-mediated enhanced sensitivity. Finally, circ_0078607 improved the sensitivity of DDP in vivo. Circ_0078607 attenuates DDP resistance via miR-196b-5p/GAS7 axis, which highlights the therapeutic potential of circ_0078607 to counter DDP resistance in OC.

An Integrated Approach to Protein Discovery and Detection From Complex Biofluids

Ovarian cancer, a leading cause of cancer-related deaths among women, has been notoriously difficult to screen for and diagnose early, as early detection significantly improves survival. Researchers and clinicians seek routinely usable and noninvasive screening methods; however, available methods (i.e., biomarker screening) lack desirable sensitivity/specificity. The most fatal form, high-grade serous ovarian cancer, often originate in the fallopian tube; therefore, sampling from the vaginal environment provides more proximal sources for tumor detection. To address these shortcomings and leverage proximal sampling, we developed an untargeted mass spectrometry microprotein profiling method and identified cystatin A, which was validated in an animal model. To overcome the limits of detection inherent to mass spectrometry, we demonstrated that cystatin A is present at 100 pM concentrations using a label-free microtoroid resonator and translated our workflow to patient-derived clinical samples, highlighting the potential utility of early stage detection where biomarker levels would be low.

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.

RNF113A targeted by miR-197 promotes proliferation and inhibits autophagy via CXCR4/CXCL12/AKT/ERK/Beclin1 axis in cervical cancer

Ring Finger Protein 113 (RNF113A), an ubiquitin E3 ligase, is genetically associated with many biological processes, including proliferation, differentiation, cell death, and neurogenesis. Recently, RNF113A has been found to be an abnormal expression in many diseases, such as X-linked trichothiodystrophy syndrome and esophageal cancer. Here, we explore the potential mechanism of RNF113A in the progression of cervical cancer (CC). In this study, we evaluated the expression level and biological function of RNF113A in CC both in vitro and in vivo by bioinformatic prediction, DIA proteomic analysis, compensation experiment, Co-IP, dual-luciferase reporter assay and nude mouse xenograft to identify the RNF113A-associated autophagy pathways involved with tumorigenesis. Consistent with the prediction from biological information analysis, we found that RNF113A was highly expressed in human CC tissues and cells. In addition, this study illustrated that the high expression of RNF113A dramatically promoted proliferation and suppressed autophagy both in vitro and in vivo. In contrast, low expression of RNF113A enhanced autophagy activities and inhibited tumor growth in CC. We also found that miRNA-197, the level of which (negative correlation with RNF113A) declined in human CC, directly restrained the expression of RNF113A. Mechanistically, proteomic and mechanistic assays uncovered that RNF113A confirmed as the direct downstream target of miR-197, promoted proliferation and restrained autophagy in CC not through direct ubiquitination degradation of autophagy marker Beclin1 but via CXCR4/CXCL12/AKT/ERK/Beclin1 signal transduction axis. In summary, we found a new miR-197/RNF113 A/CXCR4/CXCL12/AKT/ERK/Beclin1 regulation pathway that plays an important part in the survival and progression of CC.

Chemoresistant Cancer Cell Lines Are Characterized by Migratory, Amino Acid Metabolism, Protein Catabolism and IFN1 Signalling Perturbations

Simple Summary

While chemoresistance remains a major barrier to improving the outcomes for patients with ovarian cancer, the molecular features, and associated biological functions, which underpin chemoresistance in ovarian cancer remain poorly understood. In this study we aimed to provide insight into the proteins and metabolites, and their associated biological pathways, which play a role in conferring chemoresistance to ovarian cancer. Through mass spectrometry analysis comparing the proteome and metabolome of chemosensitive vs chemoresistant ovarian cancer cell lines we revealed numerous perturbations in signalling and metabolic pathways in chemoresistant cells. Further comparison to primary cells taken from patients with chemoresistant or chemosensitive disease identified a shared dysregulation in cytokine and type 1 interferon signalling. Our research sets the foundation for a deeper understanding of the proteomic and metabolomic features of chemoresistance and identifies type 1 interferon signalling as a common feature of chemoresistance.

Abstract

Chemoresistance remains the major barrier to effective ovarian cancer treatment. The molecular features and associated biological functions of this phenotype remain poorly understood. We developed carboplatin-resistant cell line models using OVCAR5 and CaOV3 cell lines with the aim of identifying chemoresistance-specific molecular features. Chemotaxis and CAM invasion assays revealed enhanced migratory and invasive potential in OVCAR5-resistant, compared to parental cell lines. Mass spectrometry analysis was used to analyse the metabolome and proteome of these cell lines, and was able to separate these populations based on their molecular features. It revealed signalling and metabolic perturbations in the chemoresistant cell lines. A comparison with the proteome of patient-derived primary ovarian cancer cells grown in culture showed a shared dysregulation of cytokine and type 1 interferon signalling, potentially revealing a common molecular feature of chemoresistance. A comprehensive analysis of a larger patient cohort, including advanced in vitro and in vivo models, promises to assist with better understanding the molecular mechanisms of chemoresistance and the associated enhancement of migration and invasion.

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.

Regulatory Role of the Adipose Microenvironment on Ovarian Cancer Progression

Simple Summary

Adipocytes or fat cells are integral part of the ovarian tumor microenvironment. Secreted factors from adipocytes, as well as direct cell-to-cell interaction with ovarian cancer cells have been shown to directly support ovarian tumor progression. Elucidating the molecular pathways involved is crucial in the identification of relevant targets.

Abstract

The tumor microenvironment of ovarian cancer is the peritoneal cavity wherein adipose tissue is a major component. The role of the adipose tissue in support of ovarian cancer progression has been elucidated in several studies from the past decades. The adipocytes, in particular, are a major source of factors, which regulate all facets of ovarian cancer progression such as acquisition of chemoresistance, enhanced metastatic potential, and metabolic reprogramming. In this review, we summarize the relevant studies, which highlight the role of adipocytes in ovarian cancer progression and offer insights into unanswered questions and possible future directions of research.

Tumor microenvironment manipulates chemoresistance in ovarian cancer (Review)

Ovarian cancer (OC) is the leading cause of mortality among the various types of gynecological cancer, and >75% of the cases are diagnosed at a late stage. Although platinum‑based chemotherapy is able to help the majority of patients to achieve remission, the disease frequently recurs and acquires chemoresistance, resulting in high mortality rates. The complexity of OC therapy is not solely governed by the intrinsic characteristics of the OC cells (OCCs) themselves, but is also largely dependent on the dynamic communication between OCCs and various components of their surrounding microenvironment. The present review attempts to describe the mutual interplay between OCCs and their surrounding microenvironment. Tumor‑associated macrophages (TAMs) and cancer‑associated fibroblasts (CAFs) are the most abundant stromal cell types in OC. Soluble factors derived from CAFs steadily nourish both the OCCs and TAMs, facilitating their proliferation and immune evasion. ATP binding cassette transporters facilitate the extrusion of cytotoxic molecules, eventually promoting cell survival and multidrug resistance. Extracellular vesicles fulfill their role as genetic exchange vectors, transferring cargo from the donor cells to the recipient cells and propagating oncogenic signaling. A greater understanding of the vital roles of the tumor microenvironment will allow researchers to be open to the prospect of developing therapeutic approaches for combating OC chemoresistance.

Hsa_circ_0001756 promotes ovarian cancer progression through regulating IGF2BP2-mediated RAB5A expression and the EGFR/MAPK signaling pathway

Hsa_circ_0001756 was reported to be upregulated in serum samples of ovarian cancer (OC) patients and may serve as a potential OC biomarker. This study aimed to investigate the role and molecular mechanisms of hsa_circ_0001756 in OC procession. Herein, we detected the expression of hsa_circ_0001756 in OC tissues and cell lines with RT-qPCR assay, which showed that hsa_circ_0001756 was upregulated in OC tissues and cell lines. Then small interfering RNA targeting hsa_circ_0001756 (si-hsa_circ_0001756) was transfected into SKOV3 and A2780 cells, and the proliferation, invasion, and expression of epithelial-mesenchymal transition (EMT) marker proteins were determined with CCK-8, Transwell and Western blotting assays, respectively. We found that hsa_circ_0001756 knockdown inhibited OC cell proliferation, invasion and EMT. Moreover, RNA pull-down assay verified the binding between hsa_circ_0001756 and IGF2 mRNA binding protein 2 (IGF2BP2), and rescue experiments indicated that IGF2BP2 overexpression reversed the effects of has_circ_0001756 knockdown on OC cell functions. Co-IP assay verified IGF2BP2 could interact with RAB GTPase 5A (RAB5A) protein. Then SKOV3 cells were transfected with si-IGF2BP2 alone or together with pcDNA-RAB5A, followed by the detection of SKOV3 cell functions. We found that IGF2BP2 knockdown inhibited OC cell proliferation, invasion, and EMT, while RAB5A overexpression reversed these effects. Finally, SKOV3 cells transfected with si-hsa_circ_0001756 were injected into nude mice through tail vein. Hsa_circ_0001756 knockdown significantly inhibited the xenograft tumor growth of OC in vivo. In conclusion, hsa_circ_0001756 knockdown inhibits OC cell proliferation, invasion, and EMT, and reduces xenograft tumor growth by suppressing IGF2BP2-mediated RAB5A expression and blocking the EGFR/MAPK signaling pathway.

Sulfation of O-glycans on Mucin-type Proteins From Serous Ovarian Epithelial Tumors

Despite sulfated O-linked glycans being abundant on ovarian cancer (OC) glycoproteins, their regulation during cancer development and involvement in cancer pathogenesis remain unexplored. We characterized O-glycans carrying sulfation on galactose residues and compared their expression with defined sulfotransferases regulated during OC development. Desialylated sulfated oligosaccharides were released from acidic glycoproteins in the cyst fluid from one patient with a benign serous cyst and one patient with serous OC. Oligosaccharides characterized by LC-MSⁿ were identified as core 1 and core 2 O-glycans up to the size of decamers and with 1 to 4 sulfates linked to GlcNAc residues and to C-3 and/or C-6 of Gal. To study the specificity of the potential ovarian sulfotransferases involved, Gal3ST2 (Gal-3S)-, Gal3ST4 (Gal-3S)-, and CHST1 (Gal-6S)-encoding expression plasmids were transfected individually into CHO cells also expressing the P-selectin glycoprotein ligand-1/mouse immunoglobulin G2b (PSGL-1/mIg G2b) fusion protein and the human core 2 transferase (GCNT1). Characterization of the PSGL-1/mIg G2b O-glycans showed that Gal3ST2 preferentially sulfated Gal on the C-6 branch of core 2 structures and Gal3ST4 preferred Gal on the C-3 branch independently if core-1 or -2. CHST1 sulfated Gal residues on both the C-3 (core 1/2) and C-6 branches of core 2 structures. Using serous ovarian tissue micro array, Gal3ST2 was found to be decreased in tissue classified as malignant compared with tissues classified as benign or borderline, with the lowest expression in poorly differentiated malignant tissue. Neither Gal3ST4 nor CHST1 was differentially expressed in benign, borderline, or malignant tissue, and there was no correlation between expression level and differentiation stage. The data displays a complex sulfation pattern of O-glycans on OC glycoproteins and that aggressiveness of the cancer is associated with a decreased expression of the Gal3ST2 transferase.

•

Ovarian cancer tissue contains highly sulfated O-glycoproteins.

•

Sulfation occurs on GlcNAc (6-position) and Gal (3- and 6-position).

•

Sulfation of Gal can be mimicked recombinantly with selected sulfotransferase.

•

The Gal3ST2 sulfotransferase level is lower in malignant cancer compared with benign.

Malignant Ascites in Ovarian Cancer: Cellular, Acellular, and Biophysical Determinants of Molecular Characteristics and Therapy Response

Ascites refers to the abnormal accumulation of fluid in the peritoneum resulting from an underlying pathology, such as metastatic cancer. Among all cancers, advanced-stage epithelial ovarian cancer is most frequently associated with the production of malignant ascites and is the leading cause of death from gynecologic malignancies. Despite decades of evidence showing that the accumulation of peritoneal fluid portends the poorest outcomes for cancer patients, the role of malignant ascites in promoting metastasis and therapy resistance remains poorly understood. This review summarizes the current understanding of malignant ascites, with a focus on ovarian cancer. The first section provides an overview of heterogeneity in ovarian cancer and the pathophysiology of malignant ascites. Next, analytical methods used to characterize the cellular and acellular components of malignant ascites, as well the role of these components in modulating cell biology, are discussed. The review then provides a perspective on the pressures and forces that tumors are subjected to in the presence of malignant ascites and the impact of physical stress on therapy resistance. Treatment options for malignant ascites, including surgical, pharmacological and photochemical interventions are then discussed to highlight challenges and opportunities at the interface of drug discovery, device development and physical sciences in oncology.

Nanomaterials for cancer therapy: current progress and perspectives

Cancer is a disease with complex pathological process. Current chemotherapy faces problems such as lack of specificity, cytotoxicity, induction of multi-drug resistance and stem-like cells growth. Nanomaterials are materials in the nanorange 1–100 nm which possess unique optical, magnetic, and electrical properties. Nanomaterials used in cancer therapy can be classified into several main categories. Targeting cancer cells, tumor microenvironment, and immune system, these nanomaterials have been modified for a wide range of cancer therapies to overcome toxicity and lack of specificity, enhance drug capacity as well as bioavailability. Although the number of studies has been increasing, the number of approved nano-drugs has not increased much over the years. To better improve clinical translation, further research is needed for targeted drug delivery by nano-carriers to reduce toxicity, enhance permeability and retention effects, and minimize the shielding effect of protein corona. This review summarizes novel nanomaterials fabricated in research and clinical use, discusses current limitations and obstacles that hinder the translation from research to clinical use, and provides suggestions for more efficient adoption of nanomaterials in cancer therapy.

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

Ovarian cancer is the most lethal gynecologic malignancy among women. Approximately 70–80% of patients with advanced ovarian cancer experience relapse within five years and develop platinum-resistance. The short life expectancy of patients with platinum-resistant or platinum-refractory disease underscores the need to develop new and more effective treatment strategies. Early detection is a critical step in mitigating the risk of disease progression from early to an advanced stage disease, and protein biomarkers have an integral role in this process. The best biological diagnostic tool for ovarian cancer will likely be a combination of biomarkers. Targeted proteomics methods, including mass spectrometry-based approaches, have emerged as robust methods that can address the chasm between initial biomarker discovery and the successful verification and validation of these biomarkers enabling their clinical translation due to the robust sensitivity, specificity, and reproducibility of these versatile methods. In this review, we provide background information on the fundamental principles of biomarkers and the need for improved treatment strategies in ovarian cancer. We also provide insight into the ways in which mass spectrometry-based targeted proteomics approaches can provide greatly needed solutions to many of the challenges related to ovarian cancer biomarker development.

Glycomic-Based Biomarkers for Ovarian Cancer: Advances and Challenges

Ovarian cancer remains one of the most common causes of death among gynecological malignancies afflicting women worldwide. Among the gynecological cancers, cervical and endometrial cancers confer the greatest burden to the developing and the developed world, respectively; however, the overall survival rates for patients with ovarian cancer are worse than the two aforementioned. The majority of patients with ovarian cancer are diagnosed at an advanced stage when cancer has metastasized to different body sites and the cure rates, including the five-year survival, are significantly diminished. The delay in diagnosis is due to the absence of or unspecific symptoms at the initial stages of cancer as well as a lack of effective screening and diagnostic biomarkers that can detect cancer at the early stages. This, therefore, provides an imperative to prospect for new biomarkers that will provide early diagnostic strategies allowing timely mitigative interventions. Glycosylation is a protein post-translational modification that is modified in cancer patients. In the current review, we document the state-of-the-art of blood-based glycomic biomarkers for early diagnosis of ovarian cancer and the technologies currently used in this endeavor.

The Role of PBK as a Potential Prognostic and Diagnostic Biomarker in Ovarian Cancer

Aim: As one of the three malignant genital tumors, mortality in women with ovarian cancer is consistently high worldwide. It is of great importance to find prognostic markers for diagnosis and treatment of ovarian cancer. In this study, the authors utilized the bioinformatics analysis to identify the potential key genes to reveal the potential mechanism for ovarian cancer. Methods: The authors used the gene expression profile (GSE14407) to perform differentially expressed gene (DEG) analysis and the weighted gene co-expression network analysis. They selected the key module and performed the gene ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis for the genes in the hub module. Then they screened the key genes in the hub module, and further validated their expression level. Results: A total of 3124 DEGs were detected after differential gene expression analysis; of these, 433 were upregulated genes and 2691 were downregulated genes. The authors selected the brown module that is significantly associated with the BRCA gene expression. Then they selected 30 hub genes from the protein-protein interaction network. And the authors identify the PDZ binding kinase (PBK) as the prognosis-associated hub gene whose expression was significantly high in the ovarian cancer tissue. Conclusions: The bioinformatics analysis for the DEGs could be important to understand the pathogenesis for ovarian cancer. In this study, PBK is identified as a potential marker that might improve the understanding of the molecular mechanism and the diagnosis level for ovarian cancer.

A multiplex biomarker assay improves the diagnostic performance of HE4 and CA125 in ovarian tumor patients

OBJECTIVE

Survival in epithelial ovarian cancer (EOC) remains poor. Most patients are diagnosed in late stages. Early diagnosis increases the chance of survival. We used the proximity extension assay from Olink Proteomics to search for new protein biomarkers with the potential to improve the diagnostic performance of CA125 and HE4 in patients with ovarian tumors.

MATERIAL AND METHODS

Plasma samples were obtained from 180 women with ovarian tumors; 30 cases of benign tumor, 28 cases with borderline tumors, 25 early EOC cases (FIGO stage I) and 97 advanced EOC cases (FIGO stages II-IV). Proteins were measured using the Olink® Oncology II and Inflammation panels. For statistical analyses, patients were categorized into benign tumors versus cancer and benign tumors versus borderline + cancer, respectively.

RESULTS

We analyzed 177 biomarkers. Thirty-four proteins had ROC AUC > 0.7 for discrimination between benign tumors and cancer. Fifteen proteins had ROC AUC > 0.7 for discrimination between benign tumors and borderline tumors + cancer. HE4 ranked highest for both comparisons. A reference model with HE4, CA125 and age (AUC 0.838 for benign tumors vs. cancer and AUC 0.770 for benign tumors vs. borderline tumors + cancer) was compared to the reference model with the addition of each of the remaining proteins with AUC > 0.7. ITGAV was the only individual biomarker found to improve diagnostic performance of the reference model, to AUC 0.874 for benign tumors vs. cancer and AUC 0.818 for benign tumors vs. borderline tumors + cancer (p < 0.05). Cross-validation and LASSO regression was combined to select multiple biomarker combinations. The best performing model for discrimination between benign tumors and borderline tumors + cancer was a 6-biomarker combination (HE4, CA125, ITGAV, CXCL1, CEACAM1, IL-10RB) and age (AUC 0.868, sensitivity 0.86 and specificity 0.82, p = 0.016 for comparison with the reference model).

CONCLUSION

HE4 was the best performing individual biomarker for discrimination between benign ovarian tumors and EOC including borderline tumors. The addition of other carcinogenesis-related biomarkers in a multiplex biomarker panel can improve the diagnostic performance of the established biomarkers HE4 and CA125.

Challenges and Opportunities in Clinical Applications of Blood-Based Proteomics in Cancer

Simple Summary

The traditional approach in identifying cancer related protein biomarkers has focused on evaluation of a single peptide/protein in tissue or circulation. At best, this approach has had limited success for clinical applications, since multiple pathological tumor pathways may be involved during initiation or progression of cancer which diminishes the significance of a single candidate protein/peptide. Emerging sensitive proteomic based technologies like liquid chromatography mass spectrometry (LC-MS)-based quantitative proteomics can provide a platform for evaluating serial serum or plasma samples to interrogate secreted products of tumor–host interactions, thereby revealing a more “complete” repertoire of biological variables encompassing heterogeneous tumor biology. However, several challenges need to be met for successful application of serum/plasma based proteomics. These include uniform pre-analyte processing of specimens, sensitive and specific proteomic analytical platforms and adequate attention to study design during discovery phase followed by validation of discovery-level signatures for prognostic, predictive, and diagnostic cancer biomarker applications.

Abstract

Blood is a readily accessible biofluid containing a plethora of important proteins, nucleic acids, and metabolites that can be used as clinical diagnostic tools in diseases, including cancer. Like the on-going efforts for cancer biomarker discovery using the liquid biopsy detection of circulating cell-free and cell-based tumor nucleic acids, the circulatory proteome has been underexplored for clinical cancer biomarker applications. A comprehensive proteome analysis of human serum/plasma with high-quality data and compelling interpretation can potentially provide opportunities for understanding disease mechanisms, although several challenges will have to be met. Serum/plasma proteome biomarkers are present in very low abundance, and there is high complexity involved due to the heterogeneity of cancers, for which there is a compelling need to develop sensitive and specific proteomic technologies and analytical platforms. To date, liquid chromatography mass spectrometry (LC-MS)-based quantitative proteomics has been a dominant analytical workflow to discover new potential cancer biomarkers in serum/plasma. This review will summarize the opportunities of serum proteomics for clinical applications; the challenges in the discovery of novel biomarkers in serum/plasma; and current proteomic strategies in cancer research for the application of serum/plasma proteomics for clinical prognostic, predictive, and diagnostic applications, as well as for monitoring minimal residual disease after treatments. We will highlight some of the recent advances in MS-based proteomics technologies with appropriate sample collection, processing uniformity, study design, and data analysis, focusing on how these integrated workflows can identify novel potential cancer biomarkers for clinical applications.

[ARTICLE WITHDRAWN] Long Noncoding RNA KCNQ1OT1 Accelerates the Progression of Ovarian Cancer via MicroRNA-212-3/LCN2 Axis

ARTICLE WITHDRAWN: This article was withdrawn by the authors with the following Withdrawal Statement - The integrity of the current study is not acceptable. The authors intend to enrich the study to make it more valuable. Thus, the authors want to withdraw the current study. Please accept our apologies for this inconvenience and we hope for your understanding. Yours sincerely (on behalf of the authors), Xiaoqin Lu.

Factors in Oncogenesis: Viral Infections in Ovarian Cancer

Ovarian cancer (OC) is one of the leading causes of cancer death in women, with high-grade serous ovarian cancer (HGSOC) being the most lethal gynecologic malignancy among women. This high fatality rate is the result of diagnosis of a high number of new cases when cancer implants have already spread. The poor prognosis is due to our inadequate understanding of the molecular mechanisms preceding ovarian malignancy. Knowledge about the site of origination has been improved recently by the discovery of tube intraepithelial cancer (TIC), but the potential risk factors are still obscure. Due to high tumoral heterogeneity in OC, the establishment of early stage biomarkers is still underway. Microbial infection may induce or result in chronic inflammatory infection and in the pathogenesis of cancers. Microbiome research has shed light on the relationships between the host and microbiota, as well as the direct roles of host pathogens in cancer development, progression, and drug efficacy. While controversial, the detection of viruses within ovarian malignancies and fallopian tube tissues suggests that these pathogens may play a role in the development of OC. Genomic and proteomic approaches have enhanced the methods for identifying candidates in early screening. This article summarizes the existing knowledge related to the molecular mechanisms that lead to tumorigenesis in the ovary, as well as the viruses detected in OC cases and how they may elevate this process.

Expression and clinical significance of WWOX, Elf5, Snail1 and EMT related factors in epithelial ovarian cancer

Expression and clinical significance of WW domain-containing oxidoreductase (WWOX), Elf5, Snail1 and epithelial-mesenchymal transition (EMT) related factors in epithelial ovarian cancer were investigated. Ovarian cancer tissues of 300 epithelial ovarian cancer patients and the adjacent normal tissues were analyzed. Immunohistochemical method was used to detect the expressions of WWOX, Elf5, Snail1 and EMT marker molecules in the specimens. The relationship between the indicators and clinicopathological parameters, and prognosis of patients with ovarian cancer was analyzed. The relationship between WWOX, Elf5, Snail1 and EMT marker molecules E-cadherin, N-cadherin and vimentin in ovarian cancer tissues was analyzed. The expression levels of WWOX, Elf5, Snail1 and EMT marker molecules in epithelial ovarian cancer tissues were significantly different from those in adjacent normal tissues, and were related to surgical pathological stage, pathological grade and lymph node metastasis. High expressions of WWOX and Elf5 were related to the survival rate of patients. The survival rate of patients with positive expression was significantly higher than that of negative expression. FIGO stage, pathological grade, lymph node metastasis and expression of WWOX and Elf5 were all independent factors affecting postoperative prognosis in ovarian cancer patients. In conclusion, the expression levels of WWOX, Elf5, Snail1 and EMT related factors in epithelial ovarian cancer tissues are consistent and different. The expression levels of WWOX and Elf5 are related to the survival and prognosis of patients with epithelial ovarian cancer.

Ovarian Cancer Biomarkers: Moving Forward in Early Detection

Ovarian cancer is a silent cancer which rate survival mainly relays in early stage detection. The discovery of reliable ovarian cancer biomarkers plays a crucial role in the disease management and strongly impact in patient's prognosis and survival. Although having many limitations CA125 is a classical ovarian cancer biomarker, but current research using proteomic or metabolomic methodologies struggles to find alternative biomarkers, using non-invasive our relatively non-invasive sources such as urine, serum, plasma, tissue, ascites or exosomes. Metabolism and metabolites are key players in cancer biology and its importance in biomarkers discovery cannot be neglected. In this chapter we overview the state of art and the challenges facing the use and discovery of biomarkers and focus on ovarian cancer early detection.

Novel Approaches in Ovarian Cancer Research against Heterogeneity, Late Diagnosis, Drug Resistance, and Transcoelomic Metastases

The development of modern technologies has revolutionised science and has had a huge impact on biomedical studies. This review focuses on possible tools that scientists can use to face the challenges of fighting ovarian cancer. Ovarian cancer is the deadliest gynaecologic malignancy and, even after years of study, the mortality has not decreased significantly. In the era of sequencing and personalised and precision medicine, we are now closer than ever to helping patients and physicians in regard to treatment and diagnosis of this disease. This work summarises the newest findings in the development of ovarian cancer research.

A Microfluidic Chip Enables Isolation of Exosomes and Establishment of Their Protein Profiles and Associated Signaling Pathways in Ovarian Cancer

Because of limits on specificity and purity to allow for in-depth protein profiling, a standardized method for exosome isolation has yet to be established. In this study, we describe a novel, in-house microfluidic-based device to isolate exosomes from culture media and patient samples. This technology overcomes contamination issues because sample separation is based on the expression of highly specific surface markers CD63 and EpCAM. Mass spectrometry revealed over 25 exosome proteins that are differentially expressed in high-grade serous ovarian cancer (HGSOC) cell lines compared with normal cells-ovarian surface epithelia cells and fallopian tube secretory epithelial cells (FTSEC). Top exosome proteins were identified on the basis of their fold change and statistical significance between groups. Ingenuity pathway analysis identified STAT3 and HGF as top regulator proteins. We further validated exosome proteins of interest (pSTAT3, HGF, and IL6) in HGSOC samples of origin-based cell lines (OVCAR-8, FTSEC) and in early-stage HGSOC patient serum exosome samples using LC/MS-MS and proximity extension assay. Our microfluidic device will allow us to make new discoveries for exosome-based biomarkers for the early detection of HGSOC and will contribute to the development of new targeted therapies based on signaling pathways that are unique to HGSOC, both of which could improve the outcome for women with HGSOC. SIGNIFICANCE: A unique platform utilizing a microfluidic device enables the discovery of new exosome-based biomarkers in ovarian cancer.

Mapping human N-linked glycoproteins and glycosylation sites using mass spectrometry

N-linked glycoprotein is a highly interesting class of proteins for clinical and biological research. Over the last decade, large-scale profiling of N-linked glycoproteins and glycosylation sites from biological and clinical samples has been achieved through mass spectrometry-based glycoproteomic approaches. In this paper, we reviewed the human glycoproteomic profiles that have been reported in more than 80 individual studies, and mainly focused on the N-glycoproteins and glycosylation sites identified through their deglycosylated forms of glycosite-containing peptides. According to our analyses, more than 30,000 glycosite-containing peptides and 7,000 human glycoproteins have been identified from five different body fluids, twelve human tissues (or related cell lines), and four special cell types. As the glycoproteomic data is still missing for many organs and tissues, a systematical glycoproteomic analysis of various human tissues and body fluids using a uniform platform is still needed for an integrated map of human N-glycoproteomes.

The contribution and perspectives of proteomics to uncover ovarian cancer tumor markers

Despite all the advances in understanding the mechanisms involved in ovarian cancer (OC) development, many aspects still need to be unraveled and understood. Tumor markers (TMs) are of special interest in this disease. Some aspects of clinical management of OC might be improved by the use of validated TMs, such as differentiating subtypes, defining the most appropriate treatment, monitoring the course of the disease, or predicting clinical outcome. The Food and Drug Administration (FDA) has approved a few TMs for OC: CA125 (cancer antigen 125; monitoring), HE4 (Human epididymis protein; monitoring), ROMA (Risk Of Malignancy Algorithm; HE4+CA125; prediction of malignancy) and OVA1 (Vermillion's first-generation Multivariate Index Assay [MIA]; prediction of malignancy). Proteomics can help advance the research in the field of TMs for OC. A variety of biological materials are being used in proteomic analysis, among them tumor tissues, interstitial fluids, tumor fluids, ascites, plasma, and ovarian cancer cell lines. However, the discovery and validation of new TMs for OC is still very challenging. The enormous heterogeneity of histological types of samples and the individual variability of patients (lifestyle, comorbidities, drug use, and family history) are difficult to overcome in research protocols. In this work, we sought to gather relevant information regarding TMs, OC, biological samples for proteomic analysis, as well as markers and algorithms approved by the FDA for use in clinical routine.

Proteomics of reproduction: Prospects and perspectives

In recent years, proteomics has been used widely in reproductive research in order to understand the molecular mechanisms related to gametes at the cellular level and the role of proteins involved in fertilization. Network and pathway analysis using bioinformatic tools have paved way to obtain a wider picture on the possible pathways associated with the key differentially expressed proteins (DEPs) and its implication in various infertility scenarios. A brief overview of advanced techniques and bioinformatic tools used for reproductive proteomics is presented. Key findings of proteomic-based studies on male and female reproduction are also presented. Furthermore, the chapter sheds light on the cellular pathways and potential biomarkers associated with male and female infertility. Proteomics coupled with bioinformatic analysis provides an ideal platform for non-invasive management of infertility in couples.

Targeted metabolomic profiling of low and high grade serous epithelial ovarian cancer tissues: a pilot study

INTRODUCTION

Epithelial ovarian cancer (EOC) remains the leading cause of death from gynecologic malignancies and has an alarming global fatality rate. Besides the differences in underlying pathogenesis, distinguishing between high grade (HG) and low grade (LG) EOC is imperative for the prediction of disease progression and responsiveness to chemotherapy.

OBJECTIVES

The aim of this study was to investigate, the tissue metabolome associated with HG and LG serous epithelial ovarian cancer.

METHODS

A combination of one dimensional proton nuclear magnetic resonance (1D H NMR) spectroscopy and targeted mass spectrometry (MS) was employed to profile the tissue metabolome of HG, LG serous EOCs, and controls.

RESULTS

Using partial least squares-discriminant analysis, we observed significant separation between all groups (p < 0.05) following cross validation. We identified which metabolites were significantly perturbed in each EOC grade as compared with controls and report the biochemical pathways which were perturbed due to the disease. Among these metabolic pathways, ascorbate and aldarate metabolism was identified, for the first time, as being significantly altered in both LG and HG serous cancers. Further, we have identified potential biomarkers of EOC and generated predictive algorithms with AUC (CI) = 0.940 and 0.929 for HG and LG, respectively.

CONCLUSION

These previously unreported biochemical changes provide a framework for future metabolomic studies for the development of EOC biomarkers. Finally, pharmacologic targeting of the key metabolic pathways identified herein could lead to novel and effective treatments of EOC.

Imaging Mass Spectrometry Reveals Crosstalk between the Fallopian Tube and the Ovary that Drives Primary Metastasis of Ovarian Cancer

High grade serous ovarian cancer (HGSOC) is the fifth leading cause of cancer deaths among women. New evidence suggests that HGSOC arises in the fallopian tube and then colonizes the ovary before spreading into the peritoneal space. Therefore, due to the proximity of this metastasis, an experimental design was optimized using imaging mass spectrometry to capture the spatial composition of small molecules uniquely expressed when fallopian-tube-derived tumor cells were grown in the microenvironment of the ovary as a model of primary metastasis. The observed mass-to-charge ratios (m/z's) that were induced specifically in coculture represent small molecules that may contribute to the metastasis of HGSOC selectively to the ovary. Human fallopian tube epithelial HGSOC and tumorigenic murine oviductal epithelial cells, but not normal cell types, repeatedly induced a signal from the ovary at m/z 170. This signal was identified as norepinephrine, which was confirmed to stimulate invasion of ovarian cancer cells lacking wild-type p53. These molecules may reveal pathways that contribute to metastasis and biological targets for therapeutic intervention to block ovarian metastasis of fallopian-tube-derived HGSOC. The developed mass spectrometry method can be adapted to other mammalian-based model systems for investigation of untargeted metabolomics that facilitate metastasis.

Mass spectrometry-based proteomics techniques and their application in ovarian cancer research

Ovarian cancer has emerged as one of the leading cause of gynecological malignancies. So far, the measurement of CA125 and HE4 concentrations in blood and transvaginal ultrasound examination are essential ovarian cancer diagnostic methods. However, their sensitivity and specificity are still not sufficient to detect disease at the early stage. Moreover, applied treatment may appear to be ineffective due to drug-resistance. Because of a high mortality rate of ovarian cancer, there is a pressing need to develop innovative strategies leading to a full understanding of complicated molecular pathways related to cancerogenesis. Recent studies have shown the great potential of clinical proteomics in the characterization of many diseases, including ovarian cancer. Therefore, in this review, we summarized achievements of proteomics in ovarian cancer management. Since the development of mass spectrometry has caused a breakthrough in systems biology, we decided to focus on studies based on this technique. According to PubMed engine, in the years 2008-2010 the number of studies concerning OC proteomics was increasing, and since 2010 it has reached a plateau. Proteomics as a rapidly evolving branch of science may be essential in novel biomarkers discovery, therapy decisions, progression predication, monitoring of drug response or resistance. Despite the fact that proteomics has many to offer, we also discussed some limitations occur in ovarian cancer studies. Main difficulties concern both complexity and heterogeneity of ovarian cancer and drawbacks of the mass spectrometry strategies. This review summarizes challenges, capabilities, and promises of the mass spectrometry-based proteomics techniques in ovarian cancer management.

Functional characterization of a panel of high-grade serous ovarian cancer cell lines as representative experimental models of the disease

Genomic analysis of ovarian cancer cell lines has revealed a panel that best represents the most common ovarian cancer subtype, high-grade serous ovarian cancer (HGSOC). However, these HGSOC-like cell lines have not been extensively applied by ovarian cancer researchers to date, and the most commonly used cell lines in the ovarian cancer field do not genetically resemble the major clinical type of the disease. For the HGSOC-like lines to serve as suitable models, they need to be characterized for common functional assays. To achieve that objective, we systematically studied a panel of HGSOC cells CAOV3, COV362, Kuramochi, OVCAR4, OVCAR5, OVCAR8, OVSAHO and SNU119 for migration, invasion, proliferation, clonogenicity, EMT phenotype and cisplatin resistance. They exhibited a range of efficacies and OVCAR5, OVCAR8 and Kuramochi were the most aggressive. SNU119 and OVSAHO cells demonstrated the lowest functional activities. Wide differences in expression of EMT markers were observed between cell lines. SNU119 were the most epithelial and OVCAR8 had the most mesenchymal phenotype. COV362 was the most resistant to cisplatin while CAOV3 was the most sensitive. Taken together, our systematic characterization represents a valuable resource to help guide the application of HGSOC cells by the cancer research community.

Protein biomarkers for early detection of diseases: The decisive contribution of combinatorial peptide ligand libraries

The present review deals with biomarker discovery, especially in regard to sample treatment via combinatorial peptide ligand libraries, perhaps the only technique at present allowing deep exploration of biological fluids and tissue extracts in search for low- to very-low-abundance proteins, which could possibly mark the onset of most pathologies. Early-stage biomarkers, in fact, might be the only way to detect the beginning of most diseases thus permitting proper intervention and care. The following cancers are reviewed, with lists of potential biomarkers suggested in various reports: hepatocellular carcinoma, ovarian cancer, breast cancer and pancreatic cancer, together with some other interesting applications. Although panels of proteins have been presented, with robust evidence, as potential early-stage biomarkers in these different pathologies, their approval by FDA as novel biomarkers in routine clinical chemistry settings would require plenty of additional work and efforts from the pharma industry. The science environment in universities could simply not afford such heavy monetary investments.

SIGNIFICANCE

After more than 16years of search for novel biomarkers, to be used in a clinical chemistry set-up, via proteomic analysis (mostly in biological fluids) it was felt a critical review was due. In the present report, though, only papers reporting biomarker discovery via combinatorial peptide ligand libraries are listed and assessed, since this methodology seems to be the most advanced one for digging in depth into low-to very-low-abundance proteins, which might represent important biomarkers for the onset of pathologies. In particular, a large survey has been made for the following diseases, since they appear to have a large incidence on human population and/or represent fatal diseases: ovarian cancer, breast cancer, pancreatic cancer and hepatocellular carcinoma.

Vinculin and filamin-C are two potential prognostic biomarkers and therapeutic targets for prostate cancer cell migration

Prostate cancer (PCa) is one of the most common diseases for male population, and the effective treatment for metastatic castration-resistant PCa is still lacking. To unravel the underlying mechanism of PCa cell migration, we plan to analyze the related crucial proteins and their roles. In our study, we firstly identify the differentially expressed proteins using quantitative proteomics, and confirm their mRNA expression using quantitative polymerase chain reaction (qPCR). The alterations of these proteins at DNA and mRNA levels are obtained from cBioPortal database. Furthermore, the functions of these proteins are evaluated using wound-healing assay. The quantitative proteomics identified vinculin (VCL) and filamin-C (FLNC) as two highly expressed proteins in PC3 cells, and the DNA and mRNA of these two proteins were amplified and upregulated in a part of PCa patients. Knockdown of VCL and FLNC gene expression significantly inhibit PCa cell migration. These findings suggest that VCL and FLNC identified by quantitative proteomics are highly expressed in PCa cells with high migration potential, and they could be effective targets for repressing PCa cell migration, paving a new avenue for the prognosis and treatment of advanced PCa.

MALDI-TOF-MS analysis in discovery and identification of serum proteomic patterns of ovarian cancer

Background

Due to high mortality and lack of efficient screening, new tools for ovarian cancer (OC) diagnosis are urgently needed. To broaden the knowledge on the pathological processes that occur during ovarian cancer tumorigenesis, protein-peptide profiling was proposed.

Methods

Serum proteomic patterns in samples from OC patients were obtained using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF). Eighty nine serum samples (44 ovarian cancer and 45 healthy controls) were pretreated using solid-phase extraction method. Next, a classification model with the most discriminative factors was identified using chemometric algorithms. Finally, the results were verified by external validation on an independent test set of samples.

Results

Main outcome of this study was an identification of potential OC biomarkers by applying liquid chromatography coupled with tandem mass spectrometry. Application of this novel strategy enabled the identification of four potential OC serum biomarkers (complement C3, kininogen-1, inter-alpha-trypsin inhibitor heavy chain H4, and transthyretin). The role of these proteins was discussed in relation to OC pathomechanism.

Conclusions

The study results may contribute to the development of clinically useful multi-component diagnostic tools in OC. In addition, identifying a novel panel of discriminative proteins could provide a new insight into complex signaling and functional networks associated with this multifactorial disease.

Electronic supplementary material

The online version of this article (doi:10.1186/s12885-017-3467-2) contains supplementary material, which is available to authorized users.

Circulating biomarkers in epithelial ovarian cancer diagnosis: from present to future perspective

Ovarian cancer (OC) represents the most lethal gynecological cancer and the poor prognosis is often attributable to late diagnosis. The diagnostic approach to woman presenting with pelvic mass is difficult and differential diagnosis often requires invasive histological examination. Serum CA125 and HE4, as well as the most of the other serum biomarkers discovered and validated, are not sufficiently sensitive and specific to make early diagnosis. Moreover, conflicting results exist about the improvement of diagnostic performance by using multivariate index assays, developed by combining circulating biomarkers with other variables (i.e., ultrasound and/or menopausal status and/or age), in comparison to CA125 or HE4 alone. In the last years, several studies focused on the microRNAs (miRs), short single-stranded non-coding RNA that regulate several messenger RNAs (mRNAs). As in other cancer types, the aberrant miRs expression has been demonstrated in gynecological cancers, in both tissues and serum samples. In particular, the diagnostic performance of single or miRs panels resulted very high. However, to date, despite the potential clinical utility has been demonstrated, none of these miRs has been validated in large OC populations.

20(S)-Rg3 blocked epithelial-mesenchymal transition through DNMT3A/miR-145/FSCN1 in ovarian cancer

Epithelial-mesenchymal transition (EMT) is one of the key mechanisms mediating cancer progression. MicroRNAs (miRs) are essential regulators of gene expression by suppressing translation or causing degradation of target mRNA. Growing evidence illustrates the crucial roles of miRs dysregulation in cancer development and progression. Here, we have found for the first time that the ginsenoside 20(S)-Rg3, a pharmacologically active component of Panax ginseng, potently increases miR-145 expression by downregulating methyltransferase DNMT3A to attenuate the hypermethylation of the promoter region in the miR-145 precursor gene. Restoration of DNMT3A reverses the inhibitory effect of 20(S)-Rg3 on EMT. FSCN1 is verified as the target of miR-145 to suppress EMT in human ovarian cancer cells. The results from nude mouse xenograft models further demonstrate the suppressive effect of miR-145 on malignant progression of ovarian cancer. Taken together, our results show that 20(S)-Rg3 blocks EMT by targeting DNMT3A/miR-145/FSCN1 pathway in ovarian cancer cells, highlighting the potentiality of 20(S)-Rg3 to be used as a therapeutic agent for ovarian cancer.

Quantitative Profiling of Single Formalin Fixed Tumour Sections: proteomics for translational research

Although re-sequencing of gene panels and mRNA expression profiling are now firmly established in clinical laboratories, in-depth proteome analysis has remained a niche technology, better suited for studying model systems rather than challenging materials such as clinical trial samples. To address this limitation, we have developed a novel and optimized platform called SP3-Clinical Tissue Proteomics (SP3-CTP) for in-depth proteome profiling of practical quantities of tumour tissues, including formalin fixed and paraffin embedded (FFPE). Using single 10 μm scrolls of clinical tumour blocks, we performed in-depth quantitative analyses of individual sections from ovarian tumours covering the high-grade serous, clear cell, and endometrioid histotypes. This examination enabled the generation of a novel high-resolution proteome map of ovarian cancer histotypes from clinical tissues. Comparison of the obtained proteome data with large-scale genome and transcriptome analyses validated the observed proteome biology for previously validated hallmarks of this disease, and also identified novel protein features. A tissue microarray analysis validated cystathionine gamma-lyase (CTH) as a novel clear cell carcinoma feature with potential clinical relevance. In addition to providing a milestone in the understanding of ovarian cancer biology, these results show that in-depth proteomic analysis of clinically annotated FFPE materials can be effectively used as a biomarker discovery tool and perhaps ultimately as a diagnostic approach.

miR-30d Blocked Transforming Growth Factor β1-Induced Epithelial-Mesenchymal Transition by Targeting Snail in Ovarian Cancer Cells

OBJECTIVE

MicroRNAs (miRs) are essential regulators of gene expression by suppressing translation or causing degradation of target mRNA. Growing evidence sheds light on the crucial roles of miR dysregulation in cancer development and progression. In this study, we focused on the role of miR-30d in transforming growth factor β1 (TGF-β1)-initiated epithelial-mesenchymal transition (EMT) in ovarian cancer cells.

METHODS

Transforming growth factor β1 (10 ng/mL) was used to initiate EMT in SKOV3 and 3AO cells. The expression of miR-30 family members was determined by quantitative real-time polymerase chain reaction. Messenger RNA and protein levels of E-cadherin, N-cadherin, vimentin, and Snail were detected by quantitative real-time polymerase chain reaction and Western blot, respectively. Cell migration and invasion capacities were evaluated by Transwell chamber assay. Luciferase activity assay was performed to verify the direct inhibition of Snail by miR-30d.

RESULTS

MiR-30b, MiR-30c, and MiR-30d were down-regulated during TGF-β1-induced EMT in SKOV3 and 3AO ovarian cancer cells. Restoration of miR-30d by miR-30d mimic reversed TGF-β1-induced EMT phenotypes including the morphological changes, expression pattern of molecular markers (E-cadherin, N-cadherin), and migratory and invasive capabilities in ovarian cancer cells. Furthermore, Snail was identified as the direct target of miR-30d.

CONCLUSIONS

Our results revealed that miR-30d functioned as a suppressor of ovarian cancer progression by decreasing Snail expression and thus blocking TGF-β1-induced EMT process, suggesting the potentiality of miR-30d analogs to be used as therapeutics for ovarian cancer.

A proteomic signature of ovarian cancer tumor fluid identified by highthroughput and verified by targeted proteomics

Tumor fluid samples have emerged as a rich source for the identification of ovarian cancer in the context of proteomics studies. To uncover differences among benign and malignant ovarian samples, we performed a quantitative proteomic study consisting of albumin immunodepletion, isotope labeling with acrylamide and in-depth proteomic profiling by LC-MS/MS in a pool of 10 samples of each histological type. 1135 proteins were identified, corresponding to 505 gene products. 223 proteins presented associated quantification and the comparative analysis of histological types revealed 75 differentially abundant proteins. Based on this, we developed a panel for targeted proteomic analysis using the multiple reaction monitoring (MRM) method for validation of 51 proteins in individual samples of high-grade serous ovarian tumor fluids (malignant) and benign serous cystadenoma tumor fluids. This analysis showed concordant results in terms of average amounts of proteins, and APOE, SERPINF2, SERPING1, ADAM17, CD44 and OVGP1 were statistically significant between benign and malignant group. The results observed in the MRM for APOE were confirmed by western blotting, where APOE was more abundant in malignant samples. This molecular signature can contribute to improve tumor stratification and shall be investigated in combination with current biomarkers in larger cohorts to improve ovarian cancer diagnosis.

BIOLOGICAL SIGNIFICANCE

Despite advances in cancer research, ovarian cancer has a high mortality and remains a major challenge due to a number of particularities of the disease, especially late diagnosis caused by vague clinical symptoms, the cellular and molecular heterogeneity of tumors, and the lack of effective treatment. Thus, efforts are directed to better understand this neoplasia, its origin, development and, particularly the identification and validation of biomarkers for early detection of the disease in asymptomatic stage. In the present work, we confirmed by MRM method in individual ovarian tumor fluid samples the regulation of 27 proteins out of 33 identified in a highthroughput study. We speculate that the presence and/or differential abundance observed in tumor fluid is a cooperation primarily of high rates of secretion of such tumor proteins to extra tumor environment that will at the end accumulate in plasma, and also the accumulation of acute-phase proteins throughout the entire body. On top of that, consideration of physiological influences in the interpretation of expression observed, including age, menopause status, route-of-elimination kinetics and metabolism of the tumor marker, coexisting disease, hormonal imbalances, life-style influences (smoking, alcoholism, obesity), among others, are mandatory to enable the selection of good protein tumor marker candidates for extensive validation.

Highly-accurate metabolomic detection of early-stage ovarian cancer

High performance mass spectrometry was employed to interrogate the serum metabolome of early-stage ovarian cancer (OC) patients and age-matched control women. The resulting spectral features were used to establish a linear support vector machine (SVM) model of sixteen diagnostic metabolites that are able to identify early-stage OC with 100% accuracy in our patient cohort. The results provide evidence for the importance of lipid and fatty acid metabolism in OC and serve as the foundation of a clinically significant diagnostic test.