Predictive and prognostic protein biomarkers in epithelial ovarian cancer: recommendation for future studies

Trefoil factor family proteins as potential diagnostic markers for mucinous invasive ovarian carcinoma

Introduction

Ovarian cancer (OC) is the leading cause of gynecological cancer-related death. Of the main OC histologic subtypes, invasive mucinous carcinomas (MC) account for only 3% of OC cases and are frequently associated with favorable prognosis. Nevertheless, MCs differ greatly from the other OC histotypes in clinical, pathological, and biological behavior. However, the origin and molecular pathogenesis of MC are not yet fully understood. Therefore, identification of novel diagnostic markers could potentially facilitate early diagnosis of OC, particularly the MC histotype, thereby leading to the development of histotype-specific treatment regimens and improved survival rates.

Methods

In the present study, Trefoil factor gene family members (TFF1, TFF2 and TFF3) were identified as MC histotype-specific biomarkers using RNA sequencing (RNA-seq) data for 95 stage I-II OCs. The diagnostic value of TFF1, TFF2 and TFF3 was then evaluated by immunohistochemistry on 206 stage I-II OCs stratified by histotype (high-grade serous carcinoma [HGSC], endometrioid carcinoma [EC], clear cell carcinoma [CCC], and MC).

Results

We showed significantly elevated intracytoplasmic protein expression levels for TFF1, TFF2 and TFF3 in MC samples, thereby revealing an association between expression of Trefoil factor gene family members and the MC histotype. Taken together, these findings suggest that the TFF proteins may play a pivotal role in tumor initiation and progression for the MC histotype.

Conclusion

Taken together, these findings suggest that the TFF proteins may play a pivotal role in tumor initiation and progression for the MC histotype. Moreover, these novel histotype-specific diagnostic biomarkers may not only improve patient stratification of early-stage ovarian carcinomas but may also be candidates for the development of molecular targeted therapies.

Copy Number Variation of Circulating Tumor DNA (ctDNA) Detected Using NIPT in Neoadjuvant Chemotherapy-Treated Ovarian Cancer Patients

Analysis of circulating tumor DNA (ctDNA) can be used to characterize and monitor cancers. Recently, non-invasive prenatal testing (NIPT) as a new next-generation sequencing (NGS)-based approach has been applied for detecting ctDNA. This study aimed to investigate the copy number variations (CNVs) utilizing the non-invasive prenatal testing in plasma ctDNA from ovarian cancer (OC) patients who were treated with neoadjuvant chemotherapy (NAC). The plasma samples of six patients, including stages II–IV, were collected during the pre- and post-NAC treatment that were divided into NAC-sensitive and NAC-resistant groups during the follow-up time. CNV analysis was performed using the NIPT via two methods “an open-source algorithm WISECONDORX and NextGENe software.” Results of these methods were compared in pre- and post-NAC of OC patients. Finally, bioinformatics tools were used for data mining from The Cancer Genome Atlas (TCGA) to investigate CNVs in OC patients. WISECONDORX analysis indicated fewer CNV changes on chromosomes before treatment in the NAC-sensitive rather than NAC-resistant patients. NextGENe data indicated that CNVs are not only observed in the coding genes but also in non-coding genes. CNVs in six genes were identified, including HSF1, TMEM249, MROH1, GSTT2B, ABR, and NOMO2, only in NAC-resistant patients. The comparison of these six genes in NAC-resistant patients with The Cancer Genome Atlas data illustrated that the total alteration frequency is amplification, and the highest incidence of the CNVs (≥35% based on TCGA data) is found in MROH1, TMEM249, and HSF1 genes on the chromosome (Chr) 8. Based on TCGA data, survival analysis showed a significant reduction in the overall survival among chemotherapy-resistant patients as well as a high expression level of these three genes compared to that of sensitive samples (all, p < 0.0001). The continued Chr8 study using WISECONDORX revealed CNV modifications in NAC-resistant patients prior to NAC therapy, but no CNV changes were observed in NAC-sensitive individuals. Our findings showed that low coverage whole-genome sequencing analysis used for NIPT could identify CNVs in ctDNA of OC patients before and after chemotherapy. These CNVs are different in NAC-sensitive and -resistant patients highlighting the potential application of this approach in cancer patient management.

High Expression of PARP1 in Tumor and Stroma Cells Predicts Different Prognosis and Platinum Resistance in Patients With Advanced Epithelial Ovarian Cancer

Objective

This study aimed to explore the roles of PARP1 mRNA and protein expression in platinum resistance and prognosis of EOC patients, and reveal the different roles of PARP1 protein in epithelial tumor and stroma cells.

Methods

The PARP1 mRNA expression of the EOC tissues was examined by RT-qPCR. The impacts of PARP1 expression on prognosis were measured by Kaplan-Meier and Cox regression. Receiver operating characteristic (ROC) curve analysis was employed for calculating the diagnostic value of PARP1 on platinum resistance. The microarray of formalin-fixed, paraffin-embedded (FFPE) tissues was processed for multiplex immunofluorescence to detect the protein levels of PARP1 and cytokeratin (CK).

Results

The PARP1mRNA expression of EOC patients was higher in the platinum-resistant group compared with the sensitive group (P<0.01). Kaplan-Meier analysis demonstrated that high PARP1 mRNA expression was associated with poor survival of EOC patients. In Cox regression analyses, high PARP1 mRNA expression independently predicted poor prognosis (P=0.001, HR=2.076, 95%CI=1.373-3.140). The area under the ROC curve of PARP1 mRNA for predicting the platinum resistance in EOC patients was 0.649, with a sensitivity of 0.607 and specificity of 0.668. Furthermore, the protein expression of PARP1 was higher in the platinum-resistant group than in the sensitive group (P<0.01) and associated with a worse prognosis. Additionally, according to CK labeling, we observed that enhanced expression of PARP1 in the CK+ region was associated with platinum resistance and lower survival, but in CK- region, it predicted a good prognosis and platinum sensitivity.

Conclusion

PARP1 may be a potential biomarker to predict platinum resistance and prognosis for EOC patients, exerting different roles on epithelial tumor and stromal cells.

The Anterior GRadient (AGR) family proteins in epithelial ovarian cancer

Epithelial ovarian cancer (EOC) is the most common gynecologic disorder. Even with the recent progresses made towards the use of new therapeutics, it still represents the most lethal gynecologic malignancy in women from developed countries.

The discovery of the anterior gradient proteins AGR2 and AGR3, which are highly related members belonging to the protein disulfide isomerase (PDI) family, attracted researchers’ attention due to their putative involvement in adenocarcinoma development. This review compiles the current knowledge on the role of the AGR family and the expression of its members in EOC and discusses the potential clinical relevance of AGR2 and AGR3 for EOC diagnosis, prognosis, and therapeutics.

A better understanding of the role of the AGR family may thus provide new handling avenues for EOC patients.

Characterization of stem cell and cancer stem cell populations in ovary and ovarian tumors

Background

Ovarian cancer is a complicated malady associated with cancer stem cells (CSCs) contributing to 238,700 estimated new cases and 151,900 deaths per year, worldwide. CSCs comprise a tiny fraction of tumor-bulk responsible for cancer recurrence and eventual mortality. CSCs or tumor initiating cells are responsible for self-renewal, differentiation and proliferative potential, tumor initiation capability, its progression, drug resistance and metastatic spread. Although several biomarkers are implicated in these processes, their distribution within the ovary and association with single cell type has neither been established nor demonstrated across ovarian tumor developmental stages. Therefore, precise identification, thorough characterization and effective targeted destruction of dormant and highly proliferating potent CSC populations is an immediate need.

Results

In view of this, distribution of various CSC (ALDH1/2, C-KIT, CD133, CD24 and CD44) and cell proliferation (KI67) specific markers in the ovarian surface epithelium (OSE) and cortex regions in normal ovary, and benign, borderline and high grade metastatic ovarian tumors by immuno-histochemistry and confocal microscopy was studied. We further confirmed their expression by RT-PCR analysis. Co-expression analysis of stem cell (OCT4, SSEA4) and CSC (ALDH1/2, CD44 and LGR5) markers with proliferation marker (KI67) in HG tumors revealed dual positive proliferating stem and CSCs, few non-proliferating stem/CSC (SSEA4⁺/KI67⁻ and ALDH1/2⁺/KI67⁻) and only KI67⁺ cells in cortex, signifying dynamic populations and interesting cellular hierarchy in cortex region. Smaller spherical (≤ 5 μm) and larger spindle/elliptical shaped (~ 10 μm) cell populations with high nucleo-cytoplasmic ratio were detected across all samples (including normal ovaries) but with variable distribution and characteristic stage-wise marker expression across different tumor stages.

Conclusions

Diverse stem and CSC populations expressing characteristic markers revealing distinct phenotypes (spherical ≤5 μm and spindle/elliptical ~ 10 μm) were distributed within different tumor stages studied signifying dynamic and probable functional hierarchy within these cell types. Involvement of extra-ovarian sites of origin of stem and CSCs requires rigorous evaluation. Quantitative analysis of potent CSC populations, their mechanisms and pathways for self-renewal, chemo-resistance, metastatic spread etc. with respect to various markers studied, will provide better insights and targets for developing effective therapeutics to prevent metastasis and eventually help improve patient mortality.

Electronic supplementary material

The online version of this article (10.1186/s13048-018-0439-3) contains supplementary material, which is available to authorized users.

Transcription factors WT1 and p53 combined: a prognostic biomarker in ovarian cancer

Background

New approaches to ovarian cancer are needed to improve survival. Wilms’ tumour 1 (WT1) is a tumour-associated antigen expressed in many ovarian cancers. P53 is also often altered. The clinical significance of the combined expression of these two transcription factors has not been studied.

Methods

One hundred ninety-six ovarian tumours were classified histopathologically. Tumours were stained for WT1 and p53 immunohistochemically. Stains were analysed according to tumour type, grade and FIGO stage. Kaplan–Meier analyses on 96 invasive carcinomas determined whether categorical variables were related to survival.

Results

WT1 and p53 were related to ovarian tumour type, grade, FIGO stage and patient survival. Uniform nuclear p53 expression was associated with invasion and WT1 expression was associated with advanced grade, FIGO stage and poor survival. When WT1 and p53 were both in the age-adjusted Cox model, WT1 was significant while p53 was not. When we combined tumours expressing WT1 and p53, then adjusted for age and tumour subtype, the hazard ratio compared to tumours without WT1 and with normal p53 was 2.70; when adjusted for age and FIGO stage, the hazard ratio was 2.40.

Conclusions

WT1, an antigen target, is a biomarker for poor prognosis, particularly when combined with altered p53.

Cancer molecular markers: A guide to cancer detection and management

Cancer is generally caused by the molecular alterations which lead to specific mutations. Advances in molecular biology have provided an impetus to the study of cancers with valuable prognostic and predictive significance. Over the hindsight various attempts have been undertaken by scientists worldwide, in the management of cancer; where, we have witnessed a number of molecular markers which allow the early detection of cancers and lead to a decrease in its mortality rate. Recent advances in oncology have led to the discovery of cancer markers that has allowed early detection and targeted therapy of tumors. In this context, current review provides a detail outlook on various molecular markers for diagnosis, prognosis and management of therapeutic response in cancer patients.

A comparison of p53 and WT1 immunohistochemical expression patterns in tubo-ovarian high-grade serous carcinoma before and after neoadjuvant chemotherapy

AIMS

The treatment of patients with tubo-ovarian high-grade serous carcinoma (HGSC) is increasingly based on diagnosis on small biopsy samples, and the first surgical sample is often taken post-chemotherapy. p53 and WT1 are important diagnostic markers for HGSC. The effect of neoadjuvant chemotherapy on p53 and WT1 expression has not been widely studied. We aimed to compare p53 and WT1 expression in paired pre-chemotherapy and post-chemotherapy samples of HGSC.

METHODS AND RESULTS

Immunohistochemistry (IHC) was carried out for p53 and WT1 on paired omental HGSC samples pre-chemotherapy and post-chemotherapy. p53 IHC was recorded as normal (wild-type) or abnormal (mutation-type), and was further classified as overexpression, complete absence, or cytoplasmic. WT1 IHC was classified as positive or negative. A subset of cases were further assessed for the extent of nuclear immunoreactivity of WT1 by use of the H-score. Fifty-seven paired samples were stained with p53. Fifty-six of 57 (98%) cases showed mutation-type p53 staining. Pre-chemotherapy and post-chemotherapy IHC results were concordant in 55 of 57 (96%) cases. For WT1, pre-chemotherapy and post-chemotherapy IHC results were concordant in 56 of 58 (97%) cases. In 23 paired WT1 cases, the mean post-treatment H-score decreased from 227 [range 20-298, standard deviation (SD) 64] to 151 (range 0-288, SD 78) (P = 0.0008).

CONCLUSIONS

Immunohistochemical expression of p53 (abnormal/mutation-type pattern) and WT1 in HGSC is almost universal and is largely concordant before and after chemotherapy. This finding underscores the reliability of these diagnostic markers in small samples and in surgical samples following neoadjuvant chemotherapy, with very few exceptions. A novel finding was the significant diminution in intensity of WT1 staining following chemotherapy.

Tissue and plasma levels of galectins in patients with high grade serous ovarian carcinoma as new predictive biomarkers

Galectins are moving closer to center stage in detecting glycosylation aberration in cancer cells. Here, we have investigated the expression of galectins in ovarian cancer (OC) and examined their potential as biomarkers in tissues and blood plasma samples of high grade serous ovarian carcinoma (HGSC) patients. In tissues, we found that increased protein expression of stromal gal-1 and epithelial gal-8/9 was associated with a poor response to treatment of HGSC patients. Gal-8/9 were both independent predictors of chemoresistance and overall survival (OS), respectively. This galectin signature increased the predictive value of the cancer antigen 125 (CA125) on 5-year disease-free survival (DFS), post-chemotherapy treatment and 5-year OS. In CA125^LOW patients, epithelial gal-9 was associated with a lower 5-year OS while stromal gal-1 and epithelial gal-8 were both associated with a lower 5-year DFS. Such negative predictive value of gal-8 and gal-9 was also found using plasma samples. In both cases, high plasma levels of gal-8 and gal-9 was associated with a lower OS and DFS. Overall, these data suggest that galectins may be promising biomarkers to identify subgroups of HGSC patients with poorer prognosis. Our study also contributes to better define the heterogeneity of the disease.

The relationship of the angiogenesis regulators VEGF-A, VEGF-R1 and VEGF-R2 to p53 status and prognostic factors in epithelial ovarian carcinoma in FIGO-stages I-II

The aim of this study was to evaluate prognostic effect of the angiogenesis regulators VEGF-R1, VEGF-R2 and VEGF-A for recurrent disease and disease-free survival (DFS), and their relation to the apoptosis regulator p53, in 131 patients with FIGO-stages I-II with epithelial ovarian cancer. For the detection of positivity of the markers the techniques of tissue microarrays and immunohistochemistry (IHC) were used. In tumors the frequency of positive staining for VEGF-R1 was 19%, for VEGF-R2 and VEGF-A, it was 77 and 70%, respectively. Positivity for p53 was detected in 25% of tumors. The total number of recurrences in the complete series was 34 out of 131 (26%) and 5-year disease-free survival (DFS) was 68%. Positive staining for VEGF-A (P=0.030), VEGF-R2 (P=0.011) and p53 (P=0.015) was found more frequently in type II tumors than in type I tumors. Patients with VEGF-R1 negative tumors had worse (P=0.021) DFS compared to patients with VEGF-R1 positive tumors. In two multivariate Cox analyzes with DFS as endpoint, FIGO-stage (HR=3.8), VEGF-R2 status (HR=0.4) and p53 status (HR=2.3), all were significant and independent prognostic factors. When the variables VEGF-R2 and p53 were replaced with the new variable VEGF-R2+p53-/other three combinations in one group, it was found that patients from that subgroup had 86% reduced risk of dying in disease (HR=0.24). Findings above, confirmed relationship between VEGF-R2 and VEGF-A and p53, respectively, with regard to recurrent disease and survival. Some findings from the present study are different from results from previous studies on the regulation of angiogenesis. Despite many trials with anti-angiogenic agents in the front line of ovarian cancer have shown to be positive for progression-free survival, no one has demonstrated an impact on overall survival. Therefore, one of the greatest challenges in ovarian cancer research, is to discover predictive and prognostic biomarkers.

Lesser-Known Molecules in Ovarian Carcinogenesis

Currently, the deciphering of the signaling pathways brings about new advances in the understanding of the pathogenic mechanism of ovarian carcinogenesis, which is based on the interaction of several molecules with different biochemical structure that, consequently, intervene in cell metabolism, through their role as regulators in proliferation, differentiation, and cell death. Given that the ensemble of biomarkers in OC includes more than 50 molecules the interest of the researchers focuses on the possible validation of each one's potential as prognosis markers and/or therapeutic targets. Within this framework, this review presents three protein molecules: ALCAM, c-FLIP, and caveolin, motivated by the perspectives provided through the current limited knowledge on their role in ovarian carcinogenesis and on their potential as prognosis factors. Their structural stability, once altered, triggers the initiation of the sequences characteristic for ovarian carcinogenesis, through their role as modulators for several signaling pathways, contributing to the disruption of cellular junctions, disturbance of pro-/antiapoptotic equilibrium, and alteration of transmission of the signals specific for the molecular pathways. For each molecule, the text is built as follows: (i) general remarks, (ii) structural details, and (iii) particularities in expression, from different tumors to landmarks in ovarian carcinoma.

Management of hepatocellular carcinoma: Predictive value of immunohistochemical markers for postoperative survival

Hepatocellular carcinoma (HCC) accounts for over 90% of all primary liver cancers. With an ever increasing incidence trend year by year, it has become the third most common cause of death from cancer worldwide. Hepatic resection is generally considered to be one of the most effective therapies for HCC patients, however, there is a high risk of recurrence in postoperative HCC. In clinical practice, there exists an urgent need for valid prognostic markers to identify patients with prognosis, hence the importance of studies on prognostic markers in improving the prediction of HCC prognosis. This review focuses on the most promising immunohistochemical prognostic markers in predicting the postoperative survival of HCC patients.

Expression of the MT1 melatonin receptor in ovarian cancer cells

Ovarian cancer (OC) is the leading cause of death among women with genital tract disorders. Melatonin exhibits oncostatic properties which it may effect through binding to its membrane receptor, MT1. The aim of this study was to determine the expression of MT1 in OC cells and to correlate this with clinical and pathological data. Immunohistochemistry was performed on 84 cases of OC. Normal ovarian epithelial (IOSE 364) and OC (SK-OV-3, OVCAR-3) cell lines were used to examine the MT1 expression at protein level using the western blot and immunofluorescence technique. The expression of MT1 was observed as cytoplasmic-membrane (MT1_CM) and membrane (MT1_M) reactions. A positive correlation between MT1_CM and MT1_M was found in all the studied cases. There were no significant differences between the expression of MT1_CM, MT1_M, and histological type, staging, grading, presence of residual disease, or overall survival time. Immunofluorescence showed both MT1_M and MT1_CM expression in all the tested cell lines. Western blot illustrated the highest protein level of MT1 in IOSE 364 and the lowest in the OVCAR-3. The results indicate the limited prognostic significance of MT1 in OC cells.

Recent Advancements in Prognostic Factors of Epithelial Ovarian Carcinoma

Ovarian cancer remains the most common cause of gynecologic cancer-related death among women in developed countries. Nevertheless, subgroups of ovarian cancer patients experience relatively longer survival. Efforts to identify prognostic factors that characterize such patients are ongoing, with investigational areas including tumor characteristics, surgical management, inheritance patterns, immunologic factors, and genomic patterns. This review discusses various demographic, clinical, and molecular factors implicating longevity and ovarian cancer survival. Continued efforts at identifying these prognosticators may result in invaluable adjuncts to the treatment of ovarian cancer, with the ultimate goal of advancing patient care.

OvMark: a user-friendly system for the identification of prognostic biomarkers in publically available ovarian cancer gene expression datasets

BACKGROUND

Ovarian cancer has the lowest survival rate of all gynaecologic cancers and is characterised by a lack of early symptoms and frequent late stage diagnosis. There is a paucity of robust molecular markers that are independent of and complementary to clinical parameters such as disease stage and tumour grade.

METHODS

We have developed a user-friendly, web-based system to evaluate the association of genes/miRNAs with outcome in ovarian cancer. The OvMark algorithm combines data from multiple microarray platforms (including probesets targeting miRNAs) and correlates them with clinical parameters (e.g. tumour grade, stage) and outcomes (disease free survival (DFS), overall survival). In total, OvMark combines 14 datasets from 7 different array platforms measuring the expression of ~17,000 genes and 341 miRNAs across 2,129 ovarian cancer samples.

RESULTS

To demonstrate the utility of the system we confirmed the prognostic ability of 14 genes and 2 miRNAs known to play a role in ovarian cancer. Of these genes, CXCL12 was the most significant predictor of DFS (HR = 1.42, p-value = 2.42x10-6). Surprisingly, those genes found to have the greatest correlation with outcome have not been heavily studied in ovarian cancer, or in some cases in any cancer. For instance, the three genes with the greatest association with survival are SNAI3, VWA3A and DNAH12.

CONCLUSIONS/IMPACT

OvMark is a powerful tool for examining putative gene/miRNA prognostic biomarkers in ovarian cancer (available at http://glados.ucd.ie/OvMark/index.html). The impact of this tool will be in the preliminary assessment of putative biomarkers in ovarian cancer, particularly for research groups with limited bioinformatics facilities.

Pathway modulations and epigenetic alterations in ovarian tumorbiogenesis

Cellular pathways are numerous and are highly integrated in function in the control of cellular systems. They collectively regulate cell division, proliferation, survival and apoptosis of cells and mutagenesis of key genes that control these pathways can initiate neoplastic transformations. Understanding these pathways is crucial to future therapeutic and preventive strategies of the disease. Ovarian cancers are of three major types; epithelial, germ-cell, and stromal. However, ovarian cancers of epithelial origin, arising from the mesothelium, are the predominant form. Of the subtypes of ovarian cancer, the high-grade serous tumors are fatal, with low survival rate due to late detection and poor response to treatments. Close examination of preserved ovarian tissues and in vitro studies have provided insights into the mechanistic changes occurring in cells mediated by a few key genes. This review will focus on pathways and key genes of the pathways that are mutated or have aberrant functions in the pathology of ovarian cancer. Non-genetic mechanisms that are gaining prominence in the pathology of ovarian cancer, miRNAs and epigenetics, will also be discussed in the review.

New hypothesis on pathogenesis of ovarian cancer lead to future tailored approaches

In the last decades, management of epithelial ovarian cancer (EOC) has been based on the staging system of the International Federation of Gynecology and Obstetrics (FIGO), and different classifications have been proposed for EOC that take account of grade of differentiation, histological subtype, and clinical features. However, despite taxonomic efforts, EOC appears to be not a unique disease; its subtypes differ for epidemiological and genetic risk factors, precursor lesions, patterns of spread, response to chemotherapy, and prognosis. Nevertheless, carboplatin plus paclitaxel combination represents the only standard treatment in adjuvant and advanced settings. This paper summarizes theories about the classification and origin of EOC and classical and new prognostic factors. It presents data about standard treatment and novel agents. We speculate about the possibility to create tailored therapy based on specific mutations in ovarian cancer and to personalize prevention.

Ovarian cancer: in search of better marker systems based on DNA repair defects

Ovarian cancer is the fifth most common female cancer in the Western world, and the deadliest gynecological malignancy. The overall poor prognosis for ovarian cancer patients is a consequence of aggressive biological behavior and a lack of adequate diagnostic tools for early detection. In fact, approximately 70% of all patients with epithelial ovarian cancer are diagnosed at advanced tumor stages. These facts highlight a significant clinical need for reliable and accurate detection methods for ovarian cancer, especially for patients at high risk. Because CA125 has not achieved satisfactory sensitivity and specificity in detecting ovarian cancer, numerous efforts, including those based on single and combined molecule detection and “omics” approaches, have been made to identify new biomarkers. Intriguingly, more than 10% of all ovarian cancer cases are of familial origin. BRCA1 and BRCA2 germline mutations are the most common genetic defects underlying hereditary ovarian cancer, which is why ovarian cancer risk assessment in developed countries, aside from pedigree analysis, relies on genetic testing of BRCA1 and BRCA2. Because not only BRCA1 and BRCA2 but also other susceptibility genes are tightly linked with ovarian cancer-specific DNA repair defects, another possible approach for defining susceptibility might be patient cell-based functional testing, a concept for which support came from a recent case-control study. This principle would be applicable to risk assessment and the prediction of responsiveness to conventional regimens involving platinum-based drugs and targeted therapies involving poly (ADP-ribose) polymerase (PARP) inhibitors.

Nano-enabled biomarker discovery and detection

The completion of the human genome project has led to intensified efforts toward comprehensive analysis of proteomes. New possibilities exist for efficient proteomic technologies. However, primary attention is given to the discovery of new predictive biomarker patterns. Understanding proteomes and, in particular, protein-mediated interactions underlying their complexity and diversity, is critical for the development of more reliable and robust diagnostic platforms, which are anticipated to enable personalized medicine. Of immediate relevance in this respect are those approaches that capitalize on the application of nanotechnology, which is seen as a powerful tool for the diagnosis of early-stage diseases. Here we highlight the current state of the field exemplified by recent nano-enabled technologies for biomarker discovery.