A multiplex platform for the identification of ovarian cancer biomarkers

Background

Currently, there are no FDA approved screening tools for detecting early stage ovarian cancer in the general population. Development of a biomarker-based assay for early detection would significantly improve the survival of ovarian cancer patients.

Methods

We used a multiplex approach to identify protein biomarkers for detecting early stage ovarian cancer. This new technology (Proseek^® Multiplex Oncology Plates) can simultaneously measure the expression of 92 proteins in serum based on a proximity extension assay. We analyzed serum samples from 81 women representing healthy, benign pathology, early, and advanced stage serous ovarian cancer patients.

Results

Principle component analysis and unsupervised hierarchical clustering separated patients into cancer versus non-cancer subgroups. Data from the Proseek^® plate for CA125 levels exhibited a strong correlation with current clinical assays for CA125 (correlation coefficient of 0.89, 95% CI 0.83, 0.93). CA125 and HE4 were present at very low levels in healthy controls and benign cases, while higher levels were found in early stage cases, with highest levels found in the advanced stage cases. Overall, significant trends were observed for 38 of the 92 proteins (p < 0.001), many of which are novel candidate serum biomarkers for ovarian cancer. The area under the ROC curve (AUC) for CA125 was 0.98 and the AUC for HE4 was 0.85 when comparing early stage ovarian cancer versus healthy controls. In total, 23 proteins had an estimated AUC of 0.7 or greater. Using a naïve Bayes classifier that combined 12 proteins, we improved the sensitivity corresponding to 95% specificity from 93 to 95% when compared to CA125 alone. Although small, a 2% increase would have a significant effect on the number of women correctly identified when screening a large population.

Conclusions

These data demonstrate that the Proseek^® technology can replicate the results established by conventional clinical assays for known biomarkers, identify new candidate biomarkers, and improve the sensitivity and specificity of CA125 alone. Additional studies using a larger cohort of patients will allow for validation of these biomarkers and lead to the development of a screening tool for detecting early stage ovarian cancer in the general population.

     

Identification and Confirmation of Differentially Expressed Fucosylated Glycoproteins in the Serum of Ovarian Cancer Patients Using a Lectin Array and LC-MS/MS

In order to discover potential glycoprotein biomarkers in ovarian cancer, we applied a lectin array and Exactag labeling based quantitative glycoproteomics approach. A lectin array strategy was used to detect overall lectin-specific glycosylation changes in serum proteins from patients with ovarian cancer and those with benign conditions. Lectins, which showed significant differential response for fucosylation, were used to extract glycoproteins that had been labeled using isobaric chemical tags. The glycoproteins were then identified and quantified by LC-MS/MS, and five glycoproteins were found to be differentially expressed in the serum of ovarian cancer patients compared to benign diseases. The differentially expressed glycoproteins were further confirmed by lectin-ELISA and ELISA assay. Corticosteroid-binding globulin (CBG), serum amyloid p component (SAP), complement factor B (CFAB), and histidine-rich glycoprotein (HRG) were identified as potential markers for differentiating ovarian cancer from benign diseases or healthy controls. A combination of CBG and HRG (AUC = 0.825) showed comparable performance to CA125 (AUC = 0.829) in differentiating early stage ovarian cancer from healthy controls. The combination of CBG, SAP, and CA125 showed improved performance for distinguishing stage III ovarian cancer from benign diseases compared to CA125 alone. The ability of CBG, SAP, HRG, and CFAB to differentiate the serum of ovarian cancer patients from that of controls was tested using an independent set of samples. Our findings suggest that glycoprotein modifications may be a means to identify novel diagnostic markers for detection of ovarian cancer.     

Serum Autoantibodies in Chronic Prostate Inflammation in Prostate Cancer Patients

Background

Chronic inflammation is frequently observed on histological analysis of malignant and non-malignant prostate specimens. It is a suspected supporting factor for prostate diseases and their progression and a main cause of false positive PSA tests in cancer screening. We hypothesized that inflammation induces autoantibodies, which may be useful biomarkers. We aimed to identify and validate prostate inflammation associated serum autoantibodies in prostate cancer patients and evaluate the expression of corresponding autoantigens.

Methods

Radical prostatectomy specimens of prostate cancer patients (N = 70) were classified into high and low inflammation groups according to the amount of tissue infiltrating lymphocytes. The corresponding pre-surgery blood serum samples were scrutinized for autoantibodies using a low-density protein array. Selected autoantigens were identified in prostate tissue and their expression pattern analyzed by immunohistochemistry and qPCR. The identified autoantibody profile was cross-checked in an independent sample set (N = 63) using the Luminex-bead protein array technology.

Results

Protein array screening identified 165 autoantibodies differentially abundant in the serum of high compared to low inflammation patients. The expression pattern of three corresponding antigens were established in benign and cancer tissue by immunohistochemistry and qPCR: SPAST (Spastin), STX18 (Syntaxin 18) and SPOP (speckle-type POZ protein). Of these, SPAST was significantly increased in prostate tissue with high inflammation. All three autoantigens were differentially expressed in primary and/or castration resistant prostate tumors when analyzed in an inflammation-independent tissue microarray. Cross-validation of the inflammation autoantibody profile on an independent sample set using a Luminex-bead protein array, retrieved 51 of the significantly discriminating autoantibodies. Three autoantibodies were significantly upregulated in both screens, MUT, RAB11B and CSRP2 (p>0.05), two, SPOP and ZNF671, close to statistical significance (p = 0.051 and 0.076).

Conclusions

We provide evidence of an inflammation-specific autoantibody profile and confirm the expression of corresponding autoantigens in prostate tissue. This supports evaluation of autoantibodies as non-invasive markers for prostate inflammation.     

Autoantibody signatures: progress and perspectives for early cancer detection

Becoming invasive is a crucial step in cancer development, and the early spread of tumour cells is usually undetected by current imaging technologies. In patients with cancer and no signs of overt metastases, sensitive methods have been developed to identify circulating autoantibodies and their antigen counterparts in several cancers. These technologies are often based on proteomic approaches, and recent advances in protein and antibody microarrays have greatly facilitated the discovery of new antibody biomarkers in sera from cancer patients. Interestingly, in a clinical application setting, combinations of multiple autoantibody reactivities into panel assays have recently been proposed as relevant screening tests and validated in several independent trials. In addition, autoantibody signatures seem to be particularly relevant for early detection of cancer in high-risk cancer patients. In this review, we highlight the concept that immunogenic epitopes associated with the humoural response and key pathogenic pathways elicit serum autoantibodies that can be considered as relevant cancer biomarkers. We outline the proteomic strategies employed to identify and validate their use in clinical practice for cancer screening and diagnosis. We particularly emphasize the clinical utility of autoantibody signatures in several cancers. Finally, we discuss the challenges remaining for clinical validation.     

Identification of new celiac disease autoantigens using proteomic analysis

Celiac disease is an autoimmune disorder in which gluten peptides presented by specific HLA-DQ2- and HLA-DQ8-positive antigen presenting cells elicit immune response in connective tissue of lamina propria. Immunoglobulin A (IgA) antiendomysial antibodies are specific for celiac disease and are used for screening, diagnosis and follow-up of this disease with an almost 100% sensitivity and specificity. The major target antigen of IgA antiendomysial antibodies was identified as tissue transglutaminase; nevertheless, the existence of the additional unique celiac disease-specific autoantigens is anticipated. In this study we have utilized a proteomic approach in order to search out new autoantigens recognized by serum antibodies of patients with active celiac disease. We report the detection of 11 proteins that were immunorecognized with various frequencies by sera of patients with celiac disease. Four autoantigens were identified by mass fingerprinting approach as actin, ATP synthase beta chain and two charge variants of enolase alpha. While production of IgA antibodies against actin molecules were described earlier, the existence of autoantibodies to ATP synthase beta chain and enolase alpha species in sera collected from patients with active celiac disease are described for the first time. These results are suggestive of the existence of additional celiac disease autoantigens with possible diagnostic utility.     

Autoantibody biomarker opens a new gateway for cancer diagnosis

The list of cancer markers of current interest has grown considerably, but none of the markers used in clinical work is a true tumor marker. These cancer biomarkers are based on the determination of tumor antigens. Here, we report a single method of autoantibody enzyme immunoassay (EIA) screens for a spectrum of serum tumor markers. A comparison of the autoantibody-based EIA to conventional antigen EIA kits, using receiver operating characteristic (ROC) plots, showed that the autoantibody EIA can significantly enhance the sensitivity and specificity of tumor markers. The detection of serum autoantibodies for a spectrum of serum tumor markers, as demonstrated here, suggests that most, if not all, serum cancer biomarkers produce autoantibodies. A unique autoantibody biomarker screening method, as presented here, might therefore facilitate achieving the accurate and early diagnosis of cancer.     

Toward standardized high-throughput serum diagnostics: multiplex-protein array identifies IL-8 and VEGF as serum markers for colon cancer

Development and progression of colon cancer may be related to cytokines. Cytokines with diagnostic value have been identified individually but have not been implemented into clinical praxis. Using a multiplex protein array, the authors explore a panel of cytokines simultaneously and compared its performance to carcinoembryonic antigen (CEA) and carbohydrate antigen 19-9 (CA 19-9). Serum concentrations of 12 cytokines were simultaneously determined by multiplex biochip technology in 50 colon cancer patients and 50 healthy controls. Serum levels of interleukin-8 (IL-8) and CEA were significantly higher in cancer patients than in healthy controls. Areas under the receiver operating characteristic curves (AUCs) were largest for IL-8, followed by CEA, vascular endothelial growth factor (VEGF), and CA 19-9. Analyses regarding marker combinations showed an advantage over single marker performance for CEA, VEGF, and CA 19-9 but not for IL-8. Multiplex biochip array technology represents a practical tool in cytokine and cancer research when simultaneous determination of different biomarkers is of interest. The results suggest that the assessment of IL-8, CEA, VEGF, and possibly CA 19-9 serum levels could be useful for colon cancer screening with the potential of also detecting early stage tumors. Further validation studies using these and additional markers on a multiplex array format are encouraged.     

Tumor-associated autoantibodies as diagnostic and prognostic biomarkers

In the process of tumorigenesis, normal cells are remodeled to cancer cells and protein expression patterns are changed to those of tumor cells. A newly formed tumor microenvironment elicits the immune system and, as a result, a humoral immune response takes place. Although the tumor antigens are undetectable in sera at the early stage of tumorigenesis, the nature of an antibody amplification response to antigens makes tumor-associated autoantibodies as promising early biomarkers in cancer diagnosis. Moreover, the recent development of proteomic techniques that make neo-epitopes of tumor-associated autoantigens discovered concomitantly has opened a new area of ‘immuno-proteomics’, which presents tumor-associated autoantibody signatures and confers information to redefine the process of tumorigenesis. In this article, the strategies recently used to identify and validate serum autoantibodies are outlined and tumor-associated antigens suggested until now as diagnostic/prognostic biomarkers in various tumor types are reviewed. Also, the meaning of autoantibody signatures and their clinical utility in personalized medicine are discussed. [BMB Reports 2012; 45(12): 677-685]     

Autoantibody biomarkers in the detection of cancer

By definition, tumor biomarkers are selective molecules that can distinguish between patients with cancer and controls. Serum tumor markers have been the most widely used approach for cancer detection. However, the limitations of these markers, which are based on the measurement of tumor antigens, preclude their general use in cancer screening and diagnosis. Here we give an overview of recent cancer biomarker developments based on the detection of autoantibodies produced against tumor antigens in patients' sera. This new detection method can measure the autoantibodies for a spectrum of tumor antigens in a single assay, with sensitivity and specificity exceeding those obtained using the conventional antigen determination method. Autoantibodies against serum cancer biomarkers offer a novel technology for cancer detection.     

Quantitative proteomic analysis by iTRAQ<Superscript>®</Superscript> for the identification of candidate biomarkers in ovarian cancer serum

Background

Ovarian cancer is the most lethal gynecologic malignancy, with the majority of cases diagnosed at an advanced stage when treatments are less successful. Novel serum protein markers are needed to detect ovarian cancer in its earliest stage; when detected early, survival rates are over 90%. The identification of new serum biomarkers is hindered by the presence of a small number of highly abundant proteins that comprise approximately 95% of serum total protein. In this study, we used pooled serum depleted of the most highly abundant proteins to reduce the dynamic range of proteins, and thereby enhance the identification of serum biomarkers using the quantitative proteomic method iTRAQ^®.

Results

Medium and low abundance proteins from 6 serum pools of 10 patients each from women with serous ovarian carcinoma, and 6 non-cancer control pools were labeled with isobaric tags using iTRAQ^® to determine the relative abundance of serum proteins identified by MS. A total of 220 unique proteins were identified and fourteen proteins were elevated in ovarian cancer compared to control serum pools, including several novel candidate ovarian cancer biomarkers: extracellular matrix protein-1, leucine-rich alpha-2 glycoprotein-1, lipopolysaccharide binding protein-1, and proteoglycan-4. Western immunoblotting validated the relative increases in serum protein levels for several of the proteins identified.

Conclusions

This study provides the first analysis of immunodepleted serum in combination with iTRAQ^® to measure relative protein expression in ovarian cancer patients for the pursuit of serum biomarkers. Several candidate biomarkers were identified which warrant further development.

     

Systematic evaluation of candidate blood markers for detecting ovarian cancer

Background

Epithelial ovarian cancer is a significant cause of mortality both in the United States and worldwide, due largely to the high proportion of cases that present at a late stage, when survival is extremely poor. Early detection of epithelial ovarian cancer, and of the serous subtype in particular, is a promising strategy for saving lives. The low prevalence of ovarian cancer makes the development of an adequately sensitive and specific test based on blood markers very challenging. We evaluated the performance of a set of candidate blood markers and combinations of these markers in detecting serous ovarian cancer.

Methods and Findings

We selected 14 candidate blood markers of serous ovarian cancer for which assays were available to measure their levels in serum or plasma, based on our analysis of global gene expression data and on literature searches. We evaluated the performance of these candidate markers individually and in combination by measuring them in overlapping sets of serum (or plasma) samples from women with clinically detectable ovarian cancer and women without ovarian cancer. Based on sensitivity at high specificity, we determined that 4 of the 14 candidate markers-MUC16, WFDC2, MSLN and MMP7-warrant further evaluation in precious serum specimens collected months to years prior to clinical diagnosis to assess their utility in early detection. We also reported differences in the performance of these candidate blood markers across histological types of epithelial ovarian cancer.

Conclusions

By systematically analyzing the performance of candidate blood markers of ovarian cancer in distinguishing women with clinically apparent ovarian cancer from women without ovarian cancer, we identified a set of serum markers with adequate performance to warrant testing for their ability to identify ovarian cancer months to years prior to clinical diagnosis. We argued for the importance of sensitivity at high specificity and of magnitude of difference in marker levels between cases and controls as performance metrics and demonstrated the importance of stratifying analyses by histological type of ovarian cancer. Also, we discussed the limitations of studies (like this one) that use samples obtained from symptomatic women to assess potential utility in detection of disease months to years prior to clinical detection.     

REG4 Is Highly Expressed in Mucinous Ovarian Cancer: A Potential Novel Serum Biomarker

Preoperative diagnostics of ovarian neoplasms rely on ultrasound imaging and the serum biomarkers CA125 and HE4. However, these markers may be elevated in non-neoplastic conditions and may fail to identify most non-serous epithelial cancer subtypes. The objective of this study was to identify histotype-specific serum biomarkers for mucinous ovarian cancer. The candidate genes with mucinous histotype specific expression profile were identified from publicly available gene-expression databases and further in silico data mining was performed utilizing the MediSapiens database. Candidate biomarker validation was done using qRT-PCR, western blotting and immunohistochemical staining of tumor tissue microarrays. The expression level of the candidate gene in serum was compared to the serum CA125 and HE4 levels in a patient cohort of prospectively collected advanced ovarian cancer. Database searches identified REG4 as a potential biomarker with specificity for the mucinous ovarian cancer subtype. The specific expression within epithelial ovarian tumors was further confirmed by mRNA analysis. Immunohistochemical staining of ovarian tumor tissue arrays showed distinctive cytoplasmic expression pattern only in mucinous carcinomas and suggested differential expression between benign and malignant mucinous neoplasms. Finally, an ELISA based serum biomarker assay demonstrated increased expression only in patients with mucinous ovarian cancer. This study identifies REG4 as a potential serum biomarker for histotype-specific detection of mucinous ovarian cancer and suggests serum REG4 measurement as a non-invasive diagnostic tool for postoperative follow-up of patients with mucinous ovarian cancer.     

The alpha 5 chain of type IV collagen is the target of IgG autoantibodies in a novel autoimmune disease with subepidermal blisters and renal insufficiency

We describe a novel autoimmune disease characterized by severe subepidermal bullous eruptions and renal insufficiency with IgG autoantibodies directed against the NC1 domain of the alpha5(IV) collagen chain. In vivo deposits of IgG and C3 were found along the dermal-epidermal junction of skin lesions. The identity of the target antigen was determined by immunochemical analyses of candidate antigens using the patients' autoantibodies. The patients' IgG autoantibodies reacted with a 185-kDa polypeptide that was distinguished from the known autoantigens of the extracellular matrix including type XVII collagen, type VII collagen, or the alpha3, beta3, and gamma2 chains of laminin 5. Preincubation of the serum with recombinant alpha5(IV)NC1 domain of type IV collagen abolished immunoreactivity with the 185-kDa antigen. The serum reacted specifically with the alpha5(IV)NC1, among the six NC1 domains of type IV collagen, by Western blot and enzyme-linked immunosorbent assay analyses. The patients' autoantibodies reacted with normal skin and renal glomerulus but not with skin and glomerulus of a patient with Alport syndrome in which the basement membranes are devoid of the alpha5(IV) collagen chain. This study provided for the first time unambiguous evidence for the alpha5(IV) collagen chain as the target antigen in a novel autoimmune disease characterized by skin and renal involvement.     

Proteomic surveillance of autoantigens in relapsing polychondritis

Relapsing polychondritis (RP) is a systemic inflammatory disease, in which autoimmunity to cartilage-related components is thought to be involved in its pathogenesis. However, the autoimmune profile in RP has not been studied fully. We therefore investigated autoantibodies/autoantigens in RP comprehensively, by 2-dimensional electrophoresis (2DE), subsequent western blotting (WB) and mass spectrometry, using cell-extracted proteins as the antigen source. As a result, we detected 15 autoantigens on 2DE-WB, and further identified five of them. On average, one RP serum recognized approximately 8 out of the 15 autoantigens. Frequencies of the autoantibodies to the 5 identified antigens of tubulin alpha ubiquitous/6, vimentin, alpha enolase, calreticulin, and colligin-1/-2 were 91%, 46%, 36%, 82%, and 36%, respectively. ELISA using recombinant proteins for them revealed that frequencies of the autoantibodies to tubulin alpha ubiquitous, vimentin, alpha enolase, calreticulin, and colligin-1 were 36%, 64%, 46%, 27%, and 18%, respectively. Our data demonstrated that the autoimmune reaction was not restricted to cartilagerelated components, rather a variety of autoimmune responses occurred in patients with RP, which may be involved in the pathophysiology of RP. In addition, the proteomic approach using cell-extracted proteins would be a powerful way to investigate autoantigens.     

Identification of biomarkers for colorectal cancer through proteomics-based approaches

The early detection of colorectal cancer is one of the great challenges in the battle against this disease. However, owing to its heterogeneous character, single markers are not likely to provide sufficient diagnostic power to be used in colorectal cancer population screens. This review provides an overview of recent studies aimed at the discovery of new diagnostic protein markers through proteomics-based approaches. It indicates that studies that start with the proteomic analysis of tumor tissue or tumor cell lines (near the source) have a high potential to yield novel and colorectal cancer-specific biomarkers. In the next step, the diagnostic accuracy of these candidate markers can be assessed by a targeted ELISA assay using serum from colorectal cancer patients and healthy controls. Instead, direct proteomic analysis of serum yields predominantly secondary markers composed of fragments of abundant serum proteins that may be associated with tumor-associated protease activity, and alternatively, immunoproteomic analysis of the serum antibody repertoire provides a valuable tool to identify the molecular imprint of colorectal cancer-associated antigens directly from patient serum samples. The latter approach also allows a relatively easy translation into targeted assays. Eventually, multimarker assays should be developed to reach a diagnostic accuracy that meets the stringent criteria for colorectal cancer screening at the population level.     

Protein arrays as tools for serum autoantibody marker discovery in cancer

Protein array technology has begun to play a significant role in the study of protein–protein interactions and in the identification of antigenic targets of serum autoantibodies in a variety of autoimmune disorders. More recently, this technology has been applied to the identification of autoantibody signatures in cancer.The identification of tumour-associated antigens (TAAs) recognised by the patient's immune response represents an exciting approach to identify novel diagnostic cancer biomarkers and may contribute towards a better understanding of the molecular mechanisms involved. Circulating autoantibodies have not only been used to identify TAAs as diagnostic/prognostic markers and potential therapeutic targets, they also represent excellent biomarkers for the early detection of tumours and potential markers for monitoring the efficacy of treatment. Protein array technology offers the ability to screen the humoral immune response in cancer against thousands of proteins in a high throughput technique, thus readily identifying new panels of TAAs. Such an approach should not only aid in improved diagnostics, but has already contributed to the identification of complex autoantibody signatures that may represent disease subgroups, early diagnostics and facilitated the analysis of vaccine trials.     

Progress and challenges in screening for early detection of ovarian cancer

Ovarian cancer is characterize by few early symptoms, presentation at an advanced stage, and poor survival. As a result, it is the most frequent cause of death from gynecological cancer. During the last decade, a research effort has been directed toward improving outcomes for ovarian cancer by screening for preclinical, early stage disease using both imaging techniques and serum markers. Numerous biomarkers have shown potential in samples from clinically diagnosed ovarian cancer patients, but few have been thoroughly assessed in preclinical disease and screening. The most thoroughly investigated biomarker in ovarian cancer screening is CA125. Prospective studies have demonstrated that both CA125 and transvaginal ultrasound can detect a significant proportion of preclinical ovarian cancers, and refinements in interpretation of results have improved sensitivity and reduced the false-positive rate of screening. There is preliminary evidence that screening can improve survival, but the impact of screening on mortality from ovarian cancer is still unclear. Prospective studies of screening are in progress in both the general population and high-risk population, including the United Kingdom Collaborative Trial of Ovarian Cancer Screening (UKCTOCS), a randomized trial involving 200,000 postmenopausal women designed to document the impact of screening on mortality. Recent advances in technology for the study of the serum proteome offer exciting opportunities for the identification of novel biomarkers or patterns of markers that will have greater sensitivity and lead time for preclinical disease than CA125. Considerable interest and controversy has been generated by initial results utilizing surface-enhanced laser desorption/ionization (SELDI) in ovarian cancer. There are challenging issues related to the design of studies to evaluate SELDI and other proteomic technology, as well as the reproducibility, sensitivity, and specificity of this new technology. Large serum banks such as that assembled in UKCTOCS, which contain preclinical samples from patients who later developed ovarian cancer and other disorders, provide a unique resource for carefully designed studies of proteomic technology. There is a sound basis for optimism that further developments in serum proteomic analysis will provide powerful methods for screening in ovarian cancer and many other diseases.     

Shared immunoproteome for ovarian cancer diagnostics and immunotherapy: potential theranostic approach to cancer

Elimination of cancer through early detection and treatment is the ultimate goal of cancer research and is especially critical for ovarian and other forms of cancer typically diagnosed at very late stages that have very poor response rates. Proteomics has opened new avenues for the discovery of diagnostic and therapeutic targets. Immunoproteomics, which defines the subset of proteins involved in the immune response, holds considerable promise for providing a better understanding of the early-stage immune response to cancer as well as important insights into antigens that may be suitable for immunotherapy. Early administration of immunotherapeutic vaccines can potentially have profound effects on prevention of metastasis and may potentially cure through efficient and complete tumor elimination. We developed a mass-spectrometry-based method to identify novel autoantibody-based serum biomarkers for the early diagnosis of ovarian cancer that uses native tumor-associated proteins immunoprecipitated by autoantibodies from sera obtained from cancer patients and from cancer-free controls to identify autoantibody signatures that occur at high frequency only in cancer patient sera. Interestingly, we identified a subset of more than 50 autoantigens that were also processed and presented by MHC class I molecules on the surfaces of ovarian cancer cells and thus were common to the two immunological processes of humoral and cell-mediated immunity. These shared autoantigens were highly representative of families of proteins with roles in key processes in carcinogenesis and metastasis, such as cell cycle regulation, cell proliferation, apoptosis, tumor suppression, and cell adhesion. Autoantibodies appearing at the early stages of cancer suggest that this detectable immune response to the developing tumor can be exploited as early-stage biomarkers for the development of ovarian cancer diagnostics. Correspondingly, because the T-cell immune response depends on MHC class I processing and presentation of peptides, proteins that go through this pathway are potential candidates for the development of immunotherapeutics designed to activate a T-cell immune response to cancer. To the best of our knowledge, this is the first comprehensive study that identifies and categorizes proteins that are involved in both humoral and cell-mediated immunity against ovarian cancer, and it may have broad implications for the discovery and selection of theranostic molecular targets for cancer therapeutics and diagnostics in general.     

Genome-scale screen for DNA methylation-based detection markers for ovarian cancer

Background

The identification of sensitive biomarkers for the detection of ovarian cancer is of high clinical relevance for early detection and/or monitoring of disease recurrence. We developed a systematic multi-step biomarker discovery and verification strategy to identify candidate DNA methylation markers for the blood-based detection of ovarian cancer.

Methodology/Principal Findings

We used the Illumina Infinium platform to analyze the DNA methylation status of 27,578 CpG sites in 41 ovarian tumors. We employed a marker selection strategy that emphasized sensitivity by requiring consistency of methylation across tumors, while achieving specificity by excluding markers with methylation in control leukocyte or serum DNA. Our verification strategy involved testing the ability of identified markers to monitor disease burden in serially collected serum samples from ovarian cancer patients who had undergone surgical tumor resection compared to CA-125 levels.We identified one marker, IFFO1 promoter methylation (IFFO1-M), that is frequently methylated in ovarian tumors and that is rarely detected in the blood of normal controls. When tested in 127 serially collected sera from ovarian cancer patients, IFFO1-M showed post-resection kinetics significantly correlated with serum CA-125 measurements in six out of 16 patients.

Conclusions/Significance

We implemented an effective marker screening and verification strategy, leading to the identification of IFFO1-M as a blood-based candidate marker for sensitive detection of ovarian cancer. Serum levels of IFFO1-M displayed post-resection kinetics consistent with a reflection of disease burden. We anticipate that IFFO1-M and other candidate markers emerging from this marker development pipeline may provide disease detection capabilities that complement existing biomarkers.