Elevation of TP53 Autoantibody Before CA125 in Preclinical Invasive Epithelial Ovarian Cancer

Sensitivity and Specificity of Selected Biomarkers and Their Combinations in the Diagnosis of Ovarian Cancer

One of the greatest challenges in modern gynecological oncology is ovarian cancer. Despite the numerous studies currently being conducted, it is still sometimes detected at late clinical stages, where the prognosis is unfavorable. One significant contributing factor is the absence of sensitive and specific parameters that could aid in early diagnosis. An ideal screening test, in view of the low incidence of ovarian cancer, should have a sensitivity of greater than 75% and a specificity of at least 99.6%. To enhance sensitivity and specificity, diagnostic panels are being created by combining individual markers. The drive to develop better screening tests for ovarian cancer focuses on modern diagnostic methods based on molecular testing, which in turn aims to find increasingly effective biomarkers. Currently, researchers' efforts are focused on the search for a complementary parameter to those most commonly used that would satisfactorily enhance the sensitivity and specificity of assays. Several biomarkers, including microRNA molecules, autoantibodies, cDNA, adipocytokines, and galectins, are currently being investigated by researchers. This article reviews recent studies comparing the sensitivity and specificity of selected parameters used alone and in combination to increase detection of ovarian cancer at an early stage.

Bayesian and deep-learning models applied to the early detection of ovarian cancer using multiple longitudinal biomarkers

BACKGROUND

Ovarian cancer is the most lethal of all gynecological cancers. Cancer Antigen 125 (CA125) is the best-performing ovarian cancer biomarker which however is still not effective as a screening test in the general population. Recent literature reports additional biomarkers with the potential to improve on CA125 for early detection when using longitudinal multimarker models.

METHODS

Our data comprised 180 controls and 44 cases with serum samples sourced from the multimodal arm of UK Collaborative Trial of Ovarian Cancer Screening (UKCTOCS). Our models were based on Bayesian change-point detection and recurrent neural networks.

RESULTS

We obtained a significantly higher performance for CA125-HE4 model using both methodologies (AUC 0.971, sensitivity 96.7% and AUC 0.987, sensitivity 96.7%) with respect to CA125 (AUC 0.949, sensitivity 90.8% and AUC 0.953, sensitivity 92.1%) for Bayesian change-point model (BCP) and recurrent neural networks (RNN) approaches, respectively. One year before diagnosis, the CA125-HE4 model also ranked as the best, whereas at 2 years before diagnosis no multimarker model outperformed CA125.

CONCLUSIONS

Our study identified and tested different combination of biomarkers using longitudinal multivariable models that outperformed CA125 alone. We showed the potential of multivariable models and candidate biomarkers to increase the detection rate of ovarian cancer.

Autoantibodies, antigen-autoantibody complexes and antigens complement CA125 for early detection of ovarian cancer

BACKGROUND

Multiple antigens, autoantibodies (AAb), and antigen-autoantibody (Ag-AAb) complexes were compared for their ability to complement CA125 for early detection of ovarian cancer.

METHODS

Twenty six biomarkers were measured in a single panel of sera from women with early stage (I-II) ovarian cancers (n = 64), late stage (III-IV) ovarian cancers (186), benign pelvic masses (200) and from healthy controls (502), and then split randomly (50:50) into a training set to identify the most promising classifier and a validation set to compare its performance to CA125 alone.

RESULTS

Eight biomarkers detected ≥ 8% of early stage cases at 98% specificity. A four-biomarker panel including CA125, HE4, HE4 Ag-AAb and osteopontin detected 75% of early stage cancers in the validation set from among healthy controls compared to 62% with CA125 alone (p = 0.003) at 98% specificity. The same panel increased sensitivity for distinguishing early-stage ovarian cancers from benign pelvic masses by 25% (p = 0.0004) at 95% specificity. From 21 autoantibody candidates, 3 AAb (anti-p53, anti-CTAG1 and annt-Il-8) detected 22% of early stage ovarian cancers, potentially lengthening lead time prior to diagnosis.

CONCLUSION

A four biomarker panel achieved greater sensitivity at the same specificity for early detection of ovarian cancer than CA125 alone.

High-Grade Serous Ovarian Cancer-A Risk Factor Puzzle and Screening Fugitive

High-grade serous ovarian cancer (HGSOC) is the most lethal tumor of the female genital tract. Despite extensive studies and the identification of some precursor lesions like serous tubal intraepithelial cancer (STIC) or the deviated mutational status of the patients (BRCA germinal mutation), the pathophysiology of HGSOC and the existence of particular risk factors is still a puzzle. Moreover, a lack of screening programs results in delayed diagnosis, which is accompanied by a secondary chemo-resistance of the tumor and usually results in a high recurrence rate after the primary therapy. Therefore, there is an urgent need to identify the substantial risk factors for both predisposed and low-risk populations of women, as well as to create an economically and clinically justified screening program. This paper reviews the classic and novel risk factors for HGSOC and methods of diagnosis and prediction, including serum biomarkers, the liquid biopsy of circulating tumor cells or circulating tumor DNA, epigenetic markers, exosomes, and genomic and proteomic biomarkers. The novel future complex approach to ovarian cancer diagnosis should be devised based on these findings, and the general outcome of such an approach is proposed and discussed in the paper.

Amyloid-like p53 as prognostic biomarker in serous ovarian cancer-a study of the OVCAD consortium

TP53 is the most commonly mutated gene in cancer and has been shown to form amyloid-like aggregates, similar to key proteins in neurodegenerative diseases. Nonetheless, the clinical implications of p53 aggregation remain unclear. Here, we investigated the presence and clinical relevance of p53 aggregates in serous ovarian cancer (OC). Using the p53-Seprion-ELISA, p53 aggregates were detected in 46 out of 81 patients, with a detection rate of 84.3% in patients with missense mutations. High p53 aggregation was associated with prolonged progression-free survival. We found associations of overall survival with p53 aggregates, but they did not reach statistical significance. Interestingly, p53 aggregation was significantly associated with elevated levels of p53 autoantibodies and increased apoptosis, suggesting that high levels of p53 aggregates may trigger an immune response and/or exert a cytotoxic effect. To conclude, for the first time, we demonstrated that p53 aggregates are an independent prognostic marker in serous OC. P53-targeted therapies based on the amount of these aggregates may improve the patient's prognosis.

Molecular Management of High-Grade Serous Ovarian Carcinoma

High-grade serous ovarian carcinoma (HGSOC) represents the most common form of epithelial ovarian carcinoma. The absence of specific symptoms leads to late-stage diagnosis, making HGSOC one of the gynecological cancers with the worst prognosis. The cellular origin of HGSOC and the role of reproductive hormones, genetic traits (such as alterations in P53 and DNA-repair mechanisms), chromosomal instability, or dysregulation of crucial signaling pathways have been considered when evaluating prognosis and response to therapy in HGSOC patients. However, the detection of HGSOC is still based on traditional methods such as carbohydrate antigen 125 (CA125) detection and ultrasound, and the combined use of these methods has yet to support significant reductions in overall mortality rates. The current paradigm for HGSOC management has moved towards early diagnosis via the non-invasive detection of molecular markers through liquid biopsies. This review presents an integrated view of the relevant cellular and molecular aspects involved in the etiopathogenesis of HGSOC and brings together studies that consider new horizons for the possible early detection of this gynecological cancer.

A Blood-Based Metabolite Panel for Distinguishing Ovarian Cancer from Benign Pelvic Masses

PURPOSE

To assess the contributions of circulating metabolites for improving upon the performance of the risk of ovarian malignancy algorithm (ROMA) for risk prediction of ovarian cancer among women with ovarian cysts.

EXPERIMENTAL DESIGN

Metabolomic profiling was performed on an initial set of sera from 101 serous and nonserous ovarian cancer cases and 134 individuals with benign pelvic masses (BPM). Using a deep learning model, a panel consisting of seven cancer-related metabolites [diacetylspermine, diacetylspermidine, N-(3-acetamidopropyl)pyrrolidin-2-one, N-acetylneuraminate, N-acetyl-mannosamine, N-acetyl-lactosamine, and hydroxyisobutyric acid] was developed for distinguishing early-stage ovarian cancer from BPM. The performance of the metabolite panel was evaluated in an independent set of sera from 118 ovarian cancer cases and 56 subjects with BPM. The contributions of the panel for improving upon the performance of ROMA were further assessed.

RESULTS

A 7-marker metabolite panel (7MetP) developed in the training set yielded an AUC of 0.86 [95% confidence interval (CI): 0.76-0.95] for early-stage ovarian cancer in the independent test set. The 7MetP+ROMA model had an AUC of 0.93 (95% CI: 0.84-0.98) for early-stage ovarian cancer in the test set, which was improved compared with ROMA alone [0.91 (95% CI: 0.84-0.98); likelihood ratio test P: 0.03]. In the entire specimen set, the combined 7MetP+ROMA model yielded a higher positive predictive value (0.68 vs. 0.52; one-sided P < 0.001) with improved specificity (0.89 vs. 0.78; one-sided P < 0.001) for early-stage ovarian cancer compared with ROMA alone.

CONCLUSIONS

A blood-based metabolite panel was developed that demonstrates independent predictive ability and complements ROMA for distinguishing early-stage ovarian cancer from benign disease to better inform clinical decision making.

Molecular Biomarkers for the Early Detection of Ovarian Cancer

Ovarian cancer is the deadliest gynecological cancer, leading to over 152,000 deaths each year. A late diagnosis is the primary factor causing a poor prognosis of ovarian cancer and often occurs due to a lack of specific symptoms and effective biomarkers for an early detection. Currently, cancer antigen 125 (CA125) is the most widely used biomarker for ovarian cancer detection, but this approach is limited by a low specificity. In recent years, multimarker panels have been developed by combining molecular biomarkers such as human epididymis secretory protein 4 (HE4), ultrasound results, or menopausal status to improve the diagnostic efficacy. The risk of ovarian malignancy algorithm (ROMA), the risk of malignancy index (RMI), and OVA1 assays have also been clinically used with improved sensitivity and specificity. Ongoing investigations into novel biomarkers such as autoantibodies, ctDNAs, miRNAs, and DNA methylation signatures continue to aim to provide earlier detection methods for ovarian cancer. This paper reviews recent advancements in molecular biomarkers for the early detection of ovarian cancer.

Anticancer Effect of Puerarin on Ovarian Cancer Progression Contributes to the Tumor Suppressor Gene Expression and Gut Microbiota Modulation

Ovarian cancer (OC) causes more deaths than any other cancer of the female reproductive system due to its late presentation and malignant nature. Although significant progress has been made in the diagnosis and treatment of OC over the last decade, chemotherapeutic drug resistance and cancer recurrence remain serious challenges in OC management. In the field of cancer therapy, traditional Chinese herbal medicines and their active compounds have been widely reported to have favorable therapeutic effects on cancer. Recent studies have also revealed the protective effect of puerarin in cancer, but the exact role and underlying mechanism of puerarin in OC remain unclear. Here, we established in vivo and in vitro OC models to evaluate the anticancer effect of puerarin. It was found that puerarin significantly inhibited OC cell viability and proliferation and induced cell apoptosis. In OC model mice, puerarin treatment suppressed tumor formation and modulated the gut microbiome. In addition, the expression of tumor suppressor genes was activated by puerarin in vitro and in vivo. These findings add to the existing knowledge on the usefulness of herbal active ingredients for the prevention and treatment of OC and provide a new perspective regarding the therapeutic potential of puerarin in cancer.

Development of a Multiprotein Classifier for the Detection of Early Stage Ovarian Cancer

BACKGROUND

Individual serum biomarkers are neither adequately sensitive nor specific for use in screening the general population for ovarian cancer. The purpose of this study was to develop a multiprotein classifier to detect the early stages of ovarian cancer, when it is most treatable.

METHODS

The Olink Proseek Multiplex Oncology II panel was used to simultaneously quantify the expression levels of 92 cancer-related proteins in sera.

RESULTS

In the discovery phase, we generated a multiprotein classifier that included CA125, HE4, ITGAV, and SEZ6L, based on an analysis of sera from 116 women with early stage ovarian cancer and 336 age-matched healthy women. CA125 alone achieved a sensitivity of 87.9% at a specificity of 95%, while the multiprotein classifier resulted in an increased sensitivity of 91.4%, while holding the specificity fixed at 95%. The performance of the multiprotein classifier was validated in a second cohort comprised of 192 women with early stage ovarian cancer and 467 age-matched healthy women. The sensitivity at 95% specificity increased from 74.5% (CA125 alone) to 79.2% with the multiprotein classifier. In addition, the multiprotein classifier had a sensitivity of 95.1% at 98% specificity for late stage ovarian cancer samples and correctly classified 80.5% of the benign samples using the 98% specificity cutpoint.

CONCLUSIONS

The inclusion of the proteins HE4, ITGAV, and SEZ6L improved the sensitivity and specificity of CA125 alone for the detection of early stages of ovarian cancer in serum samples. Furthermore, we identified several proteins that may be novel biomarkers of early stage ovarian cancer.

Current and Emerging Methods for Ovarian Cancer Screening and Diagnostics: A Comprehensive Review

With a 5-year survival rate of less than 50%, ovarian high-grade serous carcinoma (HGSC) is one of the most highly aggressive gynecological malignancies affecting women today. The high mortality rate of HGSC is largely attributable to delays in diagnosis, as most patients remain undiagnosed until the late stages of -disease. There are currently no recommended screening tests for ovarian cancer and there thus remains an urgent need for new diagnostic methods, particularly those that can detect the disease at early stages when clinical intervention remains effective. While diagnostics for ovarian cancer share many of the same technical hurdles as for other cancer types, the low prevalence of the disease in the general population, coupled with a notable lack of sensitive and specific biomarkers, have made the development of a clinically useful screening strategy particularly challenging. Here, we present a detailed review of the overall landscape of ovarian cancer diagnostics, with emphasis on emerging methods that employ novel protein, genetic, epigenetic and imaging-based biomarkers and/or advanced diagnostic technologies for the noninvasive detection of HGSC, particularly in women at high risk due to germline mutations such as BRCA1/2. Lastly, we discuss the translational potential of these approaches for achieving a clinically implementable solution for screening and diagnostics of early-stage ovarian cancer as a means of ultimately improving patient outcomes in both the general and high-risk populations.

Serum Autoantibodies against LRDD, STC1, and FOXA1 as Biomarkers in the Detection of Ovarian Cancer

Purpose

This study is aimed at evaluating serum autoantibodies against four tumor-associated antigens, including LRDD, STC1, FOXA1, and EDNRB, as biomarkers in the immunodiagnosis of ovarian cancer (OC).

Methods

The autoantibodies against LRDD, STC1, FOXA1, and EDNRB were measured using an enzyme-linked immunosorbent assay (ELISA) in 94 OC patients and 94 normal healthy controls (NHC) in the research group. In addition, the diagnostic values of different autoantibodies were validated in another independent validation group, which comprised 136 OC patients, 136 NHC, and 181 patients with benign ovarian diseases (BOD).

Results

In the research group, autoantibodies against LRDD, STC1, and FOXA1 had higher serum titer in OC patients than NHC (P < 0.001). The area under receiver operating characteristic curves (AUCs) of these three autoantibodies were 0.910, 0.879, and 0.817, respectively. In the validation group, they showed AUCs of 0.759, 0.762, and 0.817 and sensitivities of 49.3%, 42.7%, and 48.5%, respectively, at specificity over 90% for discriminating OC patients from NHC. For discriminating OC patients from BOD, they showed AUCs of 0.718, 0.729, and 0.814 and sensitivities of 47.1%, 39.0%, and 51.5%, respectively, at specificity over 90%. The parallel analyses demonstrated that the combination of anti-LRDD and anti-FOXA1 autoantibodies achieved the optimal diagnostic performance with the sensitivity of 58.1% at 87.5% specificity and accuracy of 72.8%. The positive rate of the optimal autoantibody panel improved from 62.4% to 87.1% when combined with CA125 in detecting OC patients.

Conclusion

Serum autoantibodies against LRDD, STC1, and FOXA1 have potential diagnostic values in detecting OC.

New Trends in the Detection of Gynecological Precancerous Lesions and Early-Stage Cancers

The prevention and early diagnostics of precancerous stages are key aspects of contemporary oncology. In cervical cancer, well-organized screening and vaccination programs, especially in developed countries, are responsible for the dramatic decline of invasive cancer incidence and mortality. Cytological screening has a long and successful history, and the ongoing implementation of HPV triage with increased sensitivity can further decrease mortality. On the other hand, endometrial and ovarian cancers are characterized by a poor accessibility to specimen collection, which represents a major complication for early diagnostics. Therefore, despite relatively promising data from evaluating the combined effects of genetic variants, population screening does not exist, and the implementation of new biomarkers is, thus, necessary. The introduction of various circulating biomarkers is of potential interest due to the considerable heterogeneity of cancer, as highlighted in this review, which focuses exclusively on the most common tumors of the genital tract, namely, cervical, endometrial, and ovarian cancers. However, it is clearly shown that these malignancies represent different entities that evolve in different ways, and it is therefore necessary to use different methods for their diagnosis and treatment.

Next steps in the early detection of ovarian cancer

Bast et al. discuss the early detection of ovarian cancer in the context of the recent UKCTOCS screening trial. The authors suggest potential reasons why the trial failed to achieve a reduction in mortality and outline next steps in the development of biomarkers and imaging modalities to detect ovarian cancer.

Identification of Tumor Antigens in Ovarian Cancers Using Local and Circulating Tumor-Specific Antibodies

Ovarian cancers include several disease subtypes and patients often present with advanced metastatic disease and a poor prognosis. New biomarkers for early diagnosis and targeted therapy are, therefore, urgently required. This study uses antibodies produced locally in tumor-draining lymph nodes (ASC probes) of individual ovarian cancer patients to screen two separate protein microarray platforms and identify cognate tumor antigens. The resulting antigen profiles were unique for each individual cancer patient and were used to generate a 50-antigen custom microarray. Serum from a separate cohort of ovarian cancer patients encompassing four disease subtypes was screened on the custom array and we identified 28.8% of all ovarian cancers, with a higher sensitivity for mucinous (50.0%) and serous (40.0%) subtypes. Combining local and circulating antibodies with high-density protein microarrays can identify novel, patient-specific tumor-associated antigens that may have diagnostic, prognostic or therapeutic uses in ovarian cancer.

Serum Anti-PDLIM1 Autoantibody as Diagnostic Marker in Ovarian Cancer

Background

Serum autoantibodies (AAbs) against tumor-associated antigens (TAAs) could be useful biomarkers for cancer detection. This study aims to evaluate the diagnostic value of autoantibody against PDLIM1 for improving the detection of ovarian cancer (OC).

Methods

Immunohistochemistry (IHC) test in tissue array containing 280 OC tissues, 20 adjacent tissues, and 8 normal ovarian tissues was performed to analyze the expression of PDLIM1 in tissues. Enzyme-linked immunosorbent assay (ELISA) was employed to measure the autoantibody to PDLIM1 in 545 sera samples from 182 patients with OC, 181 patients with ovarian benign diseases, and 182 healthy controls.

Results

The results of IHC indicated that 84.3% (236/280) OC tissues were positively stained with PDLIM1, while no positive staining was found in adjacent or normal ovarian tissues. The frequency of anti-PDLIM1 autoantibody was significantly higher in OC patients than that in healthy and ovarian benign controls in both training (n=122) and validation (n=423) sets. The area under the curves (AUCs) of anti-PDLIM1 autoantibody for discriminating OC from healthy controls were 0.765 in training set and 0.740 in validation set, and the AUC of anti-PDLIM1 autoantibody for discriminating OC from ovarian benign controls was 0.757 in validation set. Overall, it was able to distinguish 35.7% of OC, 40.6% of patients with early-stage, and 39.5% of patients with late-stage. When combined with CA125, the AUC increased to 0.846, and 79.2% of OC were detected, which is statistically higher than CA125 (61.7%) or anti-PDLIM1(35.7%) alone (p<0.001). Also, anti-PDLIM1 autoantibody could identify 15% (18/120) of patients that were negative with CA125 (CA125 <35 U/ml).

Conclusions

The anti-PDLIM1 autoantibody response in OC patients was positively correlated with PDLIM1 high expression in OC tissues, suggesting that the autoantibody against PDLIM1 might have the potential to be a novel serological biomarker of OC, serving as a complementary measure of CA125, which could improve the power of OC detection.

Mutated p53 in HGSC-From a Common Mutation to a Target for Therapy

Simple Summary

Ovarian high-grade serous cancer (HGSC), the most common and the deadliest subtype of epithelial ovarian cancer, is characterized by frequent mutations in the TP53 tumor suppressor gene, encoding for the p53 protein in nearly 100% of cases. This makes p53 the focus of many studies trying to understand its role in HGSC. The aim of our review paper is to provide updates on the latest findings related to the role of mutant p53 in HGSC. This includes the clinical outcomes of TP53 mutations in HGSC, upstream regulators and downstream effectors of p53, its function in the earliest stages of HGSC development and in the interplay between the tumor cells and their microenvironment. We summarize with the likelihood of p53 mutants to serve as biomarkers for early diagnosis and as targets for therapy in HGSC.

Abstract

Mutations in tumor suppressor gene TP53, encoding for the p53 protein, are the most ubiquitous genetic variation in human ovarian HGSC, the most prevalent and lethal histologic subtype of epithelial ovarian cancer (EOC). The majority of TP53 mutations are missense mutations, leading to loss of tumor suppressive function of p53 and gain of new oncogenic functions. This review presents the clinical relevance of TP53 mutations in HGSC, elaborating on several recently identified upstream regulators of mutant p53 that control its expression and downstream target genes that mediate its roles in the disease. TP53 mutations are the earliest genetic alterations during HGSC pathogenesis, and we summarize current information related to p53 function in the pathogenesis of HGSC. The role of p53 is cell autonomous, and in the interaction between cancer cells and its microenvironment. We discuss the reduction in p53 expression levels in tumor associated fibroblasts that promotes cancer progression, and the role of mutated p53 in the interaction between the tumor and its microenvironment. Lastly, we discuss the potential of TP53 mutations to serve as diagnostic biomarkers and detail some more advanced efforts to use mutated p53 as a therapeutic target in HGSC.

Joint IARC/NCI International Cancer Seminar Series Report: expert consensus on future directions for ovarian carcinoma research

Recently, ovarian cancer research has evolved considerably because of the emerging recognition that rather than a single disease, ovarian carcinomas comprise several different histotypes that vary by etiologic origin, risk factors, molecular profiles, therapeutic approaches and clinical outcome. Despite significant progress in our understanding of the etiologic heterogeneity of ovarian cancer, as well as important clinical advances, it remains the eighth most frequently diagnosed cancer in women worldwide and the most fatal gynecologic cancer. The International Agency for Research on Cancer and the United States National Cancer Institute jointly convened an expert panel on ovarian carcinoma to develop consensus research priorities based on evolving scientific discoveries. Expertise ranged from etiology, prevention, early detection, pathology, model systems, molecular characterization and treatment/clinical management. This report summarizes the current state of knowledge and highlights expert consensus on future directions to continue advancing etiologic, epidemiologic and prognostic research on ovarian carcinoma.

Anti-Cancer Auto-Antibodies: Roles, Applications and Open Issues

Auto-antibodies are classically associated with autoimmune diseases, where they are an integral part of diagnostic panels. However, recent evidence is accumulating on the presence of auto-antibodies against single or selected panels of auto-antigens in many types of cancer. Auto-antibodies might initially represent an epiphenomenon derived from the inflammatory environment induced by the tumor. However, their effect on tumor evolution can be crucial, as is discussed in this paper. It has been demonstrated that some of these auto-antibodies can be used for early detection and cancer staging, as well as for monitoring of cancer regression during treatment and follow up. Interestingly, certain auto-antibodies were found to promote cancer progression and metastasis, while others contribute to the body's defense against it. Moreover, auto-antibodies are of a polyclonal nature, which means that often several antibodies are involved in the response to a single tumor antigen. Dissection of these antibody specificities is now possible, allowing their identification at the genetic, structural, and epitope levels. In this review, we report the evidence available on the presence of auto-antibodies in the main cancer types and discuss some of the open issues that still need to be addressed by the research community.

Discovery and Validation of Serum Autoantibodies Against Tumor-Associated Antigens as Biomarkers in Gastric Adenocarcinoma Based on the Focused Protein Arrays

INTRODUCTION:

Previous studies have demonstrated that autoantibodies against tumor-associated antigens (TAAs) in patients with cancer can be used as sensitive immunodiagnostic biomarkers for the detection of cancer. Most of these TAAs are involved in the tumorigenesis pathway. Cancer driver genes with intragenic mutations can promote tumorigenesis. This study aims to identify autoantibodies against TAAs encoded by cancer driver genes in sera as potential immunodiagnostic biomarkers for gastric adenocarcinoma (GAC).

METHODS:

Protein arrays based on cancer driver genes were customized for screening candidate TAAs in 100 GAC sera and 50 normal control (NC) sera. Autoantibodies against candidate TAAs were assessed by enzyme-linked immunosorbent assay in both training group (205 GAC sera and 205 NC sera) and independent validation group (126 GAC sera and 126 NC sera). Moreover, the immunodiagnostic models were respectively established and validated in the training group and validation group.

RESULTS:

A panel with 5 autoantibodies including anti-TP53, anti-COPB1, anti-GNAS, anti–serine/arginine-rich splicing factor 2, and anti-SMARCB1 was selected by the Fisher linear discriminant analysis model with an areas under receiver operating characteristic curve (AUC) of 0.928 (95% confidence interval [CI]: 0.888–0.967) in the training cohort and an AUC of 0.885 (95% CI: 0.852–0.918) in the validation cohort. Besides, the panel with 5 autoantibodies including anti-TP53, anti-COPB1, anti-GNAS, anti-PBRM1, and anti-ACVR1B which were selected by the binary logistic regression model showed an AUC of 0.885 (95% CI: 0.852–0.919) in the training cohort and 0.884 (95% CI: 0.842–0.925) in the validation cohort.

DISCUSSION:

Two panels which were selected in this study could boost the detection of anti-TAA autoantibodies in sera as biomarkers for the detection of GAC.

Using protein microarray to identify and evaluate autoantibodies to tumor-associated antigens in ovarian cancer

The aim of this study was to develop a noninvasive serological diagnostic approach in identifying and evaluating a panel of candidate autoantibodies to tumor‐associated antigens (TAAs) based on protein microarray technology for early detection of ovarian cancer (OC). Protein microarray based on 154 proteins encoded by 138 cancer driver genes was used to screen candidate anti‐TAA autoantibodies in a discovery cohort containing 17 OC and 27 normal controls (NC). Indirect enzyme‐linked immunosorbent assay (ELISA) was used to detect the content of candidate anti‐TAA autoantibodies in sera from 140 subjects in the training cohort. Differential anti‐TAA autoantibodies were further validated in the validation cohort with 328 subjects. Subsequently, 112 sera from the patients with ovarian benign diseases with 104 OC sera and 104 NC sera together were recruited to identify the specificity of representative autoantibodies to OC among ovarian diseases. Five TAAs (GNAS, NPM1, FUBP1, p53, and KRAS) were screened out in the discovery phase, in which four of them presented higher levels in OC than controls (P < .05) in the training cohort, which was consistent with the result in the subsequent validation cohort. An optimized panel of three anti‐TAA (GNAS, p53, and NPM1) autoantibodies was identified to have relatively high sensitivity (51.2%), specificity (86.0%), and accuracy (68.6%), respectively. This panel can identify 51% of OC patients with CA125 negative. This study supports our assumption that anti‐TAA autoantibodies can be considered as potential diagnostic biomarkers for detection of OC; especially a panel of three anti‐TAA autoantibodies could be a good tool in immunodiagnosis of OC.

Biomarkers and Strategies for Early Detection of Ovarian Cancer

Early detection of ovarian cancer remains an important unmet medical need. Effective screening could reduce mortality by 10%-30%. Used individually, neither serum CA125 nor transvaginal sonography (TVS) is sufficiently sensitive or specific. Two-stage strategies have proven more effective, where a significant rise above a woman's baseline CA125 prompts TVS and an abnormal sonogram prompts surgery. Two major screening trials have documented that this strategy has adequate specificity, but sensitivity for early-stage (I-II) disease must improve to have a greater impact on mortality. To improve the first stage, different panels of protein biomarkers have detected cases missed by CA125. Autoantibodies against TP53 have detected 20% of early-stage ovarian cancers 8 months before elevation of CA125 and 22 months before clinical diagnosis. Panels of autoantibodies and antigen-autoantibody complexes are being evaluated with the goal of detecting >90% of early-stage ovarian cancers, alone or in combination with CA125, while maintaining 98% specificity in control subjects. Other biomarkers, including micro-RNAs, ctDNA, methylated DNA, and combinations of ctDNA alterations, are being tested to provide an optimal first-stage test. New technologies are also being developed with greater sensitivity than TVS to image small volumes of tumor.See all articles in this CEBP Focus section, "NCI Early Detection Research Network: Making Cancer Detection Possible."

Evaluation of paraneoplastic antigens reveals TRIM21 autoantibodies as biomarker for early detection of ovarian cancer in combination with autoantibodies to NY-ESO-1 and TP53

BACKGROUND

The majority of ovarian cancer cases are diagnosed at an advanced stage with poor prognosis. This study evaluates autoantibodies against tumor antigens to identify candidate biomarkers for early detection of ovarian cancer in women at increased risk.

OBJECTIVE

To assess the immunoreactivity of paraneoplastic antigens and tumor associated antigens with high-grade serous ovarian cancer (HGSOC) samples.

METHODS

Five paraneoplastic antigens along with three tumor-associated antigens were evaluated with HGSOC patient serum samples. Validation screening was performed with n= 164 serum samples consisting of: 50 late stage HGSOC, 14 early stage HGSOC, 50 benign ovarian cyst, and 50 healthy control samples on ELISA and western blot. The four markers TRIM21, NY-ESO-1, TP53, and PAX8 were evaluated on a second validation serum set, n= 150.

RESULTS

TRIM21 achieved the highest sensitivity in the first validation screening of 33% with 100% specificity. Combining TRIM21 with NY-ESO-1, TP53, and PAX8 provided 67% sensitivity with 94% specificity, and 56% sensitivity at 98% specificity. These four markers resulted in 46% sensitivity with 98% specificity in the second validation cohort; TRIM21 achieved the highest individual sensitivity of 36%.

CONCLUSIONS

Autoantibodies to TRIM21, NY-ESO-1, and TP53 may complement CA125 in screening of women at genetic risk for ovarian cancer.

Multi-Marker Longitudinal Algorithms Incorporating HE4 and CA125 in Ovarian Cancer Screening of Postmenopausal Women

Longitudinal CA125 algorithms are the current basis of ovarian cancer screening. We report on longitudinal algorithms incorporating multiple markers. In the multimodal arm of United Kingdom Collaborative Trial of Ovarian Cancer Screening (UKCTOCS), 50,640 postmenopausal women underwent annual screening using a serum CA125 longitudinal algorithm. Women (cases) with invasive tubo-ovarian cancer (WHO 2014) following outcome review with stored annual serum samples donated in the 5 years preceding diagnosis were matched 1:1 to controls (no invasive tubo-ovarian cancer) in terms of the number of annual samples and age at randomisation. Blinded samples were assayed for serum human epididymis protein 4 (HE4), CA72-4 and anti-TP53 autoantibodies. Multimarker method of mean trends (MMT) longitudinal algorithms were developed using the assay results and trial CA125 values on the training set and evaluated in the blinded validation set. The study set comprised of 1363 (2-5 per woman) serial samples from 179 cases and 181 controls. In the validation set, area under the curve (AUC) and sensitivity of longitudinal CA125-MMT algorithm were 0.911 (0.871-0.952) and 90.5% (82.5-98.6%). None of the longitudinal multi-marker algorithms (CA125-HE4, CA125-HE4-CA72-4, CA125-HE4-CA72-4-anti-TP53) performed better or improved on lead-time. Our population study suggests that longitudinal HE4, CA72-4, anti-TP53 autoantibodies adds little value to longitudinal serum CA125 as a first-line test in ovarian cancer screening of postmenopausal women.

Ovarian cancer screening: Current status and future directions

Ovarian cancer is the third most common gynaecological malignancy and the most lethal worldwide. Most patients are diagnosed with advanced disease which carries significant mortality. Improvements in treatment have only resulted in modest increases in survival. This has driven efforts to reduce mortality through screening. Multimodal ovarian cancer screening using a longitudinal CA125 algorithm has resulted in diagnosis at an earlier stage, both in average and high risk women in two large UK trials. However, no randomised controlled trial has demonstrated a definitive mortality benefit. Extended follow up is underway in the largest trial to date, UKCTOCS, to explore the delayed reduction in mortality that was noted. Meanwhile, screening is not currently recommended in the general population Some countries offer surveillance of high risk women. Novel screening modalities and longitudinal biomarker algorithms offer potential improvements to future screening strategies as does the development of better risk stratification tools.

Clinical Usefulness of Cancer Antigen (CA) 125, Human Epididymis 4, and CA72-4 Levels and Risk of Ovarian Malignancy Algorithm Values for Diagnosing Ovarian Tumors in Korean Patients With and Without Endometriosis

BACKGROUND

Tumor markers are useful for detection and preoperative evaluation of ovarian tumors. We evaluated the clinical usefulness of cancer antigen (CA) 125, human epididymis 4 (HE4), and CA72-4 levels and Risk of Ovarian Malignancy Algorithm (ROMA) values for differential diagnosis of malignant and borderline tumors among suspected ovarian tumors, and the effects of endometriosis on these tumor markers.

METHODS

In a total of 266 patients (213, 14, and 39 with benign, borderline and malignant tumors, respectively), CA125, HE4, and CA72-4 levels were measured, and ROMA values were calculated. Medians of each marker were compared among the three groups. The area under the ROC curve (AUC), sensitivity, and specificity were calculated to analyze the diagnostic performance of each marker.

RESULTS

All markers were significantly higher in the malignant group than in the benign group. HE4 levels and ROMA values were significantly higher in the malignant group than in the borderline group. ROMA value had the highest AUC for distinguishing the malignant and borderline groups from the benign group in premenopausal (0.773) and postmenopausal (0.927) patients. CA125 level was significantly higher in patients with endometriosis than in those without (P<0.001), whereas HE4 and CA72-4 levels were not affected by endometriosis (P=0.128 and 0.271, respectively).

CONCLUSIONS

ROMA value is the best marker to distinguish malignant and borderline tumors from benign tumors in pre- and postmenopausal patients. HE4 and CA72-4 levels provide information on possible CA125 elevation due to endometriosis.

Screening and Prevention for High-Grade Serous Carcinoma of the Ovary Based on Carcinogenesis-Fallopian Tube- and Ovarian-Derived Tumors and Incessant Retrograde Bleeding

High-grade serous carcinoma (HGSC) is the most common and lethal subtype of ovarian carcinoma. Many HGSCs are now believed to originate in the fallopian tube epithelium; ovarian surface epithelium is another possible origin. Thus, current screening methods, i.e., ultrasonography and serum CA-125 measurements, have a limitation in their early detection. Recently, circulating biomarkers, such as tumor DNA, autoantibody, and microRNA, have been investigated to detect HGSCs. As cancer cells in the fallopian tube flow into the endometrial cavity, the detection of exfoliated cells, tumor DNA, and proteome from samples obtained from the endometrial cavity or the cervix may be useful. The risk of ovarian serous carcinoma is affected by the use of oral contraceptive and menopausal hormone therapy (MHT). MHT regimens causing endometrial bleeding increase serous carcinoma risk, hence, incessant retrograde bleeding from the endometrial cavity into the Douglas pouch appears to play an important role in high-grade serous carcinogenesis. In this review, we provide an overview of current and novel screening methods and prevention approaches for ovarian and fallopian tube HGSC.

Proteome Profiling Uncovers an Autoimmune Response Signature That Reflects Ovarian Cancer Pathogenesis

Harnessing the immune response to tumor antigens in the form of autoantibodies, which occurs early during tumor development, has relevance to the detection of cancer at early stages. We conducted an initial screen of antigens associated with an autoantibody response in serous ovarian cancer using recombinant protein arrays. The top 25 recombinants that exhibited increased reactivity with cases compared to controls revealed TP53 and MYC, which are ovarian cancer driver genes, as major network nodes. A mass spectrometry based independent analysis of circulating immunoglobulin (Ig)-bound proteins in ovarian cancer and of ovarian cancer cell surface MHC-II bound peptides also revealed a TP53–MYC related network of antigens. Our findings support the occurrence of a humoral immune response to antigens linked to ovarian cancer driver genes that may have utility for early detection applications.

Human epididymis protein 4 antigen-autoantibody complexes complement cancer antigen 125 for detecting early-stage ovarian cancer

BACKGROUND

Early detection of ovarian cancer could significantly improve patient outcomes. Cancer antigen 125 (CA 125) is elevated in sera from approximately 60% of patients with early-stage (I/II) disease. Sensitivity might be improved through the combination of CA 125 with other biomarkers. Among potential biomarkers, antigen-autoantibody (Ag-AAb) complexes have received relatively little attention.

METHODS

Luminex-based immunoassays were used to measure human epididymis protein 4 (HE4), anti-HE4 autoantibody, and HE4 Ag-AAb complexes in sera from patients with early- (n = 73) and late-stage ovarian cancers (n = 49) at the time of diagnosis and from asymptomatic women with (n = 15) or without ovarian cancer (n = 212) enrolled in the Normal Risk Ovarian Cancer Screening Study.

RESULTS

At 98% specificity for healthy, asymptomatic women, 7% of patients with early-stage (I/II) ovarian cancer and 4% of patients with late-stage (III/IV) disease had elevated levels of HE4 autoantibody, whereas elevated levels of HE4 Ag-AAb complexes were detected in sera from 38% of early-stage cases and 31% of late-stage cases. Complementarity was observed in receiver operating characteristic (ROC) curves between HE4 Ag-AAb complexes and CA 125 levels in early-stage ovarian cancer (P < .001). CA 125 detected 63% of cases, and a combination of CA 125 and HE4 Ag-AAb complexes detected 81%. Complementarity was also observed in ROC curves for an independent validation set with 69 early-stage patients (P = .039). HE4 Ag-AAb complexes were detected in serial preclinical serum samples from women destined to develop ovarian cancer: they correlated with CA 125 but did not provide a lead time.

CONCLUSIONS

HE4 Ag-AAb complexes could complement CA 125 in detecting a higher fraction of early-stage ovarian cancers.

Antibodies against aberrant glycans as cancer biomarkers

Introduction: The review provides a comprehensive overview about applicability of serological detection of autoantibodies against aberrant glycans as cancer biomarkers.Areas covered: Clinical usefulness of autoantibodies as cancer biomarkers is discussed for seven types of cancers with sensitivity and specificity of such biomarkers provided. Moreover, an option of using serological antibodies against a non-natural form of sialic acid - N-glycolylneuraminic acid (Neu5Gc), which is taken into our bodies together with red meat, as a potential cancer biomarker is discussed shortly as well.Expert opinion: In the final part of the review, we discuss what measures need to be applied for selective implementation of autoantibody assays into a clinical practice. Moreover, we discuss key challenges ahead for reliable and robust detection of autoantibodies against aberrant glycans as biomarkers for disease diagnostics and for stratification of cancer patients.

Novel Approaches to Ovarian Cancer Screening

PURPOSE OF REVIEW

Both conventional and novel approaches to early detection of ovarian cancer are reviewed in the context of new developments in our understanding of ovarian cancer biology.

RECENT FINDINGS

While CA125 as a single value lacks adequate specificity or sensitivity for screening, large studies have shown that a 2-stage strategy which tracks CA125 change over time and prompts transvaginal ultrasound (TVS) for a small subset of women with abnormally rising biomarker values achieves adequate specificity and detects a higher fraction of early-stage disease. Sensitivity could clearly be improved in both blood tests and in imaging. Metastasis can occur from ovarian cancers too small to increase blood levels of protein antigens and a significant fraction of ovarian cancers arise from the fimbriae of fallopian tubes that cannot be imaged with TVS. Autoantibodies, miRNA, ctDNA, DNA methylation in blood, and cervical mucus might improve sensitivity of the initial phase and magnetic relaxometry and autofluorescence could improve imaging in the second phase. Enhancing the sensitivity of two-stage strategies for early detection could reduce mortality from ovarian cancer.

Critical questions in ovarian cancer research and treatment: Report of an American Association for Cancer Research Special Conference

Substantial progress has been made in understanding ovarian cancer at the molecular and cellular level. Significant improvement in 5-year survival has been achieved through cytoreductive surgery, combination platinum-based chemotherapy, and more effective treatment of recurrent cancer, and there are now more than 280,000 ovarian cancer survivors in the United States. Despite these advances, long-term survival in late-stage disease has improved little over the last 4 decades. Poor outcomes relate, in part, to late stage at initial diagnosis, intrinsic drug resistance, and the persistence of dormant drug-resistant cancer cells after primary surgery and chemotherapy. Our ability to accelerate progress in the clinic will depend on the ability to answer several critical questions regarding this disease. To assess current answers, an American Association for Cancer Research Special Conference on "Critical Questions in Ovarian Cancer Research and Treatment" was held in Pittsburgh, Pennsylvania, on October 1-3, 2017. Although clinical, translational, and basic investigators conducted much of the discussion, advocates participated in the meeting, and many presentations were directly relevant to patient care, including treatment with poly adenosine diphosphate ribose polymerase (PARP) inhibitors, attempts to improve immunotherapy by overcoming the immune suppressive effects of the microenvironment, and a better understanding of the heterogeneity of the disease.

High-throughput assessment of the antibody profile in ovarian cancer ascitic fluids

The identification of effective biomarkers for early diagnosis, prognosis, and response to treatments remains a challenge in ovarian cancer (OC) research. Here, we present an unbiased high-throughput approach to profile ascitic fluid autoantibodies in order to obtain a tumor-specific antigen signature in OC. We first reported the reactivity of immunoglobulins (Igs) purified from OC patient ascites towards two different OC cell lines. Using a discovery set of Igs, we selected tumor-specific antigens from a phage display cDNA library. After biopanning, 700 proteins were expressed as fusion protein and used in protein array to enable large-scale immunoscreening with independent sets of cancer and noncancerous control. Finally, the selected antigens were validated by ELISA. The initial screening identified eight antigenic clones: CREB3, MRPL46, EXOSC10, BCOR, HMGN2, HIP1R, OLFM4, and KIAA1755. These antigens were all validated by ELISA in a study involving ascitic Igs from 153 patients (69 with OC, 34 with other cancers and 50 without cancer), with CREB3 showing the highest sensitivity (86.95%) and specificity (98%). Notably, we were able to identify an association between the tumor-associated (TA) antibody response and the response to a first-line tumor treatment (platinum-based chemotherapy). A stronger association was found by combining three antigens (BCOR, CREB3, and MRLP46) as a single antibody signature. Measurement of an ascitic fluid antibody response to multiple TA antigens may aid in the identification of new prognostic signatures in OC patients and shift attention to new potentially relevant targets.

Osteopontin, Macrophage Migration Inhibitory Factor and Anti-Interleukin-8 Autoantibodies Complement CA125 for Detection of Early Stage Ovarian Cancer

Early detection of ovarian cancer promises to reduce mortality. While serum CA125 can detect more than 60% of patients with early stage (I–II) disease, greater sensitivity might be observed with a panel of biomarkers. Ten protein antigens and 12 autoantibody biomarkers were measured in sera from 76 patients with early stage (I–II), 44 patients with late stage (III–IV) ovarian cancer and 200 healthy participants in the normal risk ovarian cancer screening study. A four-biomarker panel (CA125, osteopontin (OPN), macrophage inhibitory factor (MIF), and anti-IL-8 autoantibodies) detected 82% of early stage cancers compared to 65% with CA125 alone. In early stage subjects the area under the receiver operating characteristic curve (AUC) for the panel (0.985) was significantly greater (p < 0.001) than the AUC for CA125 alone (0.885). Assaying an independent validation set of sera from 71 early stage ovarian cancer patients, 45 late stage patients and 131 healthy women, AUC in early stage disease was improved from 0.947 with CA125 alone to 0.974 with the four-biomarker panel (p = 0.015). Consequently, OPN, MIF and IL-8 autoantibodies can be used in combination with CA125 to distinguish ovarian cancer patients from healthy controls with high sensitivity. Osteopontin appears to be a robust biomarker that deserves further evaluation in combination with CA125.

Complementary Longitudinal Serum Biomarkers to CA125 for Early Detection of Ovarian Cancer

Early detection of ovarian cancer has the potential to impact mortality. A multimodal screening strategy where rising CA125 values over time, analyzed with the risk of ovarian cancer algorithm (ROCA), triggers transvaginal sonography and possible surgery has high sensitivity and specificity, but still fails to detect the 20% of early-stage cases that do not express CA125. Use of multiple biomarkers could detect cases missed by CA125. We have studied the sensitivity and lead time of a multi-marker panel (CA125, HE4, MMP-7, and CA 72-4) compared with CA125 alone. We used PRoBE design principles to select preclinical longitudinal specimens from 75 women (50 screen-positive, 25 screen-negative) who developed invasive epithelial ovarian cancer (3-5 serial specimens each) and 547 corresponding healthy controls (1-10 serial specimens each) from the ovarian cancer screening trial, UKCTOCS, in a blinded fashion. We measured the multi-marker concentrations in ultra-low serum volumes (16 μL) utilizing multiplexed bead-based immunoassays with low detection limits, high inter- and intra-assay precision, negligible cross-reactivity, and good correlation with standard immunoassays. While, at least one of the complementary biomarkers rose with CA125 in 44% (22/50) of screen-positive cases, there was no advantage in lead time over CA125. Therefore, we developed single-marker longitudinal algorithms (ROCA-like) to determine the presence of a change point to distinguish between the cases and controls. Using these algorithms, at 98% specificity, HE4 and CA72-4 identified 16% (4/25) of screen-negative cases, while MMP-7 identified none. Taken together, HE4 and CA72-4 show promise as complementary biomarkers to CA125 for longitudinal screening.

Simultaneous Measurement of 92 Serum Protein Biomarkers for the Development of a Multiprotein Classifier for Ovarian Cancer Detection

The best known ovarian cancer biomarker, CA125, is neither adequately sensitive nor specific for screening the general population. By using a combination of proteins for screening, it may be possible to increase the sensitivity and specificity over CA125 alone. In this study, we used Proseek Multiplex Oncology II plates to simultaneously measure the expression of 92 cancer-related proteins in serum using proximity extension assays. This technology combines the sensitivity of the PCR with the specificity of antibody-based detection methods, allowing multiplex biomarker detection and high-throughput quantification. We analyzed 1 μL of sera from each of 61 women with ovarian cancer and compared the values obtained with those from 88 age-matched healthy women. Principle component analysis and unsupervised hierarchical clustering separated the ovarian cancer patients from the healthy, with minimal misclassification. Data from the Proseek plates for CA125 levels exhibited a strong correlation with clinical values for CA125. We identified 52 proteins that differed significantly (P < 0.006) between ovarian cancer and healthy samples, several of which are novel serum biomarkers for ovarian cancer. In total, 40 proteins had an estimated area under the ROC curve of 0.70 or greater, suggesting their potential to serve as biomarkers for ovarian cancer. CA125 alone achieved a sensitivity of 93.4% at a specificity of 98%. By adding the Oncology II values for five proteins to CA125 in a multiprotein classifier, we increased the assay sensitivity to 98.4% at a specificity of 98%, thereby improving the sensitivity and specificity of CA125 alone.

Analysis of the inhibitory effects of miR-124 and miR-152 on human epithelial ovarian cancer xenografts in a nude mouse model

This study investigated the inhibitory effects of miR-124 and miR-152 on the growth of human ovarian cancer (OC) SKOV3 cell line subcutaneous xenografts in nude mice. Twenty-eight healthy nude mice were selected and divided into the experimental group 1 (n=4), experimental group 2 (n=4), negative control group 1 (n=4), negative control group 2 (n=4), blank control group 1 (n=4), blank control group 2 (n=4) and observation group (n=4) according to the principle of similarity in body weight. The transfected SKOV3 cells were inoculated subcutaneously into the nape of the nude mice. After tumorigenesis, miR-124 mimics, miR-152 mimics, and their negative controls were transiently transfected into human OC SKOV3 cells via lipofection method. The expression levels of miR-124 and miR-152 were detected via reverse transcription-quantitative polymerase chain reaction (RT-qPCR), and those of Ki-67 and caspase-3 were detected by western blotting. After transfection, the expression levels of miR-124 and miR-152 in the SKOV3 cells were significantly upregulated. The nude mice were sacrificed 36 days later, and tumor nodes of nude mice transfected with miR-124 and miR-152 grew slowly. Compared with that in the experimental groups, tumor size in the blank control and negative control groups was gradually increased with the increment of days (P<0.05). The volume of subcutaneous xenografts in nude mice of miR-124 and miR-152 experimental groups was obviously smaller than that in the blank control and negative control groups (P<0.05). Besides, the inhibition of tumor size in the observation group was more significant than that in the experimental groups (P<0.05). Thus, miR-124 and miR-152 inhibit the growth of human epithelial OC xenografts in nude mice, and they are expected to become new targets for gene-based therapy of OC.

Early Detection of Ovarian Cancer

Early detection of ovarian cancer could reduce mortality by 10% to 30%. Effective screening requires high sensitivity (>75%) and extremely high specificity (99.7%). Clinical trials suggest the best specificity is achieved with 2-stage strategies in which increasing serum CA125 level triggers transvaginal sonography to detect a malignant pelvic mass, although evidence for such approaches improving overall survival has been limited. Screening may be improved by combining CA125 with novel biomarkers, such as autoantibodies, circulating tumor DNA, or microRNAs. In order to detect premetastatic ovarian cancers originating in the distal fallopian tube, more sensitive approaches to diagnostic imaging are required.

Tumor-associated autoantibodies as early detection markers for ovarian cancer? A prospective evaluation

Immuno-proteomic screening has identified several tumor-associated autoantibodies (AAb) that may have diagnostic capacity for invasive epithelial ovarian cancer, with AAbs to P53 proteins and cancer-testis antigens (CTAGs) as prominent examples. However, the early detection potential of these AAbs has been insufficiently explored in prospective studies. We performed ELISA measurements of AAbs to CTAG1A, CTAG2, P53 and NUDT11 proteins, for 194 patients with ovarian cancer and 705 matched controls from the European EPIC cohort, using serum samples collected up to 36 months prior to diagnosis under usual care. CA125 was measured using electrochemo-luminiscence. Diagnostic discrimination statistics were calculated by strata of lead-time between blood collection and diagnosis. With lead times ≤6 months, ovarian cancer detection sensitivity at 0.98 specificity (SE98) varied from 0.19 [95% CI 0.08-0.40] for CTAG1A, CTAG2 and NUDT1 to 0.23 [0.10-0.44] for P53 (0.33 [0.11-0.68] for high-grade serous tumors). However, at longer lead-times, the ability of these AAb markers to distinguish future ovarian cancer cases from controls declined rapidly; at lead times >1 year, SE98 estimates were close to zero (all invasive cases, range: 0.01-0.11). Compared to CA125 alone, combined logistic regression scores of AAbs and CA125 did not improve detection sensitivity at equal level of specificity. The added value of these selected AAbs as markers for ovarian cancer beyond CA125 for early detection is therefore limited.