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.

Soluble CD137 and risk of hepatocellular carcinoma: nested case-control studies in cohorts in Shanghai and Singapore.

BACKGROUND: The majority of hepatocellular carcinoma (HCC) cases occur in the presence of cirrhosis. Biomarkers of cirrhosis-associated immune dysfunction such as CD8+ T cell cytokines could aid HCC risk assessment. METHODS: CD8+ T cell cytokines were determined in pre-diagnostic serum in two studies including 315 HCC case-control pairs in the Shanghai Cohort Study (SCS) and 197 pairs in the Singapore Chinese Health Study (SCHS). Conditional logistic regression was used to estimate odds ratio (OR) and 95% confidence interval (CI) for HCC with levels of five cytokines-soluble CD137 (sCD137), soluble Fas (sFas), perforin, macrophage inflammatory protein 1-beta (MIP-1ß), and tumour necrosis factor alpha (TNF-α). RESULTS: sCD137 levels were significantly higher in HCC cases than controls in both cohorts (Ps < 0.001). Compared with the lowest quartile, multivariable-adjusted ORs (95% CI) of HCC for the highest sCD137 quartile were 3.79 (1.73, 8.30) in the SCS and 3.49 (1.44, 8.48) in the SCHS. The sCD137-HCC association was independent of hepatitis B seropositivity and follow-up time. No other cytokine was consistently associated with HCC risk. CONCLUSION: sCD137 was associated with higher risk of HCC in two studies nested in general population cohorts. sCD137 may be a long-term risk marker of HCC development.

Multiinstitutional Validation Study of Cyst Fluid Protein Biomarkers in Patients With Cystic Lesions of the Pancreas.

OBJECTIVE: Prospective evaluation of 2 clinical-molecular models in patients with unknown pathology who underwent endoscopic ultrasound with fine-needle aspiration (EUS-FNA) for a cystic lesion of the pancreas. SUMMARY OF BACKGROUND DATA: Preoperative prediction of histologic subtype (mucinous vs nonmucinous) and grade of dysplasia in patients with pancreatic cystic neoplasms is challenging. Our group has previously published 2 clinical-molecular nomograms for intraductal papillary mucinous neoplasms (IPMN) that incorporated both clinical/radiographic features and cyst fluid protein markers (sFASL, CA72-4, MMP9, IL-4). METHODS: This multiinstitutional study enrolled patients who underwent EUS-FNA for a cystic lesion of the pancreas. Treatment recommendations regarding resection were based on standard clinical, radiographic, and endoscopic features. Predicted probabilities of high-risk IPMN (high-grade dysplasia/invasive cancer) were calculated using the previously developed clinical-molecular nomograms. RESULTS: Cyst fluid was obtained from 100 patients who underwent diagnostic EUS-FNA. Within this group there were 35 patients who underwent resection, and 65 were monitored radiographically. Within the group that underwent resection, 26 had low-risk IPMN or benign non-IPMN lesions, and 9 had high-risk IPMN. Within the surveillance group, no patient progressed to resection or developed cancer after a median follow-up of 12months (range: 0.5-38). Using the clinical/radiographic nomogram alone, 2 out of 9 patients with high-risk IPMN had a predicted probability >0.5. In the clinical-molecular models, 6 of 9 patients in model 1, and 6 of 9 in model 2, had scores >0.5. CONCLUSIONS: This prospective study of patients with unknown cyst pathology further demonstrates the importance of cyst fluid protein analysis in the preoperative identification of patients with high-risk IPMN. Longer follow-up is necessary to determine if this model will be useful in clinical practice.

Biomarker panel for early detection of endometrial cancer in the Prostate, Lung, Colorectal, and Ovarian cancer screening trial.

BACKGROUND: Endometrial cancer is the most common gynecological cancer in the United States. However, no early detection test exists for asymptomatic women at average risk for endometrial cancer. OBJECTIVE: We sought to identify early detection biomarkers for endometrial cancer using prediagnostic serum. STUDY DESIGN: We performed a nested case-control study of postmenopausal women in the Prostate, Lung, Colorectal, and Ovarian cancer screening trial (n = 78,216), including 112 incident endometrial cancer cases and 112 controls. Prediagnostic serum was immunodepleted of high-abundance proteins and digested with sequencing grade porcine trypsin via pressure cycling technology. Quantitative proteomics and phosphoproteomics was performed using high-resolution liquid chromatography-tandem mass spectrometry and highly multiplexed isobaric mass tag combined with basic reversed-phase liquid chromatography. A set of proteins able to predict cancer status was identified with an integrated score assessed by receiver-operator curve analysis. RESULTS: Mean time from blood draw to endometrial cancer diagnosis was 3.5 years (SD, 1.9 years). There were 47 differentially abundant proteins between cases and controls (P < .05). Protein alterations with high predictive potential were selected by regression analysis and compiled into an aggregate score to determine the ability to predict endometrial cancer. An integrated risk score of 6 proteins was directly related to disease incidence in cases with blood draw ≤2 years, >2 years to ≤5 years or >5 years prior to cancer diagnosis. The integrated score distinguished cases from controls with an area under the curve of 0.80 (95% confidence interval, 0.72-0.88). CONCLUSION: An integrated score of 6 proteins using prediagnostic serum from the Prostate, Lung, Colorectal, and Ovarian cancer screening trial distinguishes postmenopausal endometrial cancer cases from controls. Validation is needed to evaluate whether this test can improve prediction or detection of endometrial cancer among postmenopausal women.

Multi-institutional Validation Study of Pancreatic Cyst Fluid Protein Analysis for Prediction of High-risk Intraductal Papillary Mucinous Neoplasms of the Pancreas.

OBJECTIVE: Preliminary work by our group suggested that proteins within the pancreatic cyst fluid (CF) may discriminate degree of IPMN dysplasia. We sought to externally validate these markers and determine whether their inclusion in a preoperative clinical nomogram could increase diagnostic accuracy. SUMMARY BACKGROUND DATA: IPMN is the most common radiographically identifiable precursor to pancreatic cancer; however, the timing and frequency of its malignant progression are unknown, and there are currently no reliable preoperative tests that can determine the grade of dysplasia in IPMN. METHODS: Clinical and radiographic data, as well as CF samples, were obtained from 149 patients who underwent resection for IPMN at 1 of 3 institutions. High-risk disease was defined as the presence of high-grade dysplasia or invasive carcinoma. Multianalyte bead array analysis (Luminex) of CF was performed for 4 protein markers that were previously associated with high-risk disease. Logistic regression models were fit on training data, with and without adjustment for a previously developed clinical nomogram and validated with an external testing set. The models incorporating clinical risk score were presented graphically as nomograms. RESULTS: Within the group of 149 resected patients, 89 (60%) had low-risk disease, and 60 (40%) had high-risk disease. All 4 CF markers (MMP9, CA72-4, sFASL, and IL-4) were overexpressed in patients with high-risk IPMN (P < 0.05). Two predictive models based on preselected combinations of CF markers had concordance indices of 0.76 (Model-1) and 0.80 (Model-2). Integration of each CF marker model into a previously described clinical nomogram leads to increased discrimination compared with either the CF models or nomogram alone (c-indices of 0.84 and 0.83, respectively). CONCLUSIONS: This multi-institutional study validated 2 CF protein marker models for preoperative identification of high-risk IPMN. When combined with a clinical nomogram, the ability to predict high-grade dysplasia was even stronger.

Changes in inflammatory endometrial cancer risk biomarkers in individuals undergoing surgical weight loss.

OBJECTIVE: Obesity has been strongly linked to endometrial cancer (EC) risk. A number of potential EC risk biomarkers have been proposed, including heightened pro-inflammatory cytokines and adipokines. To evaluate if bariatric surgery can serve as a means for altering levels of such EC risk biomarkers, we investigated changes in these biomarkers after weight loss. METHODS: Blood samples were collected pre-operatively and 6months post-operatively in 107 female bariatric surgery patients aged 18-72years. Wilcoxon signed-rank tests were used to compare biomarker levels (measured using xMAP immunoassays) pre- and post-surgery. Normative comparisons were implemented to contrast 6-month post-surgery biomarker levels to levels in a sample of 74 age-matched non-obese women. Linear regression was used to evaluate the relationship between biomarker expression at baseline and 6months post-surgery and the relationship between race and biomarker levels. RESULTS: On average, participants lost 30.15kg (SD: 12.26) after the bariatric intervention. Levels of C-peptide, insulin, CRP, leptin, IL-1Rα, and IL-6 significantly decreased, while levels of SHBG, IGFBP1, and adiponectin significantly increased with weight loss. Normative comparisons showed the levels of SHBG, C-peptide, insulin, IGFBP1, adiponectin, CRP, and TNFα after bariatric intervention approached the level of markers in comparison group. Multiple regression analyses revealed significant relationships between changes in BMI and changes in biomarker levels. The changes in IL-1Rα were significantly associated with race. CONCLUSIONS: Our findings demonstrate that normalization of EC risk biomarkers can be achieved with bariatric surgery. Improved understanding of biological mechanisms associated with weight loss may inform preventive strategies for EC.

Withaferin A inhibits in vivo growth of breast cancer cells accelerated by Notch2 knockdown.

The present study offers novel insights into the molecular circuitry of accelerated in vivo tumor growth by Notch2 knockdown in triple-negative breast cancer (TNBC) cells. Therapeutic vulnerability of Notch2-altered growth to a small molecule (withaferin A, WA) is also demonstrated. MDA-MB-231 and SUM159 cells were used for the xenograft studies. A variety of technologies were deployed to elucidate the mechanisms underlying tumor growth augmentation by Notch2 knockdown and its reversal by WA, including Fluorescence Molecular Tomography for measurement of tumor angiogenesis in live mice, Seahorse Flux analyzer for ex vivo measurement of tumor metabolism, proteomics, and Luminex-based cytokine profiling. Stable knockdown of Notch2 resulted in accelerated in vivo tumor growth in both cells reflected by tumor volume and/or latency. For example, the wet tumor weight from mice bearing Notch2 knockdown MDA-MB-231 cells was about 7.1-fold higher compared with control (P < 0.0001). Accelerated tumor growth by Notch2 knockdown was highly sensitive to inhibition by a promising steroidal lactone (WA) derived from a medicinal plant. Molecular underpinnings for tumor growth intensification by Notch2 knockdown included compensatory increase in Notch1 activation, increased cellular proliferation and/or angiogenesis, and increased plasma or tumor levels of growth stimulatory cytokines. WA administration reversed many of these effects providing explanation for its remarkable anti-cancer efficacy. Notch2 functions as a tumor growth suppressor in TNBC and WA offers a novel therapeutic strategy for restoring this function.

Tumor-associated Neutrophils and Malignant Progression in Intraductal Papillary Mucinous Neoplasms: An Opportunity for Identification of High-risk Disease.

OBJECTIVES: To evaluate the association of tumor-associated neutrophils (TANs) with malignant progression in intraductal papillary mucinous neoplasms (IPMNs) and to study the cyst fluid from these lesions for biomarkers of the inflammation-carcinogenesis association. BACKGROUND: There is a strong link between TANs and malignant progression. Inflammatory mediators released by these cells may be a measurable surrogate marker of this progression. METHODS: We evaluated 78 resected IPMNs (2004-2013). Lesions were divided into the low-risk (low- and intermediate-grade dysplasia: n = 48) and high-risk (high-grade dysplasia and invasive carcinoma: n = 30) groups. TANs were assessed and categorized (negative, low, and high). A multiplexed assay was performed to evaluate 87 different cyst fluid proteins, including cyst fluid inflammatory markers (CFIMs), as possible surrogate markers for parenchymal inflammation. RESULTS: Significant positive correlation between grade of dysplasia and TANs was found. High levels of TANs were identified in 2%, 33%, and 89% of the lesions when stratified by grade of dysplasia into low/intermediate-grade dysplasia, high-grade dysplasia, and invasive carcinoma, respectively (P < 0.001). Higher grades of dysplasia were also found to have positive correlation with 29 of the measured proteins, of which 23 (79%) were CFIMs. Higher levels of TANs correlated with higher levels of 18 CFIMs, of which 16 (89%) were also found to be associated with higher grades of dysplasia. CONCLUSIONS: In this study, TANs were strongly associated with malignant progression in IPMNs. Measurement of CFIMs may be a surrogate marker for IPMN progression and allow for the identification of high-risk disease.

Distinct age-matched serum biomarker profiles in patients with cutaneous T-cell lymphoma.

Immunological functions decline with age. Because MS/SzS predominately affects the elderly, it is important to distinguish age-related from cancer-specific changes. Also, MF and SzS are malignancies of CD4(+) T-lymphocytes, further compromising an immune state of the patients. The objectives of this study were to distinguish disease-specific immunological deterioration by performing comparative age-matched Luminex multiplex assessment of 34 serum biomarkers between patients with MF/SzS, HIV-infected individuals and normal controls. Controlling for age, expression level appears to significantly differ between patients with MF/SzS and controls for the following biomarkers: G-CSF, IL-5, MIP-1ß, TNF-α, VEGF, EOTAXIN, IL-8, IL-12, IL-2R, IP10, MCP-1, MIG, TNFR1 and TNFR2 (P < 0.05), while others showed normal age-related changes. Interestingly, cluster analysis placed MF/SzS profiles closer to HIV. This further underscores an immunologically compromised state of patients with MF/SzS and suggests its potential self-perpetuating role in disease progression.

An exploratory investigation of links between changes in adipokines and quality of life in individuals undergoing weight loss interventions: possible implications for cancer research.

OBJECTIVE: Obesity has been linked to a wide spectrum of malignancies, with the strongest association demonstrated for endometrial cancer. Although the mechanisms are not yet entirely clear, a number of risk biomarkers have been proposed, including altered adipokines. Systemic levels of these adipose derived molecules have also been linked in prior research to self-reported quality of life (QOL). The study objective was to examine the hypothesis that adipokine changes during intentional weight loss may be associated with changes in QOL. METHODS: Fifty-two female participants were selected from two behavioral weight loss trials (SMART and PREFER) on the basis of achieving successful weight loss at 6month assessment, availability of blood samples and completion of standard SF-36 QOL questionnaires. Levels of adiponectin, leptin, and resistin were measured using xMAP immunoassays. Changes in QOL were examined using linear regression models in relation to pre- and post-intervention changes in biomarker levels and BMI. RESULTS: Significant changes between pre- and post-intervention were observed for leptin. Controlling for baseline BMI, leptin was the only biomarker that predicted change in QOL (Physical Component Scale, PCS). Linear regression models demonstrated that leptin continued to be a significant predictor of change in PCS when other possible predictor variables were included in the model. CONCLUSIONS: This study is among the first to demonstrate that changes in PCS may be regulated by levels of both metabolic variables and adipokines. An improved understanding of biological mechanisms associated with weight loss and the role of QOL may help guide preventive strategies for obesity-associated cancers.

The design and methods of genetic studies on acute and chronic postoperative pain in patients after total knee replacement.

OBJECTIVE: Total knee replacement (TKR) is the treatment option of choice for the millions of individuals whose osteoarthritis pain can no longer be managed through non-invasive methods. Over 500,000 TKRs are performed annually in the United States. Although most patients report improvement in pain and functioning following TKR, up to 30% report persistent pain that interferes with daily function. However, the reasons for poor outcomes are not clear. To best determine which patients are at risk for pain post TKR, a detailed and comprehensive approach is needed. In this article, we present the methodology of a study designed to identify a set of genetic, proteomic, clinical, demographic, psychosocial, and psychophysical risk factors for severe acute and chronic pain post TKR. DESIGN: Prospective longitudinal observational study. SETTING: University Hospital System. SUBJECTS: Patients scheduled for unilateral TKR with a target number of 150. METHODS: Prior to surgery, we collect demographic, psychosocial, and pain data. Biological data, including blood samples for genetic analyses, and serum, urine, and joint fluid for cytokine assessment are collected intraoperatively. Pain assessments as well as medication use are collected during each of the three days postsurgery. Additionally, pain and psychosocial information is collected 6 and 12 months following surgery. CONCLUSIONS: This study, for the first time, captures the information on both genetic and "environmental" risk factors for acute and chronic pain post-TKR and has the potential to lead to the next step-multicenter large-scale studies on predictors and biomarkers of poor TKR outcomes as well as on tailored interventions and personalized medicine approaches for those at risk.

A molecular index for biological age identified from the metabolome and senescence-associated secretome in humans.

Unlike chronological age, biological age is a strong indicator of health of an individual. However, the molecular fingerprint associated with biological age is ill-defined. To define a high-resolution signature of biological age, we analyzed metabolome, circulating senescence-associated secretome (SASP)/inflammation markers and the interaction between them, from a cohort of healthy and rapid agers. The balance between two fatty acid oxidation mechanisms, ß-oxidation and ω-oxidation, associated with the extent of functional aging. Furthermore, a panel of 25 metabolites, Healthy Aging Metabolic (HAM) index, predicted healthy agers regardless of gender and race. HAM index was also validated in an independent cohort. Causal inference with machine learning implied three metabolites, ß-cryptoxanthin, prolylhydroxyproline, and eicosenoylcarnitine as putative drivers of biological aging. Multiple SASP markers were also elevated in rapid agers. Together, our findings reveal that a network of metabolic pathways underlie biological aging, and the HAM index could serve as a predictor of phenotypic aging in humans.

A Rigorous Multi-Laboratory Study of Known PDAC Biomarkers Identifies Increased Sensitivity and Specificity Over CA19-9 Alone.

A blood test that enables surveillance for early-stage pancreatic ductal adenocarcinoma (PDAC) is an urgent need. Independent laboratories have reported PDAC biomarkers that could improve biomarker performance over CA19-9 alone, but the performance of the previously reported biomarkers in combination is not known. Therefore, we conducted a coordinated case/control study across multiple laboratories using common sets of blinded training and validation samples (132 and 295 plasma samples, respectively) from PDAC patients and non-PDAC control subjects representing conditions under which surveillance occurs. We analyzed the training set to identify candidate biomarker combination panels using biomarkers across laboratories, and we applied the fixed panels to the validation set. The panels identified in the training set, CA19-9 with CA199.STRA, LRG1, TIMP-1, TGM2, THSP2, ANG, and MUC16.STRA, achieved consistent performance in the validation set. The panel of CA19-9 with the glycan biomarker CA199.STRA improved sensitivity from 0.44 with 0.98 specificity for CA19-9 alone to 0.71 with 0.98 specificity (p < 0.001, 1000-fold bootstrap). Similarly, CA19-9 combined with the protein biomarker LRG1 and CA199.STRA improved specificity from 0.16 with 0.94 sensitivity for CA19-9 to 0.65 with 0.89 sensitivity (p < 0.001, 1000-fold bootstrap). We further validated significantly improved performance using biomarker panels that did not include CA19-9. This study establishes the effectiveness of a coordinated study of previously discovered biomarkers and identified panels of those biomarkers that significantly increased the sensitivity and specificity of early-stage PDAC detection in a rigorous validation trial.

Circulating prolactin levels and risk of epithelial ovarian cancer.

PURPOSE: Indirect evidence from experimental and epidemiological studies suggests that prolactin may be involved in ovarian cancer development. However, the relationship between circulating prolactin levels and risk of ovarian cancer is unknown. METHODS: We conducted a nested case-control study of 230 cases and 432 individually matched controls within three prospective cohorts to evaluate whether pre-diagnostic circulating prolactin is associated with subsequent risk of ovarian cancer. We also assessed whether lifestyle and reproductive factors are associated with circulating prolactin among controls. RESULTS: Prolactin levels were significantly lower among post- versus pre-menopausal women, parous versus nulliparous women, and past versus never users of oral contraceptives in our cross-sectional analysis of controls. In our nested case-control study, we observed a non-significant positive association between circulating prolactin and ovarian cancer risk (OR(Q4vsQ1) 1.56, 95 % CI 0.94, 2.63, p trend 0.15). Our findings were similar in multivariate-adjusted models and in the subgroup of women who donated blood ≥5 years prior to diagnosis. We observed a significant positive association between prolactin and risk for the subgroup of women with BMI ≥25 kg/m(2) (OR(Q4vsQ1) 3.10, 95 % CI 1.39, 6.90), but not for women with BMI <25 kg/m(2) (OR(Q4vsQ1) 0.81, 95 % CI 0.40, 1.64). CONCLUSIONS: Our findings suggest that prolactin may be associated with increased risk of ovarian cancer, particularly in overweight/obese women. Factors associated with reduced risk of ovarian cancer, such as parity and use of oral contraceptives, were associated with lower prolactin levels, which suggests that modulation of prolactin may be a mechanism underlying their association with risk.

Predicting chronic postsurgical pain: current evidence and a novel program to develop predictive biomarker signatures.

ABSTRACT: Chronic pain affects more than 50 million Americans. Treatments remain inadequate, in large part, because the pathophysiological mechanisms underlying the development of chronic pain remain poorly understood. Pain biomarkers could potentially identify and measure biological pathways and phenotypical expressions that are altered by pain, provide insight into biological treatment targets, and help identify at-risk patients who might benefit from early intervention. Biomarkers are used to diagnose, track, and treat other diseases, but no validated clinical biomarkers exist yet for chronic pain. To address this problem, the National Institutes of Health Common Fund launched the Acute to Chronic Pain Signatures (A2CPS) program to evaluate candidate biomarkers, develop them into biosignatures, and discover novel biomarkers for chronification of pain after surgery. This article discusses candidate biomarkers identified by A2CPS for evaluation, including genomic, proteomic, metabolomic, lipidomic, neuroimaging, psychophysical, psychological, and behavioral measures. Acute to Chronic Pain Signatures will provide the most comprehensive investigation of biomarkers for the transition to chronic postsurgical pain undertaken to date. Data and analytic resources generatedby A2CPS will be shared with the scientific community in hopes that other investigators will extract valuable insights beyond A2CPS's initial findings. This article will review the identified biomarkers and rationale for including them, the current state of the science on biomarkers of the transition from acute to chronic pain, gaps in the literature, and how A2CPS will address these gaps.

Longitudinal evaluation of cancer-associated biomarkers before and after weight loss in RENEW study participants: implications for cancer risk reduction.

INTRODUCTION: Obesity is a major risk factor for the development of endometrial cancer (EC). An improved understanding of biologic mechanisms associated with weight loss, including alteration in inflammation, hormonal balance, and cancer antigens expression may lead to the development of effective cancer prevention strategies. The goal of this study was to explore longitudinal biomarker changes in obese women who underwent weight loss intervention, testing the hypothesis biomarker levels can be altered through intentional weight loss. METHODS: Serum samples from 89 participants with Class II and Class III obesity and 43 non morbidly obese comparisons were obtained in Re-Energize with Nutrition, Exercise and Weight Loss (RENEW) study as previously reported. Twenty-one bead-based xMAP immunoassays were utilized, including cancer-associated antigens, cytokines, chemokines, and hormones. One-way repeated measures ANOVA was used to examine the association between changes in biomarker expression levels over time (baseline, 6 months and 12 months). Linear mixed effects models were used to examine longitudinal relationships between biomarker expression levels. RESULTS: Mean levels of VEGF, soluble E-selectin, GH, adiponectin, IL-6, IL-7, CA-125, and IGFBP-1 significantly differed between time periods. In adjusted mixed linear models, decreasing BMI was significantly associated with lower levels of soluble E-selectin and IL-6 and increases in GH, adiponectin, and IGFBP-1. CONCLUSIONS: This is one of the first efforts to explore changes in cancer-associated biomarkers in a cohort of weight loss research participants at high risk for EC development. Our findings demonstrate that changes in the expression of markers can be achieved with weight loss intervention.

Protein biomarkers of ovarian cancer: the forest and the trees.

The goal of effective population-based screening for ovarian cancer remains elusive despite intense efforts aimed at improving upon biomarker and imaging modalities. While dozens of potential serum biomarkers for ovarian cancer have been identified in recent years, none have yet overcome the limitations that have hindered the clinical use of CA-125. Avenues of opportunity in biomarker development are emerging as investigators are beginning to appreciate the significance of remote, as well as local or regional, sources of biomarkers in the construction of diagnostic panels, as well as the importance of evaluating biomarkers in prediagnostic settings. As the list of candidate biomarkers of ovarian cancer continues to grow, refinements in the methods through which specific proteins are selected for further development as components of diagnostic panels are desperately sought. Such refinements must take into account both the bioinformatic and biological significance of each candidate. Approaches incorporating these considerations may potentially overcome the challenges to early detection posed by the histological heterogeneity of ovarian cancer. Here, we review the recent progress achieved in efforts to develop diagnostic biomarker panels for ovarian cancer and discuss the challenges that remain.

The quest for ovarian cancer screening biomarkers: are we on the right road?

Recent discoveries in the field of biomarkers for screening and early detection of ovarian cancer (OC) identified current needs for biomarkers capable of recognizing preclinical disease. The suggested approaches are (1) development of highly analytically sensitive CA 125 assays capable of detecting CA 125 released from small cancerous and preneoplastic lesions; (2) identification of biomarkers effective in CA 125-negative cases; and (3) performing biomarker discovery in samples obtained from patients with prophylactic bilateral salpingo-oophorectomy with pathologically confirmed preneoplastic lesions, or in appropriate animal models of ovarian cancer.

Differential diagnosis of a pelvic mass: improved algorithms and novel biomarkers.

More than 200,000 women undergo exploratory surgery for a pelvic mass in the United States each year and 13%-21% of pelvic lesions are found to be malignant. Individual reports and meta-analysis indicate better outcomes when cancer surgery is performed by gynecologic oncologists. Despite the advantages provided by more thorough staging and cytoreductive surgery, only 30%-50% of women with ovarian cancer are referred to surgeons with specialized training in the United States. Imaging, menopausal status and biomarkers can aid in distinguishing malignant from benign pelvic masses to inform decisions regarding appropriate referral. The risk of malignancy index (RMI) uses ultrasound, menopausal status and CA125 and has been utilized in the United Kingdom for two decades, providing sensitivity that has ranged from 71%-88% and specificity it from 97%-74% for identifying patients with malignant disease. Criteria have been established by the Society of Gynecology Oncology and American College of Obstetrics and Gynecology for referral to a gynecologic oncologist, but these have lower sensitivity and specificity than the RMI. Recently, two new algorithms have been developed to identify women at sufficiently high risk to prompt referral to a specialized surgeon. The OVA1 multivariate index incorporates imaging, menopausal status, CA125 and four other proteomic biomarkers. Use of OVA1 provides 85%-96% sensitivity at 28%-40% specificity depending upon menopausal status. The negative predictive value for women judged to be at low risk is 94%-96%. The risk of malignancy algorithm (ROMA) includes CA125, human epididymal protein 4 and menopausal status, but not imaging results. The ROMA has yielded 93%-94% sensitivity at 75% specificity with a negative predictive value of 93%-98%. In a direct comparison, ROMA has achieved greater sensitivity (94%) than the RMI (75%) at 75% specificity. OVA1 has not been compared directly to ROMA, but is likely to be as sensitive, but substantially less specific. Both algorithms have high negative predictive values 94%-98%. Although a difference in specificity should not affect patient outcomes, it could affect distribution of medical resources.

Stacking Machine Learning Algorithms for Biomarker-Based Preoperative Diagnosis of a Pelvic Mass.

OBJECTIVE: To identify the most predictive parameters of ovarian malignancy and develop a machine learning (ML) based algorithm to preoperatively distinguish between a benign and malignant pelvic mass. METHODS: Retrospective study of 70 predictive parameters collected from 140 women with a pelvic mass. The women were split into a 3:1 "training" to "testing" dataset. Feature selection was performed using Gini impurity through an embedded random forest model and principal component analysis. Nine unique ML classifiers were assessed across a variety of model-specific hyperparameters using 25 bootstrap resamples of the training data. Model predictions were then combined into an ensemble stack by LASSO regression. The final ensemble stack and individual classifiers were then applied to the testing dataset to assess model performance. RESULTS: Feature selection identified HE4, CA125, and transferrin as three predictive parameters of malignancy. Assessment of the ensemble stack on the testing dataset outperformed all individual ML classifiers in predicting malignancy. The ensemble stack demonstrated an accuracy of 97.1%, a receiver operating characteristic (ROC) area under the curve (AUC) of 0.951, and a sensitivity of 93.3% with a specificity of 100%. CONCLUSIONS: Combining the measurement of three distinct biomarkers with the stacking of multiple ML classifiers into an ensemble can provide valuable preoperative diagnostic predictions for patients with a pelvic mass.