Variables affecting CA15.3 tumor antigen expression and antibodies against it in female National Health and Nutritional Survey (NHANES) participants.

BACKGROUND: Cancers of ductal origin often express glycoprotein mucin 1 (MUC1), also known as CA15.3, with higher levels leading to poorer prognosis. Conversely, anti-MUC1 antibodies develop in some patients leading to better prognosis. We sought to identify epidemiologic factors associated with CA15.3 antigen or antibody levels. METHODS: Levels of CA15.3 antigen and anti-CA15.3 IgG antibodies were measured in archived sera from 2302 mostly healthy women from the National Health and Nutritional Survey (NHANES); and epidemiologic predictors of their levels were examined using multivariate and correlational analyses. RESULTS: Among racial groups, Black women had the highest level of CA15.3 antigen and lowest levels of antibodies. Increasing BMI and current smoking were associated with low anti-CA15.3 antibody levels. Low CA15.3 antigen levels were seen in oral contraceptive (OC) users and high levels in women who were pregnant or lactating at the time of blood collection, with the latter group also having high antibody levels. Past reproductive events associated with high antigen levels included: later age at menarche, having given birth, and history of endometriosis. Lower antigen levels were seen with increasing duration of OC use. Anti-CA15.3 antibody levels decreased with an increasing estimated number of ovulatory years. CONCLUSION: Key determinants of CA.15.3 antigen or antibody levels include: race, BMI, smoking, later menarche, childbirth, number of ovulatory cycles, and endometriosis. IMPACT: This study supports the premise that known epidemiologic factors affecting risk for or survival after MUC1-expressing cancers may, at least partially, operate through their association with CA15.3 antigen or antibody levels.

Racial and ethnic differences in epithelial ovarian cancer risk: an analysis from the Ovarian Cancer Association Consortium.

BACKGROUND: Limited estimates exist on risk factors for epithelial ovarian cancer (EOC) in Asian, Hispanic, and Native Hawaiian/Pacific Islander (NHPI) women. METHODS: Participants included 1734 Asian (785 cases, 949 controls), 266 NHPI (99 cases, 167 controls), 1149 Hispanic (505 cases, 644 controls), and 24,189 White (9,981 cases, 14,208 controls) women from 11 studies in the Ovarian Cancer Association Consortium. Logistic regression models estimated odds ratios (ORs) and 95% confidence intervals (CIs) for risk associations by race and ethnicity. RESULTS: Heterogeneity in EOC risk associations by race and ethnicity (p ≤ 0.02) was observed for oral contraceptive (OC) use, parity, tubal ligation and smoking. We observed inverse associations with EOC risk for OC use and parity across all groups; associations were strongest in NHPI and Asian women. The inverse association for tubal ligation with risk was most pronounced for NHPI participants (OR=0.25, 95% CI 0.13-0.48), versus Asian and White participants, respectively (OR=0.68, 95% CI 0.51-0.90; OR=0.78, 95% CI 0.73-0.85). CONCLUSIONS: Differences in EOC risk factor associations were observed across racial and ethnic groups, which could in part be due to varying prevalence of EOC histotypes. Inclusion of greater diversity in future studies is essential to inform prevention strategies.

Sialyl-Tn serves as a potential therapeutic target for ovarian cancer.

BACKGROUND: Ovarian cancer remains the deadliest of the gynecologic cancers in the United States. There have been limited advances in treatment strategies that have seen marked increases in overall survival. Thus, it is essential to continue developing and validating new treatment strategies and markers to identify patients who would benefit from the new strategy. In this report, we sought to further validate applications for a novel humanized anti-Sialyl Tn antibody-drug conjugate (anti-STn-ADC) in ovarian cancer. METHODS: We aimed to further test a humanized anti-STn-ADC in sialyl-Tn (STn) positive and negative ovarian cancer cell line, patient-derived organoid (PDO), and patient-derived xenograft (PDX) models. Furthermore, we sought to determine whether serum STn levels would reflect STn positivity in the tumor samples enabling us to identify patients that an anti-STn-ADC strategy would best serve. We developed a custom ELISA with high specificity and sensitivity, that was used to assess whether circulating STn levels would correlate with stage, progression-free survival, overall survival, and its value in augmenting CA-125 as a diagnostic. Lastly, we assessed whether the serum levels reflected what was observed via immunohistochemical analysis in a subset of tumor samples. RESULTS: Our in vitro experiments further define the specificity of the anti-STn-ADC. The ovarian cancer PDO, and PDX models provide additional support for an anti-STn-ADC-based strategy for targeting ovarian cancer. The custom serum ELISA was informative in potential triaging of patients with elevated levels of STn. However, it was not sensitive enough to add value to existing CA-125 levels for a diagnostic. While the ELISA identified non-serous ovarian tumors with low CA-125 levels, the sample numbers were too small to provide any confidence the STn ELISA would meaningfully add to CA-125 for diagnosis. CONCLUSIONS: Our preclinical data support the concept that an anti-STn-ADC may be a viable option for treating patients with elevated STn levels. Moreover, our STn-based ELISA could complement IHC in identifying patients with whom an anti-STn-based strategy might be more effective.

Genome-wide association analyses of ovarian cancer patients undergoing primary debulking surgery identify candidate genes for residual disease.

Survival from ovarian cancer depends on the resection status after primary surgery. We performed genome-wide association analyses for resection status of 7705 ovarian cancer patients, including 4954 with high-grade serous carcinoma (HGSOC), to identify variants associated with residual disease. The most significant association with resection status was observed for rs72845444, upstream of MGMT, in HGSOC (p = 3.9 × 10-8). In gene-based analyses, PPP2R5C was the most strongly associated gene in HGSOC after stage adjustment. In an independent set of 378 ovarian tumours from the AGO-OVAR 11 study, variants near MGMT and PPP2R5C correlated with methylation and transcript levels, and PPP2R5C mRNA levels predicted progression-free survival in patients with residual disease. MGMT encodes a DNA repair enzyme, and PPP2R5C encodes the B56γ subunit of the PP2A tumour suppressor. Our results link heritable variation at these two loci with resection status in HGSOC.

Incessant ovulation: a review of its importance in predicting cancer risk.

Estrous cycles are recurring changes in therian mammals induced by estrogen, progesterone, and other hormones culminating in endometrial proliferation, ovulation, and implantation if fertilization occurred. In women, the estrous cycle is the menstrual cycle; but, unlike most mammals, the end of an infertile cycle is marked by endometrial sloughing and the start of another without an anestrous phase. Women stop cycling at menopause, while in most mammals, cycles continue until death. Epidemiologic studies identified menarche, menopause, births, lactation, and oral contraceptive (OC) use as key risk factors for ovarian, breast, and endometrial cancers. A composite variable was created to estimate the number of cycles not interrupted by events that stop ovulation. Captured by the phrase "incessant ovulation", repetitive cycles were first postulated to affect ovarian cancer risk and later extended to breast and endometrial cancers. These associations could be explained by cumulative effects of repetitive tissue changes within reproductive organs, immune consequences of repetitive ovulation through the glycoprotein mucin 1, and residual effects of past ovulations that enhance ovarian production of testosterone. The latter two pathways could affect the risk for cancers in other organs not considered "reproductive".

A framework for assessing interactions for risk stratification models: the example of ovarian cancer.

Generally, risk stratification models for cancer use effect estimates from risk/protective factor analyses that have not assessed potential interactions between these exposures. We have developed a 4-criterion framework for assessing interactions that includes statistical, qualitative, biological, and practical approaches. We present the application of this framework in an ovarian cancer setting because this is an important step in developing more accurate risk stratification models. Using data from 9 case-control studies in the Ovarian Cancer Association Consortium, we conducted a comprehensive analysis of interactions among 15 unequivocal risk and protective factors for ovarian cancer (including 14 non-genetic factors and a 36-variant polygenic score) with age and menopausal status. Pairwise interactions between the risk/protective factors were also assessed. We found that menopausal status modifies the association among endometriosis, first-degree family history of ovarian cancer, breastfeeding, and depot-medroxyprogesterone acetate use and disease risk, highlighting the importance of understanding multiplicative interactions when developing risk prediction models.

Clinical parameters affecting survival outcomes in patients with low-grade serous ovarian carcinoma: an international multicentre analysis.

BACKGROUND: Women with low-grade ovarian serous carcinoma (LGSC) benefit from surgical treatment; however, the role of chemotherapy is controversial. We examined an international database through the Ovarian Cancer Association Consortium to identify factors that affect survival in LGSC. METHODS: We performed a retrospective cohort analysis of patients with LGSC who had had primary surgery and had overall survival data available. We performed univariate and multivariate analyses of progression-free survival and overall survival, and generated Kaplan-Meier survival curves. RESULTS: Of the 707 patients with LGSC, 680 (96.2%) had available overall survival data. The patients' median age overall was 54 years. Of the 659 patients with International Federation of Obstetrics and Gynecology stage data, 156 (23.7%) had stage I disease, 64 (9.7%) had stage II, 395 (59.9%) had stage III, and 44 (6.7%) had stage IV. Of the 377 patients with surgical data, 200 (53.0%) had no visible residual disease. Of the 361 patients with chemotherapy data, 330 (91.4%) received first-line platinum-based chemotherapy. The median follow-up duration was 5.0 years. The median progression-free survival and overall survival were 43.2 months and 110.4 months, respectively. Multivariate analysis indicated a statistically significant impact of stage and residual disease on progression-free survival and overall survival. Platinum-based chemotherapy was not associated with a survival advantage. CONCLUSION: This multicentre analysis indicates that complete surgical cytoreduction to no visible residual disease has the most impact on improved survival in LGSC. This finding could immediately inform and change practice.

Estimated Ovulatory Years Prior to Menopause and Postmenopausal Endogenous Hormone Levels.

BACKGROUND: Lifetime ovulatory years (LOY) is estimated by the difference between ages at menopause and menarche subtracting time for events interrupting ovulation. We tested whether LOY influences sex hormone levels in postmenopausal women with at least one intact ovary not using hormones. METHODS: Estradiol, estrone, estrone sulfate, total testosterone, dehydroepiandrostendione sulfate, prolactin, and sex hormone binding globulin were measured in 1,976 postmenopausal women from the Nurses' Health Study. Associations of age, body mass index (BMI), smoking, alcohol use, and other factors on hormones were assessed by t tests and ANOVA. Linear regression was used to assess multivariable adjusted associations between LOY and hormones and trends in hormone levels per 5-year increases in LOY were estimated. RESULTS: Women averaged 61.4 years old, 11.0 years since menopause, with BMI of 25.8 kg/m2. A total of 13.6% had irregular cycles, 17.5% hysterectomy, 6.4% unilateral oophorectomy, and 13.8% were current smokers. Variables associated with one or more hormone levels were included as covariates. Each 5-year increase in LOY was significantly associated with a 5.2% increase in testosterone in women with BMI < 25 kg/m2 and a 7.4% increase in testosterone and 7.3% increase in estradiol in women with above-average BMI. CONCLUSIONS: This is the first study to show that greater LOY is associated with higher testosterone in postmenopausal women and higher estradiol in those with elevated BMI, suggesting accumulation of functioning stromal and thecal cells from repeated ovulations and peripheral conversion of testosterone. IMPACT: A possible explanation for why greater LOY increases risk for breast, endometrial, and ovarian cancer is offered.

Lifetime ovulatory years and risk of epithelial ovarian cancer: a multinational pooled analysis.

BACKGROUND: The role of ovulation in epithelial ovarian cancer (EOC) is supported by the consistent protective effects of parity and oral contraceptive use. Whether these factors protect through anovulation alone remains unclear. We explored the association between lifetime ovulatory years (LOY) and EOC. METHODS: LOY was calculated using 12 algorithms. Odds ratios (ORs) and 95% confidence intervals (CIs) estimated the association between LOY or LOY components and EOC among 26 204 control participants and 21 267 case patients from 25 studies. To assess whether LOY components act through ovulation suppression alone, we compared beta coefficients obtained from regression models with expected estimates assuming 1 year of ovulation suppression has the same effect regardless of source. RESULTS: LOY was associated with increased EOC risk (OR per year increase = 1.014, 95% CI = 1.009 to 1.020 to OR per year increase = 1.044, 95% CI = 1.041 to 1.048). Individual LOY components, except age at menarche, also associated with EOC. The estimated model coefficient for oral contraceptive use and pregnancies were 4.45 times and 12- to 15-fold greater than expected, respectively. LOY was associated with high-grade serous, low-grade serous, endometrioid, and clear cell histotypes (ORs per year increase = 1.054, 1.040, 1.065, and 1.098, respectively) but not mucinous tumors. Estimated coefficients of LOY components were close to expected estimates for high-grade serous but larger than expected for low-grade serous, endometrioid, and clear cell histotypes. CONCLUSIONS: LOY is positively associated with nonmucinous EOC. Differences between estimated and expected model coefficients for LOY components suggest factors beyond ovulation underlie the associations between LOY components and EOC in general and for non-HGSOC.

CCNE1 and survival of patients with tubo-ovarian high-grade serous carcinoma: An Ovarian Tumor Tissue Analysis consortium study.

BACKGROUND: Cyclin E1 (CCNE1) is a potential predictive marker and therapeutic target in tubo-ovarian high-grade serous carcinoma (HGSC). Smaller studies have revealed unfavorable associations for CCNE1 amplification and CCNE1 overexpression with survival, but to date no large-scale, histotype-specific validation has been performed. The hypothesis was that high-level amplification of CCNE1 and CCNE1 overexpression, as well as a combination of the two, are linked to shorter overall survival in HGSC. METHODS: Within the Ovarian Tumor Tissue Analysis consortium, amplification status and protein level in 3029 HGSC cases and mRNA expression in 2419 samples were investigated. RESULTS: High-level amplification (>8 copies by chromogenic in situ hybridization) was found in 8.6% of HGSC and overexpression (>60% with at least 5% demonstrating strong intensity by immunohistochemistry) was found in 22.4%. CCNE1 high-level amplification and overexpression both were linked to shorter overall survival in multivariate survival analysis adjusted for age and stage, with hazard stratification by study (hazard ratio [HR], 1.26; 95% CI, 1.08-1.47, p = .034, and HR, 1.18; 95% CI, 1.05-1.32, p = .015, respectively). This was also true for cases with combined high-level amplification/overexpression (HR, 1.26; 95% CI, 1.09-1.47, p = .033). CCNE1 mRNA expression was not associated with overall survival (HR, 1.00 per 1-SD increase; 95% CI, 0.94-1.06; p = .58). CCNE1 high-level amplification is mutually exclusive with the presence of germline BRCA1/2 pathogenic variants and shows an inverse association to RB1 loss. CONCLUSION: This study provides large-scale validation that CCNE1 high-level amplification is associated with shorter survival, supporting its utility as a prognostic biomarker in HGSC.

Effects of risk factors for ovarian cancer in women with and without endometriosis.

OBJECTIVE: To evaluate the associations between 10 well-established ovarian cancer risk factors and risk of ovarian cancer among women with vs. without endometriosis. DESIGN: Pooled analysis of 9 case-control studies in the Ovarian Cancer Association Consortium. SETTING: Population-based. PATIENT(S): We included 8,500 women with ovarian cancer, 13,592 control women. INTERVENTION(S): Ten well-established ovarian cancer risk factors. MAIN OUTCOME MEASURE(S): Risk of ovarian cancer for women with and without endometriosis. RESULT(S): Most risk factor-ovarian cancer associations were similar when comparing women with and without endometriosis, and no interactions were statistically significant. However, body mass index (BMI) 25-<30 kg/m2 was associated with increased ovarian cancer risk among women with endometriosis (odds ratio [OR] = 1.27, 95% confidence interval [CI] 1.00-1.60), but not associated with the risk among women without endometriosis (OR = 0.97; 95% CI, 0.91-1.05) when compared with BMI 18.5-<25 kg/m2; an increased risk was observed for a BMI ≥30 kg/m2, although there was little difference comparing women with endometriosis (OR = 1.21; 95% CI, 0.94-1.57) to women without (OR = 1.13; 95% CI, 1.04-1.22) (P-interaction = .51). Genital talcum powder use and long-term menopausal estrogen-only therapy use showed increased ovarian cancer risk, but risk appeared greater for those with endometriosis vs. those without (genital talcum powder: OR = 1.38; 95% CI, 1.04-1.84 vs. OR = 1.12; 95% CI, 1.01-1.25, respectively; ≥10 years of estrogen-only therapy: OR = 1.88; 95% CI, 1.09-3.24 vs. OR = 1.42; 95% CI, 1.14-1.76, respectively); neither of these interactions were statistically significant (P-interaction = .65 and P-interaction = .96, respectively). CONCLUSION(S): The associations between ovarian cancer and most risk factors were similar among women with and without endometriosis. However, there was some suggestion of differences by endometriosis status for BMI, menopausal hormone therapy use, and genital talcum powder use, highlighting the complexity of ovarian cancer etiology.

Validated Preclinical Mouse Model for Therapeutic Testing against Multidrug-Resistant Pseudomonas aeruginosa Strains.

The rise in infections caused by antibiotic-resistant bacteria is outpacing the development of new antibiotics. The ESKAPE pathogens (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter species) are a group of clinically important bacteria that have developed resistance to multiple antibiotics and are commonly referred to as multidrug resistant (MDR). The medical and research communities have recognized that, without new antimicrobials, infections by MDR bacteria will soon become a leading cause of morbidity and death. Therefore, there is an ever-growing need to expedite the development of novel antimicrobials to combat these infections. Toward this end, we set out to refine an existing mouse model of pulmonary Pseudomonas aeruginosa infection to generate a robust preclinical tool that can be used to rapidly and accurately predict novel antimicrobial efficacy. This refinement was achieved by characterizing the virulence of a panel of genetically diverse MDR P. aeruginosa strains in this model, by both 50% lethal dose (LD50) analysis and natural history studies. Further, we defined two antibiotic regimens (aztreonam and amikacin) that can be used as comparators during the future evaluation of novel antimicrobials, and we confirmed that the model can effectively differentiate between successful and unsuccessful treatments, as predicted by in vitro inhibitory data. This validated model represents an important tool in our arsenal to develop new therapies to combat MDR P. aeruginosa strains, with the ability to provide rapid preclinical evaluation of novel antimicrobials and support data from clinical studies during the investigational drug development process. IMPORTANCE The prevalence of antibiotic resistance among bacterial pathogens is a growing problem that necessitates the development of new antibiotics. Preclinical animal models are important tools to facilitate and speed the development of novel antimicrobials. Successful outcomes in animal models not only justify progression of new drugs into human clinical trials but also can support FDA decisions if clinical trial sizes are small due to a small population of infections with specific drug-resistant strains. However, in both cases the preclinical animal model needs to be well characterized and provide robust and reproducible data. Toward this goal, we have refined an existing mouse model to better predict the efficacy of novel antibiotics. This improved model provides an important tool to better predict the clinical success of new antibiotics.

Factors Influencing the Results of COVID-19 Case Outreach-Results From a California Case Investigation/Contact Tracing Program.

CONTEXT: Considerable research has examined impacts of case investigation and contact tracing (CI/CT) programs on the spread of infectious diseases such as COVID-19, but there are few reports on factors affecting the ability of these programs to obtain interviews and acquire key information. OBJECTIVE: To investigate programmatic and case-specific factors associated with CI outcomes using data from the Public Health Institute's Tracing Health CI/CT program. Analyses were designed to detect variability in predictors of whether interviews and key information were obtained rather than quantify specific relationships. DESIGN: Logistic regression models examined variability in the predictive value of interview timeliness and respondent characteristics on outreach outcomes and interview results. SETTING AND PARTICIPANTS: Participants were members of a large California health care network with a positive laboratory test for COVID-19 and outreach from January 1 to July 31, 2021. MAIN OUTCOME MEASURES: The primary outcome was the result of outreach attempts: completed interview, refused interview, or failure to reach the infected person. Secondary outcomes considered whether respondents provided information on symptom onset, employment, and contact information or a reason for declining to provide information, and whether resource support was requested or accepted. RESULTS: Of 9391 eligible records, 65.6% were for completed interviews, 6.0% were refusals, and 28.3% were failed outreach. One-third of respondents (36.7%) provided information on contacts (mean = 0.97 contacts per respondent, 2.6 for those naming at least 1). Privacy concerns were the most common reasons for not providing contact information. Among respondent characteristics and interview timeliness, only race and number of symptoms showed statistically significant effects in all adjusted analyses. CONCLUSIONS: Significant variation existed in outreach outcomes by subject characteristics and interview timeliness. CI/CT programs carefully focused to characteristics and needs of specific communities will likely have the greatest impact on the spread of COVID-19 and other communicable diseases.

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.

A Translational Model to Improve Early Detection of Epithelial Ovarian Cancers.

Neural network analyses of circulating miRNAs have shown potential as non-invasive screening tests for ovarian cancer. A clinically useful test would detect occult disease when complete cytoreduction is most feasible. Here we used murine xenografts to sensitize a neural network model to detect low volume disease and applied the model to sera from 75 early-stage ovarian cancer cases age-matched to 200 benign adnexal masses or healthy controls. The 14-miRNA model efficiently discriminated tumor bearing animals from controls with 100% sensitivity down to tumor inoculums of 50,000 cells. Among early-stage patient samples, the model performed well with 73% sensitivity at 91% specificity. Applied to a population with 1% disease prevalence, we hypothesize the model would detect most early-stage ovarian cancers while maintaining a negative predictive value of 99.97% (95% CI 99.95%-99.98%). Overall, this supports the concept that miRNAs may be useful as screening markers for early-stage disease.

Ovarian Cancer Ascites Inhibits Transcriptional Activation of NK Cells Partly through CA125.

Malignant ascites is a common clinical problem in ovarian cancer. NK cells are present in the ascites, but their antitumor activity is inhibited. The underlying mechanisms of the inhibition have yet to be fully elucidated. Using an Fcγ receptor-mediated NK cell activation assay, we show that ascites from ovarian cancer patients potently inhibits NK cell activation. Part of the inhibitory activity is mediated by CA125, a mucin 16 fragment shed from ovarian cancer tumors. Moreover, transcriptional analyses by RNA sequencing reveal upregulation of genes involved in multiple metabolic pathways but downregulation of genes involved in cytotoxicity and signaling pathways in NK cells purified from ovarian cancer patient ascites. Transcription of genes involved in cytotoxicity pathways are also downregulated in NK cells from healthy donors after in vitro treatment with ascites or with a CA125-enriched protein fraction. These results show that ascites and CA125 inhibit antitumor activity of NK cells at transcriptional levels by suppressing expression of genes involved in NK cell activation and cytotoxicity. Our findings shed light on the molecular mechanisms by which ascites inhibits the activity of NK cells and suggest possible approaches to reactivate NK cells for ovarian cancer immunotherapy.

Application of a novel microscopic technique for quantifying CA125 binding to circulating mononuclear cells in longitudinal specimens during treatment for ovarian cancer.

BACKGROUND: Measurement of serum CA125, an antigenic fragment of human mucin 16 (MUC16), is used to monitor the clinical progression of epithelial ovarian cancer (EOC). However, rather than simply a passive marker reflecting tumor burden, MUC16 may have a more active role by binding to immune cells and altering their tumor response. We developed a research tool to measure MUC16-binding to the surfaces of peripheral blood mononuclear cell (PBMC) subtypes and tested its research value using specimens collected serially from a woman being treated for high grade serous EOC. METHODS: Cryopreserved PBMCs were mixed with anti-CA125 antibody-labeled plasmonic gold nanoparticles (PNPs) to detect cell surface MUC16-binding along with fluorescent stains to identify B cells, NK cells, NK-T cells, T cells, and monocytes. From 3D darkfield images, a computer algorithm was applied to enumerate PNP-binding and fluorescence microscopy to identify cell lineage. Average MUC16-binding was determined by fitting a Poisson distribution to PNP-counts across similar cell types. MUC16-binding to cell types was correlated with treatment details, CA125 levels, and complete blood count (CBC) data. RESULTS: Over a 21-month period, monocytes had the highest level of MUC16-binding which was positively correlated with serum CA125 and inversely correlated with circulating monocyte and lymphocyte counts. Fluctuations of PNP-binding to NK cells were associated temporally with types of chemotherapy and surgical events. Levels of MUC16 bound to NK cells were positively correlated with levels of MUC16 bound to T and NK-T cells and inversely correlated with circulating platelets. CONCLUSIONS: Assessment of MUC16-binding among cryopreserved PBMC cell types can be accomplished using darkfield and fluorescence microscopy. Correlations observed between level of binding by cell type with serum CA125, CBC data, and treatment details suggest that the new techniques may offer novel insights into EOC's clinical course.

High Prediagnosis Inflammation-Related Risk Score Associated with Decreased Ovarian Cancer Survival.

BACKGROUND: There is suggestive evidence that inflammation is related to ovarian cancer survival. However, more research is needed to identify inflammation-related factors that are associated with ovarian cancer survival and to determine their combined effects. METHODS: This analysis used pooled data on 8,147 women with invasive epithelial ovarian cancer from the Ovarian Cancer Association Consortium. The prediagnosis inflammation-related exposures of interest included alcohol use; aspirin use; other nonsteroidal anti-inflammatory drug use; body mass index; environmental tobacco smoke exposure; history of pelvic inflammatory disease, polycystic ovarian syndrome, and endometriosis; menopausal hormone therapy use; physical inactivity; smoking status; and talc use. Using Cox proportional hazards models, the relationship between each exposure and survival was assessed in 50% of the data. A weighted inflammation-related risk score (IRRS) was developed, and its association with survival was assessed using Cox proportional hazards models in the remaining 50% of the data. RESULTS: There was a statistically significant trend of increasing risk of death per quartile of the IRRS [HR = 1.09; 95% confidence interval (CI), 1.03-1.14]. Women in the upper quartile of the IRRS had a 31% higher death rate compared with the lowest quartile (95% CI, 1.11-1.54). CONCLUSIONS: A higher prediagnosis IRRS was associated with an increased mortality risk after an ovarian cancer diagnosis. Further investigation is warranted to evaluate whether postdiagnosis exposures are also associated with survival. IMPACT: Given that pre- and postdiagnosis exposures are often correlated and many are modifiable, our study results can ultimately motivate the development of behavioral recommendations to enhance survival among patients with ovarian cancer.

MCM3 is a novel proliferation marker associated with longer survival for patients with tubo-ovarian high-grade serous carcinoma.

Tubo-ovarian high-grade serous carcinomas (HGSC) are highly proliferative neoplasms that generally respond well to platinum/taxane chemotherapy. We recently identified minichromosome maintenance complex component 3 (MCM3), which is involved in the initiation of DNA replication and proliferation, as a favorable prognostic marker in HGSC. Our objective was to further validate whether MCM3 mRNA expression and possibly MCM3 protein levels are associated with survival in patients with HGSC. MCM3 mRNA expression was measured using NanoString expression profiling on formalin-fixed and paraffin-embedded tissue (N = 2355 HGSC) and MCM3 protein expression was assessed by immunohistochemistry (N = 522 HGSC) and compared with Ki-67. Kaplan-Meier curves and the Cox proportional hazards model were used to estimate associations with survival. Among chemotherapy-naïve HGSC, higher MCM3 mRNA expression (one standard deviation increase in the score) was associated with longer overall survival (HR = 0.87, 95% CI 0.81-0.92, p < 0.0001, N = 1840) in multivariable analysis. MCM3 mRNA expression was highest in the HGSC C5.PRO molecular subtype, although no interaction was observed between MCM3, survival and molecular subtypes. MCM3 and Ki-67 protein levels were significantly lower after exposure to neoadjuvant chemotherapy compared to chemotherapy-naïve tumors: 37.0% versus 46.4% and 22.9% versus 34.2%, respectively. Among chemotherapy-naïve HGSC, high MCM3 protein levels were also associated with significantly longer disease-specific survival (HR = 0.52, 95% CI 0.36-0.74, p = 0.0003, N = 392) compared to cases with low MCM3 protein levels in multivariable analysis. MCM3 immunohistochemistry is a promising surrogate marker of proliferation in HGSC.