High-throughput viable circulating tumor cell isolation using tapered-slit membrane filter-based chipsets in the differential diagnosis of ovarian tumors.

OBJECTIVE: To evaluate the diagnostic performance of circulating tumor cells (CTCs) using tapered-slit membrane filter (TSF)-based chipsets for the differential diagnosis of adnexal tumors. METHODS: A total of 230 women with indeterminate adnexal tumors were prospectively enrolled. The sensitivity, specificity, and accuracy of the CTC-detecting chipsets were analyzed according to postoperative pathological results and compared with those of cancer antigen (CA)-125 and imaging tests. RESULTS: Eighty-one (40.3%) benign tumors, 31 (15.4%) borderline tumors, and 89 (44.3%) ovarian cancers were pathologically confirmed. The sensitivity, specificity, and accuracy of CTC-detecting chipsets (75.3%, 58.0%, and 67.1%) for differentiating ovarian cancer from benign tumors were similar to CA-125 (78.7%, 53.1%, and 66.5%), but lower than CT/MRI (94.2%, 77.9%, and 86.5%). "CTC or CA125" showed increased sensitivity (91.0%) and "CTC and CA-125" revealed increased specificity (77.8%), comparable to CT/MRI. CTC detection rates in stage I/II and stage III/IV ovarian cancers were 69.6% and 81.4%, respectively. The sensitivity to detect high-grade serous (HGS) cancer from benign tumors (84.6%) was higher than that to detect non-HGS cancers (68.0%). CONCLUSION: Although the diagnostic performance of the TSF platform to differentiate between ovarian cancer and benign tumors did not yield significant results, the combination of CTC and CA-125 showed promising potential in the diagnostic accuracy of ovarian cancer.

Predictors of Blood Transfusion in Patients Undergoing Cytoreductive Surgeries for Ovarian Malignancy.

OBJECTIVES: The aims of this study were to describe the baseline estimated blood loss (EBL) in surgery and transfusion rate in patients undergoing cytoreductive surgeries for ovarian malignancy, and identify perioperative variables associated with blood loss and transfusion. METHODS: A retrospective cohort study at a single institution was performed that included patients with known or suspected ovarian malignancy undergoing cytoreductive surgery between 2016 and 2021. t tests, χ2 tests, and multiple logistic regression analyses were used. RESULTS: Among 44 patients meeting inclusion criteria, 61% received perioperative blood transfusion. There were significant differences in EBL and preoperative hemoglobin levels between patients who did and did not receive transfusion (EBL 442.6 vs 236.8 mL, P = 0.0008; preoperative hemoglobin 10.2 vs 11.2 g/dL, P = 0.049). After adjusting for preoperative hemoglobin, the risk of transfusion increased for each additional 200 mL of EBL (odds ratio [OR] 3.8, 95% confidence interval [CI] 1.5-9.5). Stratified by race, the association between EBL and transfusion risk remained statistically significant only for non-Latinx White patients (OR 6.1, 95% CI 1.7-21.9), who made up 77% of the study population, but not for patients of other races and ethnicities (OR 1.0, 95% CI 0.16-6.42). CONCLUSIONS: Perioperative blood transfusion is common in patients undergoing cytoreductive surgery. In this study, EBL and preoperative hemoglobin levels were significantly associated with transfusion receipt. Clinicians should optimize hemoglobin levels and intraoperative blood conservation strategies to reduce the need for transfusion. The results also highlight the importance of considering racial and ethnic differences when developing strategies to reduce transfusion risk.

Causal relationship between thyroid dysfunction and ovarian cancer: a two-sample Mendelian randomization study.

PURPOSE: Observational studies and clinical validation have suggested a link between thyroid dysfunction and an elevated ovarian cancer (OC) risk. However, whether this association indicates a cause-and-effect relationship remains uncertain. We aimed to investigate the plausible causal impact of thyroid dysfunction on OC through a Mendelian randomization (MR) study. METHODS: Genome-wide association study (GWAS) data for thyrotropin (TSH), free thyroxine (FT4), hypothyroidism, and hyperthyroidism were obtained as exposures and those for OC (N = 199,741) were selected as outcomes. Inverse variance-weighted method was used as the main estimation method. A series of sensitivity analyses, including Cochran's Q test, MR-Egger intercept analysis, forest plot scatter plot, and leave-one-out test, was conducted to assess the robustness of the estimates. RESULTS: Genetic prediction of hyperthyroidism was associated with a potential increase in OC risk (odds ratio = 1.094, 95% confidence interval: 1.029-1.164, p = 0.004). However, no evidence of causal effects of hypothyroidism, TSH, and FT4 on OC or reverse causality was detected. Sensitivity analyses demonstrated consistent and reliable results, with no significant estimates of heterogeneity or pleiotropy. CONCLUSIONS: This study employed MR to establish a correlation between hyperthyroidism and OC risk. By genetically predicting OC risk in patients with hyperthyroidism, our research suggests new insights for early prevention and intervention of OC.

Blood Lead Level as Marker of Increased Risk of Ovarian Cancer in BRCA1 Carriers.

BRCA1 mutations substantially elevate the risks of breast and ovarian cancer. Various modifiers, including environmental factors, can influence cancer risk. Lead, a known carcinogen, has been associated with various cancers, but its impact on BRCA1 carriers remains unexplored. A cohort of 989 BRCA1 mutation carriers underwent genetic testing at the Pomeranian Medical University, Poland. Blood lead levels were measured using inductively coupled plasma mass spectrometry. Each subject was assigned to a category based on their tertile of blood lead. Cox regression analysis was used to assess cancer risk associations. Elevated blood lead levels (>13.6 µg/L) were associated with an increased risk of ovarian cancer (univariable: HR = 3.33; 95% CI: 1.23-9.00; p = 0.02; multivariable: HR = 2.10; 95% CI: 0.73-6.01; p = 0.17). No significant correlation was found with breast cancer risk. High blood lead levels are associated with increased risk of ovarian cancer in BRCA1 carriers, suggesting priority for preventive salpingo-oophorectomy. Potential risk reduction strategies include detoxification. Validation in diverse populations and exploration of detoxification methods for lowering lead levels are required.

CA-125 elimination rate constant K (KELIM) as a promising predictor of complete cytoreduction after neoadjuvant chemotherapy in advanced ovarian cancer patients: a retrospective study from two Chinese hospitals.

BACKGROUND: The modeled CA-125 elimination constant K (KELIM) is a potential marker of tumor chemosensitivity in ovarian cancer patients treated with neoadjuvant chemotherapy (NACT) before interval surgery. The objective of this study was to externally validate the KELIM (rate of elimination of CA-125) score in patients with high-grade serous ovarian cancer (HGSC) undergoing NACT and explore its relation to the completeness of IDS and survival. METHODS: The study was based on a retrospective cohort of 133 patients treated for advanced HGSC, International Federation of Gynecology and Obstetrics (FIGO) stages III-IV, with neoadjuvant chemotherapy, folllowed by interval surgery, in two centres in China. CA-125 concentrations at baseline and during neoadjuvant chemotherapy were collected. We used standardized (std) KELIM for subsequent analysis. Clinicopathologic parameters were collected, and Kaplan‒Meier survival analyses were performed for PFS and OS. RESULTS: KELIM was an independent predictor of the probability of complete surgery and survival in our cohort. The median std KELIM score of patients with complete surgery was significantly higher than that of patients with incomplete IDS (1.20 vs. 0.71, P < 0.001). Multivariate analysis showed that a std KELIM score ≥0.925 was an independent predictive factor for achieving complete resection (OR = 5.480; 95% CI, 2.409-12.466, P < 0.001) and better PFS (HR = 0.544; 95% CI: 0.349-0.849, P = 0.007) and OS (HR = 0.484; 95% CI: 0.251-0.930, P = 0.030). CONCLUSIONS: The tumor-primary tumor chemosensitivity, assessed by the modeled CA-125 KELIM, calculated during NACT, is a major parameter to consider for decision-making regarding IDS attempts and predicting patient survival.

Automated Machine Learning and Explainable AI (AutoML-XAI) for Metabolomics: Improving Cancer Diagnostics.

Metabolomics generates complex data necessitating advanced computational methods for generating biological insight. While machine learning (ML) is promising, the challenges of selecting the best algorithms and tuning hyperparameters, particularly for nonexperts, remain. Automated machine learning (AutoML) can streamline this process; however, the issue of interpretability could persist. This research introduces a unified pipeline that combines AutoML with explainable AI (XAI) techniques to optimize metabolomics analysis. We tested our approach on two data sets: renal cell carcinoma (RCC) urine metabolomics and ovarian cancer (OC) serum metabolomics. AutoML, using Auto-sklearn, surpassed standalone ML algorithms like SVM and k-Nearest Neighbors in differentiating between RCC and healthy controls, as well as OC patients and those with other gynecological cancers. The effectiveness of Auto-sklearn is highlighted by its AUC scores of 0.97 for RCC and 0.85 for OC, obtained from the unseen test sets. Importantly, on most of the metrics considered, Auto-sklearn demonstrated a better classification performance, leveraging a mix of algorithms and ensemble techniques. Shapley Additive Explanations (SHAP) provided a global ranking of feature importance, identifying dibutylamine and ganglioside GM(d34:1) as the top discriminative metabolites for RCC and OC, respectively. Waterfall plots offered local explanations by illustrating the influence of each metabolite on individual predictions. Dependence plots spotlighted metabolite interactions, such as the connection between hippuric acid and one of its derivatives in RCC, and between GM3(d34:1) and GM3(18:1_16:0) in OC, hinting at potential mechanistic relationships. Through decision plots, a detailed error analysis was conducted, contrasting feature importance for correctly versus incorrectly classified samples. In essence, our pipeline emphasizes the importance of harmonizing AutoML and XAI, facilitating both simplified ML application and improved interpretability in metabolomics data science.

Serum anti-CFL1, anti-EZR, and anti-CYPA autoantibody as diagnostic markers in ovarian cancer.

The purpose of this study was to identify novel autoantibodies against tumor-associated antigens (TAAs) and explore a diagnostic panel for Ovarian cancer (OC). Enzyme-linked immunosorbent assay was used to detect the expression of five anti-TAA autoantibodies in the discovery (70 OC and 70 normal controls) and validation cohorts (128 OC and 128 normal controls). Machine learning methods were used to construct a diagnostic panel. Serum samples from 81 patients with benign ovarian disease were used to identify the specificity of anti-TAA autoantibodies for OC. In both the discovery and validation cohorts, the expression of anti-CFL1, anti-EZR, anti-CYPA, and anti-PFN1 was higher in patients with OC than that in normal controls. The area under the receiver operating characteristic curve, sensitivity, and specificity of the panel containing anti-CFL1, anti-EZR, and anti-CYPA were 0.762, 55.56%, and 81.31%. The panel identified 53.06%, 53.33%, and 51.11% of CA125 negative, HE4 negative and the Risk of Ovarian Malignancy Algorithm negative OC patients, respectively. The combination of the three anti-TAA autoantibodies can serve as a favorable diagnostic tool for OC and has the potential to be a complementary biomarker for CA125 and HE4 in the diagnosis of ovarian cancer.

Evaluation of serum CA125, HE4 and CA724 and the risk of ovarian malignancy algorithm score in the diagnosis of high-grade serous ovarian cancer.

AIM: To develop a new algorithm for the detection of high-grade serous ovarian cancer (HGSOC). METHODS: Patients diagnosed with HGSOC, borderline ovarian tumours (BOTs) or benign ovarian masses (BOMs) were enrolled between February 2019 and December 2020. Patients with BOTs or BOMs were grouped as non-HGSOC. The cases were divided randomly into a training cohort (two-thirds of cases) and a validation cohort (one-third of cases). Logistic regression was used to find risk factors for HGSOC and to create a new algorithm in the training cohort. Receiver operating characteristic curves were used to compare the diagnostic value of tumour biomarkers. Sensitivity and specificity of tumour markers and the new algorithm were calculated in the training cohort and validation cohort. RESULTS: This study found significant differences in age; BRCA1/2 mutation status; CA125, CA724 and HE4 levels; and Risk of Ovarian Malignancy Algorithm score between the two groups.Logistic regression analysis showed that CA125 and BRCA1/2 were risk factors for HGSOC. A new algorithm combining CA125 and BRCA1/2 increased the specificity of CA125 for diagnosis of HGSOC. The new algorithm had sensitivity of 81.08% and specificity of 93.10% in the training cohort. CONCLUSION: The new algorithm using CA125 and BRCA1/2 helped to distinguish between patients with HGSOC and patients with non-HGSOC.

Diagnosing and staging epithelial ovarian cancer by serum glycoproteomic profiling.

BACKGROUND: There is a need for diagnostic tests for screening, triaging and staging of epithelial ovarian cancer (EOC). Glycoproteomics of blood samples has shown promise for biomarker discovery. METHODS: We applied glycoproteomics to serum of people with EOC or benign pelvic masses and healthy controls. A total of 653 analytes were quantified and assessed in multivariable models, which were tested in an independent cohort. Additionally, we analyzed glycosylation patterns in serum markers and in tissues. RESULTS: We identified a biomarker panel that distinguished benign lesions from EOC with sensitivity and specificity of 83.5% and 90.1% in the training set, and of 86.7 and 86.7% in the test set, respectively. ROC analysis demonstrated strong performance across a range of cutoffs. Fucosylated multi-antennary glycopeptide markers were higher in late-stage than in early-stage EOC. A comparable pattern was found in late-stage EOC tissues. CONCLUSIONS: Blood glycopeptide biomarkers have the potential to distinguish benign from malignant pelvic masses, and early- from late-stage EOC. Glycosylation of circulating and tumor tissue proteins may be related. This study supports the hypothesis that blood glycoproteomic profiling can be used for EOC diagnosis and staging and it warrants further clinical evaluation.

Circulating tumor DNA as a biomarker for predicting progression-free survival and overall survival in patients with epithelial ovarian cancer: a systematic review and meta-analysis.

OBJECTIVES: Circulating tumor DNA (ctDNA) is emerging as a potential prognostic biomarker in multiple tumor types. However, despite the many studies available on small series of patients with ovarian cancer, a recent systematic review and meta-analysis is lacking. The objective of this study was to determine the association of ctDNA with progression-free-survival and overall survival in patients with epithelial ovarian cancer. METHODS: An electronic search was conducted using PubMed (MEDLINE), Embase, CENTRAL (Cochrane Library), and CINAHL-Complete from January 2000 to September 15, 2023. To be included in the analysis the studies had to meet the following pre-specified inclusion criteria: (1) evaluable ctDNA; (2) progression-free-survival and overall survival reported as hazard ratio (HR); and (3) the patient population had epithelial ovarian cancer at the time of ctDNA detection. We evaluated the association of ctDNA with progression-free survival and overall survival. Secondary outcomes focused on sub-group analysis of genomic alterations and international Federation of Gynecology and Obstetrics (FIGO) stage. RESULTS: A total of 26 studies reporting on 1696 patients with epithelial ovarian cancer were included. The overall concordance rate between plasma-based and tissue-based analyses was approximately 62%. We found that a high level of ctDNA in epithelial ovarian cancer was associated with worse progression-free survival (HR 5.31, 95% CI 2.14 to 13.17, p<0.001) and overall survival (HR 2.98, 95% CI 1.86 to 4.76, p<0.0001). The sub-group analysis showed a greater than threefold increase in the risk of relapse in patients with positive HOXA9 meth-ctDNA (HR 3.84, 95% CI 1.57 to 9.41, p=0.003). CONCLUSIONS: ctDNA was significantly associated with worse progression-free survival and overall survival in patients with epithelial ovarian cancer. Further prospective studies are needed. PROSPERO REGISTRATION NUMBER: CRD42023469390.

Serum Lipidome Profiling Reveals a Distinct Signature of Ovarian Cancer in Korean Women.

BACKGROUND: Distinguishing ovarian cancer from other gynecological malignancies is crucial for patient survival yet hindered by non-specific symptoms and limited understanding of ovarian cancer pathogenesis. Accumulating evidence suggests a link between ovarian cancer and deregulated lipid metabolism. Most studies have small sample sizes, especially for early-stage cases, and lack racial/ethnic diversity, necessitating more inclusive research for improved ovarian cancer diagnosis and prevention. METHODS: Here, we profiled the serum lipidome of 208 ovarian cancer, including 93 early-stage patients with ovarian cancer and 117 nonovarian cancer (other gynecological malignancies) patients of Korean descent. Serum samples were analyzed with a high-coverage liquid chromatography high-resolution mass spectrometry platform, and lipidome alterations were investigated via statistical and machine learning (ML) approaches. RESULTS: We found that lipidome alterations unique to ovarian cancer were present in Korean women as early as when the cancer is localized, and those changes increase in magnitude as the diseases progresses. Analysis of relative lipid abundances revealed specific patterns for various lipid classes, with most classes showing decreased abundance in ovarian cancer in comparison with other gynecological diseases. ML methods selected a panel of 17 lipids that discriminated ovarian cancer from nonovarian cancer cases with an AUC value of 0.85 for an independent test set. CONCLUSIONS: This study provides a systemic analysis of lipidome alterations in human ovarian cancer, specifically in Korean women. IMPACT: Here, we show the potential of circulating lipids in distinguishing ovarian cancer from nonovarian cancer conditions.

Evaluating the effectiveness of pre-operative diagnosis of ovarian cancer using minimally invasive liquid biopsies by combining serum human epididymis protein 4 and cell-free DNA in patients with an ovarian mass.

OBJECTIVE: To assess the feasibility of scalable, objective, and minimally invasive liquid biopsy-derived biomarkers such as cell-free DNA copy number profiles, human epididymis protein 4 (HE4), and cancer antigen 125 (CA125) for pre-operative risk assessment of early-stage ovarian cancer in a clinically representative and diagnostically challenging population and to compare the performance of these biomarkers with the Risk of Malignancy Index (RMI). METHODS: In this case-control study, we included 100 patients with an ovarian mass clinically suspected to be early-stage ovarian cancer. Of these 100 patients, 50 were confirmed to have a malignant mass (cases) and 50 had a benign mass (controls). Using WisecondorX, an algorithm used extensively in non-invasive prenatal testing, we calculated the benign-calibrated copy number profile abnormality score. This score represents how different a sample is from benign controls based on copy number profiles. We combined this score with HE4 serum concentration to separate cases and controls. RESULTS: Combining the benign-calibrated copy number profile abnormality score with HE4, we obtained a model with a significantly higher sensitivity (42% vs 0%; p<0.002) at 99% specificity as compared with the RMI that is currently employed in clinical practice. Investigating performance in subgroups, we observed especially large differences in the advanced stage and non-high-grade serous ovarian cancer groups. CONCLUSION: This study demonstrates that cell-free DNA can be successfully employed to perform pre-operative risk of malignancy assessment for ovarian masses; however, results warrant validation in a more extensive clinical study.

Associations of serum trimethylamine N-oxide and its precursors with colorectal cancer risk in the Prostate, Lung, Colorectal, Ovarian Cancer Screening Trial Cohort.

BACKGROUND: Dietary intake influences gut microbiome composition, which in turn may be associated with colorectal cancer (CRC). Associations of the gut microbiome with colorectal carcinogenesis may be mediated through bacterially regulated, metabolically active metabolites, including trimethylamine N-oxide (TMAO) and its precursors, choline, L-carnitine, and betaine. METHODS: Prospective associations of circulating TMAO and its precursors with CRC risk were investigated. TMAO, choline, betaine, and L-carnitine were measured in baseline serum samples from 761 incident CRC cases and 1:1 individually matched controls in the prospective Prostate, Lung, Colorectal, Ovarian Cancer Screening Trial Cohort using targeted fully quantitative liquid chromatography tandem mass spectrometry panels. Prospective associations of the metabolites with CRC risk, using multivariable conditional logistic regression, were measured. Associations of a priori-selected dietary exposures with the four metabolites were also investigated. RESULTS: TMAO and its precursors were not associated with CRC risk overall, but TMAO and choline were positively associated with higher risk for distal CRC (continuous ORQ90 vs. Q10 [95% CI] = 1.90 [CI, 1.24-2.92; p = .003] and 1.26 [1.17-1.36; p < .0001], respectively). Conversely, choline was inversely associated with rectal cancer (ORQ90 vs. Q10 [95% CI] = 0.77 [0.76-0.79; p < .001]). Red meat, which was previously associated with CRC risk in the Prostate, Lung, Colorectal, Ovarian Cancer Screening Trial Cohort , was positively associated with TMAO (Spearman rho = 0.10; p = .0003). CONCLUSIONS: Serum TMAO and choline may be associated with higher risk of distal CRC, and red meat may be positively associated with serum TMAO. These findings provide insight into a potential microbially mediated mechanism underlying CRC etiology.

Hybrid chain reaction and selective recognition-based homogeneous dual-fluorescence analysis of circulating tumor cells in clinical ovarian cancer samples.

BACKGROUND: Oncological analysis is important in tumor diagnosis. We constructed a dual-fluorescence and binary visual analysis system for circulating tumor cells (CTCs) using the folate receptor as a biomarker, combined with hybridization chain reaction and nanomaterial amplification. This strategy integrates terminal protection, selective recognition properties of N-methyl mesoporphyrin IX and CdTe quantum dots for Cu2+ and double-stranded templated copper nanoparticles, and inkjet printing technology. RESULTS: In fluorescence mode, folate receptor and A2780 ovarian cancer cells were specifically detected with a limit of detection of 0.1 fg mL-1, and 10 cells mL-1 were observed. The detection limits of both the color and distance reading modes were comparable to those obtained in fluorescence mode. The applicability of the method for quantifying CTCs was validated using 27 (6 negative and 21 positive) clinical ovarian cancer samples; the results agreed with those of both the clinical folate receptor-polymerase chain reaction kit and radiological and pathological results. SIGNIFICANCE: This dual-fluorescence and binary visual CTCs detection method provides multiple options for clinical tumor liquid biopsy.

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.

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.

Refined characterization of circulating tumor DNA through biological feature integration.

Circulating tumor DNA (ctDNA) in blood plasma is present at very low concentrations compared to cell-free DNA (cfDNA) of non-tumor origin. To enhance ctDNA detection, recent studies have been focused on understanding the non-random fragmentation pattern of cfDNA. These studies have investigated fragment sizes, genomic position of fragment end points, and fragment end motifs. Although these features have been described and shown to be aberrant in cancer patients, there is a lack of understanding of how the individual and integrated analysis of these features enrich ctDNA fraction and enhance ctDNA detection. Using whole genome sequencing and copy number analysis of plasma samples from 5 high grade serious ovarian cancer patients, we observed that (1) ctDNA is enriched not only in fragments shorter than mono-nucleosomes (~ 167 bp), but also in those shorter than di-nucleosomes (~ 240-330 bp) (28-159% enrichment). (2) fragments that start and end at the border or within the nucleosome core are enriched in ctDNA (5-46% enrichment). (3) certain DNA motifs conserved in regions 10 bp up- and down- stream of fragment ends (i.e. cleavage sites) could be used to detect tumor-derived fragments (10-44% enrichment). We further show that the integrated analysis of these three features resulted in a higher enrichment of ctDNA when compared to using fragment size alone (additional 7-25% enrichment after fragment size selection). We believe these genome wide features, which are independent of genetic mutational changes, could allow new ways to analyze and interpret cfDNA data, as significant aberrations of these features from a healthy state could improve its utility as a diagnostic biomarker.

High expression of TRIM24 predicts worse prognosis and promotes proliferation and metastasis of epithelial ovarian cancer.

BACKGROUND: Tripartite Motif-Containing 24 (TRIM24) is a member of the tripartite motif family. TRIM24 is claimed aberrantly activated in a number of cancers, such as breast cancer, prostate cancer and lung cancer. However, the expression of TRIM24 in epithelial ovarian cancer (EOC) and its relationship with prognosis remain unclear. In this study, we investigated the expression pattern and underlying clinical significance of TRIM24 in EOC. RESULTS: Data from Oncomine and immunohistochemistry of tissue samples demonstrated that TRIM24 expression was obviously elevated in ovarian carcinoma compared with normal ovary tissues. Elevated TRIM24 expression was closely correlated with serum CA-125 (P = 0.0294), metastasis (P = 0.0022), FIGO (International Federation of Gynecology and Obstetrics) stage (P = 0.0068) and Ki-67 level (P = 0.0395). Kaplan-Meier survival analysis found that TRIM24 expression increased inversely with the clinical prognosis of patients with EOC. Moreover, colony formation and CCK-8 assays showed that TRIM24 promoted EOC cell growth, and tumorigenic experiments in nude mice showed that TRIM24 knockdown inhibited tumor growth in vivo. The Spearman's correlations revealed that the expression of TRIM24 was significantly correlated with levels of Ki-67 (P = 0.01), at a correlation coefficient of 0.517. Wound-healing and transwell migration assays demonstrated TRIM24 facilitated cell migration. Mechanism studies showed that TRIM24 could promote the phosphorylation level of Akt and the process of EMT. CONCLUSION: Our results confirmed that TRIM24 could predict poor prognosis of EOC patients and promote tumor progression by regulating Akt pathway and EMT. TRIM24 may be used as a new prognostic marker for EOC and may provide a new strategy for targeted therapy of epithelial ovarian cancer.

Detection of plasma exosomal miRNA-205 as a biomarker for early diagnosis and an adjuvant indicator of ovarian cancer staging.

BACKGROUND: Ovarian cancer (OC) is one of the serious threats to the health of women worldwide, and accurate biomarkers are urgently demanded for early diagnosis of OC. We have previously confirmed that miR-205 promotes the invasion and metastasis of OC cells by inhibiting the expression of the tumor suppressor gene TCF21. In this study, we used liquid biopsy technology to detect the expression levels of the four genes, miR-205, CA125, HE4 and TCF21, in the exosomes of plasma of OC patients. Combined with analysis of clinicopathological parameters of OC patients, we aimed to provide efficient and non-invasive laboratory biomarkers for early diagnosis of OC. METHODS: 36 OC patients who were diagnosed in local hospitals from September 2020 to July 2021 were selected as OC group, 31 cases of surgically diagnosed with ovarian benign lesions were selected as benign group, and 32 healthy people who underwent physical examination during the same period were selected as a control group. We employed transmission electron microscope (TEM), Western blotting (WB), and nanoparticle tracking analysis (NTA) to identify biomarkers in the exosomes extracted from plasma of the three groups. The RNA levels of miR-205, CA125, HE4 and TCF21 genes in plasma exosomes were detected by real-time quantitative PCR (qRT-PCR) method. We used clinical pathological parameters and the Receiver Operating Characteristic (ROC) curves to evaluate the diagnostic efficacy for the genes detected in plasma exosomes. RESULTS: We found that the expression level of miR-205 in plasma exosomes of the OC group was significantly higher than that of the benign and control groups (P <  0.05), and the level of miR-205 was elevated during the III-IV periods of OC and lymph node metastasis. CONCLUSION: The level of miR-205 in plasma exosomes is a valuable tumor biomarker to improve OC diagnosis.

A prognostic model of patients with ovarian mucinous adenocarcinoma: a population-based analysis.

BACKGROUND: Ovarian mucinous carcinoma is a disease that requires unique treatment. But for a long time, guidelines for ovarian serous carcinoma have been used for the treatment of ovarian mucinous carcinoma. This study aimed to construct and validate nomograms for predicting the overall survival (OS) and cancer-specific survival (CSS) in patients with ovarian mucinous adenocarcinoma. METHODS: In this study, patients initially diagnosed with ovarian mucinous adenocarcinoma from 2004 to 2015 were screened from the Surveillance, Epidemiology, and End Results (SEER) database, and divided into the training group and the validation group at a ratio of 7:3. Independent risk factors for OS and CSS were determined by multivariate Cox regression analysis, and nomograms were constructed and validated. RESULTS: In this study, 1309 patients with ovarian mucinous adenocarcinoma were finally screened and randomly divided into 917 cases in the training group and 392 cases in the validation group according to a 7:3 ratio. Multivariate Cox regression analysis showed that the independent risk factors of OS were age, race, T_stage, N_stage, M_stage, grade, CA125, and chemotherapy. Independent risk factors of CSS were age, race, marital, T_stage, N_stage, M_stage, grade, CA125, and chemotherapy. According to the above results, the nomograms of OS and CSS in ovarian mucinous adenocarcinoma were constructed. In the training group, the C-index of the OS nomogram was 0.845 (95% CI: 0.821-0.869) and the C-index of the CSS nomogram was 0.862 (95%CI: 0.838-0.886). In the validation group, the C-index of the OS nomogram was 0.843 (95% CI: 0.810-0.876) and the C-index of the CSS nomogram was 0.841 (95%CI: 0.806-0.876). The calibration curve showed the consistency between the predicted results and the actual results, indicating the high accuracy of the nomogram. CONCLUSION: The nomogram provides 3-year and 5-year OS and CSS predictions for patients with ovarian mucinous adenocarcinoma, which helps clinicians predict the prognosis of patients and formulate appropriate treatment plans.