Protocol for identifying metabolite biomarkers in patient uterine fluid for early ovarian cancer detection.

High mortality of ovarian cancer (OC) is primarily attributed to the lack of effective early detection methods. Uterine fluid, pooling molecules from neighboring ovaries, presents an organ-specific advantage over conventional blood samples. Here, we present a protocol for identifying metabolite biomarkers in uterine fluid for early OC detection. We describe steps for uterine fluid collection from patients, metabolite extraction, metabolomics experiments, and candidate metabolite biomarker screening. This standardized workflow holds the potential to achieve early OC diagnosis in clinical practice. For complete details on the use and execution of this protocol, please refer to Wang et al.1.

Profiling the metabolome of uterine fluid for early detection of ovarian cancer.

Ovarian cancer (OC) causes high mortality in women because of ineffective biomarkers for early diagnosis. Here, we perform metabolomics analysis on an initial training set of uterine fluid from 96 gynecological patients. A seven-metabolite-marker panel consisting of vanillylmandelic acid, norepinephrine, phenylalanine, beta-alanine, tyrosine, 12-S-hydroxy-5,8,10-heptadecatrienoic acid, and crithmumdiol is established for detecting early-stage OC. The panel is further validated in an independent sample set from 123 patients, discriminating early OC from controls with an area under the curve (AUC) of 0.957 (95% confidence interval [CI], 0.894-1). Interestingly, we find elevated norepinephrine and decreased vanillylmandelic acid in most OC cells, resulting from excess 4-hydroxyestradiol that antagonizes the catabolism of norepinephrine by catechol-O-methyltransferase. Moreover, exposure to 4-hydroxyestradiol induces cellular DNA damage and genomic instability that could lead to tumorigenesis. Thus, this study not only reveals metabolic features in uterine fluid of gynecological patients but also establishes a noninvasive approach for the early diagnosis of OC.

Proteomic Mapping and Targeting of Mitotic Pericentriolar Material in Tumors Bearing Centrosome Amplification.

Recent work has made it clear that pericentriolar material (PCM), the matrix of proteins surrounding centrioles, contributes to most functions of centrosomes. Given the occurrence of centrosome amplification in most solid tumors and the unconventional survival of these tumor cells, it is tempting to hypothesize that gel-like mitotic PCM would cluster extra centrosomes to defend against mitotic errors and increase tumor cell survival. However, because PCM lacks an encompassing membrane, is highly dynamic, and is physically connected to centrioles, few methods can decode the components of this microscale matrix. In this study, we took advantage of differential labeling between two sets of APEX2-centrosome reactions to design a strategy for acquiring the PCM proteome in living undisturbed cells without synchronization treatment, which identified 392 PCM proteins. Localization of ubiquitination promotion proteins away from PCM was a predominant mechanism to maintain the large size of PCM for centrosome clustering during mitosis in cancer cells. Depletion of PCM gene kinesin family member 20A (KIF20A) caused centrosome clustering failure and apoptosis in cancer cells in vitro and in vivo. Thus, our study suggests a strategy for targeting a wide range of tumors exhibiting centrosome amplification and provides a proteomic resource for future mining of PCM proteins. SIGNIFICANCE: This study identifies the proteome of pericentriolar material and reveals therapeutic vulnerabilities in tumors bearing centrosome amplification.

Evaluation of Ovarian Reserve Tests and Age in the Prediction of Poor Ovarian Response to Controlled Ovarian Stimulation-A Real-World Data Analysis of 89,002 Patients.

Aims: This study aimed to explore the value of ovarian reserve tests (ORTs) for predicting poor ovary response (POR) and whether an age cutoff could improve this forecasting, so as to facilitate clinical decision-making for women undergoing in vitro fertilization (IVF). Methods: A retrospective cohort study was conducted on poor ovary response (POR) patients using real-world data from five reproductive centers of university-affiliated hospitals or large academic hospitals in China. A total of 89,002 women with infertility undergoing their first traditional ovarian stimulation cycle for in vitro fertilization from January 2013 to December 2019 were included. The receiver operating characteristic (ROC) curve was performed to estimate the prediction value of POR by the following ORTs: anti-Mullerian hormone (AMH), antral follicle count (AFC), basal FSH (bFSH), as well as patient age. Results: In this retrospective cohort, the frequency of POR in the first IVF cycle was 14.8%. Age, AFC, AMH, and bFSH were used as predicting factors for POR, of which AMH and AFC were the best indicators when using a single factor for prediction (AUC 0.862 and 0.842, respectively). The predictive values of the multivariate model included age and AMH (AUC 0.865), age and AFC (AUC 0.850), age and all three ORTs (AUC 0.873). Compared with using a single factor alone, the combinations of ORTs and female age can increase the predictive value of POR. Adding age to single AMH model improved the prediction accuracy compared with AMH alone (AUC 0.865 vs. 0.862), but the improvement was not significant. The AFC with age model significantly improved the prediction accuracy of the single AFC model (AUC 0.846 vs. 0.837). To reach 90% specificity for POR prediction, the cutoff point for age was 38 years old with a sensitivity of 40.7%, 5 for AFC with a sensitivity of 55.9%, and 1.18 ng/ml for AMH with a sensitivity of 63.3%. Conclusion: AFC and AMH demonstrated a high accuracy when using ROC regression to predict POR. When testing is reliable, AMH can be used alone to forecast POR. When AFC is used as a prediction parameter, age is suggested to be considered as well. Based on the results of the cutoff threshold analysis, AFC ≤ 5 and AMH ≤ 1.18 ng/ml should be recommended to predict POR more accurately in IVF/ICSI patients.

9-(3-Methoxy-phen-yl)-6,6-dimethyl-4-phenyl-2,3,5,6,7,9-hexa-hydro-thieno[3,2-b]quinolin-8(4H)-one 1,1-dioxide.

The title compound, C(26)H(27)NO(4)S, with a thiophene ring fused to a quinoline ring, was synthesized via the condensation of dihydro-thio-phen-3(2H)-one 1,1-dioxide, 5,5-dimethyl-3-(phenyl-amino)cyclo-hex-2-enone and 3-methoxy-benzaldehyde in refluxing ethanol. In the crystal structure, the thiophene dioxide ring and the pyridine ring adopt envelope conformations. The connection of the pyridine ring to the phenyl and benzene rings can be described by the C-C-C-C and C-N-C-C torsion angles of 45.5 (2) and 88.7 (2)°, respectively. The cyclo-hex-2-enone ring is in a half-chair conformation. The crystal packing is stabilized by non-classical inter-molecular C-H⋯O hydrogen bonds with the carbonyl O and sulfone O atoms acting as acceptors.

5'-Amino-1,3-dioxo-2',3'-di-hydro-7'H-spiro-[indane-2,7'-thieno[3,2-b]pyran]-6'-carbonitrile 1',1'-dioxide.

The title compound, C(16)H(10)N(2)O(5)S, was synthesized via the condesation of dihydro-thio-phen-3(2H)-one 1,1-dioxide, 1H-indene-1,2,3-trione and malononitrile in ethanol. The 2,3-dihydro-thio-phene 1,1-dioxide and pyran rings adopt envelope conformations. The mean planes through the planar part of the pyran ring and the benzene ring are nearly perpendicular, forming a dihedral angle of 88.40 (7)°. The crystal packing is stabilized by inter-molecular N-H⋯O and N-H⋯N hydrogen bonds with the sulfone O atom and the cyano N atom acting as acceptors.