Dataset Information

Comprehensive Library Generation for Identification and Quantification of Endometrial Cancer Protein Biomarkers in Cervico-Vaginal Fluid.

ABSTRACT: Endometrial cancer is the most common gynaecological malignancy in high-income countries and its incidence is rising. Early detection, aided by highly sensitive and specific biomarkers, has the potential to improve outcomes as treatment can be provided when it is most likely to effect a cure. Sequential window acquisition of all theoretical mass spectra (SWATH-MS), an accurate and reproducible platform for analysing biological samples, offers a technological advance for biomarker discovery due to its reproducibility, sensitivity and potential for data re-interrogation. SWATH-MS requires a spectral library in order to identify and quantify peptides from multiplexed mass spectrometry data. Here we present a bespoke spectral library of 154,206 transitions identifying 19,394 peptides and 2425 proteins in the cervico-vaginal fluid of postmenopausal women with, or at risk of, endometrial cancer. We have combined these data with a library of over 6000 proteins generated based on mass spectrometric analysis of two endometrial cancer cell lines. This unique resource enables the study of protein biomarkers for endometrial cancer detection in cervico-vaginal fluid. Data are available via ProteomeXchange with unique identifier PXD025925.

SUBMITTER: Njoku K

PROVIDER: S-EPMC8345211 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature

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Comprehensive Library Generation for Identification and Quantification of Endometrial Cancer Protein Biomarkers in Cervico-Vaginal Fluid.

Njoku Kelechi K Chiasserini Davide D Geary Bethany B Pierce Andrew A Jones Eleanor R ER Whetton Anthony D AD Crosbie Emma J EJ

Cancers 20210728 15

Endometrial cancer is the most common gynaecological malignancy in high-income countries and its incidence is rising. Early detection, aided by highly sensitive and specific biomarkers, has the potential to improve outcomes as treatment can be provided when it is most likely to effect a cure. Sequential window acquisition of all theoretical mass spectra (SWATH-MS), an accurate and reproducible platform for analysing biological samples, offers a technological advance for biomarker discovery due t ...[more]

PMID: 34359700

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Project description:BackgroundThe anatomical continuity between the uterine cavity and the lower genital tract allows for the exploitation of uterine-derived biomaterial in cervico-vaginal fluid for endometrial cancer detection based on non-invasive sampling methodologies. Plasma is an attractive biofluid for cancer detection due to its simplicity and ease of collection. In this biomarker discovery study, we aimed to identify proteomic signatures that accurately discriminate endometrial cancer from controls in cervico-vaginal fluid and blood plasma.MethodsBlood plasma and Delphi Screener-collected cervico-vaginal fluid samples were acquired from symptomatic post-menopausal women with (n = 53) and without (n = 65) endometrial cancer. Digitised proteomic maps were derived for each sample using sequential window acquisition of all theoretical mass spectra (SWATH-MS). Machine learning was employed to identify the most discriminatory proteins. The best diagnostic model was determined based on accuracy and model parsimony.FindingsA protein signature derived from cervico-vaginal fluid more accurately discriminated cancer from control samples than one derived from plasma. A 5-biomarker panel of cervico-vaginal fluid derived proteins (HPT, LG3BP, FGA, LY6D and IGHM) predicted endometrial cancer with an AUC of 0.95 (0.91-0.98), sensitivity of 91% (83%-98%), and specificity of 86% (78%-95%). By contrast, a 3-marker panel of plasma proteins (APOD, PSMA7 and HPT) predicted endometrial cancer with an AUC of 0.87 (0.81-0.93), sensitivity of 75% (64%-86%), and specificity of 84% (75%-93%). The parsimonious model AUC values for detection of stage I endometrial cancer in cervico-vaginal fluid and blood plasma were 0.92 (0.87-0.97) and 0.88 (0.82-0.95) respectively.InterpretationHere, we leveraged the natural shed of endometrial tumours to potentially develop an innovative approach to endometrial cancer detection. We show proof of principle that endometrial cancers secrete unique protein signatures that can enable cancer detection via cervico-vaginal fluid assays. Confirmation in a larger independent cohort is warranted.FundingCancer Research UK, Blood Cancer UK, National Institute for Health Research.

Project description:Study questionWhich inflammation biomarkers detected in the vaginal fluid are most informative for identifying preterm delivery (PTD) risk?Summary answerElevated interleukin (IL)-6 at mid-trimester was associated with increased odds of spontaneous PTD at <35 weeks and with PTD plus histologic chorioamnionitis (HCA), and had the greatest sensitivity for detecting these two PTD subtypes.What is known alreadyMaternal and/or fetal inflammation play a role in some preterm deliveries, therefore inflammation biomarkers might help to identify women at greater risk.Study design, size, durationWe examined 1115 women from the Pregnancy Outcomes and Community Health Study, a cohort study conducted from September 1998 through June 2004, for whom data were available on mid-pregnancy inflammatory biomarkers.Participants/materials, setting, methodsAt enrollment at 16-27 weeks gestation, vaginal fluid samples were collected from a swab and 15 eluted biomarkers were measured using the Meso Scale Discovery multiplex electrochemiluminescence platform. Associations of biomarkers with PTD were examined, according to clinical circumstance, week at delivery and presence/absence of HCA. Weighted logistic regression was used to determine odds ratios (OR) and 95% confidence intervals (CI) adjusted for race. Sensitivity and specificity were compared between individual and multiple biomarkers, identified by a bootstrapping method.Main results and the role of chanceElevated IL-6 (>75th percentile) displayed the strongest association with spontaneous PTD <35 weeks (OR 2.3; CI 1.3-4.0) and PTD with HCA (OR 2.8; CI 1.4-6.0). The sensitivity of IL-6 to detect spontaneous PTD <35 weeks or PTD with HCA was 0.43 and 0.51, respectively, while specificity was 0.74 and 0.75, respectively. IL-6 plus IL1β, IL-6r, tumor necrosis factor-alpha or granulocyte-macrophage colony-stimulating factor increased specificity (range 0.84-0.88), but decreased sensitivity (range 0.28-0.34) to detect both PTD subtypes. Results were similar when a combination of IL-6 and bacterial vaginosis (BV) was explored. Thus, the use of multiple biomarkers did not detect PTD subtypes with a greater sensitivity than IL-6 alone, and IL-6 is a specific but non-sensitive marker for the detection of spontaneous PTD.Limitations, reasons for cautionOur ability to find small effect size associations between PTD and inflammation biomarkers (OR <2.0) might have been limited by the modest number of less common PTD subtypes in our population (e.g. spontaneous delivery <35 weeks, PTD accompanied by HCA) and by relatively higher variability for some cytokines, for example tumor necrosis factor-α, IL-12p70, IL-10 and granulocyte-macrophage colony-stimulating factor, that are less stable and commonly undetectable or detectable at low levels in human vaginal secretions.Wider implications of the findingsLarger studies are needed to further explore a role of inflammation biomarkers in combination with other risk factors, including specific BV-associated organisms, for the prediction of PTD subtypes.Study funding/competing interest(s)This work was supported by the National Institute of Child Health and Human Development, National Institute of Nursing, March of Dimes Foundation, Thrasher Research Foundation and Centers for Disease Control and Prevention. The authors have no conflicts of interest.

Project description:The separation of exfoliated cells from the brushes used during cervico-vaginal smears is difficult, a problem which may affect the quality of ribonucleic acid (RNA) extracted. We compared the results of RNA extraction from cervico-vaginal cytology samples according to the type of tubes, preservative solutions, and storage temperature. The samples included exfoliated cervico-vaginal cytological specimens from patients with human papilloma virus 16, positive for cervical intraepithelial neoplasia or cervical cancer. Exfoliated cells were obtained by shaking a brush in a conventional rigid vial tube or squeezing the brush in a soft vial tube. RNA quantity and quality were compared between the two tubes. The concentration and purity of RNA (A260/A280 and A260/A230 ratios) was compared amongst five groups: Group 1, standard frozen storage; Group 2-4, RNA stabilization reagents with room temperature [RNAlater RNA Stabilization Reagent, RNAprotect cell Reagent and AllProtect Tissue Reagent]; and Group 5, Surepath Preservative fluid. To demonstrate the utility of the extracted RNA for PCR-based cDNA synthesis, GAPDH and E6 were targeted and gel band densities of GAPDH and E6 were measured. The median RNA concentration was significantly higher in the soft tubes compared with the rigid tubes (100.2 vs. 7.1 ng/μL, p = 0.0209). The purity of the RNA was higher in soft vial tubes than in rigid vials, as measured by A260/280 and A260/230 ratios. The RNA concentration, purity, and GAPDH density of groups 1, 2 and 3 were significantly higher than those of groups 4 and 5. Moreover, E6 density of group 1 and 2 was significantly higher than that of group 3, 4 and 5. The use of soft tubes enhanced the mRNA quantity and quality in cervico-vaginal cytology. The products of mRNA extraction using RNAlater RNA Stabilization Reagent and RNAprotect Cell Reagent at room temperature were comparable to those obtained by conventional frozen storage. Our protocol improved the yield and quality of RNA and might produce better results for molecular analysis in cervico-vaginal cytology.

Dataset Information

Comprehensive Library Generation for Identification and Quantification of Endometrial Cancer Protein Biomarkers in Cervico-Vaginal Fluid.

Publications

Comprehensive Library Generation for Identification and Quantification of Endometrial Cancer Protein Biomarkers in Cervico-Vaginal Fluid.

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