| 1. |
- Dahm-Kähler, Pernilla, 1964, et al.
(författare)
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Monocyte chemotactic protein-1 (MCP-1), its receptor, and macrophages in the perifollicular stroma during the human ovulatory process
- 2009
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Ingår i: Fertility and Sterility. - : Elsevier BV. - 1556-5653 .- 0015-0282. ; 91:1, s. 231-239
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Tidskriftsartikel (refereegranskat)abstract
- OBJECTIVE: To evaluate the expression and localization of the macrophage-specific chemokine monocyte chemotactic protein-1 (MCP-1), CC chemokine receptor 2 (CCR2), and macrophages (CD68) in the perifollicular stroma of different phases of the human ovulatory process and its relation to macrophage influx. DESIGN: Experimental study on patient-controlled material. SETTING: University hospital. PATIENT(S): Twenty-eight women planned to undergo laparoscopic sterilization. INTERVENTION(S): Surgery was performed at either of four distinct ovulatory phases, and a biopsy sample was obtained from the perifollicular stroma of the ovulatory follicle. MAIN OUTCOME MEASURE(S): Real-time polymerase chain reaction, immunoblotting, and immunohistochemistry were used for measurements of MCP-1, CCR2, and macrophages. RESULT(S): The messenger RNA levels of MCP-1 in the perifollicular stroma increased from the preovulatory to the late ovulatory phase and declined during the postovulatory phase. A higher density of macrophages was found in the preovulatory and early ovulatory phases compared with late and postovulatory phases. Monocyte chemotactic protein-1 and CCR2 were present in the stroma. Protein expression of CD68 and CCR2 were identified in the four ovulatory phases. CONCLUSION(S): This study demonstrates an upregulation of MCP-1 in the stroma compartment around the human follicle during the ovulatory process, and a high density of macrophages was found at earlier phases. Thus, inflammation-like reactions are integral in the ovulatory process and may be targeted to stimulate or inhibit this process.
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| 2. |
- Enroth, Stefan, 1976-, et al.
(författare)
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A two-step strategy for identification of plasma protein biomarkers for endometrial and ovarian cancer
- 2018
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Ingår i: Clinical Proteomics. - : Springer Science and Business Media LLC. - 1542-6416 .- 1559-0275. ; 15
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Tidskriftsartikel (refereegranskat)abstract
- BackgroundOver 500,000 women worldwide are diagnosed with ovarian or endometrial cancer each year. We have used a two-step strategy to identify plasma proteins that could be used to improve the diagnosis of women with an indication of gynecologic tumor and in population screening.MethodsIn the discovery step we screened 441 proteins in plasma using the proximity extension assay (PEA) and five Olink Multiplex assays (CVD II, CVD III, INF I, ONC II, NEU I) in women with ovarian cancer (n=106), endometrial cancer (n=74), benign ovarian tumors (n=150) and healthy population controls (n=399). Based on the discovery analyses a set of 27 proteins were selected and two focused multiplex PEA assays were developed. In a replication step the focused assays were used to study an independent set of cases with ovarian cancer (n=280), endometrial cancer (n=228), women with benign ovarian tumors (n=76) and healthy controls (n=57).ResultsIn the discovery step, 27 proteins that showed an association to cancer status were identified. In the replication analyses, the focused assays distinguished benign tumors from ovarian cancer stage III-IV with a sensitivity of 0.88 and specificity of 0.92 (AUC=0.92). The assays had a significantly higher AUC for distinguishing benign tumors from late stage ovarian cancer than using CA125 and HE4 (p=9.56e-22). Also, population controls could be distinguished from ovarian cancer stage III-IV with a sensitivity of 0.85 and a specificity of 0.92 (AUC=0.89).ConclusionThe PEA assays represent useful tools for identification of new biomarkers for gynecologic cancers. The selected protein assays could be used to distinguish benign tumors from ovarian and endometrial cancer in women diagnosed with an unknown suspicious pelvic mass. The panels could also be used in population screening, for identification of women in need of specialized gynecologic transvaginal ultrasound examination.FundingThe Swedish Cancer Foundation, Vinnova (SWELIFE), The Foundation for Strategic Research (SSF), Assar Gabrielsson Foundation.
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| 3. |
- Enroth, Stefan, 1976-, et al.
(författare)
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Data-driven analysis of a validated risk score for ovarian cancer identifies clinically distinct patterns during follow-up and treatment
- 2022
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Ingår i: Communications Medicine. - : Springer Nature. - 2730-664X. ; 2:1
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Tidskriftsartikel (refereegranskat)abstract
- BackgroundOvarian cancer is the eighth most common cancer among women and due to late detection prognosis is poor with an overall 5-year survival of 30–50%. Novel biomarkers are needed to reduce diagnostic surgery and enable detection of early-stage cancer by population screening. We have previously developed a risk score based on an 11-biomarker plasma protein assay to distinguish benign tumors (cysts) from malignant ovarian cancer in women with adnexal ovarian mass.MethodsProtein concentrations of 11 proteins were characterized in plasma from 1120 clinical samples with a custom version of the proximity extension assay. The performance of the assay was evaluated in terms of prediction accuracy based on receiver operating characteristics (ROC) and multiple hypothesis adjusted Fisher’s Exact tests on achieved sensitivity and specificity.ResultsThe assay’s performance is validated in two independent clinical cohorts with a sensitivity of 0.83/0.91 and specificity of 0.88/0.92. We also show that the risk score follows the clinical development and is reduced upon treatment, and increased with relapse and cancer progression. Data-driven modeling of the risk score patterns during a 2-year follow-up after diagnosis identifies four separate risk score trajectories linked to clinical development and survival. A Cox proportional hazard regression analysis of 5-year survival shows that at time of diagnosis the risk score is the second-strongest predictive variable for survival after tumor stage, whereas MUCIN-16 (CA-125) alone is not significantly predictive.ConclusionThe robust performance of the biomarker assay across clinical cohorts and the correlation with clinical development indicates its usefulness both in the diagnostic work-up of women with adnexal ovarian mass and for predicting their clinical course.
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| 4. |
- Enroth, Stefan, 1976-, et al.
(författare)
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High throughput proteomics identifies a high-accuracy 11 plasma protein biomarker signature for ovarian cancer
- 2019
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Ingår i: Communications Biology. - : Springer Science and Business Media LLC. - 2399-3642. ; 2
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Tidskriftsartikel (refereegranskat)abstract
- Ovarian cancer is usually detected at a late stage and the overall 5-year survival is only 30-40%. Additional means for early detection and improved diagnosis are acutely needed. To search for novel biomarkers, we compared circulating plasma levels of 593 proteins in three cohorts of patients with ovarian cancer and benign tumors, using the proximity extension assay (PEA). A combinatorial strategy was developed for identification of different multivariate biomarker signatures. A final model consisting of 11 biomarkers plus age was developed into a multiplex PEA test reporting in absolute concentrations. The final model was evaluated in a fourth independent cohort and has an AUC = 0.94, PPV = 0.92, sensitivity = 0.85 and specificity = 0.93 for detection of ovarian cancer stages I-IV. The novel plasma protein signature could be used to improve the diagnosis of women with adnexal ovarian mass or in screening to identify women that should be referred to specialized examination.
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| 5. |
- Gyllensten, Ulf B., et al.
(författare)
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Next Generation Plasma Proteomics Identifies High-Precision Biomarker Candidates for Ovarian Cancer
- 2022
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Ingår i: Cancers. - : MDPI AG. - 2072-6694. ; 14:7
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Tidskriftsartikel (refereegranskat)abstract
- Simple Summary Ovarian cancer is the eighth most common cancer among women and has a 5-year survival of only 30-50%. The survival is close to 90% for patients in stage I but only 20% for patients in stage IV. The presently available biomarkers have insufficient sensitivity and specificity for early detection and there is an urgent need to identify novel biomarkers. The aim of our study was to broadly measure protein biomarkers to find tests for the early detection of ovarian cancer. We found that combinations of 4-7 protein biomarkers can provide highly accurate detection of early- and late-stage ovarian cancer compared to benign conditions. The performance of the tests was then validated in a second independent cohort. Background: Ovarian cancer is the eighth most common cancer among women and has a 5-year survival of only 30-50%. The survival is close to 90% for patients in stage I but only 20% for patients in stage IV. The presently available biomarkers have insufficient sensitivity and specificity for early detection and there is an urgent need to identify novel biomarkers. Methods: We employed the Explore PEA technology for high-precision analysis of 1463 plasma proteins and conducted a discovery and replication study using two clinical cohorts of previously untreated patients with benign or malignant ovarian tumours (N = 111 and N = 37). Results: The discovery analysis identified 32 proteins that had significantly higher levels in malignant cases as compared to benign diagnoses, and for 28 of these, the association was replicated in the second cohort. Multivariate modelling identified three highly accurate models based on 4 to 7 proteins each for separating benign tumours from early-stage and/or late-stage ovarian cancers, all with AUCs above 0.96 in the replication cohort. We also developed a model for separating the early-stage from the late-stage achieving an AUC of 0.81 in the replication cohort. These models were based on eleven proteins in total (ALPP, CXCL8, DPY30, IL6, IL12, KRT19, PAEP, TSPAN1, SIGLEC5, VTCN1, and WFDC2), notably without MUCIN-16. The majority of the associated proteins have been connected to ovarian cancer but not identified as potential biomarkers. Conclusions: The results show the ability of using high-precision proteomics for the identification of novel plasma protein biomarker candidates for the early detection of ovarian cancer.
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| 6. |
- Gyllensten, Ulf B., et al.
(författare)
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Preoperative Fasting and General Anaesthesia Alter the Plasma Proteome
- 2020
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Ingår i: Cancers. - : MDPI AG. - 2072-6694. ; 12:9
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Tidskriftsartikel (refereegranskat)abstract
- Background: Blood plasma collected at time of surgery is an excellent source of patient material for investigations into disease aetiology and for the discovery of novel biomarkers. Previous studies on limited sets of proteins and patients have indicated that pre-operative fasting and anaesthesia can affect protein levels, but this has not been investigated on a larger scale. These effects could produce erroneous results in case-control studies if samples are not carefully matched. Methods: The proximity extension assay (PEA) was used to characterize 983 unique proteins in a total of 327 patients diagnosed with ovarian cancer and 50 age-matched healthy women. The samples were collected either at time of initial diagnosis or before surgery under general anaesthesia. Results: 421 of the investigated proteins (42.8%) showed statistically significant differences in plasma abundance levels comparing samples collected at time of diagnosis or just before surgery under anaesthesia. Conclusions: The abundance levels of the plasma proteome in samples collected before incision, i.e., after short-time fasting and under general anaesthesia differs greatly from levels in samples from awake patients. This emphasizes the need for careful matching of the pre-analytical conditions of samples collected from controls to cases at time of surgery in the discovery as well as clinical use of protein biomarkers.
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| 7. |
- Hedlund Lindberg, Julia, et al.
(författare)
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Toward ovarian cancer screening with protein biomarkers using dried, self-sampled cervico-vaginal fluid
- 2024
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Ingår i: iScience. - : Cell Press. - 2589-0042. ; 27:2
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Tidskriftsartikel (refereegranskat)abstract
- Early detection is key for increased survival in ovarian cancer, but no general screening program exists today due to lack of biomarkers and overall cost versus benefit over traditional clinical methods. Here, we used dried cervico-vaginal fluid (CVF) as sampling matrix coupled with mass spectrometry for detection of protein biomarkers. We find that self-collected CVF on paper cards yields robust results and is suitable for high-throughput proteomics. Artificial intelligence–based methods were used to identify an 11-protein panel that separates cases from controls. In validation data, the panel achieved a sensitivity of 0.97 (95% CI 0.91–1.00) at a specificity of 0.67 (0.40–0.87). Analyses of samples collected prior to development of symptoms indicate that the panel is informative also of future risk of disease. Dried CVF is used in cervical cancer screening, and our results opens the possibility for a screening program also for ovarian cancer, based on self-collected CVF samples.
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| 8. |
- Ivansson, Emma, et al.
(författare)
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Large-scale proteomics reveals precise biomarkers for detection of ovarian cancer in symptomatic women.
- 2024
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Ingår i: Scientific Reports. - 2045-2322. ; 14:1, s. 17288-
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Tidskriftsartikel (refereegranskat)abstract
- Ovarian cancer is the 8th most common cancer among women and has a 5-year survival of only 30-50%. While the survival is close to 90% for stage I tumours it is only 20% for stage IV. Current biomarkers are not sensitive nor specific enough, and novel biomarkers are urgently needed. We used the Explore PEA technology for large-scale analysis of 2943 plasma proteins to search for new biomarkers using two independent clinical cohorts. The discovery analysis using the first cohort identified 296 proteins that had significantly different levels in malign tumours as compared to benign and for 269 (91%) of these, the association was replicated in the second cohort. Multivariate modelling, including all proteins independent of their association in the univariate analysis, identified a model for separating benign conditions from malign tumours (stage I-IV) consisting of three proteins; WFDC2, KRT19 and RBFOX3. This model achieved an AUC of 0.92 in the replication cohort and a sensitivity and specificity of 0.93 and 0.77 at a cut-off developed in the discovery cohort. There was no statistical difference of the performance in the replication cohort compared to the discovery cohort. WFDC2 and KRT19 have previously been associated with ovarian cancer but RBFOX3 has not previously been identified as a potential biomarker. Our results demonstrate the ability of using high-throughput precision proteomics for identification of novel plasma protein biomarker for ovarian cancer detection.
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| 9. |
- Ivansson, Emma, et al.
(författare)
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Large-scale proteomics reveals precise biomarkers for detection of ovarian cancer in symptomatic women
- 2024
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Ingår i: SCIENTIFIC REPORTS. - 2045-2322. ; 14:1
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Tidskriftsartikel (refereegranskat)abstract
- Ovarian cancer is the 8th most common cancer among women and has a 5-year survival of only 30-50%. While the survival is close to 90% for stage I tumours it is only 20% for stage IV. Current biomarkers are not sensitive nor specific enough, and novel biomarkers are urgently needed. We used the Explore PEA technology for large-scale analysis of 2943 plasma proteins to search for new biomarkers using two independent clinical cohorts. The discovery analysis using the first cohort identified 296 proteins that had significantly different levels in malign tumours as compared to benign and for 269 (91%) of these, the association was replicated in the second cohort. Multivariate modelling, including all proteins independent of their association in the univariate analysis, identified a model for separating benign conditions from malign tumours (stage I-IV) consisting of three proteins; WFDC2, KRT19 and RBFOX3. This model achieved an AUC of 0.92 in the replication cohort and a sensitivity and specificity of 0.93 and 0.77 at a cut-off developed in the discovery cohort. There was no statistical difference of the performance in the replication cohort compared to the discovery cohort. WFDC2 and KRT19 have previously been associated with ovarian cancer but RBFOX3 has not previously been identified as a potential biomarker. Our results demonstrate the ability of using high-throughput precision proteomics for identification of novel plasma protein biomarker for ovarian cancer detection.
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| 10. |
- Ivarsson, Karin, 1970, et al.
(författare)
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Diverse effects of FSH and LH on proliferation of human ovarian surface epithelial cells.
- 2001
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Ingår i: Human reproduction (Oxford, England). - : Oxford University Press (OUP). - 0268-1161 .- 1460-2350. ; 16:1, s. 18-23
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Tidskriftsartikel (refereegranskat)abstract
- The purpose of this study was to evaluate the effects of FSH and LH on growth regulation of normal ovarian surface epithelial (OSE) cells harvested from both premenopausal and postmenopausal women. Ovarian surface epithelial cells were obtained through brushing of the ovarian surface during surgery. FSH and LH were added to the OSE cultures and the proliferative effects were analysed using two different culture models, non-confluent and confluent cells, and two different detection methods, [(3)H]thymidine incorporation and a colorimetric cell number assay. FSH lowered the OSE proliferation under non-confluent conditions (10-27%), and the inhibitory effect was most pronounced among cells from postmenopausal women (P: < 0.01). In the confluent model only cells from postmenopausal women showed significantly (P: < 0.05) decreased proliferation. No effects of LH on OSE cells were detected. The unexpected results of an anti-proliferative effect of FSH on OSE, and the absence of effect by LH, do not support the theory that gonadotrophins are directly involved in ovarian carcinogenesis through an enhanced proliferation of OSE cells.
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