The Experts below are selected from a list of 15699 Experts worldwide ranked by ideXlab platform
Hiroto Kobayashi - One of the best experts on this subject based on the ideXlab platform.
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patient derived organoids from Endometrial Disease capture clinical heterogeneity and are amenable to drug screening
Nature Cell Biology, 2019Co-Authors: Matteo Boretto, Nina Maenhoudt, Xinlong Luo, Aurelie Hennes, Bram Boeckx, Bich Bui, R Heremans, Lisa Perneel, Hiroto KobayashiAbstract:Endometrial disorders represent a major gynaecological burden. Current research models fail to recapitulate the nature and heterogeneity of these Diseases, thereby hampering scientific and clinical progress. Here we developed long-term expandable organoids from a broad spectrum of Endometrial pathologies. Organoids from endometriosis show Disease-associated traits and cancer-linked mutations. Endometrial cancer-derived organoids accurately capture cancer subtypes, replicate the mutational landscape of the tumours and display patient-specific drug responses. Organoids were also established from precancerous pathologies encompassing Endometrial hyperplasia and Lynch syndrome, and inherited gene mutations were maintained. Endometrial Disease organoids reproduced the original lesion when transplanted in vivo. In summary, we developed multiple organoid models that capture Endometrial Disease diversity and will provide powerful research models and drug screening and discovery tools.
Bich Bui - One of the best experts on this subject based on the ideXlab platform.
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patient derived organoids from Endometrial Disease capture clinical heterogeneity and are amenable to drug screening
Nature Cell Biology, 2019Co-Authors: Matteo Boretto, Nina Maenhoudt, Xinlong Luo, Aurelie Hennes, Bram Boeckx, Bich Bui, R Heremans, Lisa Perneel, Hiroto KobayashiAbstract:Endometrial disorders represent a major gynaecological burden. Current research models fail to recapitulate the nature and heterogeneity of these Diseases, thereby hampering scientific and clinical progress. Here we developed long-term expandable organoids from a broad spectrum of Endometrial pathologies. Organoids from endometriosis show Disease-associated traits and cancer-linked mutations. Endometrial cancer-derived organoids accurately capture cancer subtypes, replicate the mutational landscape of the tumours and display patient-specific drug responses. Organoids were also established from precancerous pathologies encompassing Endometrial hyperplasia and Lynch syndrome, and inherited gene mutations were maintained. Endometrial Disease organoids reproduced the original lesion when transplanted in vivo. In summary, we developed multiple organoid models that capture Endometrial Disease diversity and will provide powerful research models and drug screening and discovery tools.
Matteo Boretto - One of the best experts on this subject based on the ideXlab platform.
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patient derived organoids from Endometrial Disease capture clinical heterogeneity and are amenable to drug screening
Nature Cell Biology, 2019Co-Authors: Matteo Boretto, Nina Maenhoudt, Xinlong Luo, Aurelie Hennes, Bram Boeckx, Bich Bui, R Heremans, Lisa Perneel, Hiroto KobayashiAbstract:Endometrial disorders represent a major gynaecological burden. Current research models fail to recapitulate the nature and heterogeneity of these Diseases, thereby hampering scientific and clinical progress. Here we developed long-term expandable organoids from a broad spectrum of Endometrial pathologies. Organoids from endometriosis show Disease-associated traits and cancer-linked mutations. Endometrial cancer-derived organoids accurately capture cancer subtypes, replicate the mutational landscape of the tumours and display patient-specific drug responses. Organoids were also established from precancerous pathologies encompassing Endometrial hyperplasia and Lynch syndrome, and inherited gene mutations were maintained. Endometrial Disease organoids reproduced the original lesion when transplanted in vivo. In summary, we developed multiple organoid models that capture Endometrial Disease diversity and will provide powerful research models and drug screening and discovery tools.
Justin T Clark - One of the best experts on this subject based on the ideXlab platform.
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outpatient hysteroscopy and ultrasonography in the management of Endometrial Disease
Current Opinion in Obstetrics & Gynecology, 2004Co-Authors: Justin T ClarkAbstract:Purpose of reviewThis review is to inform the ongoing debate about the choice between ultrasound and hysteroscopy in the management of Endometrial Disease presenting with abnormal uterine bleeding using information provided from recently published literature.Recent findingsTransvaginal ultrasound me
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accuracy of hysteroscopy in the diagnosis of Endometrial cancer and hyperplasia a systematic quantitative review
JAMA, 2002Co-Authors: Justin T Clark, Doris Voit, Janesh K Gupta, Chris Hyde, Fujian Song, Khalid S KhanAbstract:ContextHysteroscopy (direct endoscopic visualization of the Endometrial cavity) is used extensively in the evaluation of common gynecologic problems, such as menorrhagia and postmenopausal bleeding. However, there is a continuing debate about the value of this technology in the diagnosis of serious Endometrial Disease.ObjectiveTo determine the accuracy of hysteroscopy in diagnosing Endometrial cancer and hyperplasia in women with abnormal uterine bleeding.Data SourcesRelevant articles were identified through searches of the Cochrane Library, MEDLINE, and EMBASE (1984-2001), manual searches of bibliographies of known primary and review articles, and contact with manufacturers.Study SelectionStudies were selected blindly, independently, and in duplicate if accuracy of hysteroscopy was estimated in women with abnormal uterine bleeding, using histopathologic findings as a reference standard. Our search identified 3486 articles; 208 of these were deemed to be potentially eligible and were retrieved for detailed data extraction. Sixty-five primary studies were analyzed, including 26 346 women.Data ExtractionData were abstracted on characteristics and quality from each study. Results for diagnostic accuracy were extracted to form 2 × 2 contingency tables separately for Endometrial cancer and Endometrial Disease (cancer, hyperplasia, or both). Pooled likelihood ratios (LRs) were used as summary accuracy measures.Data SynthesisThe pretest probability of Endometrial cancer was 3.9% (95% confidence interval [CI], 3.7%-4.2%). A positive hysteroscopy result (pooled LR, 60.9; 95% CI, 51.2-72.5) increased the probability of cancer to 71.8% (95% CI, 67.0%-76.6%), whereas a negative hysteroscopy result (pooled LR, 0.15; 95% CI, 0.13-0.18) reduced the probability of cancer to 0.6% (95% CI, 0.5%-0.8%). There was statistical heterogeneity in pooling of LRs, but an explanation for this could not be found in spectrum composition and study quality. The overall accuracy for the diagnosis of Endometrial Disease was modest compared with that of cancer, and the results were heterogeneous. The accuracy tended to be higher among postmenopausal women and in the outpatient setting.ConclusionThe diagnostic accuracy of hysteroscopy is high for Endometrial cancer, but only moderate for Endometrial Disease (cancer or hyperplasia).
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evaluation of outpatient hysteroscopy and ultrasonography in the diagnosis of Endometrial Disease
Obstetrics & Gynecology, 2002Co-Authors: Justin T Clark, Janesh K Gupta, Shagaf H Bakour, Khalid S KhanAbstract:Abstract OBJECTIVE: To develop a multivariable approach to determine the added value of tests in routine practice where some diagnostic information is already available from clinical history. METHODS: Multivariable logistic regression models were built in a stepwise fashion, considering the clinical sequence used in the rapid access ambulatory diagnosis clinic (clinical history followed by transvaginal ultrasonography and hysteroscopy). The reference standard for confirmation of diagnosis was Endometrial biopsy. The diagnostic accuracy of the models was determined by the area under the receiver operating characteristic curve. RESULTS: The area under the receiver operating characteristic curve for the model including historical features alone was 0.78. When hysteroscopy and ultrasonography were each added to the model, it increased to 0.81 (P = .008 for improvement) and 0.82 (P = .02 for improvement), respectively. CONCLUSION: The type of stepwise analysis we have developed is crucial in facilitating meaningful clinical interpretation about the value of diagnostic technology. Our finding that hysteroscopy or ultrasonography marginally but significantly increased the prediction of serious Endometrial pathology above that predicted from patient history alone needs validation in an independent data set. The use of this approach is recommended when evaluating strategies for diagnosis.
Lisa Perneel - One of the best experts on this subject based on the ideXlab platform.
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patient derived organoids from Endometrial Disease capture clinical heterogeneity and are amenable to drug screening
Nature Cell Biology, 2019Co-Authors: Matteo Boretto, Nina Maenhoudt, Xinlong Luo, Aurelie Hennes, Bram Boeckx, Bich Bui, R Heremans, Lisa Perneel, Hiroto KobayashiAbstract:Endometrial disorders represent a major gynaecological burden. Current research models fail to recapitulate the nature and heterogeneity of these Diseases, thereby hampering scientific and clinical progress. Here we developed long-term expandable organoids from a broad spectrum of Endometrial pathologies. Organoids from endometriosis show Disease-associated traits and cancer-linked mutations. Endometrial cancer-derived organoids accurately capture cancer subtypes, replicate the mutational landscape of the tumours and display patient-specific drug responses. Organoids were also established from precancerous pathologies encompassing Endometrial hyperplasia and Lynch syndrome, and inherited gene mutations were maintained. Endometrial Disease organoids reproduced the original lesion when transplanted in vivo. In summary, we developed multiple organoid models that capture Endometrial Disease diversity and will provide powerful research models and drug screening and discovery tools.