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3. Genomic Classifiers in Personalized Prostate Cancer Radiation Therapy Approaches: A Systematic Review and Future Perspectives Based on International Consensus.

Author

Spohn, S.K.B., Draulans, C., Kishan, A.U., Spratt, D., Ross, A., Maurer, T., Tilki, D., Berlin, A., Blanchard, P., Collins, S., Bronsert, P., Chen, Ronald, Pra, A.D., Meerleer, G. de, Eade, T., Haustermans, K., Hölscher, T., Höcht, S., Ghadjar, P., Davicioni, E., Heck, M., Kerkmeijer, L.G.W., Kirste, S., Tselis, N., Tran, P.T., Pinkawa, M., Pommier, P., Deltas, C., Schmidt-Hegemann, N.S., Wiegel, T., Zilli, T., Tree, A.C., Qiu, X., Murthy, V., Epstein, J.I., Graztke, C., Gao, X., Grosu, A.L., Kamran, S.C., Zamboglou, C., Spohn, S.K.B., Draulans, C., Kishan, A.U., Spratt, D., Ross, A., Maurer, T., Tilki, D., Berlin, A., Blanchard, P., Collins, S., Bronsert, P., Chen, Ronald, Pra, A.D., Meerleer, G. de, Eade, T., Haustermans, K., Hölscher, T., Höcht, S., Ghadjar, P., Davicioni, E., Heck, M., Kerkmeijer, L.G.W., Kirste, S., Tselis, N., Tran, P.T., Pinkawa, M., Pommier, P., Deltas, C., Schmidt-Hegemann, N.S., Wiegel, T., Zilli, T., Tree, A.C., Qiu, X., Murthy, V., Epstein, J.I., Graztke, C., Gao, X., Grosu, A.L., Kamran, S.C., and Zamboglou, C.

Abstract

Item does not contain fulltext, Current risk-stratification systems for prostate cancer (PCa) do not sufficiently reflect the disease heterogeneity. Genomic classifiers (GC) enable improved risk stratification after surgery, but less data exist for patients treated with definitive radiation therapy (RT) or RT in oligo-/metastatic disease stages. To guide future perspectives of GCs for RT, we conducted (1) a systematic review on the evidence of GCs for patients treated with RT and (2) a survey of experts using the Delphi method, addressing the role of GCs in personalized treatments to identify relevant fields of future clinical and translational research. We performed a systematic review and screened ongoing clinical trials on ClinicalTrials.gov. Based on these results, a multidisciplinary international team of experts received an adapted Delphi method survey. Thirty-one and 30 experts answered round 1 and round 2, respectively. Questions with ≥75% agreement were considered relevant and included in the qualitative synthesis. Evidence for GCs as predictive biomarkers is mainly available to the postoperative RT setting. Validation of GCs as prognostic markers in the definitive RT setting is emerging. Experts used GCs in patients with PCa with extensive metastases (30%), in postoperative settings (27%), and in newly diagnosed PCa (23%). Forty-seven percent of experts do not currently use GCs in clinical practice. Expert consensus demonstrates that GCs are promising tools to improve risk-stratification in primary and oligo-/metastatic patients in addition to existing classifications. Experts were convinced that GCs might guide treatment decisions in terms of RT-field definition and intensification/deintensification in various disease stages. This work confirms the value of GCs and the promising evidence of GC utility in the setting of RT. Additional studies of GCs as prognostic biomarkers are anticipated and form the basis for future studies addressing predictive capabilities of GCs to optimize RT and

Published
2023

4. Preoperative CA125 Significantly Improves Risk Stratification in High-Grade Endometrial Cancer

Author

Lombaers, M.S., Cornel, Karlijn M.C., Visser, N.C.M., Bulten, J., Kusters-van de Velde, H.V.N., Amant, Frederic, Boll, Dorry, Bronsert, P., Colas, E., Geomini, Peggy M. A. J., Gil-Moreno, A., Hamont, D. van, Huvila, J., Krakstad, Camilla, Kraayenbrink, A.A., Koskas, M., Mancebo, G., Matias-Guiu, X., Ngo, Huy, Pijlman, B.M., Vos, Maria Caroline, Weinberger, Vit, Snijders, Marc P. L. M., Koeverden, S.W. van, Haldorsen, Ingfrid S., Reijnen, C., Pijnenborg, J.M.A., Lombaers, M.S., Cornel, Karlijn M.C., Visser, N.C.M., Bulten, J., Kusters-van de Velde, H.V.N., Amant, Frederic, Boll, Dorry, Bronsert, P., Colas, E., Geomini, Peggy M. A. J., Gil-Moreno, A., Hamont, D. van, Huvila, J., Krakstad, Camilla, Kraayenbrink, A.A., Koskas, M., Mancebo, G., Matias-Guiu, X., Ngo, Huy, Pijlman, B.M., Vos, Maria Caroline, Weinberger, Vit, Snijders, Marc P. L. M., Koeverden, S.W. van, Haldorsen, Ingfrid S., Reijnen, C., and Pijnenborg, J.M.A.

Abstract

Contains fulltext : 294914.pdf (Publisher’s version ) (Open Access)

Published
2023

5. The cutoff for estrogen and progesterone receptor expression in endometrial cancer revisited: a European Network for Individualized Treatment of Endometrial Cancer collaboration study

Author

Weelden, W.J. van, Reijnen, C., Kusters-vandevelde, H.V., Bulten, J., Bult, P., Leung, S., Visser, N.C.M., Santacana, M., Bronsert, P., Hirschfeld, M., Colas, E., Gil-Moreno, A., Reques, A., Mancebo, G., Huvila, J., Koskas, M., Weinberger, V., Bednarikova, M., Hausnerova, J., Snijders, M., Matias-Guiu, X., Amant, F., Weelden, W.J. van, Reijnen, C., Kusters-vandevelde, H.V., Bulten, J., Bult, P., Leung, S., Visser, N.C.M., Santacana, M., Bronsert, P., Hirschfeld, M., Colas, E., Gil-Moreno, A., Reques, A., Mancebo, G., Huvila, J., Koskas, M., Weinberger, V., Bednarikova, M., Hausnerova, J., Snijders, M., Matias-Guiu, X., and Amant, F.

Abstract

Item does not contain fulltext, There is no consensus on the cutoff for positivity of estrogen receptor (ER) and progesterone receptor (PR) in endometrial cancer (EC). Therefore, we determined the cutoff value for ER and PR expression with the strongest prognostic impact on the outcome. Immunohistochemical expression of ER and PR was scored as a percentage of positive EC cell nuclei. Cutoff values were related to disease-specific survival (DSS) and disease-free survival (DFS) using sensitivity, specificity, and multivariable regression analysis. The results were validated in an independent cohort. The study cohort (n = 527) included 82% of grade 1-2 and 18% of grade 3 EC. Specificity for DSS and DFS was highest for the cutoff values of 1-30%. Sensitivity was highest for the cutoff values of 80-90%. ER and PR expression were independent markers for DSS at cutoff values of 10% and 80%. Consequently, three subgroups with distinct clinical outcomes were identified: 0-10% of ER/PR expression with, unfavorable outcome (5-year DSS = 75.9-83.3%); 20-80% of ER/PR expression with, intermediate outcome (5-year DSS = 93.0-93.9%); and 90-100% of ER/PR expression with, favorable outcome (5-year DSS = 97.8-100%). The association between ER/PR subgroups and outcomes was confirmed in the validation cohort (n = 265). We propose classification of ER and PR expression based on a high-risk (0-10%), intermediate-risk (20-80%), and low-risk (90-100%) group.

Published
2021

6. The cutoff for estrogen and progesterone receptor expression in endometrial cancer revisited: a European Network for Individualized Treatment of Endometrial Cancer collaboration study

Author

Weelden, W.J. van, Reijnen, C., Kusters-vandevelde, H.V., Bulten, J., Bult, P., Leung, S., Visser, N.C.M., Santacana, M., Bronsert, P., Hirschfeld, M., Colas, E., Gil-Moreno, A., Reques, A., Mancebo, G., Huvila, J., Koskas, M., Weinberger, V., Bednarikova, M., Hausnerova, J., Snijders, M., Matias-Guiu, X., Amant, F., Weelden, W.J. van, Reijnen, C., Kusters-vandevelde, H.V., Bulten, J., Bult, P., Leung, S., Visser, N.C.M., Santacana, M., Bronsert, P., Hirschfeld, M., Colas, E., Gil-Moreno, A., Reques, A., Mancebo, G., Huvila, J., Koskas, M., Weinberger, V., Bednarikova, M., Hausnerova, J., Snijders, M., Matias-Guiu, X., and Amant, F.

Abstract

Contains fulltext : 232535.pdf (Publisher’s version ) (Closed access), There is no consensus on the cutoff for positivity of estrogen receptor (ER) and progesterone receptor (PR) in endometrial cancer (EC). Therefore, we determined the cutoff value for ER and PR expression with the strongest prognostic impact on the outcome. Immunohistochemical expression of ER and PR was scored as a percentage of positive EC cell nuclei. Cutoff values were related to disease-specific survival (DSS) and disease-free survival (DFS) using sensitivity, specificity, and multivariable regression analysis. The results were validated in an independent cohort. The study cohort (n = 527) included 82% of grade 1-2 and 18% of grade 3 EC. Specificity for DSS and DFS was highest for the cutoff values of 1-30%. Sensitivity was highest for the cutoff values of 80-90%. ER and PR expression were independent markers for DSS at cutoff values of 10% and 80%. Consequently, three subgroups with distinct clinical outcomes were identified: 0-10% of ER/PR expression with, unfavorable outcome (5-year DSS = 75.9-83.3%); 20-80% of ER/PR expression with, intermediate outcome (5-year DSS = 93.0-93.9%); and 90-100% of ER/PR expression with, favorable outcome (5-year DSS = 97.8-100%). The association between ER/PR subgroups and outcomes was confirmed in the validation cohort (n = 265). We propose classification of ER and PR expression based on a high-risk (0-10%), intermediate-risk (20-80%), and low-risk (90-100%) group.

Published
2021

7. The cutoff for estrogen and progesterone receptor expression in endometrial cancer revisited: a European Network for Individualized Treatment of Endometrial Cancer collaboration study

Author

Weelden, W.J. van, Reijnen, C., Kusters-vandevelde, H.V., Bulten, J., Bult, P., Leung, S., Visser, N.C.M., Santacana, M., Bronsert, P., Hirschfeld, M., Colas, E., Gil-Moreno, A., Reques, A., Mancebo, G., Huvila, J., Koskas, M., Weinberger, V., Bednarikova, M., Hausnerova, J., Snijders, M., Matias-Guiu, X., Amant, F., Weelden, W.J. van, Reijnen, C., Kusters-vandevelde, H.V., Bulten, J., Bult, P., Leung, S., Visser, N.C.M., Santacana, M., Bronsert, P., Hirschfeld, M., Colas, E., Gil-Moreno, A., Reques, A., Mancebo, G., Huvila, J., Koskas, M., Weinberger, V., Bednarikova, M., Hausnerova, J., Snijders, M., Matias-Guiu, X., and Amant, F.

Abstract

Contains fulltext : 232535.pdf (Publisher’s version ) (Closed access), There is no consensus on the cutoff for positivity of estrogen receptor (ER) and progesterone receptor (PR) in endometrial cancer (EC). Therefore, we determined the cutoff value for ER and PR expression with the strongest prognostic impact on the outcome. Immunohistochemical expression of ER and PR was scored as a percentage of positive EC cell nuclei. Cutoff values were related to disease-specific survival (DSS) and disease-free survival (DFS) using sensitivity, specificity, and multivariable regression analysis. The results were validated in an independent cohort. The study cohort (n = 527) included 82% of grade 1-2 and 18% of grade 3 EC. Specificity for DSS and DFS was highest for the cutoff values of 1-30%. Sensitivity was highest for the cutoff values of 80-90%. ER and PR expression were independent markers for DSS at cutoff values of 10% and 80%. Consequently, three subgroups with distinct clinical outcomes were identified: 0-10% of ER/PR expression with, unfavorable outcome (5-year DSS = 75.9-83.3%); 20-80% of ER/PR expression with, intermediate outcome (5-year DSS = 93.0-93.9%); and 90-100% of ER/PR expression with, favorable outcome (5-year DSS = 97.8-100%). The association between ER/PR subgroups and outcomes was confirmed in the validation cohort (n = 265). We propose classification of ER and PR expression based on a high-risk (0-10%), intermediate-risk (20-80%), and low-risk (90-100%) group.

Published
2021

8. Preoperative risk stratification in endometrial cancer (ENDORISK) by a Bayesian network model: A development and validation study

Author

Reijnen, C., Gogou, E., Visser, N.C.M., Engerud, H., Ramjith, J., Putten, L.J.M. van der, Vijver, K. van der, Santacana, M., Bronsert, P., Bulten, J., Hirschfeld, M., Colas, E., Gil-Moreno, A., Reques, A., Mancebo, G., Krakstad, C., Trovik, J., Haldorsen, I.S., Huvila, J., Koskas, M., Weinberger, V., Bednarikova, M., Hausnerova, J., Wurff, A.A. van der, Matias-Guiu, X., Amant, F., Massuger, L.F.A.G., Snijders, M.P., Kusters-van de Velde, H.V.N., Lucas, P.J., Pijnenborg, J.M.A., Reijnen, C., Gogou, E., Visser, N.C.M., Engerud, H., Ramjith, J., Putten, L.J.M. van der, Vijver, K. van der, Santacana, M., Bronsert, P., Bulten, J., Hirschfeld, M., Colas, E., Gil-Moreno, A., Reques, A., Mancebo, G., Krakstad, C., Trovik, J., Haldorsen, I.S., Huvila, J., Koskas, M., Weinberger, V., Bednarikova, M., Hausnerova, J., Wurff, A.A. van der, Matias-Guiu, X., Amant, F., Massuger, L.F.A.G., Snijders, M.P., Kusters-van de Velde, H.V.N., Lucas, P.J., and Pijnenborg, J.M.A.

Abstract

Contains fulltext : 220465.pdf (publisher's version ) (Open Access), BACKGROUND: Bayesian networks (BNs) are machine-learning-based computational models that visualize causal relationships and provide insight into the processes underlying disease progression, closely resembling clinical decision-making. Preoperative identification of patients at risk for lymph node metastasis (LNM) is challenging in endometrial cancer, and although several biomarkers are related to LNM, none of them are incorporated in clinical practice. The aim of this study was to develop and externally validate a preoperative BN to predict LNM and outcome in endometrial cancer patients. METHODS AND FINDINGS: Within the European Network for Individualized Treatment of Endometrial Cancer (ENITEC), we performed a retrospective multicenter cohort study including 763 patients, median age 65 years (interquartile range [IQR] 58-71), surgically treated for endometrial cancer between February 1995 and August 2013 at one of the 10 participating European hospitals. A BN was developed using score-based machine learning in addition to expert knowledge. Our main outcome measures were LNM and 5-year disease-specific survival (DSS). Preoperative clinical, histopathological, and molecular biomarkers were included in the network. External validation was performed using 2 prospective study cohorts: the Molecular Markers in Treatment in Endometrial Cancer (MoMaTEC) study cohort, including 446 Norwegian patients, median age 64 years (IQR 59-74), treated between May 2001 and 2010; and the PIpelle Prospective ENDOmetrial carcinoma (PIPENDO) study cohort, including 384 Dutch patients, median age 66 years (IQR 60-73), treated between September 2011 and December 2013. A BN called ENDORISK (preoperative risk stratification in endometrial cancer) was developed including the following predictors: preoperative tumor grade; immunohistochemical expression of estrogen receptor (ER), progesterone receptor (PR), p53, and L1 cell adhesion molecule (L1CAM); cancer antigen 125 serum level; thrombocyte

Published
2020

9. Preoperative risk stratification in endometrial cancer (ENDORISK) by a Bayesian network model: A development and validation study

Author

Reijnen, C., Gogou, E., Visser, N.C.M., Engerud, H., Ramjith, J., Putten, L.J.M. van der, Vijver, K. van der, Santacana, M., Bronsert, P., Bulten, J., Hirschfeld, M., Colas, E., Gil-Moreno, A., Reques, A., Mancebo, G., Krakstad, C., Trovik, J., Haldorsen, I.S., Huvila, J., Koskas, M., Weinberger, V., Bednarikova, M., Hausnerova, J., Wurff, A.A. van der, Matias-Guiu, X., Amant, F., Massuger, L.F.A.G., Snijders, M.P., Kusters-van de Velde, H.V.N., Lucas, P.J., Pijnenborg, J.M.A., Reijnen, C., Gogou, E., Visser, N.C.M., Engerud, H., Ramjith, J., Putten, L.J.M. van der, Vijver, K. van der, Santacana, M., Bronsert, P., Bulten, J., Hirschfeld, M., Colas, E., Gil-Moreno, A., Reques, A., Mancebo, G., Krakstad, C., Trovik, J., Haldorsen, I.S., Huvila, J., Koskas, M., Weinberger, V., Bednarikova, M., Hausnerova, J., Wurff, A.A. van der, Matias-Guiu, X., Amant, F., Massuger, L.F.A.G., Snijders, M.P., Kusters-van de Velde, H.V.N., Lucas, P.J., and Pijnenborg, J.M.A.

Abstract

Contains fulltext : 220465.pdf (publisher's version ) (Open Access), BACKGROUND: Bayesian networks (BNs) are machine-learning-based computational models that visualize causal relationships and provide insight into the processes underlying disease progression, closely resembling clinical decision-making. Preoperative identification of patients at risk for lymph node metastasis (LNM) is challenging in endometrial cancer, and although several biomarkers are related to LNM, none of them are incorporated in clinical practice. The aim of this study was to develop and externally validate a preoperative BN to predict LNM and outcome in endometrial cancer patients. METHODS AND FINDINGS: Within the European Network for Individualized Treatment of Endometrial Cancer (ENITEC), we performed a retrospective multicenter cohort study including 763 patients, median age 65 years (interquartile range [IQR] 58-71), surgically treated for endometrial cancer between February 1995 and August 2013 at one of the 10 participating European hospitals. A BN was developed using score-based machine learning in addition to expert knowledge. Our main outcome measures were LNM and 5-year disease-specific survival (DSS). Preoperative clinical, histopathological, and molecular biomarkers were included in the network. External validation was performed using 2 prospective study cohorts: the Molecular Markers in Treatment in Endometrial Cancer (MoMaTEC) study cohort, including 446 Norwegian patients, median age 64 years (IQR 59-74), treated between May 2001 and 2010; and the PIpelle Prospective ENDOmetrial carcinoma (PIPENDO) study cohort, including 384 Dutch patients, median age 66 years (IQR 60-73), treated between September 2011 and December 2013. A BN called ENDORISK (preoperative risk stratification in endometrial cancer) was developed including the following predictors: preoperative tumor grade; immunohistochemical expression of estrogen receptor (ER), progesterone receptor (PR), p53, and L1 cell adhesion molecule (L1CAM); cancer antigen 125 serum level; thrombocyte

Published
2020

10. Preoperative risk stratification in endometrial cancer (ENDORISK) by a Bayesian network model: A development and validation study

Author

Reijnen, C., Gogou, E., Visser, N.C.M., Engerud, H., Ramjith, J., Putten, L.J.M. van der, Vijver, K. van der, Santacana, M., Bronsert, P., Bulten, J., Hirschfeld, M., Colas, E., Gil-Moreno, A., Reques, A., Mancebo, G., Krakstad, C., Trovik, J., Haldorsen, I.S., Huvila, J., Koskas, M., Weinberger, V., Bednarikova, M., Hausnerova, J., Wurff, A.A. van der, Matias-Guiu, X., Amant, F., Massuger, L.F.A.G., Snijders, M.P., Kusters-van de Velde, H.V.N., Lucas, P.J., Pijnenborg, J.M.A., Reijnen, C., Gogou, E., Visser, N.C.M., Engerud, H., Ramjith, J., Putten, L.J.M. van der, Vijver, K. van der, Santacana, M., Bronsert, P., Bulten, J., Hirschfeld, M., Colas, E., Gil-Moreno, A., Reques, A., Mancebo, G., Krakstad, C., Trovik, J., Haldorsen, I.S., Huvila, J., Koskas, M., Weinberger, V., Bednarikova, M., Hausnerova, J., Wurff, A.A. van der, Matias-Guiu, X., Amant, F., Massuger, L.F.A.G., Snijders, M.P., Kusters-van de Velde, H.V.N., Lucas, P.J., and Pijnenborg, J.M.A.

Abstract

Contains fulltext : 220465.pdf (publisher's version ) (Open Access), BACKGROUND: Bayesian networks (BNs) are machine-learning-based computational models that visualize causal relationships and provide insight into the processes underlying disease progression, closely resembling clinical decision-making. Preoperative identification of patients at risk for lymph node metastasis (LNM) is challenging in endometrial cancer, and although several biomarkers are related to LNM, none of them are incorporated in clinical practice. The aim of this study was to develop and externally validate a preoperative BN to predict LNM and outcome in endometrial cancer patients. METHODS AND FINDINGS: Within the European Network for Individualized Treatment of Endometrial Cancer (ENITEC), we performed a retrospective multicenter cohort study including 763 patients, median age 65 years (interquartile range [IQR] 58-71), surgically treated for endometrial cancer between February 1995 and August 2013 at one of the 10 participating European hospitals. A BN was developed using score-based machine learning in addition to expert knowledge. Our main outcome measures were LNM and 5-year disease-specific survival (DSS). Preoperative clinical, histopathological, and molecular biomarkers were included in the network. External validation was performed using 2 prospective study cohorts: the Molecular Markers in Treatment in Endometrial Cancer (MoMaTEC) study cohort, including 446 Norwegian patients, median age 64 years (IQR 59-74), treated between May 2001 and 2010; and the PIpelle Prospective ENDOmetrial carcinoma (PIPENDO) study cohort, including 384 Dutch patients, median age 66 years (IQR 60-73), treated between September 2011 and December 2013. A BN called ENDORISK (preoperative risk stratification in endometrial cancer) was developed including the following predictors: preoperative tumor grade; immunohistochemical expression of estrogen receptor (ER), progesterone receptor (PR), p53, and L1 cell adhesion molecule (L1CAM); cancer antigen 125 serum level; thrombocyte

Published
2020

11. Addition of IMP3 to L1CAM for discrimination between low- and high-grade endometrial carcinomas: a European Network for Individualised Treatment of Endometrial Cancer collaboration study

Author

Visser, N.C.M., Putten, L.J.M. van der, Egerschot, Alex van, Vijver, K.K. Van de, Santacana, M., Bronsert, P., Massuger, L.F.A.G., Bulten, J., Pijnenborg, J.M.A., Visser, N.C.M., Putten, L.J.M. van der, Egerschot, Alex van, Vijver, K.K. Van de, Santacana, M., Bronsert, P., Massuger, L.F.A.G., Bulten, J., and Pijnenborg, J.M.A.

Abstract

Contains fulltext : 206010.pdf (publisher's version ) (Closed access)

Published
2019

12. Addition of IMP3 to L1CAM for discrimination between low- and high-grade endometrial carcinomas: a European Network for Individualised Treatment of Endometrial Cancer collaboration study

Author

Visser, N.C.M., Putten, L.J.M. van der, Egerschot, Alex van, Vijver, K.K. Van de, Santacana, M., Bronsert, P., Massuger, L.F.A.G., Bulten, J., Pijnenborg, J.M.A., Visser, N.C.M., Putten, L.J.M. van der, Egerschot, Alex van, Vijver, K.K. Van de, Santacana, M., Bronsert, P., Massuger, L.F.A.G., Bulten, J., and Pijnenborg, J.M.A.

Abstract

Contains fulltext : 206010.pdf (publisher's version ) (Closed access)

Published
2019

13. Added Value of Estrogen Receptor, Progesterone Receptor, and L1 Cell Adhesion Molecule Expression to Histology-Based Endometrial Carcinoma Recurrence Prediction Models: An ENITEC Collaboration Study

Author

Putten, L.J.M. van der, Visser, N.C.M., Vijver, K.K. Van de, Santacana, M., Bronsert, P., Bulten, J., Massuger, L.F.A.G., Pijnenborg, J.M.A., Putten, L.J.M. van der, Visser, N.C.M., Vijver, K.K. Van de, Santacana, M., Bronsert, P., Bulten, J., Massuger, L.F.A.G., and Pijnenborg, J.M.A.

Abstract

Contains fulltext : 189747.pdf (publisher's version ) (Closed access)

Published
2018

14. Added Value of Estrogen Receptor, Progesterone Receptor, and L1 Cell Adhesion Molecule Expression to Histology-Based Endometrial Carcinoma Recurrence Prediction Models: An ENITEC Collaboration Study

Author

Putten, L.J.M. van der, Visser, N.C.M., Vijver, K.K. Van de, Santacana, M., Bronsert, P., Bulten, J., Massuger, L.F.A.G., Pijnenborg, J.M.A., Putten, L.J.M. van der, Visser, N.C.M., Vijver, K.K. Van de, Santacana, M., Bronsert, P., Bulten, J., Massuger, L.F.A.G., and Pijnenborg, J.M.A.

Abstract

Contains fulltext : 189747.pdf (publisher's version ) (Closed access)

Published
2018

15. Added Value of Estrogen Receptor, Progesterone Receptor, and L1 Cell Adhesion Molecule Expression to Histology-Based Endometrial Carcinoma Recurrence Prediction Models: An ENITEC Collaboration Study

Author

Putten, L.J.M. van der, Visser, N.C.M., Vijver, K.K. Van de, Santacana, M., Bronsert, P., Bulten, J., Massuger, L.F.A.G., Pijnenborg, J.M.A., Putten, L.J.M. van der, Visser, N.C.M., Vijver, K.K. Van de, Santacana, M., Bronsert, P., Bulten, J., Massuger, L.F.A.G., and Pijnenborg, J.M.A.

Abstract

Contains fulltext : 189747.pdf (publisher's version ) (Closed access)

Published
2018

16. L1CAM expression in endometrial carcinomas: an ENITEC collaboration study

Author

Putten, L.J.M. van der, Visser, N.C.M., Vijver, K. van der, Santacana, M., Bronsert, P., Bulten, J., Hirschfeld, M., Colas, E., Gil-Moreno, A., Garcia, A., Mancebo, G., Alameda, F., Trovik, J., Kopperud, R.K., Huvila, J., Schrauwen, S., Koskas, M., Walker, F., Weinberger, V., Minar, L., Jandakova, E., Snijders, M.P.M.L., Erp, S. van, Matias-Guiu, X., Salvesen, H.B., Amant, F., Massuger, L.F.A.G., Pijnenborg, J.M.A., Putten, L.J.M. van der, Visser, N.C.M., Vijver, K. van der, Santacana, M., Bronsert, P., Bulten, J., Hirschfeld, M., Colas, E., Gil-Moreno, A., Garcia, A., Mancebo, G., Alameda, F., Trovik, J., Kopperud, R.K., Huvila, J., Schrauwen, S., Koskas, M., Walker, F., Weinberger, V., Minar, L., Jandakova, E., Snijders, M.P.M.L., Erp, S. van, Matias-Guiu, X., Salvesen, H.B., Amant, F., Massuger, L.F.A.G., and Pijnenborg, J.M.A.

Abstract

Contains fulltext : 165692.pdf (publisher's version ) (Open Access), BACKGROUND: Identification of aggressive endometrioid endometrial carcinomas (EECs) and non-endometrioid carcinomas (NEECs) is essential to improve outcome. L1 cell adhesion molecule (L1CAM) expression is a strong prognostic marker in stage I EECs, but less is known about L1CAM expression in advanced-stage EECs and NEECs. This study analyses L1CAM expression in a clinically representative cohort of endometrial carcinomas. METHODS: The expression of L1CAM was immunohistochemically determined in 1199 endometrial carcinomas, treated at one of the European Network for Individualized Treatment of Endometrial Cancer (ENITEC) centres. Staining was considered positive when >10% of the tumour cells expressed L1CAM. The association between L1CAM expression and several clincopathological characteristics and disease outcome was calculated. RESULTS: In all, L1CAM was expressed in 10% of the 935 stage I EECs, 18% of the 160 advanced stage EECs, and 75% of the 104 NEECs. The expression of L1CAM was associated with advanced stage, nodal involvement, high tumour grade, non-endometrioid histology, lymphovascular space invasion, and distant recurrences in all cases, and with reduced survival in the EECs, but not in the NEECs. CONCLUSIONS: The expression of L1CAM is a strong predictor of poor outcome in EECs, but not NEECs. It is strongly associated with non-endometrioid histology and distant spread, and could improve the postoperative selection of high-risk endometrial carcinomas. The value of L1CAM expression in the preoperative selection of high-risk endometrial carcinomas should be studied.

Published
2016

17. L1CAM expression in endometrial carcinomas: an ENITEC collaboration study

Author

Putten, L.J.M. van der, Visser, N.C.M., Vijver, K. van der, Santacana, M., Bronsert, P., Bulten, J., Hirschfeld, M., Colas, E., Gil-Moreno, A., Garcia, A., Mancebo, G., Alameda, F., Trovik, J., Kopperud, R.K., Huvila, J., Schrauwen, S., Koskas, M., Walker, F., Weinberger, V., Minar, L., Jandakova, E., Snijders, M.P.M.L., Erp, S. van, Matias-Guiu, X., Salvesen, H.B., Amant, F., Massuger, L.F.A.G., Pijnenborg, J.M.A., Putten, L.J.M. van der, Visser, N.C.M., Vijver, K. van der, Santacana, M., Bronsert, P., Bulten, J., Hirschfeld, M., Colas, E., Gil-Moreno, A., Garcia, A., Mancebo, G., Alameda, F., Trovik, J., Kopperud, R.K., Huvila, J., Schrauwen, S., Koskas, M., Walker, F., Weinberger, V., Minar, L., Jandakova, E., Snijders, M.P.M.L., Erp, S. van, Matias-Guiu, X., Salvesen, H.B., Amant, F., Massuger, L.F.A.G., and Pijnenborg, J.M.A.

Abstract

Contains fulltext : 165692.pdf (publisher's version ) (Open Access), BACKGROUND: Identification of aggressive endometrioid endometrial carcinomas (EECs) and non-endometrioid carcinomas (NEECs) is essential to improve outcome. L1 cell adhesion molecule (L1CAM) expression is a strong prognostic marker in stage I EECs, but less is known about L1CAM expression in advanced-stage EECs and NEECs. This study analyses L1CAM expression in a clinically representative cohort of endometrial carcinomas. METHODS: The expression of L1CAM was immunohistochemically determined in 1199 endometrial carcinomas, treated at one of the European Network for Individualized Treatment of Endometrial Cancer (ENITEC) centres. Staining was considered positive when >10% of the tumour cells expressed L1CAM. The association between L1CAM expression and several clincopathological characteristics and disease outcome was calculated. RESULTS: In all, L1CAM was expressed in 10% of the 935 stage I EECs, 18% of the 160 advanced stage EECs, and 75% of the 104 NEECs. The expression of L1CAM was associated with advanced stage, nodal involvement, high tumour grade, non-endometrioid histology, lymphovascular space invasion, and distant recurrences in all cases, and with reduced survival in the EECs, but not in the NEECs. CONCLUSIONS: The expression of L1CAM is a strong predictor of poor outcome in EECs, but not NEECs. It is strongly associated with non-endometrioid histology and distant spread, and could improve the postoperative selection of high-risk endometrial carcinomas. The value of L1CAM expression in the preoperative selection of high-risk endometrial carcinomas should be studied.

Published
2016

18. L1CAM expression in endometrial carcinomas: an ENITEC collaboration study

Author

Putten, L.J.M. van der, Visser, N.C.M., Vijver, K. van der, Santacana, M., Bronsert, P., Bulten, J., Hirschfeld, M., Colas, E., Gil-Moreno, A., Garcia, A., Mancebo, G., Alameda, F., Trovik, J., Kopperud, R.K., Huvila, J., Schrauwen, S., Koskas, M., Walker, F., Weinberger, V., Minar, L., Jandakova, E., Snijders, M.P.M.L., Erp, S. van, Matias-Guiu, X., Salvesen, H.B., Amant, F., Massuger, L.F.A.G., Pijnenborg, J.M.A., Putten, L.J.M. van der, Visser, N.C.M., Vijver, K. van der, Santacana, M., Bronsert, P., Bulten, J., Hirschfeld, M., Colas, E., Gil-Moreno, A., Garcia, A., Mancebo, G., Alameda, F., Trovik, J., Kopperud, R.K., Huvila, J., Schrauwen, S., Koskas, M., Walker, F., Weinberger, V., Minar, L., Jandakova, E., Snijders, M.P.M.L., Erp, S. van, Matias-Guiu, X., Salvesen, H.B., Amant, F., Massuger, L.F.A.G., and Pijnenborg, J.M.A.

Abstract

Contains fulltext : 165692.pdf (publisher's version ) (Open Access), BACKGROUND: Identification of aggressive endometrioid endometrial carcinomas (EECs) and non-endometrioid carcinomas (NEECs) is essential to improve outcome. L1 cell adhesion molecule (L1CAM) expression is a strong prognostic marker in stage I EECs, but less is known about L1CAM expression in advanced-stage EECs and NEECs. This study analyses L1CAM expression in a clinically representative cohort of endometrial carcinomas. METHODS: The expression of L1CAM was immunohistochemically determined in 1199 endometrial carcinomas, treated at one of the European Network for Individualized Treatment of Endometrial Cancer (ENITEC) centres. Staining was considered positive when >10% of the tumour cells expressed L1CAM. The association between L1CAM expression and several clincopathological characteristics and disease outcome was calculated. RESULTS: In all, L1CAM was expressed in 10% of the 935 stage I EECs, 18% of the 160 advanced stage EECs, and 75% of the 104 NEECs. The expression of L1CAM was associated with advanced stage, nodal involvement, high tumour grade, non-endometrioid histology, lymphovascular space invasion, and distant recurrences in all cases, and with reduced survival in the EECs, but not in the NEECs. CONCLUSIONS: The expression of L1CAM is a strong predictor of poor outcome in EECs, but not NEECs. It is strongly associated with non-endometrioid histology and distant spread, and could improve the postoperative selection of high-risk endometrial carcinomas. The value of L1CAM expression in the preoperative selection of high-risk endometrial carcinomas should be studied.

Published
2016

19. Cell reflect ampullary cancer subtypes

Author

Bolm, L, Lai, ZW, Bronsert, P, Bausch, D, Keck, T, Schilling, O, Wellner, UF, Bolm, L, Lai, ZW, Bronsert, P, Bausch, D, Keck, T, Schilling, O, and Wellner, UF

Published
2016

20. Cell reflect ampullary cancer subtypes

Author

Bolm, L, Lai, ZW, Bronsert, P, Bausch, D, Keck, T, Schilling, O, Wellner, UF, Bolm, L, Lai, ZW, Bronsert, P, Bausch, D, Keck, T, Schilling, O, and Wellner, UF

Published
2016

23. Identification of a blood-borne miRNA signature of synovial sarcoma

Author

Fricke, A, Ullrich, PV, Heinz, J, Pfeifer, D, Scholber, J, Herget, GW, Hauschild, O, Bronsert, P, Stark, GB, Bannasch, H, Braig, D, Eisenhardt, SU, Fricke, A, Ullrich, PV, Heinz, J, Pfeifer, D, Scholber, J, Herget, GW, Hauschild, O, Bronsert, P, Stark, GB, Bannasch, H, Braig, D, and Eisenhardt, SU

Published
2015

24. Identification of a blood-borne miRNA signature of synovial sarcoma

Author

Fricke, A, Ullrich, PV, Heinz, J, Pfeifer, D, Scholber, J, Herget, GW, Hauschild, O, Bronsert, P, Stark, GB, Bannasch, H, Braig, D, Eisenhardt, SU, Fricke, A, Ullrich, PV, Heinz, J, Pfeifer, D, Scholber, J, Herget, GW, Hauschild, O, Bronsert, P, Stark, GB, Bannasch, H, Braig, D, and Eisenhardt, SU

Published
2015

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