Irene Venturo
Research Subjects
Irene Venturo has a total of 15 co-authors. Here are the top co-authors by number of shared publications:
- Isabella Sperduti
Biostatistics, IRCCS Regina Elena National Cancer Institute, 00144 Rome, Italy
2 shared publications - Alessandra Fabi
Precision Medicine Breast Unit, Scientific Directorate, Department of Women, Children and Public Health Sciences, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy
1 shared publication - Anna Di Benedetto
Department of Pathology, "Regina Elena" National Cancer Institute, Rome, Italy
1 shared publication - Cecilia Nisticò
Department of Medical Oncology, Regina Elena National Cancer Institute, Rome, Italy
1 shared publication - Elisa Melucci
Department of Pathology, Regina Elena National Cancer Institute, Rome, Italy
1 shared publication - Flavia Novelli
Laboratory of Biomedical Technologies, Italian National Agency for New Technologies, Energy and Sustainable Economic Development, ENEA, Casaccia Research Center, Via Anguillarese 301, 00123 Rome, Italy
1 shared publication
Latest Publications
- 1 February 2011
- Published by Elsevier in Cancer Epidemiology
- Vol. 35 (1) , 44-47
Colorectal cancer after breast cancer: A case-control study
- 1 February 2011
- Published by Elsevier in Cancer Epidemiology
- Vol. 35 (1) , 44-47
Colorectal cancer after breast cancer: A case-control study
- Open Access
- 4 September 2008
- Published by Springer Nature in Breast Cancer Research
- Vol. 10 (5) , R74
A divergent role for estrogen receptor-beta in node-positive and node-negative breast cancer classified according to molecular subtypes: an observational prospective study
Introduction: Estrogen receptor-alpha (ER-α) and progesterone receptor (PgR) are consolidated predictors of response to hormonal therapy (HT). In contrast, little information regarding the role of estrogen receptor-beta (ER-β) in various breast cancer risk groups treated with different therapeutic regimens is available. In particular, there are no data concerning ER-β distribution within the novel molecular breast cancer subtypes luminal A (LA) and luminal B (LB), HER2 (HS), and triple-negative (TN). Methods: We conducted an observational prospective study using immunohistochemistry to evaluate ER-β expression in 936 breast carcinomas. Associations with conventional biopathological factors and with molecular subtypes were analyzed by multiple correspondence analysis (MCA), while univariate and multivariate Cox regression analysis and classification and regression tree analysis were applied to determine the impact of ER-β on disease-free survival in the 728 patients with complete follow-up data. Results: ER-β evenly distributes (55.5%) across the four molecular breast cancer subtypes, confirming the lack of correlation between ER-β and classical prognosticators. However, the relationships among the biopathological factors, analyzed by MCA, showed that ER-β positivity is located in the quadrant containing more aggressive phenotypes such as HER2 and TN or ER-α/PgR/Bcl2- tumors. Kaplan-Meier curves and Cox regression analysis identified ER-β as a significant discriminating factor for disease-free survival both in the node-negative LA (P = 0.02) subgroup, where it is predictive of response to HT, and in the node-positive LB (P = 0.04) group, where, in association with PgR negativity, it conveys a higher risk of relapse. Conclusion: Our data indicated that, in contrast to node-negative patients, in node-positive breast cancer patients, ER-β positivity appears to be a biomarker related to a more aggressive clinical course. In this context, further investigations are necessary to better assess the role of the different ER-β isophorms.
- 4 September 2008
- Published by Springer Nature in Breast Cancer Research
- Vol. 10 (5) , R74
Open AccessA divergent role for estrogen receptor-beta in node-positive and node-negative breast cancer classified according to molecular subtypes: an observational prospective study
Introduction: Estrogen receptor-alpha (ER-α) and progesterone receptor (PgR) are consolidated predictors of response to hormonal therapy (HT). In contrast, little information regarding the role of estrogen receptor-beta (ER-β) in various breast cancer risk groups treated with different therapeutic regimens is available. In particular, there are no data concerning ER-β distribution within the novel molecular breast cancer subtypes luminal A (LA) and luminal B (LB), HER2 (HS), and triple-negative (TN). Methods: We conducted an observational prospective study using immunohistochemistry to evaluate ER-β expression in 936 breast carcinomas. Associations with conventional biopathological factors and with molecular subtypes were analyzed by multiple correspondence analysis (MCA), while univariate and multivariate Cox regression analysis and classification and regression tree analysis were applied to determine the impact of ER-β on disease-free survival in the 728 patients with complete follow-up data. Results: ER-β evenly distributes (55.5%) across the four molecular breast cancer subtypes, confirming the lack of correlation between ER-β and classical prognosticators. However, the relationships among the biopathological factors, analyzed by MCA, showed that ER-β positivity is located in the quadrant containing more aggressive phenotypes such as HER2 and TN or ER-α/PgR/Bcl2- tumors. Kaplan-Meier curves and Cox regression analysis identified ER-β as a significant discriminating factor for disease-free survival both in the node-negative LA (P = 0.02) subgroup, where it is predictive of response to HT, and in the node-positive LB (P = 0.04) group, where, in association with PgR negativity, it conveys a higher risk of relapse. Conclusion: Our data indicated that, in contrast to node-negative patients, in node-positive breast cancer patients, ER-β positivity appears to be a biomarker related to a more aggressive clinical course. In this context, further investigations are necessary to better assess the role of the different ER-β isophorms.