Peter N. Fiorica
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Peter N. Fiorica has a total of 149 co-authors. Here are the top co-authors by number of shared publications:
- Song Yao
Department of Cancer Prevention and Control, Roswell Park Comprehensive Cancer Center, Buffalo, USA
42 shared publications - Christine B. Ambrosone
Department of Cancer Prevention and Control, Roswell Park Comprehensive Cancer Center, Buffalo, USA
41 shared publications - Marilyn L. Kwan
Division of Research Kaiser Permanente Northern California Pleasanton California USA
38 shared publications - Qianqian Zhu
Department of Biostatistics and Bioinformatics, Roswell Park Comprehensive Cancer Center, Buffalo, USA
37 shared publications - Cecile. A. Laurent
Division of Research, Kaiser Permanente Northern California , Pleasanton, CA
36 shared publications - Haiyang Sheng
Department of Cancer Prevention and Control, Roswell Park Comprehensive Cancer Center, Buffalo, New York
36 shared publications
Latest Publications
- Open Access
- 17 June 2026
- Published by American Association for Cancer Research (AACR)
Figure S4 from Germline Pathogenic DROSHA Variants Are Linked to Pineoblastoma and Wilms Tumor Predisposition
Figure S4 from Germline Pathogenic DROSHA Variants Are Linked to Pineoblastoma and Wilms Tumor Predisposition
- 17 June 2026
- Published by American Association for Cancer Research (AACR)
Open AccessFigure S4 from Germline Pathogenic DROSHA Variants Are Linked to Pineoblastoma and Wilms Tumor Predisposition
Figure S4 from Germline Pathogenic DROSHA Variants Are Linked to Pineoblastoma and Wilms Tumor Predisposition
- Open Access
- 17 June 2026
- Published by American Association for Cancer Research (AACR)
Supplementary Data 1 from Germline Pathogenic DROSHA Variants Are Linked to Pineoblastoma and Wilms Tumor Predisposition
Supplemental Tables including Representativeness of Study Participants
- 17 June 2026
- Published by American Association for Cancer Research (AACR)
Open AccessSupplementary Data 1 from Germline Pathogenic DROSHA Variants Are Linked to Pineoblastoma and Wilms Tumor Predisposition
Supplemental Tables including Representativeness of Study Participants
- Open Access
- 17 February 2026
- Published by Elsevier in JACC: Cardiooncology
- Vol. 8 (1) , 65-76
Polygenic Risk for Cardiometabolic and Cardiovascular Disease in a Multiethnic Cohort of Breast Cancer Survivors
- 17 February 2026
- Published by Elsevier in JACC: Cardiooncology
- Vol. 8 (1) , 65-76
Open AccessPolygenic Risk for Cardiometabolic and Cardiovascular Disease in a Multiethnic Cohort of Breast Cancer Survivors
- 2 February 2026
- Published by Springer Nature in Nature Genetics
- Vol. 58 (3) , 560-569
Improved polygenic risk prediction models for breast cancer subtypes in women of African ancestry
Polygenic risk score (PRS) models effectively predict breast cancer (BC) risk in European-ancestry women but have limited accuracy for African-ancestry women, particularly for aggressive subtypes. We developed PRS models for overall BC, estrogen receptor (ER)-positive, ER-negative and triple-negative BC (TNBC) in African-ancestry women using data from the African Ancestry Breast Cancer Genetics consortium (17,391 cases and 18,800 controls). We applied several PRS methods and integrated information across ancestries and BC subtypes. The best models for overall, ER-positive, ER-negative and TNBC showed an area under the receiving operating curve of 0.612, 0.621, 0.611 and 0.639, respectively, and maintained predictive accuracy in external validation studies with area under the receiving operating curves of 0.612, 0.640, 0.605 and 0.652. We further introduce a parsimonious 162-variant PRS for TNBC with comparable accuracy (0.626). These findings demonstrate markedly improved PRS accuracy for BC risk prediction in African-ancestry women. Using these PRS models for screening will help promote more equitable cancer prevention efforts.
- 2 February 2026
- Published by Springer Nature in Nature Genetics
- Vol. 58 (3) , 560-569
Improved polygenic risk prediction models for breast cancer subtypes in women of African ancestry
Polygenic risk score (PRS) models effectively predict breast cancer (BC) risk in European-ancestry women but have limited accuracy for African-ancestry women, particularly for aggressive subtypes. We developed PRS models for overall BC, estrogen receptor (ER)-positive, ER-negative and triple-negative BC (TNBC) in African-ancestry women using data from the African Ancestry Breast Cancer Genetics consortium (17,391 cases and 18,800 controls). We applied several PRS methods and integrated information across ancestries and BC subtypes. The best models for overall, ER-positive, ER-negative and TNBC showed an area under the receiving operating curve of 0.612, 0.621, 0.611 and 0.639, respectively, and maintained predictive accuracy in external validation studies with area under the receiving operating curves of 0.612, 0.640, 0.605 and 0.652. We further introduce a parsimonious 162-variant PRS for TNBC with comparable accuracy (0.626). These findings demonstrate markedly improved PRS accuracy for BC risk prediction in African-ancestry women. Using these PRS models for screening will help promote more equitable cancer prevention efforts.