Abstract B04: Immune modeling analysis identifies ICOS and CTLA-4 as predictive biomarkers in serous epithelial ovarian cancer

Author(s):  
Nicole James ◽  
Matthew Oliver ◽  
Joyce Ou ◽  
Jenna Emerson ◽  
Katherine Miller ◽  
...  
2017 ◽  
Vol 145 ◽  
pp. 5-6
Author(s):  
M.E. McDonald ◽  
E.A. Salinas ◽  
A.M. Newtson ◽  
M.J. Goodheart ◽  
K.K. Leslie ◽  
...  

2014 ◽  
Vol 9 (2) ◽  
pp. 422-436 ◽  
Author(s):  
Marta M. Kamieniak ◽  
Daniel Rico ◽  
Roger L. Milne ◽  
Ivan Muñoz-Repeto ◽  
Kristina Ibáñez ◽  
...  

2020 ◽  
Vol 21 (13) ◽  
pp. 4806
Author(s):  
Razia Zakarya ◽  
Viive M. Howell ◽  
Emily K. Colvin

High-grade serous epithelial ovarian cancer (HGSC) is the most aggressive subtype of epithelial ovarian cancer. The identification of germline and somatic mutations along with genomic information unveiled by The Cancer Genome Atlas (TCGA) and other studies has laid the foundation for establishing preclinical models with high fidelity to the molecular features of HGSC. Notwithstanding such progress, the field of HGSC research still lacks a model that is both robust and widely accessible. In this review, we discuss the recent advancements and utility of HGSC genetically engineered mouse models (GEMMs) to date. Further analysis and critique on alternative approaches to modelling HGSC considers technological advancements in somatic gene editing and modelling prototypic organs, capable of tumorigenesis, on a chip.


2020 ◽  
Vol 3 (7) ◽  
pp. e207566
Author(s):  
Lara Paracchini ◽  
Chiara Pesenti ◽  
Martina Delle Marchette ◽  
Luca Beltrame ◽  
Tommaso Bianchi ◽  
...  

BMC Genomics ◽  
2013 ◽  
Vol 14 (1) ◽  
pp. 508 ◽  
Author(s):  
Patrizia Pinciroli ◽  
Chiara Alberti ◽  
Marialuisa Sensi ◽  
Silvana Canevari ◽  
Antonella Tomassetti

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