Specific Targets in Sarcoma and Developmental Therapeutics

2010 ◽  
Vol 8 (6) ◽  
pp. 677-686 ◽  
Author(s):  
David M. Thomas ◽  
Andrew J. Wagner
Keyword(s):  
Targeted Therapy ◽  
Growth Factor ◽  
Personalized Medicine ◽  
Connective Tissue ◽  
Drug Development ◽  
Therapeutic Agents ◽  
Insulin Like Growth Factor ◽  
Developmental Therapeutics ◽  
Novel Therapeutic

Connective tissue tumors comprise a rich array of subtypes, many of which possess strong pathognomonic phenotypes and genotypes of therapeutic significance. This article describes recent applications of targeted and nontargeted therapeutic agents in connective tissue tumors that illustrate important themes in drug development. Targeted therapy has exploited the paradigms of oncogene and lineage addiction. In other cases, potential targets are more difficult to classify, such as the role of the insulin-like growth factor 1 pathway in Ewing's sarcoma. Understanding why these pathways seem critical in some cancers, and in some individuals but not others, is important in identifying novel therapeutic opportunities in an age of personalized medicine.

The role of insulin receptor and insulin-like growth factor I receptor in pancreatic ductal adenocarcinoma

2013 ◽  
Vol 51 (08) ◽  
Author(s):  
E Kalideris ◽  
B Grüner ◽  
M Trajkovic-Arsic ◽  
P Mazur ◽  
RM Schmid ◽  
...  
Keyword(s):  
Growth Factor ◽  
Insulin Receptor ◽  
Pancreatic Ductal Adenocarcinoma ◽  
Ductal Adenocarcinoma ◽  
Insulin Like Growth Factor ◽  
Factor I ◽  
Growth Factor I

scholarly journals The Role of Network Science in Glioblastoma

Cancers ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 1045
Author(s):  
Marta B. Lopes ◽  
Eduarda P. Martins ◽  
Susana Vinga ◽  
Bruno M. Costa
Keyword(s):  
Personalized Medicine ◽  
Drug Development ◽  
Information Flow ◽  
Clinical Studies ◽  
Network Science ◽  
Cancer Genomics ◽  
High Dimensional ◽  
Network Discovery ◽  
Software Implementations

Network science has long been recognized as a well-established discipline across many biological domains. In the particular case of cancer genomics, network discovery is challenged by the multitude of available high-dimensional heterogeneous views of data. Glioblastoma (GBM) is an example of such a complex and heterogeneous disease that can be tackled by network science. Identifying the architecture of molecular GBM networks is essential to understanding the information flow and better informing drug development and pre-clinical studies. Here, we review network-based strategies that have been used in the study of GBM, along with the available software implementations for reproducibility and further testing on newly coming datasets. Promising results have been obtained from both bulk and single-cell GBM data, placing network discovery at the forefront of developing a molecularly-informed-based personalized medicine.

The Role of the Insulin-like Growth Factor-I Receptor in Cancer

1995 ◽  
Vol 766 (1 Receptor Acti) ◽  
pp. 402-408 ◽  
Author(s):  
D. LEROITH ◽  
H. WERNER ◽  
S. NEUENSCHWANDER ◽  
T. KALEBIC ◽  
L. J. HELMAN
Keyword(s):  
Growth Factor ◽  
Insulin Like Growth Factor ◽  
Factor I ◽  
Growth Factor I

Gonadotropin suppression of apoptosis in cultured preovulatory follicles: mediatory role of endogenous insulin-like growth factor I.

Endocrinology ◽  
1994 ◽  
Vol 135 (5) ◽  
pp. 1845-1853 ◽  
Author(s):  
S Y Chun ◽  
H Billig ◽  
J L Tilly ◽  
I Furuta ◽  
A Tsafriri ◽  
...  
Keyword(s):  
Growth Factor ◽  
Insulin Like Growth Factor ◽  
Factor I ◽  
Endogenous Insulin ◽  
Preovulatory Follicles ◽  
Growth Factor I

The role of insulin-like growth factor-I (IGF-I) and estradiol in rabbit corpus luteum progesterone production

Endocrine ◽  
1997 ◽  
Vol 6 (1) ◽  
pp. 73-77 ◽  
Author(s):  
Serena H. Chen ◽  
Vanna Zanagnolo ◽  
Sangchai Preutthipan ◽  
Kenneth P. Roberts ◽  
Sandra B. Goodman ◽  
...  
Keyword(s):  
Growth Factor ◽  
Corpus Luteum ◽  
Insulin Like Growth Factor ◽  
Factor I ◽  
Progesterone Production ◽  
Igf I ◽  
Growth Factor I
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