Differential influence of pentoxifylline on murine colon adenocarcinoma- and melanoma-derived metastatic tumor development in lungs

2004 ◽  
Author(s):  
Maciej Lazarczyk ◽  
Tomasz Grzela ◽  
Justyna Niderla ◽  
Marta Lazarczyk ◽  
Lukasz Milewski ◽  
...  
2013 ◽  
Vol 217 (3) ◽  
pp. S127
Author(s):  
Karen K. Lo ◽  
Carlton C. Barnett ◽  
Sean P. Colgan ◽  
Richard D. Schulick ◽  
Denis D. Bensard ◽  
...  

Gene Therapy ◽  
2014 ◽  
Vol 22 (1) ◽  
pp. 29-39 ◽  
Author(s):  
P F Forde ◽  
L J Hall ◽  
M de Kruijf ◽  
M G Bourke ◽  
T Doddy ◽  
...  

2007 ◽  
Vol 139 (2) ◽  
pp. 164-169 ◽  
Author(s):  
Angela M. Jack ◽  
Nebil Aydin ◽  
Grace Montenegro ◽  
Khorshed Alam ◽  
Marc Wallack

Cells ◽  
2019 ◽  
Vol 8 (3) ◽  
pp. 203 ◽  
Author(s):  
Jakub Kryczka ◽  
Izabela Papiewska-Pajak ◽  
M. Anna Kowalska ◽  
Joanna Boncela

During tumor development and ongoing metastasis the acquisition of mesenchymal cell traits by epithelial carcinoma cells is achieved through a programmed phenotypic shift called the epithelial-to-mesenchymal transition, EMT. EMT contributes to increased cancer cell motility and invasiveness mainly through invadosomes, the adhesion structures that accompany the mesenchymal migration. The invadosomes and their associated proteases restrict protease activity to areas of the cell in direct contact with the ECM, thus precisely controlling cell invasion. Our data prove that Snail-overexpressing HT-29 cells that imitate the phenotype of colon cancer cells in the early stage of the EMT showed an increase in the expression and pericellular activity of cathepsin B. It appears that the pericellular localization of cathepsin B, also observed in colon and rectum adenocarcinoma tissue samples, plays a key role in its function.


1996 ◽  
Vol 87 (1) ◽  
pp. 78-85 ◽  
Author(s):  
Keita Sakata ◽  
Ken-ichi Kozaki ◽  
Ken-ichi Iida ◽  
Rie Tanaka ◽  
Sadako Yamagata ◽  
...  

2021 ◽  
Author(s):  
Mariano Bizzarri ◽  
Valeria Fedeli ◽  
Noemi Monti ◽  
Alessandra Cucina ◽  
Maroua Jalouli ◽  
...  

AbstractThe agenda of pharmacology discovery in the field of personalized oncology was dictated by the search of molecular targets assumed to deterministically drive tumor development. In this perspective, genes play a fundamental “causal” role while cells simply act as causal proxies, i.e., an intermediate between the molecular input and the organismal output. However, the ceaseless genomic change occurring across time within the same primary and metastatic tumor has broken the hope of a personalized treatment based only upon genomic fingerprint. Indeed, current models are unable in capturing the unfathomable complexity behind the outbreak of a disease, as they discard the contribution of non-genetic factors, environment constraints, and the interplay among different tiers of organization. Herein, we posit that a comprehensive personalized model should view at the disease as a “historical” process, in which different spatially and timely distributed factors interact with each other across multiple levels of organization, which collectively interact with a dynamic gene-expression pattern. Given that a disease is a dynamic, non-linear process — and not a static-stable condition — treatments should be tailored according to the “timing-frame” of each condition. This approach can help in detecting those critical transitions through which the system can access different attractors leading ultimately to diverse outcomes — from a pre-disease state to an overt illness or, alternatively, to recovery. Identification of such tipping points can substantiate the predictive and the preventive ambition of the Predictive, Preventive and Personalized Medicine (PPPM/3PM). However, an unusual effort is required to conjugate multi-omics approaches, data collection, and network analysis reconstruction (eventually involving innovative Artificial Intelligent tools) to recognize the critical phases and the relevant targets, which could help in patient stratification and therapy personalization.


2014 ◽  
Vol 187 (1) ◽  
pp. 19-23 ◽  
Author(s):  
Kenton Howard ◽  
Karen K. Lo ◽  
Lihua Ao ◽  
Fabia Gamboni ◽  
Barish H. Edil ◽  
...  

1990 ◽  
Vol 46 (1) ◽  
pp. 118-124
Author(s):  
Yoshikazu Sugimoto ◽  
Tomoko Oh-hara ◽  
Yuji Heike ◽  
Masahiko Watanabe ◽  
Yoko Nakatsuru ◽  
...  

Tumor Biology ◽  
2015 ◽  
Vol 36 (9) ◽  
pp. 7035-7043 ◽  
Author(s):  
Satoshi Kudo ◽  
Hajime Saito ◽  
Satoru Motoyama ◽  
Tomohiko Sasaki ◽  
Kazuhiro Imai ◽  
...  

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