ETD system

Electronic theses and dissertations repository

 

Tesi etd-01302017-204740


Thesis type
Tesi di dottorato di ricerca
Author
CITI, VALENTINA
URN
etd-01302017-204740
Title
Mechanisms resistance analysis of inhibitors involved in the PI3K/Akt/mTOR pathway in vitro and in cftDNA collected from patients with breast tumors
Settore scientifico disciplinare
BIO/14
Corso di studi
SCIENZE CLINICHE E TRASLAZIONALI
Commissione
relatore Prof. Danesi, Romano
tutor Dott.ssa Del Re, Marzia
Parole chiave
  • breast cancer
  • mTOR
  • everolimus
Data inizio appello
25/02/2017;
Consultabilità
completa
Riassunto analitico
Reverting cancer drug resistance to chemotherapy and molecular targeted therapies is one of the principal challenges in current cancer research. The mechanisms of resistance to ‘classical’ cytotoxic chemotherapeutics and to target therapies that are designed to be selective for specific molecular targets can be due to different causes. Though, they share many features including alterations in drug transport and metabolism, mutation and amplification of drug targets, alterations in the drug target, activation of pro-survival pathways and ineffective induction of cell death. Another important characteristic which recently has been described is the tumour heterogeneity that may also contribute to resistance. It consists in the presence of small subpopulation of cells which may acquire resistance or may already be able to overcome drug pressure. <br>Understanding the molecular mechanisms which lead to drug resistance is even more challenging as those pathways controlling cell growth, cell death and apoptosis may lead to multi drug resistance, making clinically difficult the molecular characterization of cancer tissue. With the increasing development of anticancer agents, improving preclinical models and the advent of powerful high-throughput screening techniques, there are now many opportunities to understand and overcome drug resistance through the clinical assessment of rational therapeutic drug combinations and the use of predictive biomarkers to enable patient stratification.<br>
File