Pharmacological Inhibition of CA-IX Impairs Tumor Cell Proliferation, Migration and Invasiveness.
Valerio CicconeArianna FilippelliAndrea AgeliClaudiu T SupuranLucia MorbidelliPublished in: International journal of molecular sciences (2020)
Carbonic anhydrase IX (CA-IX) plays a pivotal role in regulation of pH in tumor milieu catalyzing carbonic acid formation by hydrating CO2. An acidification of tumor microenvironment contributes to tumor progression via multiple processes, including reduced cell-cell adhesion, increased migration and matrix invasion. We aimed to assess whether the pharmacological inhibition of CA-IX could impair tumor cell proliferation and invasion. Tumor epithelial cells from breast (MDA-MB-231) and lung (A549) cancer were used to evaluate the cytotoxic effect of sulfonamide CA-IX inhibitors. Two CA-IX enzyme blockers were tested, SLC-0111 (at present in phase Ib clinical trial) and AA-06-05. In these cells, the drugs inhibited cell proliferation, migration and invasion through shifting of the mesenchymal phenotype toward an epithelial one and by impairing matrix metalloprotease-2 (MMP-2) activity. The antitumor activity was elicited via apoptosis pathway activation. An upregulation of p53 was observed, which in turn regulated the activation of caspase-3. Inhibition of proteolytic activity was accompanied by upregulation of the endogenous tissue inhibitor TIMP-2. Collectively, these data confirm the potential use of CA-IX inhibitors, and in particular SLC-0111 and AA-06-05, as agents to be further developed, alone or in combination with other conventional anticancer drugs.
Keyphrases
- cell proliferation
- clinical trial
- cell cycle arrest
- induced apoptosis
- protein kinase
- cell death
- cell adhesion
- cell cycle
- signaling pathway
- cell therapy
- endoplasmic reticulum stress
- oxidative stress
- squamous cell carcinoma
- bone marrow
- machine learning
- randomized controlled trial
- study protocol
- sensitive detection
- angiotensin ii
- angiotensin converting enzyme
- data analysis
- deep learning