Numerous studies mapping multiple omics dimensions to annotated pathways and cancer Belinostat cell line hallmarks support the notion that alterations work

in concert to selectively deregulate pathways and further confirm that AC and SqCC develop through distinct oncogenic pathways [11], [50], [51] and [65]. Single subtype analyses have identified several affected pathways/hallmarks including; focal adhesions, cell cycle, activation of the JAK/STAT pathway and sustainment of proliferation in AC [22] and [52] and oxidative stress response, squamous differentiation and deregulation of the PI3K pathway in SqCC [51]. Of therapeutic relevance, was the finding that ∼70% of SqCC tumors had alterations in one of the PI3K/AKT, receptor tyrosine kinase, or RAS pathways, however the optimal intervention points of these pathways are still under investigation. Work by our group comparing AC and SqCC identified 778 subtype-specific genes (altered by CNA or DNA methylation and a two-fold expression change) which were found to differentially disrupt cellular GDC-0199 supplier pathways and networks, including down-regulation of the HNF4alpha pathway in AC and disruption of histone modifying enzymes and the E2F1 transcription factor in SqCC [65].

Differential pathway activation of the cell cycle in AC, and DNA repair in SqCC, have been reported along with differences in multiple metabolic pathways [78]. With distinct patterns of genetic disruption underscoring tumor development, it is unrealistic to assume AC and SqCC would have similar responses to all chemotherapies, especially those targeting specific proteins.

Both bevacizumab, a monoclonal antibody against vascular endothelial growth factor (VEGF) and pemetrexed, an antifolate chemotherapy that targets thymidylate synthetase (TS) are contraindicated in SqCC due to an increased tuclazepam risk of pulmonary hemorrhage and reduced survival times, respectively [79], [80] and [81]. TS gene expression has been shown to be predictive of pemetrexed efficiency [82] and [83] and is elevated in SqCC compared to AC, providing an explanation for the reduced efficacy in these patients [81] and [84]. In silico screening of compounds capable of “reversing” gene expression signatures has been shown to identify compounds with subtype specific efficacy. For example, treatment of lung cancer cell lines with the HDAC inhibitor Trichostatin A, revealed SqCC lines were significantly more sensitive than AC lines [65]. These findings highlight the potential importance of information about the underlying biology to inform decisions regarding treatment regimes, such that treatments can be tailored to the individual to potentially improve patient response and survival.