Proteomics and pathway analysis identifies JNK signaling as critical for high linear energy transfer radiation-induced apoptosis in non-small lung cancer cells.
During the past decade, we have witnessed an explosive increase in generation of large proteomics data sets, not least in cancer research. There is a growing need to extract and correctly interpret information from such data sets to generate biologically relevant hypotheses. A pathway search engine (PSE) has recently been developed as a novel tool intended to meet these requirements. Ionizing radiation (IR) is an anticancer treatment modality that triggers multiple signal transduction networks. In this work, we show that high linear energy transfer (LET) IR induces apoptosis in a non-small cell lung cancer cell line, U-1810, whereas low LET IR does not. PSE was applied to study changes in pathway status between high and low LET IR to find pathway candidates of importance for high LET-induced apoptosis. Such pathways are potential clinical targets, and they were further validated in vitro. We used an unsupervised shotgun proteomics approach where high resolution mass spectrometry coupled to nanoflow liquid chromatography determined the identity and relative abundance of expressed proteins. Based on the proteomics data, PSE suggested the JNK pathway (p = 6.10(-6)) as a key event in response to high LET IR. In addition, the Fas pathway was found to be activated (p = 3.10(-5)) and the p38 pathway was found to be deactivated (p = 0.001) compared with untreated cells. Antibody-based analyses confirmed that high LET IR caused an increase in phosphorylation of JNK. Moreover pharmacological inhibition of JNK blocked high LET-induced apoptotic signaling. In contrast, neither an activation of p38 nor a role for p38 in high LET IR-induced apoptotic signaling was found. We conclude that, in contrast to conventional low LET IR, high LET IR can trigger activation of the JNK pathway, which in turn is critical for induction of apoptosis in these cells. Thus PSE predictions were largely confirmed, and PSE was proven to be a useful hypothesis-generating tool.
Ståhl
Sara
S
Department of Oncology/Pathology, Karolinska Biomics Center, Karolinska Institutet, S-17176 Stockholm, Sweden.
Fung
Eva
E
Adams
Christopher
C
Lengqvist
Johan
J
Mörk
Birgitta
B
Stenerlöw
Bo
B
Lewensohn
Rolf
R
Lehtiö
Janne
J
Zubarev
Roman
R
Viktorsson
Kristina
K
D017209:Apoptosis / Q000187:drug effects / Q000528:radiation effects*; D002289:Carcinoma, Non-Small-Cell Lung / Q000201:enzymology* / Q000473:pathology*; D053148:Caspase 3 / Q000378:metabolism; D045744:Cell Line, Tumor; D019295:Computational Biology; D004789:Enzyme Activation / Q000187:drug effects / Q000528:radiation effects; D006801:Humans; D048031:JNK Mitogen-Activated Protein Kinases / Q000037:antagonists & inhibitors / Q000378:metabolism*; D018499:Linear Energy Transfer; D008175:Lung Neoplasms / Q000201:enzymology / Q000473:pathology; D020935:MAP Kinase Signaling System / Q000528:radiation effects*; D047428:Protein Kinase Inhibitors / Q000494:pharmacology; D040901:Proteomics; D015203:Reproducibility of Results; D013997:Time Factors; D048051:p38 Mitogen-Activated Protein Kinases / Q000378:metabolism
D047428:Protein Kinase Inhibitors; D048031:JNK Mitogen-Activated Protein Kinases; D048051:p38 Mitogen-Activated Protein Kinases; D053148:Caspase 3