In silico analysis of pathways activation landscape in oral squamous cell carcinoma and oral leukoplakia.

Makarev, Eugene; Schubert, Adrian; Kanherkar, Riya R; London, Nyall; Teka, Mahder; Ozerov, Ivan; Lezhnina, Ksenia; Bedi, Atul; Ravi, Rajani; Mehra, Rannee; Hoque, Mohammad O; Sloma, Ido; Gaykalova, Daria A; Csoka, Antonei B; Sidransky, David; Zhavoronkov, Alex; Izumchenko, Evgeny (2017). In silico analysis of pathways activation landscape in oral squamous cell carcinoma and oral leukoplakia. Cell death discovery, 3, p. 17022. Nature 10.1038/cddiscovery.2017.22

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A subset of patients with oral squamous cell carcinoma (OSCC), the most common subtype of head and neck squamous cell carcinoma (HNSCC), harbor dysplastic lesions (often visually identified as leukoplakia) prior to cancer diagnosis. Although evidence suggest that leukoplakia represents an initial step in the progression to cancer, signaling networks driving this progression are poorly understood. Here, we applied in silico Pathway Activation Network Decomposition Analysis (iPANDA), a new bioinformatics software suite for qualitative analysis of intracellular signaling pathway activation using transcriptomic data, to assess a network of molecular signaling in OSCC and pre-neoplastic oral lesions. In tumor samples, our analysis detected major conserved mitogenic and survival signaling pathways strongly associated with HNSCC, suggesting that some of the pathways identified by our algorithm, but not yet validated as HNSCC related, may be attractive targets for future research. While pathways activation landscape in the majority of leukoplakias was different from that seen in OSCC, a subset of pre-neoplastic lesions has demonstrated some degree of similarity to the signaling profile seen in tumors, including dysregulation of the cancer-driving pathways related to survival and apoptosis. These results suggest that dysregulation of these signaling networks may be the driving force behind the early stages of OSCC tumorigenesis. While future studies with larger leukoplakia data sets are warranted to further estimate the values of this approach for capturing signaling features that characterize relevant lesions that actually progress to cancers, our platform proposes a promising new approach for detecting cancer-promoting pathways and tailoring the right therapy to prevent tumorigenesis.

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