@article{(Open Science Index):https://publications.waset.org/pdf/10005074,
	  title     = {Metabolomics Profile Recognition for Cancer Diagnostics},
	  author    = {Valentina L. Kouznetsova and  Jonathan W. Wang and  Igor F. Tsigelny},
	  country	= {},
	  institution	= {},
	  abstract     = {Metabolomics has become a rising field of research
for various diseases, particularly cancer. Increases or decreases in
metabolite concentrations in the human body are indicative of various
cancers. Further elucidation of metabolic pathways and their
significance in cancer research may greatly spur medicinal discovery.
We analyzed the metabolomics profiles of lung cancer. Thirty-three
metabolites were selected as significant. These metabolites are
involved in 37 metabolic pathways delivered by MetaboAnalyst
software. The top pathways are glyoxylate and dicarboxylate
pathway (its hubs are formic acid and glyoxylic acid) along with
Citrate cycle pathway followed by Taurine and hypotaurine pathway
(the hubs in the latter are taurine and sulfoacetaldehyde) and Glycine,
serine, and threonine pathway (the hubs are glycine and L-serine). We
studied interactions of the metabolites with the proteins involved in
cancer-related signaling networks, and developed an approach to
metabolomics biomarker use in cancer diagnostics. Our analysis
showed that a significant part of lung-cancer-related metabolites
interacts with main cancer-related signaling pathways present in this
network: PI3K–mTOR–AKT pathway, RAS–RAF–ERK1/2 pathway,
and NFKB pathway. These results can be employed for use of
metabolomics profiles in elucidation of the related cancer proteins
signaling networks.},
	    journal   = {International Journal of Biotechnology and Bioengineering},
	  volume    = {10},
	  number    = {7},
	  year      = {2016},
	  pages     = {384 - 389},
	  ee        = {https://publications.waset.org/pdf/10005074},
	  url   	= {https://publications.waset.org/vol/115},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 115, 2016},