ePrints@IIScePrints@IISc Home | About | Browse | Latest Additions | Advanced Search | Contact | Help

Modelling metabolic rewiring during melanoma progression using Flux Balance Analysis

Metri, Rahul and Saxena, Shikhar and Mishra, Madhulika and Chandra, Nagasuma (2017) Modelling metabolic rewiring during melanoma progression using Flux Balance Analysis. In: IEEE International Conference on Bioinformatics and Biomedicine (IEEE BIBM), NOV 13-16, 2017, Kansas City, MI, pp. 134-137.

[img] PDF
BIBM_134_2017.pdf - Published Version
Restricted to Registered users only

Download (289kB) | Request a copy
Official URL: http://dx.doi.org/10.1109/BIBM.2017.8217638


Improvements in melanoma diagnosis, treatment and prognosis are urgently warranted, given that it causes 3 out of 4 skin cancer deaths. A large amount of genomic and molecular data indicate that alterations occur at multiple scales in different stages of melanoma. Metabolic rewiring is a characteristic feature of progressive cancers that facilitates sustenance of tumors, and caters to the changing energy requirements. Since such rewiring involves multiple variations in the metabolic network that are orchestrated, a systems perspective is necessary to understand the nature, significance, mechanisms and identification of the key steps. To address this, we integrate patient transcriptome data with a prior human reference metabolic model and construct stage-specific genome-scale metabolic models. Using flux balance analysis, we simulate the metabolic flows and compute the reaction fluxes specific to normal skin, primary melanoma and metastatic melanoma, from which the reactions with flux differences between conditions were identified. Reactions related to Warburg effect, as anticipated and in addition, ROS detoxification and tyrosine metabolism were largely altered in all stages of melanoma. Vitamin A and vitamin C sub-systems are identified to be involved in different stages, consistent with experimental studies from literature that indicate their support to cancer progression. Gene essentiality studies using the melanoma model identified 5 important genes NME2, CMPK1, HSD17B4, DTYMK and PRODH for the proliferation of melanoma cells, which can be explored as potential drug targets.

Item Type: Conference Proceedings
Series.: IEEE International Conference on Bioinformatics and Biomedicine-BIBM
Publisher: IEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA
Additional Information: Copy right for the article belong to IEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA
Department/Centre: Division of Biological Sciences > Biochemistry
Division of Physical & Mathematical Sciences > Mathematics
Date Deposited: 28 Mar 2018 16:17
Last Modified: 28 Mar 2018 16:17
URI: http://eprints.iisc.ac.in/id/eprint/59424

Actions (login required)

View Item View Item