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2018 ; 7
(5
): 1875-1895
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Biological signaling pathways and potential mathematical network representations:
biological discovery through optimization
#MMPMID29635835
Isaza C
; Rosas JF
; Lorenzo E
; Marrero A
; Ortiz C
; Ortiz MR
; Perez L
; Cabrera-Ríos M
Cancer Med
2018[May]; 7
(5
): 1875-1895
PMID29635835
show ga
Establishing the role that different genes play in the development of cancer is a
daunting task. A step toward this end is the detection of genes that are
important in the illness from high-throughput biological experiments.
Furthermore, it is safe to say that it is highly unlikely that these show
expression changes independently, even with a list of potentially important
genes. A biological signaling pathway is a more plausible underlying mechanism as
favored in the literature. This work attempts to build a mathematical network
problem through the analysis of microarray experiments. A preselection of genes
is carried out with a multiple criteria optimization framework previously
published by our research group . Afterward, application of the Traveling
Salesperson Problem and Minimum Spanning Tree network optimization models are
proposed to identify potential signaling pathways via the most correlated path
among the genes of interest. Biological evidencing is provided to assess the
effectiveness of the proposed methods. The capability of our analysis strategy is
also demonstrated through the undertaking of meta-analysis studies. Three
important aspects are novel in this work: (1) our joint analyses of different
groups of lung cancer states reveal new correlations, biologically evidenced, and
previously undocumented; (2) computation of the correlation coefficients from
expression differences leads to an effective use of network optimization methods;
and (3) the methods yield mathematically optimal correlation structures: no other
configuration is better correlated using the available information.
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