High-order gene-gene interactions using STREE
Multiple interaction analyses involving various genes implicated in SLC
transporters add a new dimension to assess the high-order parametric
interactions within them and their impact on the overall survival of
lung cancer patients. The recursive partitioning strategy was adopted to
generate a survival tree in this study, demonstrating various SLC SNPs’
roles in prognosis. Figure 6a shows the tree generated by the
STREE software. The log-rank approach was used to generate the tree out
of all the methods available. There were a total of four-terminal nodes
found. SLC19A1G80A was the most crucial
factor as it is a root node influencing the prognosis of patients.
Terminal node 5 with the highest MST was used as a reference node (13.1
months). In addition, each node’s HR is mentioned. The survival curves
and the MST associated with each terminal node are illustrated inFigure 6b . It shows a difference between the median survival
time of different nodes and the reference node (log-rank p 0.18), though
a significant correlation was not observed. The findings of the Cox
regression analysis for every terminal node are summarized inSupplementary Table 6 . Significant differences were observed in
the median survival times when terminal node 4 was compared to the
reference node (4.8 months versus 13.1 months; HR=2.24, 95% CI=
0.99-5.02; p=0.05). After adjusting with different covariates,
including age, gender, stage, smoking, histology, regimen, ECOG, and
KPS, the death risk was 1.94 times as compared to the reference node
(HR=1.94; p=0.002 ). A similar trend was noted in all the other
nodes; however, significant differences were not achieved.