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Application to the ROS1 Project

This project sought to develop compounds that inhibit ROS1 (reactive oxygen species), known to be over-expressed in several cancer types. Excessive quantities of ROS1 causes oxidative stress that is generally detrimental to cells (Gorrini, Harris, and Mak, 2013). A cellular assay for target inhibition showed several compounds with high inhibitory activity. FF -2086493472 came out to be the top fingerprint feature that can well separate the bioactivity of the compounds (Figure 16.10b). Here, the feature can be linked with lower potency since all compounds having the fingerprint feature have lower pIC50 values than those compounds not having the feature.

The joint modeling resulted in identification of genes that are associated with the pIC50. A number of genes showed positive correlation, like FNIP1, while TXNRD1 along with other genes showed negative correlation (Figure 16.11a).

Interestingly, TXNRD1, a key player in oxidative stress control, is also evaluated as a cancer drug target associated with aggressive tumor growth (Powis and Kirkpatrick, 2007; Eriksson et al., 2009). Elevated levels of this gene in many human cancers contribute to increased proliferation, resistance to cell death, and increased angiogenesis. Dai et al. (2013) show that simultaneous inhibition of TXNRD1 and AKT pathways (activated by ROS1) induced robust ROS1 production. Discovering potential inhibitors of this gene could contribute to cancer therapy (Urig and Becker, 2006). In this experiment, compounds with high ROS1 inhibitory activity also show inhibition of TXNRD1.

The joint model furthermore revealed that potent compounds with lower gene expression effects on TXNRD1 lack FF-2086493472. Moreover, the association between the pIC50 and the expression of gene TXRND1 can be fully

TABLE 16.4

List of top 10 differentially expressed genes with low adjusted association (p- adj(p) > 0.05) after adjusting for FF -442307337 (EGFR).

Genes

Effect

p-adj( Effect)

r

P

P-adj(p)

KRAS

-0.30

0.00

0.62

0.34

0.07

MAP9

-0.13

0.00

0.62

0.29

0.13

SMG1

-0.10

0.00

0.62

0.35

0.06

PTER

-0.10

0.00

0.61

0.35

0.06

ODZ3

-0.14

0.01

0.59

0.35

0.06

SCAF11

-0.16

0.00

0.59

0.30

0.12

PCYOX1

-0.23

0.00

0.58

0.30

0.12

PHACTR2

-0.13

0.01

0.58

0.35

0.06

USP3

-0.07

0.01

0.57

0.35

0.06

FBX021

-0.12

0.00

0.57

0.27

0.16

explained by the absence/presence of this feature (Figure 16.11b). Table 16.5 shows a set of differentially expressed genes with the same type of association observed between TXNRD1 and pIC50 that disappears after adjusting for FF- 2086493472 (Figure 16.13). Figure 16.12 shows how the correlation between the pIC50 and all genes changes after accounting for FF-2086493472.

Little is known about the biology of the FNIP1 gene, particularly relating to cancer. Hasumi et al. (2008) indicated that FNIP1 mRNA was significantly higher in renal cell carcinoma compared to normal kidney. Unlike TXNRD1, the correlation between the bioassay and the gene remains moderately strong after adjusting for the fingerprint feature. This implies that FNIP1 remains to be linearly associated with the efficacy data independent of this structural feature. Table 16.6 presents 9 other genes showing the same type of association with pIC50 as FNIP1 (Figure 16.14). The number of genes in each subclass is given in Table 16.7.

TABLE 16.5

List of top 10 differentially expressed genes with low adjusted association (p- adj(p) > 0.05) after adjusting for FF -2086493472 (ROS1).

Genes

Effect

p-adj(Effect) r

P P-adj {p)

TXNRD1

0.39

0.00

-0.65

-0.08

0.54

PFKFB3

0.57

0.00

-0.61

0.00

0.97

SNORD52

0.23

0.00

-0.65

-0.12

0.33

GDF15

-1.09

0.00

0.67

0.21

0.07

ZNF292

-0.30

0.00

0.59

0.01

0.95

CTPS

0.30

0.00

-0.63

-0.16

0.19

KIRREL

0.34

0.00

-0.64

-0.19

0.11

HMGCS1

0.77

0.00

-0.58

-0.04

0.77

TFPI

-0.46

0.00

0.60

0.11

0.37

HIST1H1A

0.49

0.00

-0.52

0.09

0.49

FIGURE 16.5

Two on-target genes that correlate with EGFR inhibition: FGFBP1 and KRAS. Each point is a compound with the two reference compounds as highlighted circles. The solid blue points indicate the presence of FF -442307337.

FIGURE 16.6

Unadjusted versus adjusted correlations. Each point is a gene. Genes that have high correlation but very low adjusted correlation indicates that the fingerprint feature is creating the association.

FIGURE 16.7

Top 5 differentially expressed genes with high adjusted correlation. The correlation between the gene expression and the inhibitory activity against EGFR, given by the pIC50, of the compounds (represented by points in the plots) can be explained by the substructure FF -ff2307337.

FIGURE 16.8

Top 5 differentially expressed genes with low adjusted correlation. The correlation between the gene expression and the inhibitory activity against EGFR, given by the pIC50, of the compounds (represented by points in the plots) can be explained by the substructure FF -442307337.

FIGURE 16.9

Chemical structures of (a) identified less potent compound; (b) highly potent compound in the EGFR project; and the two reference compounds in this experiment, (c) erlotinib and (d) gefitinib.

FIGURE 16.10

Plots highlighting the most relevant fingerprint features for the ROS1 project.

FIGURE 16.11

Two cancer-related genes that correlate with ROS1-inhibition: FNIP1 and TXNRD1. The solid points indicate the presence of FF -2086493472.

FIGURE 16.12

Unadjusted versus adjusted correlations. Each point is a gene. Genes that have high correlation but very low adjusted correlation indicates that the fingerprint feature is creating the association.

FIGURE 16.13

Top 5 differentially expressed genes with low adjusted correlation.

FIGURE 16.14

Top 5 significantly differentially expressed genes with significant adjusted correlation.

TABLE 16.6

List of top 10 differentially expressed genes with high adjusted association (p- adj(p) < 0.05) after adjusting for FF -2086493472 (ROS1).

Genes

Effect

p-adj( Effect) r

P P-adj(p)

FNIP1

-0.16

0.00

0.75

0.51

0.00

GRAMD3

0.20

0.00

-0.72

-0.27

0.02

SLC2A12

-0.37

0.00

0.66

0.41

0.00

MYC

0.52

0.00

-0.66

-0.33

0.00

BHLHE40

0.55

0.00

-0.66

-0.36

0.00

TGFB2

0.57

0.00

-0.66

-0.33

0.00

TMEM177

0.13

0.00

-0.65

-0.27

0.02

SNORD4B

0.25

0.00

-0.65

-0.49

0.00

TNFRSF12A

0.82

0.00

-0.65

-0.34

0.00

SNORD44

0.19

0.00

-0.65

-0.36

0.00

TABLE 16.7

Results for FF -2086493472 (ROS) at 5% FDR.

p

^ 0 0

= 0 “ 0

  • 139 239
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