Genes associated with genotype-specific DNA methylation in squamous cell

carcinoma as drug target candidates

Ryoichi Kinoshita1, Mitsuo Iwadate2,

Hideaki Umeyama2 and Y-H. Taguchi1

1Department of Physics2Department of Biological Science

Chuo UniversityJSBi Poster

#24

1. Background

Gene (protein coding) → Mutation → Cancer

→ does not explain all cancer related gene anomaly

→ anomaly in unmutated (protein coding) gene expression may also be important

e.g. cancer ↔ aberrant promoter methylation

Cancer Drug → efficiency is always < 100%

→ Need of tailor-made medicine

→ possibly because of genomic divergence

genomic divergence ↔ SNPs ?

Purpose of this study:SNP ↔ DNA methlylation → gene anomaly → Drug discovery

2 Materials

Genotype DNA methylation

microarray measurement Nsp:262339 probes (SNPs)

blood30 samples

adjacentnormaltissue

30 samples

tumor30 samples

microarray measurement Sty:238379 probes (SNPs)

GEO:GSE20123

Taken from 30 patients

assumed to be unmutated

mutatedin between

names of Restriction enzyme → SNP arrays

blood normaltissue

tumor bloodnormaltissue

tumor

Sty1300

SNPs

Nsp68

SNPs

Sty181

SNPs

Sty250

SNPs

Nsp300

SNPs

Sty2300

SNPs

Sty1300

SNPs

Nsp300

SNPs

Sty2300

SNPs

Intersection between genotype and DNA methylation

Selection by PCA

Genotype DNA methylation

These SNPs are …, abundant and aberrantly methylated in cancer

3. Methods

Selection by PCAP

C2

PC1

Gen

otyp

eD

NA

met

hyl

atio

n

2D embeddings of SNPs PC1 PC2

☓

Can

c er△　

adjac ent n

ormal tis su

e◯　

blood

☓

Can

c er△　

adjac ent n

ormal tis su

e◯　

blood

Comparison of commonly selcted SNPs between genotype and methylation

hypom

ethylated

abundant in ca

ncer

These SNPs are …, abundant and aberrantly methylated in cancer

Nsp68

SNPs

Nsp59

SNPs

Sty181

SNPs

Sty122

SNPs

Sty250

SNPs

Sty237

SNPs

Screened by pairwise t test (blood, normal tissue, tumor)

155Genes

Genes associated with SNPs

Screened by t test and detection of associated genes

155Genes

86Genes

3DStructures

3D structure Prediction by FAMS & phyre2

Screened by cancer association (by gendoo server)

Screened by cancer association and prediction of protein 3D structure

Literature baseddisease association data base

Profile basedstructure prediction server

ALK1 EGLN3 NUAK1

4FOD_0UV_n13LCS_STU_n2

3AOX_EMH_n34FOC_0UU_n44FOB_0US_n52YFX_VGH_n62XB7_GUI_n72XBA_571_n9

3HQR_OGA_n13OUJ_AKG_n2[2HBT_FE2_n3]2HBT_UN9_n42G19_4HG_n53OUH_014_n63OUI_42Z_n7

Ligands

3I7C_BK2_n13V5T_UW9_n23I7B_BK1_n33V51_I76_n4

3UPZ_B5A_n53NYV_DTQ_n63SX9_BK7_n73T3V_BK4_n83SXF_BK5_n9

3T3U_BK6_n103V5P_C88_n113N51_BK3_n123UPX_B6A_n13

DrugBank(6583 compounds)

3D structure(6510 compounds)

Babel

Tanimoto Index

905 compounds

>0.25

1001 compounds

905 compounds

>0.20 >0.201090

compounds

Candidatecompounds

Drug discovery phase for selected three genes

ligands binding to templates PDBs

4FOC_A 2HBT_A 3I7C_A Templates (PDB ID)

905 compounds

1001 compounds

1090 compounds

ChooseLD

Ranked 1001 compoundsfor ELGN3

(with/without Fe)

Ranked 905 compounds

for ALK

Ranked 1090

compoundsfor NUAK1

Candidatecompounds

Rankeddrug candidates

Virtual screening

ligand protein docking simulator

10 top ranked drug candidate compounds for ALK

7-Hydroxystaurosporine binding to ALK(Top ranked drug candidate)

ALK

7-Hydroxystaurosporine

Conclusion

We have successfully constructed virtual screening pipe line for drug discovery from genotype specific DNA methylation information.

This pipeline is expected to be applied to other diseases than cancers

JSBi Poster#24

This study was accepted for the publication in BMC Systems Biology in a supplementary issue as a proceedings of APBC2014 (17th-19th Jan. 2014, Shanghai)

Supported by

中央大学共同研究プロジェクト「FAMSを用いたタンパク質機能予測に基づくDrug Discovery」２０１３年ー２０１５年

(Chuo University Joint Research Grant,“Drug Discovery based on protein function inference by FAMS” 2013-2015)