Presentation at ICIC2014, Taiyuan, China Full paper http://link.springer.com/chapter/10.1007/978-3-319-09330-7_52

1. Integrative Analysis of Gene Expression and
Promoter Methylation during Reprogramming
of a Non-Small-Cell Lung Cancer Cell Line
using Principal Component Analysis-Based
Unsupervised Feature Extraction
Y-h. Taguchi
Dept. Phys., Chuo Univ., Tokyo, Japan
物理学科、中央大学、東京、日本

2. Targeted disease:
Non-Small-Cell Lung Cancer (NSCLC) is lethal
cancer. 5 years survival rate is at most less
than 50%.
New therapy targets are ever waited.
Treatment:
Reprogramming cancers :
new candidate cancer therapy treatment

3. Methods:
Principal component analysis (PCA) based
unsupervised feature extraction (FE)
Standard PCA : apply PCA to samples
This study: apply PCA to features
Biologically informative PCs are selected
Outliers along the selected PCs are extracted

4. Data setData set: (GEO)
NSCLC cell line pre/post reprogramming + a
few other differentiated/ undifferentiated
cell lines (by microarray)
NSCLC: H358,H460
H1: ES
IMR90: fibroblast
iPCH358,iPCH460,iPCSIMR90: reprogrammed
piPCH358: re-differentiated

5. Two dimensional embedding of probes
mRNA
methylation
PC2
PC1
91%
3%
84%
6%

6. mRNA
methylation
H1
H358
H460
IMR90
iPCH358
iPCH460
iPSIMR90
piPCH358
PC2PC1
Sample contributions to each PC
H1
H358
H460
IMR90
iPCH358
iPCH460
iPSIMR90
piPCH358
91% 3%
84% 6%

7. PC2 was selected as informative PC because
1. Negatively correlated between mRNA and
methylation .
2. Small fluctuation within same cell lines
while divergence between distinct cell lines
3. 6 genes were commonly selected within top
300 ranked genes between mRNA and
methylation (P=0.003).
Thus PCs' contributions do not always matter.

8. Gene
Symbol
Disease Associations (P-values)
TGFBI
Neoplasms, Radiation-Induced (3×10-5); Neoplasm Invasiveness
(2×10-4); Cell Transformation, Neoplastic (6.7×10-3); Bronchial
Neoplasms (0.02); Cocarcinogenesis (0.03)
S100A6
Skin Neoplasms (1.1×10-11); Pancreatic Neoplasms (1.8×10-11);
Adenocarcinoma (3.6×10-8); Melanoma (6.4×10-8); Precancerous
Conditions (9.1×10-8);
CSRP1
Carcinoma, Hepatocellular (1.3×10-2); Liver Neoplasms (0.014);
Prostatic Neoplasms (0.017)
CLDN11 No associations
PRKCDBP
Lung Neoplasms (4.9×10-4); Hamartoma (5.0×10-4); Glioblastoma
(7.9×10-3); Adenoma (0.012); Carcinoma, Non-Small-Cell Lung
(0.013)
CRIP1
Carcinoma, Hepatocellular (0.025), Liver Neoplasms (0.028),
Prostatic Neoplasms (0.033)
Gendoo server reports …,

9. TGFBI
Corr=-0.82
P=2.4x10-6
mRNA methylation
H1
H358
H460
IMR90
iPCH358
iPCH460
iPSIMR90
piPCH358
H1
H358
H460
IMR90
iPCH358
iPCH460
iPSIMR90
piPCH358
S100A6
Corr=-0.69
P=2.5x10-4

10. H1
H358
H460
IMR90
iPCH358
iPCH460
iPSIMR90
piPCH358
H1
H358
H460
IMR90
iPCH358
iPCH460
iPSIMR90
piPCH358
CSRP1
Corr=-0.92
P=2.6x10-6
CLDN11
Corr=-0.85
P=2.2x10-6
mRNA methylation

11. H1
H358
H460
IMR90
iPCH358
iPCH460
iPSIMR90
piPCH358
H1
H358
H460
IMR90
iPCH358
iPCH460
iPSIMR90
piPCH358
PRKCDBP
Corr=-0.85
P=2.2x10-6
CRIP1
Corr=-0.82
P=2.6x10-6
mRNA methylation

12. Conclusion
In spite of simpleness (embedding
probes by PCA and extracting outliers
along specified PC), PCA based
unsupervised FE successfully extracted
six genes that are NSCLC specific but
reversed by reprogramming.
Six genes can be new theraphy targets.
Also there will be no reasons not to try
PCA based unsupervised FE for all other
opportunities, since it is very very easy!