Supplementary Appendix Supplementary tables: 7 Supplementary figures: 2 Supplementary Table S1



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Supplementary Appendix
Supplementary tables: 7

Supplementary figures: 2

Supplementary Table S1: Clinicopathological Characteristics of 24 Nasopharyngeal Carcinoma (NPC) Tissues and 24 Non-cancer Nasopharyngitis Biopsy Tissues (NCNBT)



Variables

NPC

N (%)

NCNBT

N (%)

Age (Mean ± SD)

42.8± 10.5

43.1±10.2

Gender







Male

15 (63)

15(63)

Female

9 (37)

9(37)

T stage







T1

0




T2

4(17)




T3

15(63)




T4

5(20)




N stage







N0

3(13)




N1

12(50)




N2

9(37)




N3

0




TNM stage







I-II

2(8)




III-IV

22(92)




WHO pathologic type







Undifferentiated non-keratinizing

24(100)




TNM: tumor-node-metastasis.

Supplementary Table S2: Clinical Characteristics of Nasopharyngeal Carcinoma Patients According to Gene Methylation Panel in Training, Validation, and Independent Cohorts.

 

Training Cohort (n=151)

P-value*

Validation Cohort (n=150)

P-value*

Independent Cohort (n=153)

P-value*

Characteristic

Low Methylation Group (%)

High Methylation Group (%)

Low Methylation Group (%)

High Methylation Group (%)

Low Methylation Group (%)

High Methylation Group (%)

 

n=75

n=76

n=79

n=71

n=69

n=84

Age (mean ± SD)




























<45

35 (46.7)

36 (47.4)

0.931

39 (49.4)

32 (45.1)

0.599

22 (31.9)

28 (33.3)

0.849

≥45

40 (53.3)

40 (52.6)




40 (50.6)

39 (54.9)




47 (68.1)

56 (66.7)




Sex




























Male

56 (74.7)

58 (76.3)

0.814

58 (73.4)

54 (76.1)

0.711

46 (66.7)

63 (75.0)

0.257

Female

19 (25.3)

18 (23.7)




21 (26.6)

17 (23.9)




23 (33.3)

21 (25.0)




WHO pathologic type




























Undifferentiated non-keratinizing

74 (98.7)

73 (96.1)

0.317

78 (98.7)

70 (98.6)

0.939

61 (88.4)

78 (92.9)

0.342

Differentiated non-keratinizing

1 (1.3)

3 (3.9)




1 (1.3)

1 (1.4)




8 (11.6)

6 (7.1)




T Stage




























T1

11 (14.7)

5 (6.6)

0.277

11 (13.9)

8 (11.3)

0.505

14 (20.3)

15 (17.9)

0.775

T2

20 (26.7)

20 (26.3)




21 (26.6)

20 (28.2)




35 (50.7)

38 (45.2)




T3

28 (37.3)

27 (35.5)




29 (36.7)

20 (28.2)




13 (18.8)

21 (25.0)




T4

16 (21.3)

24 (31.6)




18 (22.8)

23 (32.4)




7 (10.1)

10 (11.9)




N Stage




























N0

14 (18.7)

10 (13.2)

0.629

10 (12.7)

16 (22.5)

0.193

9 (13.0)

19 (22.6)

0.372

N1

36 (48.0)

35 (46.1)




37 (46.8)

37 (52.1)




22 (31.9)

26 (31.0)




N2

15 (20.0)

20 (26.3)




22 (27.8)

14 (19.7)




32 (46.4)

30 (35.7)




N3

10 (13.3)

11 (14.5)




10 (12.7)

4 (5.6)




6 (8.7)

9 (10.7)




TNM Stage




























I

1 (1.3)

2 (2.6)

0.576

2 (2.5)

3 (4.2)

0.815

1 (1.4)

1 (1.2)

0·589

II

18 (24.0)

12 (15.8)




20 (25.3)

19 (26.8)




17 (24.6)

21 (25.0)




III

30 (40.0)

31 (40.8)




32 (40.5)

24 (33.8)




39 (56.5)

40 (47.6)




IV

26 (34.7)

31 (40.8)




25 (31.6)

25 (35.2)




12 (17.4)

22 (26.2)




Concurrent chemotherapy




























Yes

42 (56.0)

44 (55.3)

0.927

42 (53.2)

45 (63.4)

0.206

45 (65.2)

57 (67.9)

0.595

No

33 (44.0)

34 (44.7)




37 (46.8)

26 (36.6)




24 (34.8)

27 (32.1)




2 test or Fisher’s exact test. TNM tumor-node-metastasis, RT radiotherapy

Supplementary Table S3: Primer Sequences of 28 Genes and GAPDH

Gene

Forward primer (5'-3')

Reverse primer (5'-3')

Tm

(°C)

Product

(bp)

ALDH1A3

CTCTGCTGTGGGAACACCAT

TTTCCAACCTCTGTGGAGCC

60

206

CCNA1

GCCTGGCAAACTATACTGTGA

AAGCCTTGTACTTCTCCCTAAT

60

165

CD38

GAGGCCTGGGTGATACATGG

AAAACAACCACAGCGACTGG

60

210

CD44

CCCCAGCAACCCTACTGATG

TTGCCTCTTGGTTGCTGTCT

60

211

CDKN1B

GCCTCAGAAGACGTCAAACG

TCCAACGCTTTTAGAGGCAGA

60

224

DKK1

GAGTACTGCGCTAGTCCCAC

TGGAATACCCATCCAAGGTGC

60

226

DPP4

GCAGAATGTCCAGATGCCCT

GTGCTTGCAAGGTAAGTGGC

60

198

F2R

GTCAGGAGAGAGGGTGAAGC

CGGGGATCTAAGGTGGCATT

60

198

GAPDH (1)

AAGGCTGAGAACGGGAAGC

GAGGGATCTCGCTCCTGGA

60

68

G0S2

AAAGATATAAGCGGCCCCCG

GGAGGCGGGAATGACCTTAG

60

186

GREM1

AAGTTGGCAGCAGTAATCT

CCCTCTTTGGCTAGTGATA

56

155

HCK

CAGGATGGGGTGCATGAAGT

CCTCCCTGATTCCTGGTGTG

60

167

HIC1

TAAATCGGGAGAGTGTGCTGG

TCCAGGTTGAGCAGGTTGTC

60

225

IGFBP3

GTGCGGCATCTACACCGA

TCTTCCTCCGACTCACTAGCA

60

189

MT3

CCCCTGCCCTTCTGGTGG

CGCCTTTGCACACACAGTCCT

60

143

NT5E

TGATGAACGCAACAATGGAATC

ACCACGTTGATATCTTGGTCAC

60

240

PER1

AGGCTGCGTGGACTCGACAG

GCCCGAGGGTTCTGGTGGT

61

143

PRKCDBP

AGGAAGATCCCGGGAGACC

CGCTCCTTATTAGGGCGTGA

60

154

RASSF1

TGAAGGAAAATGACTCTGGGGA

GCGGCAATAGGAGTACTTCTGC

60

134

RPRM

GGGGTCTCACAAATCCGTGT

CTGTAACTCCTCAGGCAGGC

60

196

SFRP1

AGTTCTTCGGCTTCTACTGGC

CAGGGAGGACACACCGTTG

60

133

SOCS1

CACTTCCGCACATTCCGTTC

AGGCCATCTTCACGCTAAGG

60

202

SULF1

GGAGCTGTGTGGTCTTCTCC

TCTGCCTTGAAGAACCTGCAT

60

158

TNFRSF10C

GTTAGGGAACTCTGGGGACA

TGGTGGCAGAGTAAGCTAGG

60

173

TP73

TGGAGACGAGGACACGTACTACC

CTGCCGATAGGAGTCCACCA

60

127

TWIST1

GGACAGTGATTCCCAGACGG

CCTTTCAGTGGCTGATTGGC

60

173

UCHL1

AACGTGGATGGCCACCTCTA

AAGTCCCTCCCACAGAGCAT

60

193

VIM

AGGCGAGGAGAGCAGGATTT

CTGCACTGAGTGTGTGCAATTT

60

209

WIF1

ACTGCTCAACCACCTGCTTT

GACAGGGTTGTGGGCATTTG

60

114


Supplementary Table S4: Primer Used for Pyrosequencing Methylation Analysis of Candidate Genes

Gene

Primer

Primer sequence

No. of CpGs

Annealing

temperature (°C)

WIF1

Forward primer

5'- biotin-GAGGGATTTTAGAGGTTGTATTTATAGT-3'

6

54




Reverse primer

5'-AACCTTATCTACTCTCCCCATTTC-3'










Sequencing primer

5'- AAAATCTCTAAATACCCTTCT-3'

UCHL1

Forward primer

5'-GGTTTTGTTTTTGTTTTTTTTGTATAGG-3'

3

54




Reverse primer

5'-biotin-AATCTCCATCCACTTAAACTACATCTTC-3'










Sequencing primer

5'-TTGTATAGGTTTTATAGTG-3'

RASSF1

Forward primer

5'- biotin-CTCAAAAATTCCAAATAAAAAATAACA-3'

3

54




Reverse primer

5 '-CTCTCCCTAAAACTTCCCTTCAA-3'










Sequencing primer

5'-TCAATCTCCRAAACATT-3'

CCNA1

Forward primer

5'-GTTGTTAGAGGTTGTTGGGAGAA-3'

4

54




Reverse primer

5'-biotin-TCTACACACCTCCCCTCTAATCC-3'










Sequencing primer

5'-GGAAATAGTTTTTTTTAAAGT-3'

TP73

Forward primer

5'-GTTTAGTATGTAGGGTTTTTTAGTTAGGG-3'

3

54




Reverse primer

5'-biotin- CCCCTACTCCTCCTAAACCAT-3'










Sequencing primer

5'-TTTAGTTAGGGTTTGGTGTA-3'

SFRP1

Forward primer

5'-biotin-GTTAAAATTAAGGGTTTTTATTAGGGTAGA-3'

3

56

(For fresh tissues)

Reverse primer

5'-TCACTCCCAACTCTCCAAAACT-3'

Sequencing primer

5'-TAACAAAAAAACTTCTATTCC-3'

SFRP1

Forward primer

5'-GTTAAAATTAAGGGTTTTTATTAGGGTAGA-3'

1

56

(For FFPE specimens)

Reverse primer

5'- biotin-CTCAAAAATTCCAAATAAAAAATAACA-3'

Sequencing primer

5'-TTAAGAGGAAGGTATTAGTATAA-3'

FFPE:  Formalin-Fixed Paraffin-Embedded

Supplementary Table S5: Differentially Methylated CpG Sites (2173 Sites) in 24 Nasopharyngeal Carcinoma (NPC) Tissues and 24 Non-cancer Nasopharyngitis Biopsy Tissues (NCNBT)



(See supplementary table S5 in a PDF file)
Supplementary Table S6: Data Analysis with PubMeth and NCBI PubMed




Gene in PubMeth

Cancer with Methylation-associated Prognosis Published in NCBI PubMed

1

ALDH1A3

Bladder cance (2); glioblastoma (3); melanoma (4);

2

CCNA1

Acute myeloid leukaemia (5); prostate cancer (6); head and neck squamous cell carcinoma (7)

3

CD38

Chronic lymphocytic leukemia (8);

4

CD44

Breast Cancer (9); oral cavity squamous cell carcinoma (10);

5

CDKN1B

Breast cancer (11); Lung cancer (12); prostate cancer (13) ;

6

DKK1

Intrahepatic cholangiocarcinoma (14); esophageal squamous cell carcinoma (15); hepatocellular carcinomas (16)

7

DPP4

Colon cancer (17); renal cancer (18);

8

F2R

Prostate cancer (19)

9

G0S2

Hepatocellular Carcinoma (20); squamous lung cancer (21);

10

GREM1

Renal cell carcinoma (22); pancreatic neuroendocrine tumors (23)

11

HCK

Pancreatic adenocarcinoma (24); acute lymphocytic leukemia (25); renal clear cell carcinoma (26);

12

HIC1

Prostate cancer (27); hepatocellular carcinoma (28); colon cancer (29);

13

IGFBP3

Liver cancer (30); glioblastoma (31); ovarian endometrioid carcinoma (32)

14

MT3

Esophageal adenocarcinomas (33); breast cancer (34); prostate cancer (35);

15

MX1

None

16

NT5E

Breast cancer (36); melanoma (37);

17

PER1

Buccal squamous cell carcinoma (38); colorectal cancer (39); prostate cancer (40)

18

PLEKHG5

None

19

POU3F1

None

20

PRKCDBP

Colorectal cancer (41); neuroblastoma (42); breast cancer (43);

21

PRTFDC1

None

22

RASSF1

Lung cancer (44); oral squamous cell carcinoma (45); melanoma (46), Breast Cancer(47);

23

RPRM

Prostate cancer (48); pancreatic ductal adenocarcinoma (49)

24

SFRP1

Renal cell carcinoma (50); breast cancer (51); colorectal cancer (52); gastric cancer (53);

25

SLC1A2

None

26

SOCS1

Multiple myeloma (54);colorectal cancer (55); melanoma (56)

27

SULF1

Gastric cancer (57); ovarian cancer (58);

28

TNFRSF10C

Colorectal carcinomas (59)

29

TP73

Pancreatic cancer (60); colon cancer (61); glioma (62)

30

TWIST1

Breast cancer (63); colorectal carcinomas (64)

31

UCHL1

Renal cell cancer (65); esophageal squamous cell carcinoma (66);

32

VIM

Bladder cancer (67) ; colorectal cancer (68);breast cancer (69);

33

WIF1

Melanoma (56); acute lymphoblastic leukemia (70); renal cell carcinoma (50)

Supplementary Table S7: Correlation Analysis between Methylation of Six Genes in the Training Cohort




UCHL1

RASSF1

CCNA1

TP73

SFRP1

WIF1

R=0.406

P<0.001

R=0.436

P<0.001

R=0.389

P<0.001

R=0.535

P<0.001

R=0.486

P<0.001

UCHL1




R=0.465

P<0.001

R=0.317

P<0.001

R=0.524

P<0.001

R=0.269

P<0.001

RASSF1







R=0.379

P<0.001

R=0.605

P<0.001

R=0.394

P<0.001

CCNA1










R=0.433

P<0.001

R=0.222

P<0.009

TP73













R=0.464

P<0.001

Supplementary Figure Legends

Supplementary Figure S1: Representative Pyrograms of Methylation Analysis by Bisulfite Pyrosequencing. Percentages of methylation represent the ratio between signal intensities of C and T in each C of a CpG site.

Supplementary Figure S2. Kaplan-Meier curves estimation of disease-free survival (DFS) and overall survival (OS) for patients with high or low methylation levels stratified by tumor stage or the receipt of concurrent chemotherapy.

(A, B) Stage I-II patient DFS and OS. (C, D) Stage III-IV patients with high methylation DFS and OS. HR and P values were calculated with adjusted multivariate Cox proportional hazards models. The following parameters were included in the model as the covariates for each analysis: methylation gene panel (high methylation vs. low methylation), sex, age (<45 years vs. ≥45 years), World Health Organization (WHO) pathology type (undifferentiated non-keratinizing vs. differentiated non-keratinizing) and concurrent chemotherapy (yes vs. no). HR: hazard ratio, CI: confidence interval. CT: chemotherapy.




Reference

1. Xing J, Wu X, Vaporciyan AA, Spitz MR, Gu J. Prognostic significance of ataxia-telangiectasia mutated, DNA-dependent protein kinase catalytic subunit, and Ku heterodimeric regulatory complex 86-kD subunit expression in patients with nonsmall cell lung cancer. Cancer. 2008;112:2756-64.

2. Kim YJ, Yoon HY, Kim JS, Kang HW, Min BD, Kim SK, et al. HOXA9, ISL1 and ALDH1A3 methylation patterns as prognostic markers for nonmuscle invasive bladder cancer: array-based DNA methylation and expression profiling. Int J Cancer. 2013;133:1135-42.

3. Zhang W, Yan W, You G, Bao Z, Wang Y, Liu Y, et al. Genome-wide DNA methylation profiling identifies ALDH1A3 promoter methylation as a prognostic predictor in G-CIMP- primary glioblastoma. Cancer Lett. 2013;328:120-5.

4. Luo Y, Dallaglio K, Chen Y, Robinson WA, Robinson SE, McCarter MD, et al. ALDH1A isozymes are markers of human melanoma stem cells and potential therapeutic targets. Stem Cells. 2012;30:2100-13.

5. Nakamaki T, Hamano Y, Hisatake J, Yokoyama A, Kawakami K, Tomoyasu S, et al. Elevated levels of cyclin A1 and A (A2) mRNA in acute myeloid leukaemia are associated with increased survival. Br J Haematol. 2003;123:72-80.

6. Wegiel B, Bjartell A, Culig Z, Persson JL. Interleukin-6 activates PI3K/Akt pathway and regulates cyclin A1 to promote prostate cancer cell survival. Int J Cancer. 2008;122:1521-9.

7. Tan HK, Saulnier P, Auperin A, Lacroix L, Casiraghi O, Janot F, et al. Quantitative methylation analyses of resection margins predict local recurrences and disease-specific deaths in patients with head and neck squamous cell carcinomas. Br J Cancer. 2008;99:357-63.

8. Irving L, Mainou-Fowler T, Parker A, Ibbotson RE, Oscier DG, Strathdee G. Methylation markers identify high risk patients in IGHV mutated chronic lymphocytic leukemia. Epigenetics. 2011;6:300-6.

9. Tulsyan S, Agarwal G, Lal P, Agrawal S, Mittal RD, Mittal B. CD44 Gene Polymorphisms in Breast Cancer Risk and Prognosis: A Study in North Indian Population. PLoS One. 2013;8:e71073.

10. Dunkel J, Vaittinen S, Grenman R, Kinnunen I, Irjala H. Prognostic markers in stage I oral cavity squamous cell carcinoma. Laryngoscope. 2013;123:2435-41.

11. Catzavelos C, Bhattacharya N, Ung YC, Wilson JA, Roncari L, Sandhu C, et al. Decreased levels of the cell-cycle inhibitor p27Kip1 protein: prognostic implications in primary breast cancer. Nat Med. 1997;3:227-30.

12. Tsukamoto S, Sugio K, Sakada T, Ushijima C, Yamazaki K, Sugimachi K. Reduced expression of cell-cycle regulator p27(Kip1) correlates with a shortened survival in non-small cell lung cancer. Lung Cancer. 2001;34:83-90.

13. Tsihlias J, Kapusta LR, DeBoer G, Morava-Protzner I, Zbieranowski I, Bhattacharya N, et al. Loss of cyclin-dependent kinase inhibitor p27Kip1 is a novel prognostic factor in localized human prostate adenocarcinoma. Cancer Res. 1998;58:542-8.

14. Shi RY, Yang XR, Shen QJ, Yang LX, Xu Y, Qiu SJ, et al. High expression of Dickkopf-related protein 1 is related to lymphatic metastasis and indicates poor prognosis in intrahepatic cholangiocarcinoma patients after surgery. Cancer. 2013;119:993-1003.

15. Makino T, Yamasaki M, Takemasa I, Takeno A, Nakamura Y, Miyata H, et al. Dickkopf-1 expression as a marker for predicting clinical outcome in esophageal squamous cell carcinoma. Ann Surg Oncol. 2009;16:2058-64.

16. Yu B, Yang X, Xu Y, Yao G, Shu H, Lin B, et al. Elevated expression of DKK1 is associated with cytoplasmic/nuclear beta-catenin accumulation and poor prognosis in hepatocellular carcinomas. J Hepatol. 2009;50:948-57.

17. Gerger A, Zhang W, Yang D, Bohanes P, Ning Y, Winder T, et al. Common cancer stem cell gene variants predict colon cancer recurrence. Clin Cancer Res. 2011;17:6934-43.

18. Varona A, Blanco L, Perez I, Gil J, Irazusta J, Lopez JI, et al. Expression and activity profiles of DPP IV/CD26 and NEP/CD10 glycoproteins in the human renal cancer are tumor-type dependent. BMC Cancer. 2010;10:193.

19. Latil A, Bieche I, Chene L, Laurendeau I, Berthon P, Cussenot O, et al. Gene expression profiling in clinically localized prostate cancer: a four-gene expression model predicts clinical behavior. Clin Cancer Res. 2003;9:5477-85.

20. Honda M, Yamashita T, Arai K, Sakai Y, Sakai A, Nakamura M, et al. Peretinoin, an acyclic retinoid, improves the hepatic gene signature of chronic hepatitis C following curative therapy of hepatocellular carcinoma. BMC Cancer. 2013;13:191.

21. Kusakabe M, Kutomi T, Watanabe K, Emoto N, Aki N, Kage H, et al. Identification of G0S2 as a gene frequently methylated in squamous lung cancer by combination of in silico and experimental approaches. Int J Cancer. 2010;126:1895-902.

22. van Vlodrop IJ, Baldewijns MM, Smits KM, Schouten LJ, van Neste L, van Criekinge W, et al. Prognostic significance of Gremlin1 (GREM1) promoter CpG island hypermethylation in clear cell renal cell carcinoma. Am J Pathol. 2010;176:575-84.

23. Chen MH, Yeh YC, Shyr YM, Jan YH, Chao Y, Li CP, et al. Expression of gremlin 1 correlates with increased angiogenesis and progression-free survival in patients with pancreatic neuroendocrine tumors. J Gastroenterol. 2013;48:101-8.

24. Loukopoulos P, Shibata T, Katoh H, Kokubu A, Sakamoto M, Yamazaki K, et al. Genome-wide array-based comparative genomic hybridization analysis of pancreatic adenocarcinoma: identification of genetic indicators that predict patient outcome. Cancer Sci. 2007;98:392-400.

25. Hoshino K, Quintas-Cardama A, Yang H, Sanchez-Gonzalez B, Garcia-Manero G. Aberrant DNA methylation of the Src kinase Hck, but not of Lyn, in Philadelphia chromosome negative acute lymphocytic leukemia. Leukemia. 2007;21:906-11.

26. Qayyum T, McArdle PA, Lamb GW, Jordan F, Orange C, Seywright M, et al. Expression and prognostic significance of Src family members in renal clear cell carcinoma. Br J Cancer. 2012;107:856-63.

27. Zheng J, Wang J, Sun X, Hao M, Ding T, Xiong D, et al. HIC1 modulates prostate cancer progression by epigenetic modification. Clin Cancer Res. 2013;19:1400-10.

28. Nishida N, Kudo M, Nagasaka T, Ikai I, Goel A. Characteristic patterns of altered DNA methylation predict emergence of human hepatocellular carcinoma. Hepatology. 2012;56:994-1003.

29. Ogino S, Nosho K, Kirkner GJ, Kawasaki T, Meyerhardt JA, Loda M, et al. CpG island methylator phenotype, microsatellite instability, BRAF mutation and clinical outcome in colon cancer. Gut. 2009;58:90-6.

30. Regel I, Eichenmuller M, Joppien S, Liebl J, Haberle B, Muller-Hocker J, et al. IGFBP3 impedes aggressive growth of pediatric liver cancer and is epigenetically silenced in vascular invasive and metastatic tumors. Mol Cancer. 2012;11:9.

31. Rohrmann S, Linseisen J, Becker S, Allen N, Schlehofer B, Overvad K, et al. Concentrations of IGF-I and IGFBP-3 and brain tumor risk in the European Prospective Investigation into Cancer and Nutrition. Cancer Epidemiol Biomarkers Prev. 2011;20:2174-82.

32. Torng PL, Lee YC, Huang CY, Ye JH, Lin YS, Chu YW, et al. Insulin-like growth factor binding protein-3 (IGFBP-3) acts as an invasion-metastasis suppressor in ovarian endometrioid carcinoma. Oncogene. 2008;27:2137-47.

33. Peng D, Hu TL, Jiang A, Washington MK, Moskaluk CA, Schneider-Stock R, et al. Location-specific epigenetic regulation of the metallothionein 3 gene in esophageal adenocarcinomas. PLoS One. 2011;6:e22009.

34. Sens MA, Somji S, Garrett SH, Beall CL, Sens DA. Metallothionein isoform 3 overexpression is associated with breast cancers having a poor prognosis. Am J Pathol. 2001;159:21-6.

35. Dutta R, Sens DA, Somji S, Sens MA, Garrett SH. Metallothionein isoform 3 expression inhibits cell growth and increases drug resistance of PC-3 prostate cancer cells. Prostate. 2002;52:89-97.

36. Lo Nigro C, Monteverde M, Lee S, Lattanzio L, Vivenza D, Comino A, et al. NT5E CpG island methylation is a favourable breast cancer biomarker. Br J Cancer. 2012;107:75-83.

37. Wang H, Lee S, Nigro CL, Lattanzio L, Merlano M, Monteverde M, et al. NT5E (CD73) is epigenetically regulated in malignant melanoma and associated with metastatic site specificity. Br J Cancer. 2012;106:1446-52.

38. Zhao N, Yang K, Yang G, Chen D, Tang H, Zhao D, et al. Aberrant expression of clock gene period1 and its correlations with the growth, proliferation and metastasis of buccal squamous cell carcinoma. PLoS One. 2013;8:e55894.

39. Mazzoccoli G, Panza A, Valvano MR, Palumbo O, Carella M, Pazienza V, et al. Clock gene expression levels and relationship with clinical and pathological features in colorectal cancer patients. Chronobiol Int. 2011;28:841-51.

40. Cao Q, Gery S, Dashti A, Yin D, Zhou Y, Gu J, et al. A role for the clock gene per1 in prostate cancer. Cancer Res. 2009;69:7619-25.

41. Lee JH, Kang MJ, Han HY, Lee MG, Jeong SI, Ryu BK, et al. Epigenetic alteration of PRKCDBP in colorectal cancers and its implication in tumor cell resistance to TNFalpha-induced apoptosis. Clin Cancer Res. 2011;17:7551-62.

42. Caren H, Djos A, Nethander M, Sjoberg RM, Kogner P, Enstrom C, et al. Identification of epigenetically regulated genes that predict patient outcome in neuroblastoma. BMC Cancer. 2011;11:66.

43. Wikman H, Sielaff-Frimpong B, Kropidlowski J, Witzel I, Milde-Langosch K, Sauter G, et al. Clinical relevance of loss of 11p15 in primary and metastatic breast cancer: association with loss of PRKCDBP expression in brain metastases. PLoS One. 2012;7:e47537.

44. de Fraipont F, Levallet G, Creveuil C, Bergot E, Beau-Faller M, Mounawar M, et al. An apoptosis methylation prognostic signature for early lung cancer in the IFCT-0002 trial. Clin Cancer Res. 2012;18:2976-86.

45. Huang KH, Huang SF, Chen IH, Liao CT, Wang HM, Hsieh LL. Methylation of RASSF1A, RASSF2A, and HIN-1 is associated with poor outcome after radiotherapy, but not surgery, in oral squamous cell carcinoma. Clin Cancer Res. 2009;15:4174-80.

46. Mori T, O'Day SJ, Umetani N, Martinez SR, Kitago M, Koyanagi K, et al. Predictive utility of circulating methylated DNA in serum of melanoma patients receiving biochemotherapy. J Clin Oncol. 2005;23:9351-8.

47. Muller HM, Widschwendter A, Fiegl H, Ivarsson L, Goebel G, Perkmann E, et al. DNA methylation in serum of breast cancer patients: an independent prognostic marker. Cancer Res. 2003;63:7641-5.

48. Ellinger J, Bastian PJ, Jurgan T, Biermann K, Kahl P, Heukamp LC, et al. CpG island hypermethylation at multiple gene sites in diagnosis and prognosis of prostate cancer. Urology. 2008;71:161-7.

49. Sato N, Fukushima N, Matsubayashi H, Iacobuzio-Donahue CA, Yeo CJ, Goggins M. Aberrant methylation of Reprimo correlates with genetic instability and predicts poor prognosis in pancreatic ductal adenocarcinoma. Cancer. 2006;107:251-7.

50. Urakami S, Shiina H, Enokida H, Hirata H, Kawamoto K, Kawakami T, et al. Wnt antagonist family genes as biomarkers for diagnosis, staging, and prognosis of renal cell carcinoma using tumor and serum DNA. Clin Cancer Res. 2006;12:6989-97.

51. Veeck J, Niederacher D, An H, Klopocki E, Wiesmann F, Betz B, et al. Aberrant methylation of the Wnt antagonist SFRP1 in breast cancer is associated with unfavourable prognosis. Oncogene. 2006;25:3479-88.

52. Rawson JB, Manno M, Mrkonjic M, Daftary D, Dicks E, Buchanan DD, et al. Promoter methylation of Wnt antagonists DKK1 and SFRP1 is associated with opposing tumor subtypes in two large populations of colorectal cancer patients. Carcinogenesis. 2011;32:741-7.

53. Qu Y, Ray PS, Li J, Cai Q, Bagaria SP, Moran C, et al. High levels of secreted frizzled-related protein 1 correlate with poor prognosis and promote tumourigenesis in gastric cancer. Eur J Cancer. 2013.

54. Depil S, Saudemont A, Quesnel B. SOCS-1 gene methylation is frequent but does not appear to have prognostic value in patients with multiple myeloma. Leukemia. 2003;17:1678-9.

55. Ogino S, Nosho K, Irahara N, Meyerhardt JA, Baba Y, Shima K, et al. Lymphocytic reaction to colorectal cancer is associated with longer survival, independent of lymph node count, microsatellite instability, and CpG island methylator phenotype. Clin Cancer Res. 2009;15:6412-20.

56. Tanemura A, Terando AM, Sim MS, van Hoesel AQ, de Maat MF, Morton DL, et al. CpG island methylator phenotype predicts progression of malignant melanoma. Clin Cancer Res. 2009;15:1801-7.

57. Hur K, Han TS, Jung EJ, Yu J, Lee HJ, Kim WH, et al. Up-regulated expression of sulfatases (SULF1 and SULF2) as prognostic and metastasis predictive markers in human gastric cancer. J Pathol. 2012;228:88-98.

58. Han CH, Huang YJ, Lu KH, Liu Z, Mills GB, Wei Q, et al. Polymorphisms in the SULF1 gene are associated with early age of onset and survival of ovarian cancer. J Exp Clin Cancer Res. 2011;30:5.

59. Granci V, Bibeau F, Kramar A, Boissiere-Michot F, Thezenas S, Thirion A, et al. Prognostic significance of TRAIL-R1 and TRAIL-R3 expression in metastatic colorectal carcinomas. Eur J Cancer. 2008;44:2312-8.

60. Dong X, Jiao L, Li Y, Evans DB, Wang H, Hess KR, et al. Significant associations of mismatch repair gene polymorphisms with clinical outcome of pancreatic cancer. J Clin Oncol. 2009;27:1592-9.

61. Dominguez G, Garcia JM, Pena C, Silva J, Garcia V, Martinez L, et al. DeltaTAp73 upregulation correlates with poor prognosis in human tumors: putative in vivo network involving p73 isoforms, p53, and E2F-1. J Clin Oncol. 2006;24:805-15.

62. Wager M, Guilhot J, Blanc JL, Ferrand S, Milin S, Bataille B, et al. Prognostic value of increase in transcript levels of Tp73 DeltaEx2-3 isoforms in low-grade glioma patients. Br J Cancer. 2006;95:1062-9.

63. Riaz M, Sieuwerts AM, Look MP, Timmermans MA, Smid M, Foekens JA, et al. High TWIST1 mRNA expression is associated with poor prognosis in lymph node-negative and estrogen receptor-positive human breast cancer and is co-expressed with stromal as well as ECM related genes. Breast Cancer Res. 2012;14:R123.

64. Gomez I, Pena C, Herrera M, Munoz C, Larriba MJ, Garcia V, et al. TWIST1 is expressed in colorectal carcinomas and predicts patient survival. PLoS One. 2011;6:e18023.

65. Seliger B, Fedorushchenko A, Brenner W, Ackermann A, Atkins D, Hanash S, et al. Ubiquitin COOH-terminal hydrolase 1: a biomarker of renal cell carcinoma associated with enhanced tumor cell proliferation and migration. Clin Cancer Res. 2007;13:27-37.

66. Mandelker DL, Yamashita K, Tokumaru Y, Mimori K, Howard DL, Tanaka Y, et al. PGP9.5 promoter methylation is an independent prognostic factor for esophageal squamous cell carcinoma. Cancer Res. 2005;65:4963-8.

67. Reinert T, Borre M, Christiansen A, Hermann GG, Orntoft TF, Dyrskjot L. Diagnosis of bladder cancer recurrence based on urinary levels of EOMES, HOXA9, POU4F2, TWIST1, VIM, and ZNF154 hypermethylation. PLoS One. 2012;7:e46297.

68. Toiyama Y, Yasuda H, Saigusa S, Tanaka K, Inoue Y, Goel A, et al. Increased expression of Slug and Vimentin as novel predictive biomarkers for lymph node metastasis and poor prognosis in colorectal cancer. Carcinogenesis. 2013.

69. Karihtala P, Auvinen P, Kauppila S, Haapasaari KM, Jukkola-Vuorinen A, Soini Y. Vimentin, zeb1 and Sip1 are up-regulated in triple-negative and basal-like breast cancers: association with an aggressive tumour phenotype. Breast Cancer Res Treat. 2013;138:81-90.



70. Roman-Gomez J, Cordeu L, Agirre X, Jimenez-Velasco A, San Jose-Eneriz E, Garate L, et al. Epigenetic regulation of Wnt-signaling pathway in acute lymphoblastic leukemia. Blood. 2007;109:3462-9.

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