Skin Cutaneous Melanoma: Correlation between gene methylation status and clinical features
(All_Samples cohort)
Maintained by Juok Cho (Broad Institute)
Overview
Introduction

This pipeline uses various statistical tests to identify genes whose promoter methylation levels correlated to selected clinical features.

Summary

Testing the association between 17134 genes and 8 clinical features across 195 samples, statistically thresholded by Q value < 0.05, 8 clinical features related to at least one genes.

  • 1 gene correlated to 'Time to Death'.

    • NR4A3

  • 21 genes correlated to 'AGE'.

    • PTX3 ,  BBX ,  XKR6 ,  VGF ,  CAMK1 ,  ...

  • 45 genes correlated to 'PRIMARY.SITE.OF.DISEASE'.

    • S100A2 ,  AGAP11 ,  DCLRE1C ,  KLF2 ,  LAX1 ,  ...

  • 1 gene correlated to 'GENDER'.

    • DDX43

  • 407 genes correlated to 'RADIATIONS.RADIATION.REGIMENINDICATION'.

    • HRNR ,  ABT1 ,  IGF1R ,  ZNF280A ,  TMEM49 ,  ...

  • 220 genes correlated to 'DISTANT.METASTASIS'.

    • LDHAL6B ,  COL5A1 ,  CCNG1 ,  FAM186A ,  SELT ,  ...

  • 33 genes correlated to 'LYMPH.NODE.METASTASIS'.

    • CCDC25 ,  NGLY1 ,  LIMK2 ,  C17ORF63 ,  PCLO ,  ...

  • 10 genes correlated to 'NEOPLASM.DISEASESTAGE'.

    • POLE4 ,  C4ORF3 ,  GRAMD1B ,  RAD21L1 ,  ZNF587 ,  ...

Results
Overview of the results

Complete statistical result table is provided in Supplement Table 1

Table 1.  Get Full Table This table shows the clinical features, statistical methods used, and the number of genes that are significantly associated with each clinical feature at Q value < 0.05.

Clinical feature Statistical test Significant genes Associated with                 Associated with
Time to Death Cox regression test N=1 shorter survival N=0 longer survival N=1
AGE Spearman correlation test N=21 older N=21 younger N=0
PRIMARY SITE OF DISEASE ANOVA test N=45        
GENDER t test N=1 male N=0 female N=1
RADIATIONS RADIATION REGIMENINDICATION t test N=407 yes N=93 no N=314
DISTANT METASTASIS ANOVA test N=220        
LYMPH NODE METASTASIS ANOVA test N=33        
NEOPLASM DISEASESTAGE ANOVA test N=10        
Clinical variable #1: 'Time to Death'

One gene related to 'Time to Death'.

Table S1.  Basic characteristics of clinical feature: 'Time to Death'

Time to Death Duration (Months) 0-357.4 (median=41.6)
  censored N = 97
  death N = 88
     
  Significant markers N = 1
  associated with shorter survival 0
  associated with longer survival 1
List of one gene significantly associated with 'Time to Death' by Cox regression test

Table S2.  Get Full Table List of one gene significantly associated with 'Time to Death' by Cox regression test

HazardRatio Wald_P Q C_index
NR4A3 0.07 3.047e-07 0.0052 0.325

Figure S1.  Get High-res Image As an example, this figure shows the association of NR4A3 to 'Time to Death'. four curves present the cumulative survival rates of 4 quartile subsets of patients. P value = 3.05e-07 with univariate Cox regression analysis using continuous log-2 expression values.

Clinical variable #2: 'AGE'

21 genes related to 'AGE'.

Table S3.  Basic characteristics of clinical feature: 'AGE'

AGE Mean (SD) 56.52 (16)
  Significant markers N = 21
  pos. correlated 21
  neg. correlated 0
List of top 10 genes significantly correlated to 'AGE' by Spearman correlation test

Table S4.  Get Full Table List of top 10 genes significantly correlated to 'AGE' by Spearman correlation test

SpearmanCorr corrP Q
PTX3 0.4047 6.377e-09 0.000109
BBX 0.3821 4.911e-08 0.000841
XKR6 0.3779 7.087e-08 0.00121
VGF 0.3625 2.556e-07 0.00438
CAMK1 0.349 7.489e-07 0.0128
BARHL2 0.3483 7.916e-07 0.0136
C11ORF66 0.3478 8.214e-07 0.0141
TRPV4 0.3475 8.421e-07 0.0144
ACTA2 0.3459 9.556e-07 0.0164
FAS 0.3459 9.556e-07 0.0164

Figure S2.  Get High-res Image As an example, this figure shows the association of PTX3 to 'AGE'. P value = 6.38e-09 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #3: 'PRIMARY.SITE.OF.DISEASE'

45 genes related to 'PRIMARY.SITE.OF.DISEASE'.

Table S5.  Basic characteristics of clinical feature: 'PRIMARY.SITE.OF.DISEASE'

PRIMARY.SITE.OF.DISEASE Labels N
  DISTANT METASTASIS 27
  PRIMARY TUMOR 24
  REGIONAL CUTANEOUS OR SUBCUTANEOUS TISSUE (INCLUDES SATELLITE AND IN-TRANSIT METASTASIS) 34
  REGIONAL LYMPH NODE 110
     
  Significant markers N = 45
List of top 10 genes differentially expressed by 'PRIMARY.SITE.OF.DISEASE'

Table S6.  Get Full Table List of top 10 genes differentially expressed by 'PRIMARY.SITE.OF.DISEASE'

ANOVA_P Q
S100A2 2.733e-08 0.000468
AGAP11 5.374e-08 0.000921
DCLRE1C 7.03e-08 0.0012
KLF2 8.427e-08 0.00144
LAX1 8.505e-08 0.00146
ERI3 8.892e-08 0.00152
CD3D 1.075e-07 0.00184
SP140 1.117e-07 0.00191
SLC39A13 1.645e-07 0.00282
SLA2 1.69e-07 0.00289

Figure S3.  Get High-res Image As an example, this figure shows the association of S100A2 to 'PRIMARY.SITE.OF.DISEASE'. P value = 2.73e-08 with ANOVA analysis.

Clinical variable #4: 'GENDER'

One gene related to 'GENDER'.

Table S7.  Basic characteristics of clinical feature: 'GENDER'

GENDER Labels N
  FEMALE 74
  MALE 121
     
  Significant markers N = 1
  Higher in MALE 0
  Higher in FEMALE 1
List of one gene differentially expressed by 'GENDER'

Table S8.  Get Full Table List of one gene differentially expressed by 'GENDER'

T(pos if higher in 'MALE') ttestP Q AUC
DDX43 -4.86 2.437e-06 0.0417 0.7091

Figure S4.  Get High-res Image As an example, this figure shows the association of DDX43 to 'GENDER'. P value = 2.44e-06 with T-test analysis.

Clinical variable #5: 'RADIATIONS.RADIATION.REGIMENINDICATION'

407 genes related to 'RADIATIONS.RADIATION.REGIMENINDICATION'.

Table S9.  Basic characteristics of clinical feature: 'RADIATIONS.RADIATION.REGIMENINDICATION'

RADIATIONS.RADIATION.REGIMENINDICATION Labels N
  NO 3
  YES 192
     
  Significant markers N = 407
  Higher in YES 93
  Higher in NO 314
List of top 10 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

Table S10.  Get Full Table List of top 10 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

T(pos if higher in 'YES') ttestP Q AUC
HRNR -24.55 5.151e-61 8.79e-57 0.9271
ABT1 -22.9 1.848e-54 3.15e-50 0.9566
IGF1R -21.34 6.178e-50 1.05e-45 0.9427
ZNF280A -17.25 8.431e-41 1.44e-36 0.9479
TMEM49 -15.6 1.558e-35 2.66e-31 0.8194
TBC1D20 -17.02 1.438e-33 2.45e-29 0.9653
EPS8 -15.32 1.604e-32 2.74e-28 0.9149
SGK3 -14.38 2.34e-32 3.99e-28 0.908
FAM178B -14.8 3.547e-32 6.05e-28 0.8264
FAM83B -14 3.318e-31 5.66e-27 0.7639

Figure S5.  Get High-res Image As an example, this figure shows the association of HRNR to 'RADIATIONS.RADIATION.REGIMENINDICATION'. P value = 5.15e-61 with T-test analysis.

Clinical variable #6: 'DISTANT.METASTASIS'

220 genes related to 'DISTANT.METASTASIS'.

Table S11.  Basic characteristics of clinical feature: 'DISTANT.METASTASIS'

DISTANT.METASTASIS Labels N
  M0 169
  M1 2
  M1A 2
  M1B 2
  M1C 3
     
  Significant markers N = 220
List of top 10 genes differentially expressed by 'DISTANT.METASTASIS'

Table S12.  Get Full Table List of top 10 genes differentially expressed by 'DISTANT.METASTASIS'

ANOVA_P Q
LDHAL6B 1.786e-24 3.06e-20
COL5A1 3.706e-24 6.35e-20
CCNG1 4.551e-24 7.8e-20
FAM186A 3.268e-21 5.6e-17
SELT 7.134e-21 1.22e-16
C10ORF88 8.201e-21 1.4e-16
MDM1 1.25e-19 2.14e-15
LOC728758 1.468e-19 2.51e-15
FGFR2 3.975e-19 6.81e-15
ZNF585A 1.597e-18 2.73e-14

Figure S6.  Get High-res Image As an example, this figure shows the association of LDHAL6B to 'DISTANT.METASTASIS'. P value = 1.79e-24 with ANOVA analysis.

Clinical variable #7: 'LYMPH.NODE.METASTASIS'

33 genes related to 'LYMPH.NODE.METASTASIS'.

Table S13.  Basic characteristics of clinical feature: 'LYMPH.NODE.METASTASIS'

LYMPH.NODE.METASTASIS Labels N
  N0 108
  N1 2
  N1A 7
  N1B 16
  N2 1
  N2A 5
  N2B 13
  N2C 6
  N3 17
  NX 5
     
  Significant markers N = 33
List of top 10 genes differentially expressed by 'LYMPH.NODE.METASTASIS'

Table S14.  Get Full Table List of top 10 genes differentially expressed by 'LYMPH.NODE.METASTASIS'

ANOVA_P Q
CCDC25 2.569e-189 4.4e-185
NGLY1 4.062e-70 6.96e-66
LIMK2 3.97e-38 6.8e-34
C17ORF63 7.288e-26 1.25e-21
PCLO 2.619e-21 4.49e-17
CSRP2BP 3.44e-20 5.89e-16
GPR44 2.493e-16 4.27e-12
ASAP3 3.05e-16 5.22e-12
MEGF6 4.401e-15 7.54e-11
POP5 6.48e-14 1.11e-09

Figure S7.  Get High-res Image As an example, this figure shows the association of CCDC25 to 'LYMPH.NODE.METASTASIS'. P value = 2.57e-189 with ANOVA analysis.

Clinical variable #8: 'NEOPLASM.DISEASESTAGE'

10 genes related to 'NEOPLASM.DISEASESTAGE'.

Table S15.  Basic characteristics of clinical feature: 'NEOPLASM.DISEASESTAGE'

NEOPLASM.DISEASESTAGE Labels N
  I OR II NOS 3
  STAGE I 17
  STAGE IA 10
  STAGE IB 15
  STAGE II 20
  STAGE IIA 9
  STAGE IIB 10
  STAGE IIC 22
  STAGE III 8
  STAGE IIIA 6
  STAGE IIIB 20
  STAGE IIIC 25
  STAGE IV 7
     
  Significant markers N = 10
List of 10 genes differentially expressed by 'NEOPLASM.DISEASESTAGE'

Table S16.  Get Full Table List of 10 genes differentially expressed by 'NEOPLASM.DISEASESTAGE'

ANOVA_P Q
POLE4 2.38e-09 4.08e-05
C4ORF3 3.314e-09 5.68e-05
GRAMD1B 2.5e-08 0.000428
RAD21L1 2.602e-08 0.000446
ZNF587 2.763e-08 0.000473
HEMK1 1.276e-07 0.00219
GALNT7 3.837e-07 0.00657
LOC100128191 1.185e-06 0.0203
TMPO 1.185e-06 0.0203
LZTS1 1.829e-06 0.0313

Figure S8.  Get High-res Image As an example, this figure shows the association of POLE4 to 'NEOPLASM.DISEASESTAGE'. P value = 2.38e-09 with ANOVA analysis.

Methods & Data
Input

  • Expresson data file = SKCM-All_Samples.meth.for_correlation.filtered_data.txt

  • Clinical data file = SKCM-All_Samples.clin.merged.picked.txt

  • Number of patients = 195

  • Number of genes = 17134

  • Number of clinical features = 8

Survival analysis

For survival clinical features, Wald's test in univariate Cox regression analysis with proportional hazards model (Andersen and Gill 1982) was used to estimate the P values using the 'coxph' function in R. Kaplan-Meier survival curves were plot using the four quartile subgroups of patients based on expression levels

Correlation analysis

For continuous numerical clinical features, Spearman's rank correlation coefficients (Spearman 1904) and two-tailed P values were estimated using 'cor.test' function in R

ANOVA analysis

For multi-class clinical features (ordinal or nominal), one-way analysis of variance (Howell 2002) was applied to compare the log2-expression levels between different clinical classes using 'anova' function in R

Student's t-test analysis

For two-class clinical features, two-tailed Student's t test with unequal variance (Lehmann and Romano 2005) was applied to compare the log2-expression levels between the two clinical classes using 't.test' function in R

Q value calculation

For multiple hypothesis correction, Q value is the False Discovery Rate (FDR) analogue of the P value (Benjamini and Hochberg 1995), defined as the minimum FDR at which the test may be called significant. We used the 'Benjamini and Hochberg' method of 'p.adjust' function in R to convert P values into Q values.

Download Results

This is an experimental feature. The full results of the analysis summarized in this report can be downloaded from the TCGA Data Coordination Center.

References
[1] Andersen and Gill, Cox's regression model for counting processes, a large sample study, Annals of Statistics 10(4):1100-1120 (1982)
[2] Spearman, C, The proof and measurement of association between two things, Amer. J. Psychol 15:72-101 (1904)
[3] Howell, D, Statistical Methods for Psychology. (5th ed.), Duxbury Press:324-5 (2002)
[4] Lehmann and Romano, Testing Statistical Hypotheses (3E ed.), New York: Springer. ISBN 0387988645 (2005)
[5] Benjamini and Hochberg, Controlling the false discovery rate: a practical and powerful approach to multiple testing, Journal of the Royal Statistical Society Series B 59:289-300 (1995)
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