Correlation between gene methylation status and clinical features
Skin Cutaneous Melanoma (Metastatic)
15 January 2014  |  analyses__2014_01_15
Maintainer Information
Citation Information
doi:10.7908/C18C9TQ3
Maintained by Juok Cho (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2014): Correlation between gene methylation status and clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C18C9TQ3
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 19685 genes and 12 clinical features across 260 samples, statistically thresholded by Q value < 0.05, 7 clinical features related to at least one genes.

  • 11 genes correlated to 'AGE'.

    • NFATC2 ,  TRPV4 ,  NIPAL2 ,  SP1 ,  FBXL13__2 ,  ...

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

    • TMEM101 ,  ZNF559 ,  EXOC3 ,  ACTN3 ,  ZDHHC24__1 ,  ...

  • 7 genes correlated to 'NEOPLASM.DISEASESTAGE'.

    • FGL1 ,  AGPAT9 ,  C18ORF22 ,  GPR137C__1 ,  TXNDC16__1 ,  ...

  • 291 genes correlated to 'PATHOLOGY.M.STAGE'.

    • COL5A1 ,  C10ORF88 ,  FAM186A ,  LMF1 ,  FGFR2 ,  ...

  • 27 genes correlated to 'MELANOMA.PRIMARY.KNOWN'.

    • CMTM7 ,  CARD11 ,  MIR564 ,  TMEM42 ,  MCL1 ,  ...

  • 3 genes correlated to 'BRESLOW.THICKNESS'.

    • FAM100B ,  ITSN2 ,  HMGA2

  • 1 gene correlated to 'GENDER'.

    • KIF4B

  • No genes correlated to 'Time from Specimen Diagnosis to Death', 'Time to Death', 'PATHOLOGY.T.STAGE', 'PATHOLOGY.N.STAGE', and 'MELANOMA.ULCERATION'.

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 from Specimen Diagnosis to Death Cox regression test   N=0        
Time to Death Cox regression test   N=0        
AGE Spearman correlation test N=11 older N=11 younger N=0
PRIMARY SITE OF DISEASE ANOVA test N=59        
NEOPLASM DISEASESTAGE ANOVA test N=7        
PATHOLOGY T STAGE Spearman correlation test   N=0        
PATHOLOGY N STAGE Spearman correlation test   N=0        
PATHOLOGY M STAGE ANOVA test N=291        
MELANOMA ULCERATION t test   N=0        
MELANOMA PRIMARY KNOWN t test N=27 yes N=25 no N=2
BRESLOW THICKNESS Spearman correlation test N=3 higher breslow.thickness N=3 lower breslow.thickness N=0
GENDER t test N=1 male N=0 female N=1
Clinical variable #1: 'Time from Specimen Diagnosis to Death'

No gene related to 'Time from Specimen Diagnosis to Death'.

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

Time from Specimen Diagnosis to Death Duration (Months) 0.1-124.3 (median=13.9)
  censored N = 127
  death N = 120
     
  Significant markers N = 0
Clinical variable #2: 'Time to Death'

No gene related to 'Time to Death'.

Table S2.  Basic characteristics of clinical feature: 'Time to Death'

Time to Death Duration (Months) 0.2-357.4 (median=48.2)
  censored N = 132
  death N = 122
     
  Significant markers N = 0
Clinical variable #3: 'AGE'

11 genes related to 'AGE'.

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

AGE Mean (SD) 55.59 (16)
  Significant markers N = 11
  pos. correlated 11
  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
NFATC2 0.3228 1.284e-07 0.00253
TRPV4 0.3212 1.496e-07 0.00294
NIPAL2 0.321 1.511e-07 0.00297
SP1 0.3024 8.178e-07 0.0161
FBXL13__2 0.3003 9.847e-07 0.0194
LRRC17 0.3003 9.847e-07 0.0194
STL 0.3002 9.91e-07 0.0195
TES 0.2968 1.334e-06 0.0262
SOSTDC1 0.2947 1.589e-06 0.0313
CMBL 0.293 1.838e-06 0.0362

Figure S1.  Get High-res Image As an example, this figure shows the association of NFATC2 to 'AGE'. P value = 1.28e-07 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #4: 'PRIMARY.SITE.OF.DISEASE'

59 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 33
  PRIMARY TUMOR 1
  REGIONAL CUTANEOUS OR SUBCUTANEOUS TISSUE 55
  REGIONAL LYMPH NODE 170
     
  Significant markers N = 59
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
TMEM101 2.793e-58 5.5e-54
ZNF559 9.9e-47 1.95e-42
EXOC3 3.612e-16 7.11e-12
ACTN3 5.861e-13 1.15e-08
ZDHHC24__1 5.861e-13 1.15e-08
TUBB3 1.406e-10 2.77e-06
EPHB4 4.946e-10 9.73e-06
DKFZP686I15217 9.109e-10 1.79e-05
RHOJ 1.508e-08 0.000297
GALR2 2.29e-08 0.000451

Figure S2.  Get High-res Image As an example, this figure shows the association of TMEM101 to 'PRIMARY.SITE.OF.DISEASE'. P value = 2.79e-58 with ANOVA analysis.

Clinical variable #5: 'NEOPLASM.DISEASESTAGE'

7 genes related to 'NEOPLASM.DISEASESTAGE'.

Table S7.  Basic characteristics of clinical feature: 'NEOPLASM.DISEASESTAGE'

NEOPLASM.DISEASESTAGE Labels N
  I OR II NOS 10
  STAGE 0 5
  STAGE I 21
  STAGE IA 10
  STAGE IB 24
  STAGE II 16
  STAGE IIA 10
  STAGE IIB 13
  STAGE IIC 10
  STAGE III 30
  STAGE IIIA 11
  STAGE IIIB 23
  STAGE IIIC 41
  STAGE IV 12
     
  Significant markers N = 7
List of 7 genes differentially expressed by 'NEOPLASM.DISEASESTAGE'

Table S8.  Get Full Table List of 7 genes differentially expressed by 'NEOPLASM.DISEASESTAGE'

ANOVA_P Q
FGL1 1.299e-07 0.00256
AGPAT9 3.564e-07 0.00702
C18ORF22 1.11e-06 0.0219
GPR137C__1 1.434e-06 0.0282
TXNDC16__1 1.434e-06 0.0282
RNASEL 1.541e-06 0.0303
HOXA10 1.694e-06 0.0333

Figure S3.  Get High-res Image As an example, this figure shows the association of FGL1 to 'NEOPLASM.DISEASESTAGE'. P value = 1.3e-07 with ANOVA analysis.

Clinical variable #6: 'PATHOLOGY.T.STAGE'

No gene related to 'PATHOLOGY.T.STAGE'.

Table S9.  Basic characteristics of clinical feature: 'PATHOLOGY.T.STAGE'

PATHOLOGY.T.STAGE Mean (SD) 2.4 (1.3)
  N
  0 21
  1 30
  2 57
  3 50
  4 53
     
  Significant markers N = 0
Clinical variable #7: 'PATHOLOGY.N.STAGE'

No gene related to 'PATHOLOGY.N.STAGE'.

Table S10.  Basic characteristics of clinical feature: 'PATHOLOGY.N.STAGE'

PATHOLOGY.N.STAGE Mean (SD) 0.83 (1.1)
  N
  0 134
  1 48
  2 31
  3 31
     
  Significant markers N = 0
Clinical variable #8: 'PATHOLOGY.M.STAGE'

291 genes related to 'PATHOLOGY.M.STAGE'.

Table S11.  Basic characteristics of clinical feature: 'PATHOLOGY.M.STAGE'

PATHOLOGY.M.STAGE Labels N
  M0 233
  M1 4
  M1A 2
  M1B 2
  M1C 5
     
  Significant markers N = 291
List of top 10 genes differentially expressed by 'PATHOLOGY.M.STAGE'

Table S12.  Get Full Table List of top 10 genes differentially expressed by 'PATHOLOGY.M.STAGE'

ANOVA_P Q
COL5A1 1.636e-33 3.22e-29
C10ORF88 9.973e-31 1.96e-26
FAM186A 1.187e-29 2.34e-25
LMF1 2.774e-29 5.46e-25
FGFR2 7.298e-27 1.44e-22
FRMD5 2.727e-25 5.37e-21
LOC728758 2.727e-25 5.37e-21
HSPA9 2.484e-22 4.89e-18
SNORD63 2.484e-22 4.89e-18
FAM186B 4.999e-22 9.84e-18

Figure S4.  Get High-res Image As an example, this figure shows the association of COL5A1 to 'PATHOLOGY.M.STAGE'. P value = 1.64e-33 with ANOVA analysis.

Clinical variable #9: 'MELANOMA.ULCERATION'

No gene related to 'MELANOMA.ULCERATION'.

Table S13.  Basic characteristics of clinical feature: 'MELANOMA.ULCERATION'

MELANOMA.ULCERATION Labels N
  NO 98
  YES 64
     
  Significant markers N = 0
Clinical variable #10: 'MELANOMA.PRIMARY.KNOWN'

27 genes related to 'MELANOMA.PRIMARY.KNOWN'.

Table S14.  Basic characteristics of clinical feature: 'MELANOMA.PRIMARY.KNOWN'

MELANOMA.PRIMARY.KNOWN Labels N
  NO 31
  YES 229
     
  Significant markers N = 27
  Higher in YES 25
  Higher in NO 2
List of top 10 genes differentially expressed by 'MELANOMA.PRIMARY.KNOWN'

Table S15.  Get Full Table List of top 10 genes differentially expressed by 'MELANOMA.PRIMARY.KNOWN'

T(pos if higher in 'YES') ttestP Q AUC
CMTM7 6.39 8.43e-10 1.66e-05 0.6642
CARD11 6.05 5.29e-09 0.000104 0.637
MIR564 5.83 1.73e-08 0.000341 0.583
TMEM42 5.83 1.73e-08 0.000341 0.583
MCL1 6.01 2.287e-08 0.00045 0.6615
NPAS3 5.75 5.231e-08 0.00103 0.5997
HPN__1 5.75 6.277e-08 0.00124 0.603
SETBP1 5.57 6.707e-08 0.00132 0.6252
ANKRD34A 5.43 1.341e-07 0.00264 0.667
KIAA0319 5.4 1.54e-07 0.00303 0.6232

Figure S5.  Get High-res Image As an example, this figure shows the association of CMTM7 to 'MELANOMA.PRIMARY.KNOWN'. P value = 8.43e-10 with T-test analysis.

Clinical variable #11: 'BRESLOW.THICKNESS'

3 genes related to 'BRESLOW.THICKNESS'.

Table S16.  Basic characteristics of clinical feature: 'BRESLOW.THICKNESS'

BRESLOW.THICKNESS Mean (SD) 3.58 (5.1)
  Significant markers N = 3
  pos. correlated 3
  neg. correlated 0
List of 3 genes significantly correlated to 'BRESLOW.THICKNESS' by Spearman correlation test

Table S17.  Get Full Table List of 3 genes significantly correlated to 'BRESLOW.THICKNESS' by Spearman correlation test

SpearmanCorr corrP Q
FAM100B 0.3415 1.254e-06 0.0247
ITSN2 0.3364 1.838e-06 0.0362
HMGA2 0.3335 2.271e-06 0.0447

Figure S6.  Get High-res Image As an example, this figure shows the association of FAM100B to 'BRESLOW.THICKNESS'. P value = 1.25e-06 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #12: 'GENDER'

One gene related to 'GENDER'.

Table S18.  Basic characteristics of clinical feature: 'GENDER'

GENDER Labels N
  FEMALE 101
  MALE 159
     
  Significant markers N = 1
  Higher in MALE 0
  Higher in FEMALE 1
List of one gene differentially expressed by 'GENDER'

Table S19.  Get Full Table List of one gene differentially expressed by 'GENDER'

T(pos if higher in 'MALE') ttestP Q AUC
KIF4B -5.54 1.015e-07 0.002 0.7098

Figure S7.  Get High-res Image As an example, this figure shows the association of KIF4B to 'GENDER'. P value = 1.01e-07 with T-test analysis.

Methods & Data
Input

  • Expresson data file = SKCM-TM.meth.by_min_clin_corr.data.txt

  • Clinical data file = SKCM-TM.merged_data.txt

  • Number of patients = 260

  • Number of genes = 19685

  • Number of clinical features = 12

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

In addition to the links below, the full results of the analysis summarized in this report can also be downloaded programmatically using firehose_get, or interactively from either the Broad GDAC website or TCGA Data Coordination Center Portal.

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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