Kidney Renal Clear Cell Carcinoma: Correlation between gene methylation status and clinical features
(primary solid tumor 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 17337 genes and 8 clinical features across 272 samples, statistically thresholded by Q value < 0.05, 7 clinical features related to at least one genes.

  • 480 genes correlated to 'Time to Death'.

    • FLJ42289 ,  TLL2 ,  RIOK3 ,  RPRD2 ,  ARHGEF12 ,  ...

  • 15 genes correlated to 'AGE'.

    • ELOVL2 ,  ME3 ,  MRPS33 ,  DOK6 ,  TSPYL5 ,  ...

  • 69 genes correlated to 'GENDER'.

    • UTP14C ,  KIF4B ,  CCDC146 ,  UQCRH ,  CAV2 ,  ...

  • 808 genes correlated to 'PATHOLOGY.T'.

    • KDR ,  CLEC2L ,  OPRK1 ,  ACTA1 ,  SYN2 ,  ...

  • 9 genes correlated to 'PATHOLOGY.N'.

    • CARD16 ,  CASP1 ,  SFXN5 ,  VGF ,  ZFP64 ,  ...

  • 68 genes correlated to 'PATHOLOGICSPREAD(M)'.

    • C20ORF112 ,  OPRK1 ,  HTR6 ,  PLCD1 ,  NBLA00301 ,  ...

  • 884 genes correlated to 'TUMOR.STAGE'.

    • KDR ,  UTF1 ,  LOC645323 ,  OPRK1 ,  CLEC2L ,  ...

  • No genes correlated to 'KARNOFSKY.PERFORMANCE.SCORE'

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=480 shorter survival N=293 longer survival N=187
AGE Spearman correlation test N=15 older N=12 younger N=3
GENDER t test N=69 male N=7 female N=62
KARNOFSKY PERFORMANCE SCORE Spearman correlation test   N=0        
PATHOLOGY T Spearman correlation test N=808 higher pT N=399 lower pT N=409
PATHOLOGY N t test N=9 n1 N=2 n0 N=7
PATHOLOGICSPREAD(M) t test N=68 m1 N=62 m0 N=6
TUMOR STAGE Spearman correlation test N=884 higher stage N=559 lower stage N=325
Clinical variable #1: 'Time to Death'

480 genes related to 'Time to Death'.

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

Time to Death Duration (Months) 0.1-109.6 (median=27.9)
  censored N = 177
  death N = 92
     
  Significant markers N = 480
  associated with shorter survival 293
  associated with longer survival 187
List of top 10 genes significantly associated with 'Time to Death' by Cox regression test

Table S2.  Get Full Table List of top 10 genes significantly associated with 'Time to Death' by Cox regression test

HazardRatio Wald_P Q C_index
FLJ42289 0.03 1.837e-12 3.2e-08 0.304
TLL2 0.02 4.808e-12 8.3e-08 0.314
RIOK3 7501 1.987e-11 3.4e-07 0.668
RPRD2 54 2.331e-11 4e-07 0.681
ARHGEF12 44 2.398e-11 4.2e-07 0.642
GRIN2D 0 3.355e-11 5.8e-07 0.32
IGLL1 0.01 7.656e-11 1.3e-06 0.311
MBNL2 28 1.233e-10 2.1e-06 0.672
PLCB3 0 1.283e-10 2.2e-06 0.379
PCCA 51 1.561e-10 2.7e-06 0.66

Figure S1.  Get High-res Image As an example, this figure shows the association of FLJ42289 to 'Time to Death'. four curves present the cumulative survival rates of 4 quartile subsets of patients. P value = 1.84e-12 with univariate Cox regression analysis using continuous log-2 expression values.

Clinical variable #2: 'AGE'

15 genes related to 'AGE'.

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

AGE Mean (SD) 61.34 (12)
  Significant markers N = 15
  pos. correlated 12
  neg. correlated 3
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
ELOVL2 0.4681 3.221e-16 5.58e-12
ME3 -0.3185 7.937e-08 0.00138
MRPS33 0.3184 7.954e-08 0.00138
DOK6 0.3171 9.071e-08 0.00157
TSPYL5 0.3157 1.041e-07 0.0018
ADAMTS17 0.3108 1.67e-07 0.00289
RANBP17 0.3048 2.966e-07 0.00514
ZYG11A 0.3047 2.99e-07 0.00518
PVT1 -0.3018 3.907e-07 0.00677
LYSMD2 -0.2976 5.769e-07 0.01

Figure S2.  Get High-res Image As an example, this figure shows the association of ELOVL2 to 'AGE'. P value = 3.22e-16 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #3: 'GENDER'

69 genes related to 'GENDER'.

Table S5.  Basic characteristics of clinical feature: 'GENDER'

GENDER Labels N
  FEMALE 93
  MALE 179
     
  Significant markers N = 69
  Higher in MALE 7
  Higher in FEMALE 62
List of top 10 genes differentially expressed by 'GENDER'

Table S6.  Get Full Table List of top 10 genes differentially expressed by 'GENDER'

T(pos if higher in 'MALE') ttestP Q AUC
UTP14C 17.67 7.204e-34 1.25e-29 0.9717
KIF4B -11.84 5.539e-25 9.6e-21 0.8806
CCDC146 -10.57 5.83e-22 1.01e-17 0.8016
UQCRH 10.04 1.417e-19 2.46e-15 0.7614
CAV2 -9.94 1.455e-19 2.52e-15 0.8024
DNAJB13 -9.66 4.784e-19 8.29e-15 0.7821
C5ORF27 -9.64 2.049e-18 3.55e-14 0.8035
TLE1 -9.45 3.198e-17 5.54e-13 0.8072
NICN1 -9.2 5.664e-17 9.82e-13 0.8059
COX7C -8.77 8.392e-15 1.45e-10 0.809

Figure S3.  Get High-res Image As an example, this figure shows the association of UTP14C to 'GENDER'. P value = 7.2e-34 with T-test analysis.

Clinical variable #4: 'KARNOFSKY.PERFORMANCE.SCORE'

No gene related to 'KARNOFSKY.PERFORMANCE.SCORE'.

Table S7.  Basic characteristics of clinical feature: 'KARNOFSKY.PERFORMANCE.SCORE'

KARNOFSKY.PERFORMANCE.SCORE Mean (SD) 92.59 (8.1)
  Score N
  70 1
  80 3
  90 11
  100 12
     
  Significant markers N = 0
Clinical variable #5: 'PATHOLOGY.T'

808 genes related to 'PATHOLOGY.T'.

Table S8.  Basic characteristics of clinical feature: 'PATHOLOGY.T'

PATHOLOGY.T Mean (SD) 1.96 (0.98)
  N
  T1 128
  T2 34
  T3 102
  T4 8
     
  Significant markers N = 808
  pos. correlated 399
  neg. correlated 409
List of top 10 genes significantly correlated to 'PATHOLOGY.T' by Spearman correlation test

Table S9.  Get Full Table List of top 10 genes significantly correlated to 'PATHOLOGY.T' by Spearman correlation test

SpearmanCorr corrP Q
KDR 0.5042 6.031e-19 1.05e-14
CLEC2L 0.4782 6.046e-17 1.05e-12
OPRK1 0.4675 3.548e-16 6.15e-12
ACTA1 0.4589 1.436e-15 2.49e-11
SYN2 0.4447 1.292e-14 2.24e-10
NEUROD2 0.4434 1.581e-14 2.74e-10
AVPR1A 0.4427 1.759e-14 3.05e-10
UTF1 0.4407 2.363e-14 4.1e-10
LOC645323 0.4489 2.413e-14 4.18e-10
SLC35F1 0.4393 2.929e-14 5.08e-10

Figure S4.  Get High-res Image As an example, this figure shows the association of KDR to 'PATHOLOGY.T'. P value = 6.03e-19 with Spearman correlation analysis.

Clinical variable #6: 'PATHOLOGY.N'

9 genes related to 'PATHOLOGY.N'.

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

PATHOLOGY.N Labels N
  N0 122
  N1 9
     
  Significant markers N = 9
  Higher in N1 2
  Higher in N0 7
List of 9 genes differentially expressed by 'PATHOLOGY.N'

Table S11.  Get Full Table List of 9 genes differentially expressed by 'PATHOLOGY.N'

T(pos if higher in 'N1') ttestP Q AUC
CARD16 -6.43 6.705e-09 0.000116 0.6648
CASP1 -6.43 6.705e-09 0.000116 0.6648
SFXN5 -6.15 4.185e-07 0.00725 0.7049
VGF -5.23 6.713e-07 0.0116 0.6594
ZFP64 -5.25 6.953e-07 0.0121 0.6266
CYP27C1 5.19 1.082e-06 0.0188 0.6803
TSPO -5.37 1.108e-06 0.0192 0.6266
PLAG1 -4.97 2.112e-06 0.0366 0.7696
LOC150568 5.4 2.289e-06 0.0397 0.742

Figure S5.  Get High-res Image As an example, this figure shows the association of CARD16 to 'PATHOLOGY.N'. P value = 6.71e-09 with T-test analysis.

Clinical variable #7: 'PATHOLOGICSPREAD(M)'

68 genes related to 'PATHOLOGICSPREAD(M)'.

Table S12.  Basic characteristics of clinical feature: 'PATHOLOGICSPREAD(M)'

PATHOLOGICSPREAD(M) Labels N
  M0 221
  M1 51
     
  Significant markers N = 68
  Higher in M1 62
  Higher in M0 6
List of top 10 genes differentially expressed by 'PATHOLOGICSPREAD(M)'

Table S13.  Get Full Table List of top 10 genes differentially expressed by 'PATHOLOGICSPREAD(M)'

T(pos if higher in 'M1') ttestP Q AUC
C20ORF112 7.56 3.47e-12 6.02e-08 0.7674
OPRK1 7.56 2.711e-11 4.7e-07 0.769
HTR6 7.33 1.327e-10 2.3e-06 0.773
PLCD1 6.64 3.601e-10 6.24e-06 0.7151
NBLA00301 6.47 4.007e-09 6.94e-05 0.726
MUSK 6.27 4.755e-09 8.24e-05 0.7137
SESN1 6.25 4.926e-09 8.54e-05 0.7077
PDGFB 6.14 7.019e-09 0.000122 0.7197
STK24 6.35 7.347e-09 0.000127 0.7532
ASB4 6.08 1.011e-08 0.000175 0.694

Figure S6.  Get High-res Image As an example, this figure shows the association of C20ORF112 to 'PATHOLOGICSPREAD(M)'. P value = 3.47e-12 with T-test analysis.

Clinical variable #8: 'TUMOR.STAGE'

884 genes related to 'TUMOR.STAGE'.

Table S14.  Basic characteristics of clinical feature: 'TUMOR.STAGE'

TUMOR.STAGE Mean (SD) 2.2 (1.2)
  N
  Stage 1 126
  Stage 2 22
  Stage 3 68
  Stage 4 56
     
  Significant markers N = 884
  pos. correlated 559
  neg. correlated 325
List of top 10 genes significantly correlated to 'TUMOR.STAGE' by Spearman correlation test

Table S15.  Get Full Table List of top 10 genes significantly correlated to 'TUMOR.STAGE' by Spearman correlation test

SpearmanCorr corrP Q
KDR 0.5281 6.164e-21 1.07e-16
UTF1 0.4971 2.218e-18 3.84e-14
LOC645323 0.5017 4.807e-18 8.33e-14
OPRK1 0.4921 5.436e-18 9.42e-14
CLEC2L 0.4888 9.614e-18 1.67e-13
ACTA1 0.4879 1.125e-17 1.95e-13
NEUROD2 0.4833 2.516e-17 4.36e-13
SYN2 0.4751 1.016e-16 1.76e-12
AVPR1A 0.468 3.259e-16 5.65e-12
FAM38B 0.4676 3.507e-16 6.08e-12

Figure S7.  Get High-res Image As an example, this figure shows the association of KDR to 'TUMOR.STAGE'. P value = 6.16e-21 with Spearman correlation analysis.

Methods & Data
Input

  • Expresson data file = KIRC-TP.meth.for_correlation.filtered_data.txt

  • Clinical data file = KIRC-TP.clin.merged.picked.txt

  • Number of patients = 272

  • Number of genes = 17337

  • 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

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] Lehmann and Romano, Testing Statistical Hypotheses (3E ed.), New York: Springer. ISBN 0387988645 (2005)
[4] 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)
Copyright © 2013 Broad Institute TCGA GDAC as part of the TCGA Research Network. All rights reserved.
Made with Nozzle