PANCANCER cohort with 12 disease types: 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 15521 genes and 13 clinical features across 238 samples, statistically thresholded by Q value < 0.05, 6 clinical features related to at least one genes.

- 21 genes correlated to 'Time to Death'.

- LGALS4 , ALG3 , TEX101 , VIL1 , PPY2 , ...

- 6 genes correlated to 'AGE'.

- FAM123C , C7ORF13 , KIF15 , TSPYL5 , BOC , ...

- 5146 genes correlated to 'PRIMARY.SITE.OF.DISEASE'.

- ZNF416 , BBS10 , AGK , SYNGR1 , HERPUD2 , ...

- 332 genes correlated to 'GENDER'.

- CDKL2 , ZNF295 , UTP14C , GLIPR1L1 , TBC1D24 , ...

- 2406 genes correlated to 'HISTOLOGICAL.TYPE'.

- ZNF419 , INSM2 , INHA , BBS10 , NDNL2 , ...

- 19 genes correlated to 'RADIATIONS.RADIATION.REGIMENINDICATION'.

- DEPDC4 , ZFAND6 , SLC39A5 , SMAD4 , PIP4K2C , ...

- No genes correlated to 'PATHOLOGY.T', 'PATHOLOGY.N', 'TUMOR.STAGE', 'NUMBERPACKYEARSSMOKED', 'STOPPEDSMOKINGYEAR', 'TOBACCOSMOKINGHISTORYINDICATOR', and 'YEAROFTOBACCOSMOKINGONSET'.

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=21 | shorter survival | N=0 | longer survival | N=21
AGE | Spearman correlation test | N=6 | older | N=6 | younger | N=0
PRIMARY SITE OF DISEASE | ANOVA test | N=5146 |  |  |  |
GENDER | t test | N=332 | male | N=66 | female | N=266
HISTOLOGICAL TYPE | ANOVA test | N=2406 |  |  |  |
PATHOLOGY T | Spearman correlation test | N=0 |  |  |  |
PATHOLOGY N | Spearman correlation test | N=0 |  |  |  |
TUMOR STAGE | Spearman correlation test | N=0 |  |  |  |
RADIATIONS RADIATION REGIMENINDICATION | t test | N=19 | yes | N=6 | no | N=13
NUMBERPACKYEARSSMOKED | Spearman correlation test | N=0 |  |  |  |
STOPPEDSMOKINGYEAR | Spearman correlation test | N=0 |  |  |  |
TOBACCOSMOKINGHISTORYINDICATOR | ANOVA test | N=0 |  |  |  |
YEAROFTOBACCOSMOKINGONSET | Spearman correlation test | N=0 |  |  |  |

Clinical variable #1: 'Time to Death'

21 genes related to 'Time to Death'.

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

Time to Death | Duration (Months) | 0.1-223.4 (median=29.1)
| censored | N = 194
| death | N = 40
| Significant markers | N = 21
| associated with shorter survival | 0
| associated with longer survival | 21

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
--- | --- | --- | --- | ---
LGALS4 | 0 | 1.372e-08 | 0.00021 | 0.269
ALG3 | 0 | 8.947e-08 | 0.0014 | 0.263
TEX101 | 0 | 8.948e-08 | 0.0014 | 0.32
VIL1 | 0.01 | 1.447e-07 | 0.0022 | 0.337
PPY2 | 0 | 1.611e-07 | 0.0025 | 0.342
APOC2 | 0.01 | 1.989e-07 | 0.0031 | 0.341
TNNT2 | 0 | 2.96e-07 | 0.0046 | 0.335
PTGDS | 0 | 4.373e-07 | 0.0068 | 0.342
ADCK5 | 0 | 4.438e-07 | 0.0069 | 0.331
PTP4A3 | 0 | 4.442e-07 | 0.0069 | 0.338

Figure S1. Get High-res Image As an example, this figure shows the association of LGALS4 to 'Time to Death'. four curves present the cumulative survival rates of 4 quartile subsets of patients. P value = 1.37e-08 with univariate Cox regression analysis using continuous log-2 expression values.

Clinical variable #2: 'AGE'

6 genes related to 'AGE'.

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

AGE | Mean (SD) | 56.59 (13)
| Significant markers | N = 6
| pos. correlated | 6
| neg. correlated | 0

List of 6 genes significantly correlated to 'AGE' by Spearman correlation test

Table S4. Get Full Table List of 6 genes significantly correlated to 'AGE' by Spearman correlation test

| SpearmanCorr | corrP | Q
--- | --- | --- | ---
FAM123C | 0.33 | 2.11e-07 | 0.00328
C7ORF13 | 0.3178 | 6.151e-07 | 0.00955
KIF15 | 0.315 | 7.841e-07 | 0.0122
TSPYL5 | 0.3113 | 1.067e-06 | 0.0166
BOC | 0.3111 | 1.089e-06 | 0.0169
HNRNPC | 0.3012 | 2.707e-06 | 0.042

Figure S2. Get High-res Image As an example, this figure shows the association of FAM123C to 'AGE'. P value = 2.11e-07 with Spearman correlation analysis. The straight line presents the best linear regression.

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

5146 genes related to 'PRIMARY.SITE.OF.DISEASE'.

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

PRIMARY.SITE.OF.DISEASE | Labels | N
| BREAST | 214
| COLON | 1
| KIDNEY | 2
| LUNG | 20
| RECTUM | 1
| Significant markers | N = 5146

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
--- | --- | ---
ZNF416 | 1.01e-243 | 1.57e-239
BBS10 | 1.016e-224 | 1.58e-220
AGK | 1.598e-223 | 2.48e-219
SYNGR1 | 1.037e-214 | 1.61e-210
HERPUD2 | 3.057e-209 | 4.74e-205
C20ORF194 | 1.437e-195 | 2.23e-191
PARD6G | 5.208e-188 | 8.08e-184
RAB6B | 1.442e-165 | 2.24e-161
MEIS3 | 5.212e-161 | 8.09e-157
RDX | 8.948e-156 | 1.39e-151

Figure S3. Get High-res Image As an example, this figure shows the association of ZNF416 to 'PRIMARY.SITE.OF.DISEASE'. P value = 1.01e-243 with ANOVA analysis.

Clinical variable #4: 'GENDER'

332 genes related to 'GENDER'.

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

GENDER | Labels | N
| FEMALE | 222
| MALE | 16
| Significant markers | N = 332
| Higher in MALE | 66
| Higher in FEMALE | 266

List of top 10 genes differentially expressed by 'GENDER'

Table S8. Get Full Table List of top 10 genes differentially expressed by 'GENDER'

| T(pos if higher in 'MALE') | ttestP | Q | AUC
--- | --- | --- | --- | ---
CDKL2 | -16.25 | 2.559e-40 | 3.97e-36 | 0.8705
ZNF295 | -13.25 | 5.311e-28 | 8.24e-24 | 0.8756
UTP14C | 18.1 | 3.502e-26 | 5.44e-22 | 0.9428
GLIPR1L1 | -10.29 | 1.166e-20 | 1.81e-16 | 0.877
TBC1D24 | 11.6 | 5.696e-20 | 8.84e-16 | 0.8694
SLC35E2 | 10.08 | 7.628e-20 | 1.18e-15 | 0.6765
LRIG3 | -9.83 | 2.76e-19 | 4.28e-15 | 0.8218
IRF9 | 11.24 | 4.911e-19 | 7.62e-15 | 0.8156
TMED3 | 10.44 | 1.72e-18 | 2.67e-14 | 0.7897
BAT2 | 10.82 | 2.581e-18 | 4e-14 | 0.8528

Figure S4. Get High-res Image As an example, this figure shows the association of CDKL2 to 'GENDER'. P value = 2.56e-40 with T-test analysis.

Clinical variable #5: 'HISTOLOGICAL.TYPE'

2406 genes related to 'HISTOLOGICAL.TYPE'.

Table S9. Basic characteristics of clinical feature: 'HISTOLOGICAL.TYPE'

HISTOLOGICAL.TYPE | Labels | N
| COLON ADENOCARCINOMA | 1
| KIDNEY CLEAR CELL RENAL CARCINOMA | 2
| LUNG BASALOID SQUAMOUS CELL CARCINOMA | 2
| LUNG SQUAMOUS CELL CARCINOMA- NOT OTHERWISE SPECIFIED (NOS) | 18
| RECTAL ADENOCARCINOMA | 1
| Significant markers | N = 2406

List of top 10 genes differentially expressed by 'HISTOLOGICAL.TYPE'

Table S10. Get Full Table List of top 10 genes differentially expressed by 'HISTOLOGICAL.TYPE'

| ANOVA_P | Q
--- | --- | ---
ZNF419 | 2.704e-42 | 4.2e-38
INSM2 | 8.355e-40 | 1.3e-35
INHA | 8.637e-39 | 1.34e-34
BBS10 | 3.063e-38 | 4.75e-34
NDNL2 | 1.319e-37 | 2.05e-33
MED12L | 2.544e-37 | 3.95e-33
EPM2AIP1 | 3.466e-37 | 5.38e-33
P2RX5 | 1.154e-36 | 1.79e-32
C1QL1 | 1.459e-36 | 2.26e-32
TMEM64 | 3.167e-36 | 4.91e-32

Figure S5. Get High-res Image As an example, this figure shows the association of ZNF419 to 'HISTOLOGICAL.TYPE'. P value = 2.7e-42 with ANOVA analysis.

Clinical variable #6: 'PATHOLOGY.T'

No gene related to 'PATHOLOGY.T'.

Table S11. Basic characteristics of clinical feature: 'PATHOLOGY.T'

PATHOLOGY.T | Mean (SD) | 1.96 (0.86)
|  | N
| T1 | 7
| T2 | 13
| T3 | 2
| T4 | 2
| Significant markers | N = 0

Clinical variable #7: 'PATHOLOGY.N'

No gene related to 'PATHOLOGY.N'.

Table S12. Basic characteristics of clinical feature: 'PATHOLOGY.N'

PATHOLOGY.N | Mean (SD) | 0.5 (0.67)
|  | N
| N0 | 13
| N1 | 7
| N2 | 2
| Significant markers | N = 0

Clinical variable #8: 'TUMOR.STAGE'

No gene related to 'TUMOR.STAGE'.

Table S13. Basic characteristics of clinical feature: 'TUMOR.STAGE'

TUMOR.STAGE | Mean (SD) | 1.79 (0.88)
|  | N
| Stage 1 | 11
| Stage 2 | 8
| Stage 3 | 4
| Stage 4 | 1
| Significant markers | N = 0

Clinical variable #9: 'RADIATIONS.RADIATION.REGIMENINDICATION'

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

Table S14. Basic characteristics of clinical feature: 'RADIATIONS.RADIATION.REGIMENINDICATION'

RADIATIONS.RADIATION.REGIMENINDICATION | Labels | N
| NO | 79
| YES | 159
| Significant markers | N = 19
| Higher in YES | 6
| Higher in NO | 13

List of top 10 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

Table S15. Get Full Table List of top 10 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

| T(pos if higher in 'YES') | ttestP | Q | AUC
--- | --- | --- | --- | ---
DEPDC4 | -5.99 | 1.358e-08 | 0.000211 | 0.7293
ZFAND6 | -5.99 | 1.44e-08 | 0.000223 | 0.746
SLC39A5 | -5.4 | 1.79e-07 | 0.00278 | 0.6896
SMAD4 | -5.4 | 2.379e-07 | 0.00369 | 0.7004
PIP4K2C | -5.34 | 2.914e-07 | 0.00452 | 0.7163
BNIP2 | -5.32 | 3.194e-07 | 0.00496 | 0.6945
C18ORF8 | -5.23 | 5.995e-07 | 0.0093 | 0.7098
SBK1 | -5.16 | 6.828e-07 | 0.0106 | 0.6853
CDC27 | -5.11 | 9.06e-07 | 0.0141 | 0.6959
LCAT | -5 | 1.247e-06 | 0.0193 | 0.6848

Figure S6. Get High-res Image As an example, this figure shows the association of DEPDC4 to 'RADIATIONS.RADIATION.REGIMENINDICATION'. P value = 1.36e-08 with T-test analysis.

Clinical variable #10: 'NUMBERPACKYEARSSMOKED'

No gene related to 'NUMBERPACKYEARSSMOKED'.

Table S16. Basic characteristics of clinical feature: 'NUMBERPACKYEARSSMOKED'

NUMBERPACKYEARSSMOKED | Mean (SD) | 54.79 (42)
| Significant markers | N = 0

Clinical variable #11: 'STOPPEDSMOKINGYEAR'

No gene related to 'STOPPEDSMOKINGYEAR'.

Table S17. Basic characteristics of clinical feature: 'STOPPEDSMOKINGYEAR'

STOPPEDSMOKINGYEAR | Mean (SD) | 1995.54 (11)
| Significant markers | N = 0

Clinical variable #12: 'TOBACCOSMOKINGHISTORYINDICATOR'

No gene related to 'TOBACCOSMOKINGHISTORYINDICATOR'.

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

TOBACCOSMOKINGHISTORYINDICATOR | Labels | N
| CURRENT REFORMED SMOKER FOR < OR = 15 YEARS | 7
| CURRENT REFORMED SMOKER FOR > 15 YEARS | 6
| CURRENT SMOKER | 7
| Significant markers | N = 0

Clinical variable #13: 'YEAROFTOBACCOSMOKINGONSET'

No gene related to 'YEAROFTOBACCOSMOKINGONSET'.

Table S19. Basic characteristics of clinical feature: 'YEAROFTOBACCOSMOKINGONSET'

YEAROFTOBACCOSMOKINGONSET | Mean (SD) | 1956.38 (6.9)
| Significant markers | N = 0

Methods & Data
Input

- Expresson data file = PANCAN12-TP.meth.for_correlation.filtered_data.txt

- Clinical data file = PANCAN12-TP.clin.merged.picked.txt

- Number of patients = 238

- Number of genes = 15521

- Number of clinical features = 13

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.

- Analysis Results (MD5 checksum)

- Auxiliary Data (MD5 checksum)

- MAGE-TAB File (MD5 checksum)

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)
Copyright © 2013 Broad Institute TCGA GDAC as part of the TCGA Research Network. All rights reserved.
Made with Nozzle