Correlation between gene methylation status and clinical features
Lung Adenocarcinoma (Primary solid tumor)
23 September 2013  |  analyses__2013_09_23
Maintainer Information
Citation Information
doi:10.7908/C1NC5ZHZ
Maintained by Juok Cho (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2013): Correlation between gene methylation status and clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C1NC5ZHZ
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 20000 genes and 13 clinical features across 391 samples, statistically thresholded by Q value < 0.05, 11 clinical features related to at least one genes.

  • 23 genes correlated to 'Time to Death'.

    • LARP1 ,  PPP3CA ,  CD109 ,  CYFIP1 ,  LRBA ,  ...

  • 6 genes correlated to 'AGE'.

    • LOC148696 ,  KIAA1143 ,  KIF15 ,  CLEC5A ,  NHLRC1 ,  ...

  • 16 genes correlated to 'NEOPLASM.DISEASESTAGE'.

    • PAN2 ,  ZNF546 ,  MRPS14 ,  PRPF31 ,  TFPT ,  ...

  • 7 genes correlated to 'PATHOLOGY.T.STAGE'.

    • ACBD5 ,  TACC2 ,  PRDM15 ,  NME1-NME2 ,  NME2 ,  ...

  • 1 gene correlated to 'PATHOLOGY.N.STAGE'.

    • POLR2J3__1

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

    • PPP2R5B ,  C8ORF55 ,  HOMER3 ,  KILLIN ,  PTEN ,  ...

  • 119 genes correlated to 'GENDER'.

    • KIF4B ,  YARS2 ,  EIF4A1 ,  SNORA48 ,  FRG1B ,  ...

  • 101 genes correlated to 'HISTOLOGICAL.TYPE'.

    • DNAJC25-GNG10__1 ,  GNG10 ,  PDCD11 ,  USMG5 ,  MURC ,  ...

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

    • ZNF642 ,  HIST1H4J ,  FAM43A ,  PRELP ,  MGMT ,  ...

  • 2 genes correlated to 'NUMBERPACKYEARSSMOKED'.

    • FAM128A__1 ,  LOC150776__1

  • 110 genes correlated to 'COMPLETENESS.OF.RESECTION'.

    • DDX52 ,  CCDC53 ,  ANKIB1 ,  KRIT1 ,  SLC6A16 ,  ...

  • No genes correlated to 'KARNOFSKY.PERFORMANCE.SCORE', 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=23 shorter survival N=8 longer survival N=15
AGE Spearman correlation test N=6 older N=5 younger N=1
NEOPLASM DISEASESTAGE ANOVA test N=16        
PATHOLOGY T STAGE Spearman correlation test N=7 higher stage N=1 lower stage N=6
PATHOLOGY N STAGE Spearman correlation test N=1 higher stage N=0 lower stage N=1
PATHOLOGY M STAGE ANOVA test N=187        
GENDER t test N=119 male N=11 female N=108
KARNOFSKY PERFORMANCE SCORE Spearman correlation test   N=0        
HISTOLOGICAL TYPE ANOVA test N=101        
RADIATIONS RADIATION REGIMENINDICATION t test N=62 yes N=41 no N=21
NUMBERPACKYEARSSMOKED Spearman correlation test N=2 higher numberpackyearssmoked N=0 lower numberpackyearssmoked N=2
YEAROFTOBACCOSMOKINGONSET Spearman correlation test   N=0        
COMPLETENESS OF RESECTION ANOVA test N=110        
Clinical variable #1: 'Time to Death'

23 genes related to 'Time to Death'.

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

Time to Death Duration (Months) 0-224 (median=10.6)
  censored N = 263
  death N = 98
     
  Significant markers N = 23
  associated with shorter survival 8
  associated with longer survival 15
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
LARP1 0.01 1.107e-09 2.2e-05 0.332
PPP3CA 17 2.483e-08 5e-04 0.649
CD109 0.02 5.397e-08 0.0011 0.361
CYFIP1 0.01 5.759e-08 0.0012 0.346
LRBA 0 9.3e-08 0.0019 0.392
MAB21L2 0 9.3e-08 0.0019 0.392
TPP1 0 9.782e-08 0.002 0.359
MYOF 0.04 1.302e-07 0.0026 0.34
SLC12A6 0 1.607e-07 0.0032 0.365
ZFAND2A 0.03 1.831e-07 0.0037 0.359

Figure S1.  Get High-res Image As an example, this figure shows the association of LARP1 to 'Time to Death'. four curves present the cumulative survival rates of 4 quartile subsets of patients. P value = 1.11e-09 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) 65.18 (10)
  Significant markers N = 6
  pos. correlated 5
  neg. correlated 1
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
LOC148696 -0.2615 4.333e-07 0.00867
KIAA1143 0.2599 5.138e-07 0.0103
KIF15 0.2599 5.138e-07 0.0103
CLEC5A 0.2595 5.379e-07 0.0108
NHLRC1 0.2506 1.33e-06 0.0266
ZYG11A 0.2465 2.004e-06 0.0401

Figure S2.  Get High-res Image As an example, this figure shows the association of LOC148696 to 'AGE'. P value = 4.33e-07 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #3: 'NEOPLASM.DISEASESTAGE'

16 genes related to 'NEOPLASM.DISEASESTAGE'.

Table S5.  Basic characteristics of clinical feature: 'NEOPLASM.DISEASESTAGE'

NEOPLASM.DISEASESTAGE Labels N
  STAGE I 3
  STAGE IA 96
  STAGE IB 114
  STAGE IIA 40
  STAGE IIB 54
  STAGE IIIA 57
  STAGE IIIB 9
  STAGE IV 17
     
  Significant markers N = 16
List of top 10 genes differentially expressed by 'NEOPLASM.DISEASESTAGE'

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

ANOVA_P Q
PAN2 3.465e-12 6.93e-08
ZNF546 2.284e-10 4.57e-06
MRPS14 6.66e-10 1.33e-05
PRPF31 1.299e-09 2.6e-05
TFPT 1.299e-09 2.6e-05
ASNA1 4.099e-09 8.2e-05
PCSK4 4.338e-09 8.67e-05
REEP6__1 4.338e-09 8.67e-05
PAFAH1B3 6.41e-08 0.00128
PRR19 6.41e-08 0.00128

Figure S3.  Get High-res Image As an example, this figure shows the association of PAN2 to 'NEOPLASM.DISEASESTAGE'. P value = 3.46e-12 with ANOVA analysis.

Clinical variable #4: 'PATHOLOGY.T.STAGE'

7 genes related to 'PATHOLOGY.T.STAGE'.

Table S7.  Basic characteristics of clinical feature: 'PATHOLOGY.T.STAGE'

PATHOLOGY.T.STAGE Mean (SD) 1.85 (0.73)
  N
  1 123
  2 217
  3 33
  4 15
     
  Significant markers N = 7
  pos. correlated 1
  neg. correlated 6
List of 7 genes significantly correlated to 'PATHOLOGY.T.STAGE' by Spearman correlation test

Table S8.  Get Full Table List of 7 genes significantly correlated to 'PATHOLOGY.T.STAGE' by Spearman correlation test

SpearmanCorr corrP Q
ACBD5 -0.273 4.652e-08 0.00093
TACC2 -0.2639 1.331e-07 0.00266
PRDM15 0.2547 3.681e-07 0.00736
NME1-NME2 -0.2451 1.024e-06 0.0205
NME2 -0.2451 1.024e-06 0.0205
DDX21 -0.2428 1.3e-06 0.026
SLC41A3 -0.2414 1.495e-06 0.0299

Figure S4.  Get High-res Image As an example, this figure shows the association of ACBD5 to 'PATHOLOGY.T.STAGE'. P value = 4.65e-08 with Spearman correlation analysis.

Clinical variable #5: 'PATHOLOGY.N.STAGE'

One gene related to 'PATHOLOGY.N.STAGE'.

Table S9.  Basic characteristics of clinical feature: 'PATHOLOGY.N.STAGE'

PATHOLOGY.N.STAGE Mean (SD) 0.5 (0.76)
  N
  0 251
  1 71
  2 59
  3 1
     
  Significant markers N = 1
  pos. correlated 0
  neg. correlated 1
List of one gene significantly correlated to 'PATHOLOGY.N.STAGE' by Spearman correlation test

Table S10.  Get Full Table List of one gene significantly correlated to 'PATHOLOGY.N.STAGE' by Spearman correlation test

SpearmanCorr corrP Q
POLR2J3__1 -0.247 1.018e-06 0.0204

Figure S5.  Get High-res Image As an example, this figure shows the association of POLR2J3__1 to 'PATHOLOGY.N.STAGE'. P value = 1.02e-06 with Spearman correlation analysis.

Clinical variable #6: 'PATHOLOGY.M.STAGE'

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

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

PATHOLOGY.M.STAGE Labels N
  M0 256
  M1 12
  M1A 1
  M1B 3
  MX 115
     
  Significant markers N = 187
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
PPP2R5B 7.551e-83 1.51e-78
C8ORF55 1.605e-60 3.21e-56
HOMER3 7.691e-38 1.54e-33
KILLIN 1.296e-29 2.59e-25
PTEN 1.296e-29 2.59e-25
POLR2J2 2.633e-28 5.26e-24
FBXL19__1 4.857e-28 9.71e-24
NCRNA00095__1 4.857e-28 9.71e-24
ANKRD55 3.765e-25 7.53e-21
DEM1 5.068e-24 1.01e-19

Figure S6.  Get High-res Image As an example, this figure shows the association of PPP2R5B to 'PATHOLOGY.M.STAGE'. P value = 7.55e-83 with ANOVA analysis.

Clinical variable #7: 'GENDER'

119 genes related to 'GENDER'.

Table S13.  Basic characteristics of clinical feature: 'GENDER'

GENDER Labels N
  FEMALE 210
  MALE 181
     
  Significant markers N = 119
  Higher in MALE 11
  Higher in FEMALE 108
List of top 10 genes differentially expressed by 'GENDER'

Table S14.  Get Full Table List of top 10 genes differentially expressed by 'GENDER'

T(pos if higher in 'MALE') ttestP Q AUC
KIF4B -13.96 8.089e-36 1.62e-31 0.8452
YARS2 -12.78 4.484e-31 8.97e-27 0.8231
EIF4A1 -10.35 4.029e-22 8.06e-18 0.7893
SNORA48 -10.35 4.029e-22 8.06e-18 0.7893
FRG1B -9.22 2.925e-18 5.85e-14 0.7743
RNASEH2C 8.58 2.263e-16 4.52e-12 0.7188
COX7C -8.03 1.528e-14 3.06e-10 0.7321
CCDC121__1 -7.59 2.734e-13 5.47e-09 0.7024
GPN1__1 -7.59 2.734e-13 5.47e-09 0.7024
CCL13 -7.43 9.492e-13 1.9e-08 0.6988

Figure S7.  Get High-res Image As an example, this figure shows the association of KIF4B to 'GENDER'. P value = 8.09e-36 with T-test analysis.

Clinical variable #8: 'KARNOFSKY.PERFORMANCE.SCORE'

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

Table S15.  Basic characteristics of clinical feature: 'KARNOFSKY.PERFORMANCE.SCORE'

KARNOFSKY.PERFORMANCE.SCORE Mean (SD) 84.56 (22)
  Significant markers N = 0
Clinical variable #9: 'HISTOLOGICAL.TYPE'

101 genes related to 'HISTOLOGICAL.TYPE'.

Table S16.  Basic characteristics of clinical feature: 'HISTOLOGICAL.TYPE'

HISTOLOGICAL.TYPE Labels N
  LUNG ACINAR ADENOCARCINOMA 13
  LUNG ADENOCARCINOMA MIXED SUBTYPE 75
  LUNG ADENOCARCINOMA- NOT OTHERWISE SPECIFIED (NOS) 247
  LUNG BRONCHIOLOALVEOLAR CARCINOMA MUCINOUS 4
  LUNG BRONCHIOLOALVEOLAR CARCINOMA NONMUCINOUS 18
  LUNG CLEAR CELL ADENOCARCINOMA 1
  LUNG MICROPAPILLARY ADENOCARCINOMA 2
  LUNG MUCINOUS ADENOCARCINOMA 2
  LUNG PAPILLARY ADENOCARCINOMA 17
  LUNG SIGNET RING ADENOCARCINOMA 1
  LUNG SOLID PATTERN PREDOMINANT ADENOCARCINOMA 4
  MUCINOUS (COLLOID) CARCINOMA 7
     
  Significant markers N = 101
List of top 10 genes differentially expressed by 'HISTOLOGICAL.TYPE'

Table S17.  Get Full Table List of top 10 genes differentially expressed by 'HISTOLOGICAL.TYPE'

ANOVA_P Q
DNAJC25-GNG10__1 1.195e-38 2.39e-34
GNG10 1.195e-38 2.39e-34
PDCD11 5.151e-29 1.03e-24
USMG5 5.151e-29 1.03e-24
MURC 6.864e-28 1.37e-23
MED17 3.921e-27 7.84e-23
CCDC126 7.465e-22 1.49e-17
C8ORF42 5.763e-19 1.15e-14
HPS4 6.185e-19 1.24e-14
SRRD 6.185e-19 1.24e-14

Figure S8.  Get High-res Image As an example, this figure shows the association of DNAJC25-GNG10__1 to 'HISTOLOGICAL.TYPE'. P value = 1.2e-38 with ANOVA analysis.

Clinical variable #10: 'RADIATIONS.RADIATION.REGIMENINDICATION'

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

Table S18.  Basic characteristics of clinical feature: 'RADIATIONS.RADIATION.REGIMENINDICATION'

RADIATIONS.RADIATION.REGIMENINDICATION Labels N
  NO 17
  YES 374
     
  Significant markers N = 62
  Higher in YES 41
  Higher in NO 21
List of top 10 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

Table S19.  Get Full Table List of top 10 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

T(pos if higher in 'YES') ttestP Q AUC
ZNF642 6.75 6.279e-11 1.26e-06 0.6732
HIST1H4J 6.48 4.429e-10 8.86e-06 0.6538
FAM43A 6.57 8.622e-10 1.72e-05 0.5881
PRELP -6.31 1.289e-09 2.58e-05 0.6021
MGMT 6.19 1.49e-09 2.98e-05 0.6894
H2AFJ 6.21 1.732e-09 3.46e-05 0.5744
KIAA1529 6.15 2.248e-09 4.5e-05 0.6395
MUL1 6.08 3.431e-09 6.86e-05 0.5544
LMX1B 6.45 3.59e-09 7.18e-05 0.7051
PEBP1 6.02 4.721e-09 9.44e-05 0.6305

Figure S9.  Get High-res Image As an example, this figure shows the association of ZNF642 to 'RADIATIONS.RADIATION.REGIMENINDICATION'. P value = 6.28e-11 with T-test analysis.

Clinical variable #11: 'NUMBERPACKYEARSSMOKED'

2 genes related to 'NUMBERPACKYEARSSMOKED'.

Table S20.  Basic characteristics of clinical feature: 'NUMBERPACKYEARSSMOKED'

NUMBERPACKYEARSSMOKED Mean (SD) 40.97 (27)
  Significant markers N = 2
  pos. correlated 0
  neg. correlated 2
List of 2 genes significantly correlated to 'NUMBERPACKYEARSSMOKED' by Spearman correlation test

Table S21.  Get Full Table List of 2 genes significantly correlated to 'NUMBERPACKYEARSSMOKED' by Spearman correlation test

SpearmanCorr corrP Q
FAM128A__1 -0.3105 1.904e-07 0.00381
LOC150776__1 -0.3105 1.904e-07 0.00381

Figure S10.  Get High-res Image As an example, this figure shows the association of FAM128A__1 to 'NUMBERPACKYEARSSMOKED'. P value = 1.9e-07 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #12: 'YEAROFTOBACCOSMOKINGONSET'

No gene related to 'YEAROFTOBACCOSMOKINGONSET'.

Table S22.  Basic characteristics of clinical feature: 'YEAROFTOBACCOSMOKINGONSET'

YEAROFTOBACCOSMOKINGONSET Mean (SD) 1965.3 (12)
  Significant markers N = 0
Clinical variable #13: 'COMPLETENESS.OF.RESECTION'

110 genes related to 'COMPLETENESS.OF.RESECTION'.

Table S23.  Basic characteristics of clinical feature: 'COMPLETENESS.OF.RESECTION'

COMPLETENESS.OF.RESECTION Labels N
  R0 256
  R1 8
  R2 1
  RX 15
     
  Significant markers N = 110
List of top 10 genes differentially expressed by 'COMPLETENESS.OF.RESECTION'

Table S24.  Get Full Table List of top 10 genes differentially expressed by 'COMPLETENESS.OF.RESECTION'

ANOVA_P Q
DDX52 7.9e-182 1.58e-177
CCDC53 6.01e-139 1.2e-134
ANKIB1 3.184e-85 6.37e-81
KRIT1 3.184e-85 6.37e-81
SLC6A16 2.657e-56 5.31e-52
CWC22 4.416e-54 8.83e-50
ZBTB1 5.824e-53 1.16e-48
ZBTB25 5.824e-53 1.16e-48
HARBI1 4.309e-44 8.61e-40
KIAA0652__1 4.309e-44 8.61e-40

Figure S11.  Get High-res Image As an example, this figure shows the association of DDX52 to 'COMPLETENESS.OF.RESECTION'. P value = 7.9e-182 with ANOVA analysis.

Methods & Data
Input

  • Expresson data file = LUAD-TP.meth.by_min_expr_corr.data.txt

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

  • Number of patients = 391

  • Number of genes = 20000

  • 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

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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