Lung Adenocarcinoma: 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 17375 genes and 14 clinical features across 263 samples, statistically thresholded by Q value < 0.05, 13 clinical features related to at least one genes.

  • 19 genes correlated to 'Time to Death'.

    • FUT1 ,  MARVELD1 ,  LOC650368 ,  LARP1 ,  RRAGD ,  ...

  • 2 genes correlated to 'AGE'.

    • ACN9 ,  KIF15

  • 49 genes correlated to 'GENDER'.

    • CCNYL1 ,  KIF4B ,  EIF4A1 ,  RNASEH2C ,  GPN1 ,  ...

  • 1 gene correlated to 'KARNOFSKY.PERFORMANCE.SCORE'.

    • KRT72

  • 89 genes correlated to 'HISTOLOGICAL.TYPE'.

    • USMG5 ,  GOPC ,  MURC ,  GNG10 ,  KRT39 ,  ...

  • 1 gene correlated to 'PATHOLOGY.T'.

    • KCNK12

  • 1 gene correlated to 'PATHOLOGY.N'.

    • VAMP1

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

    • POLR2J2 ,  B3GNT2 ,  MSRA ,  HOMER3 ,  METTL11A ,  ...

  • 2 genes correlated to 'TUMOR.STAGE'.

    • VAMP1 ,  ANK3

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

    • ZNF642 ,  SLCO4C1 ,  PRELP ,  MAT2B ,  TRAPPC5 ,  ...

  • 28 genes correlated to 'TOBACCOSMOKINGHISTORYINDICATOR'.

    • SRM ,  GIT1 ,  NME2 ,  SNHG1 ,  RPS8 ,  ...

  • 1 gene correlated to 'YEAROFTOBACCOSMOKINGONSET'.

    • MYH14

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

    • DDX52 ,  MAN2A1 ,  CCDC53 ,  AFF1 ,  ZNF619 ,  ...

  • No genes correlated to 'NUMBERPACKYEARSSMOKED'

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=19 shorter survival N=7 longer survival N=12
AGE Spearman correlation test N=2 older N=2 younger N=0
GENDER t test N=49 male N=5 female N=44
KARNOFSKY PERFORMANCE SCORE Spearman correlation test N=1 higher score N=1 lower score N=0
HISTOLOGICAL TYPE ANOVA test N=89        
PATHOLOGY T Spearman correlation test N=1 higher pT N=1 lower pT N=0
PATHOLOGY N Spearman correlation test N=1 higher pN N=1 lower pN N=0
PATHOLOGICSPREAD(M) ANOVA test N=224        
TUMOR STAGE Spearman correlation test N=2 higher stage N=1 lower stage N=1
RADIATIONS RADIATION REGIMENINDICATION t test N=14 yes N=10 no N=4
NUMBERPACKYEARSSMOKED Spearman correlation test   N=0        
TOBACCOSMOKINGHISTORYINDICATOR ANOVA test N=28        
YEAROFTOBACCOSMOKINGONSET Spearman correlation test N=1 higher yearoftobaccosmokingonset N=1 lower yearoftobaccosmokingonset N=0
COMPLETENESS OF RESECTION ANOVA test N=106        
Clinical variable #1: 'Time to Death'

19 genes related to 'Time to Death'.

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

Time to Death Duration (Months) 0-224 (median=8.4)
  censored N = 174
  death N = 59
     
  Significant markers N = 19
  associated with shorter survival 7
  associated with longer survival 12
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
FUT1 12001 1.269e-08 0.00022 0.672
MARVELD1 0 1.529e-08 0.00027 0.324
LOC650368 0 4.173e-08 0.00072 0.339
LARP1 0 6.358e-08 0.0011 0.295
RRAGD 241 2.171e-07 0.0038 0.634
APOBEC4 0 3.365e-07 0.0058 0.382
IBSP 0 5.108e-07 0.0089 0.375
ZNF117 0 5.702e-07 0.0099 0.392
MAP7D1 0 9.255e-07 0.016 0.41
DPH2 140001 1.447e-06 0.025 0.563

Figure S1.  Get High-res Image As an example, this figure shows the association of FUT1 to 'Time to Death'. four curves present the cumulative survival rates of 4 quartile subsets of patients. P value = 1.27e-08 with univariate Cox regression analysis using continuous log-2 expression values.

Clinical variable #2: 'AGE'

2 genes related to 'AGE'.

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

AGE Mean (SD) 65.34 (9.9)
  Significant markers N = 2
  pos. correlated 2
  neg. correlated 0
List of 2 genes significantly correlated to 'AGE' by Spearman correlation test

Table S4.  Get Full Table List of 2 genes significantly correlated to 'AGE' by Spearman correlation test

SpearmanCorr corrP Q
ACN9 0.3045 2.066e-06 0.0359
KIF15 0.3021 2.387e-06 0.0415

Figure S2.  Get High-res Image As an example, this figure shows the association of ACN9 to 'AGE'. P value = 2.07e-06 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #3: 'GENDER'

49 genes related to 'GENDER'.

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

GENDER Labels N
  FEMALE 143
  MALE 120
     
  Significant markers N = 49
  Higher in MALE 5
  Higher in FEMALE 44
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
CCNYL1 -21.89 4.347e-57 7.55e-53 0.9524
KIF4B -12.13 7.838e-27 1.36e-22 0.8591
EIF4A1 -8.51 2.563e-15 4.45e-11 0.7906
RNASEH2C 8.06 2.851e-14 4.95e-10 0.7512
GPN1 -7.17 1.107e-11 1.92e-07 0.7272
FRG1B -6.84 6.513e-11 1.13e-06 0.7513
SPESP1 -6.47 6.527e-10 1.13e-05 0.7106
ZNF839 -6.41 6.917e-10 1.2e-05 0.7186
ATP5J 6.48 1.092e-09 1.9e-05 0.7308
GABPA 6.48 1.092e-09 1.9e-05 0.7308

Figure S3.  Get High-res Image As an example, this figure shows the association of CCNYL1 to 'GENDER'. P value = 4.35e-57 with T-test analysis.

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

One gene related to 'KARNOFSKY.PERFORMANCE.SCORE'.

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

KARNOFSKY.PERFORMANCE.SCORE Mean (SD) 73.81 (32)
  Significant markers N = 1
  pos. correlated 1
  neg. correlated 0
List of one gene significantly correlated to 'KARNOFSKY.PERFORMANCE.SCORE' by Spearman correlation test

Table S8.  Get Full Table List of one gene significantly correlated to 'KARNOFSKY.PERFORMANCE.SCORE' by Spearman correlation test

SpearmanCorr corrP Q
KRT72 0.8588 6.26e-07 0.0109

Figure S4.  Get High-res Image As an example, this figure shows the association of KRT72 to 'KARNOFSKY.PERFORMANCE.SCORE'. P value = 6.26e-07 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #5: 'HISTOLOGICAL.TYPE'

89 genes related to 'HISTOLOGICAL.TYPE'.

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

HISTOLOGICAL.TYPE Labels N
  LUNG ACINAR ADENOCARCINOMA 10
  LUNG ADENOCARCINOMA MIXED SUBTYPE 59
  LUNG ADENOCARCINOMA- NOT OTHERWISE SPECIFIED (NOS) 154
  LUNG BRONCHIOLOALVEOLAR CARCINOMA MUCINOUS 3
  LUNG BRONCHIOLOALVEOLAR CARCINOMA NONMUCINOUS 14
  LUNG CLEAR CELL ADENOCARCINOMA 1
  LUNG MICROPAPILLARY ADENOCARCINOMA 2
  LUNG MUCINOUS ADENOCARCINOMA 2
  LUNG PAPILLARY ADENOCARCINOMA 12
  LUNG SOLID PATTERN PREDOMINANT ADENOCARCINOMA 2
  MUCINOUS (COLLOID) ADENOCARCINOMA 4
     
  Significant markers N = 89
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
USMG5 9.011e-32 1.57e-27
GOPC 9.788e-28 1.7e-23
MURC 4.088e-27 7.1e-23
GNG10 1.288e-26 2.24e-22
KRT39 2.439e-22 4.24e-18
KAT5 1.228e-20 2.13e-16
MED17 8.191e-19 1.42e-14
BCR 8.288e-19 1.44e-14
GLTSCR2 9.392e-16 1.63e-11
CRISPLD2 1.62e-14 2.81e-10

Figure S5.  Get High-res Image As an example, this figure shows the association of USMG5 to 'HISTOLOGICAL.TYPE'. P value = 9.01e-32 with ANOVA analysis.

Clinical variable #6: 'PATHOLOGY.T'

One gene related to 'PATHOLOGY.T'.

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

PATHOLOGY.T Mean (SD) 1.88 (0.77)
  N
  T1 80
  T2 146
  T3 21
  T4 14
     
  Significant markers N = 1
  pos. correlated 1
  neg. correlated 0
List of one gene significantly correlated to 'PATHOLOGY.T' by Spearman correlation test

Table S12.  Get Full Table List of one gene significantly correlated to 'PATHOLOGY.T' by Spearman correlation test

SpearmanCorr corrP Q
KCNK12 0.2914 1.671e-06 0.029

Figure S6.  Get High-res Image As an example, this figure shows the association of KCNK12 to 'PATHOLOGY.T'. P value = 1.67e-06 with Spearman correlation analysis.

Clinical variable #7: 'PATHOLOGY.N'

One gene related to 'PATHOLOGY.N'.

Table S13.  Basic characteristics of clinical feature: 'PATHOLOGY.N'

PATHOLOGY.N Mean (SD) 0.53 (0.77)
  N
  N0 163
  N1 50
  N2 43
     
  Significant markers N = 1
  pos. correlated 1
  neg. correlated 0
List of one gene significantly correlated to 'PATHOLOGY.N' by Spearman correlation test

Table S14.  Get Full Table List of one gene significantly correlated to 'PATHOLOGY.N' by Spearman correlation test

SpearmanCorr corrP Q
VAMP1 0.3081 4.95e-07 0.0086

Figure S7.  Get High-res Image As an example, this figure shows the association of VAMP1 to 'PATHOLOGY.N'. P value = 4.95e-07 with Spearman correlation analysis.

Clinical variable #8: 'PATHOLOGICSPREAD(M)'

224 genes related to 'PATHOLOGICSPREAD(M)'.

Table S15.  Basic characteristics of clinical feature: 'PATHOLOGICSPREAD(M)'

PATHOLOGICSPREAD(M) Labels N
  M0 165
  M1 11
  M1B 1
  MX 79
     
  Significant markers N = 224
List of top 10 genes differentially expressed by 'PATHOLOGICSPREAD(M)'

Table S16.  Get Full Table List of top 10 genes differentially expressed by 'PATHOLOGICSPREAD(M)'

ANOVA_P Q
POLR2J2 5.642e-170 9.8e-166
B3GNT2 1.475e-142 2.56e-138
MSRA 4.996e-85 8.68e-81
HOMER3 1.717e-76 2.98e-72
METTL11A 1.8e-64 3.13e-60
C8ORF55 2.765e-44 4.8e-40
C7ORF46 7.301e-44 1.27e-39
FAM13B 1.361e-39 2.36e-35
GSG1 1.35e-38 2.34e-34
DDAH2 1.324e-37 2.3e-33

Figure S8.  Get High-res Image As an example, this figure shows the association of POLR2J2 to 'PATHOLOGICSPREAD(M)'. P value = 5.64e-170 with ANOVA analysis.

Clinical variable #9: 'TUMOR.STAGE'

2 genes related to 'TUMOR.STAGE'.

Table S17.  Basic characteristics of clinical feature: 'TUMOR.STAGE'

TUMOR.STAGE Mean (SD) 1.75 (0.93)
  N
  Stage 1 137
  Stage 2 58
  Stage 3 50
  Stage 4 12
     
  Significant markers N = 2
  pos. correlated 1
  neg. correlated 1
List of 2 genes significantly correlated to 'TUMOR.STAGE' by Spearman correlation test

Table S18.  Get Full Table List of 2 genes significantly correlated to 'TUMOR.STAGE' by Spearman correlation test

SpearmanCorr corrP Q
VAMP1 0.3131 2.985e-07 0.00519
ANK3 -0.2921 1.98e-06 0.0344

Figure S9.  Get High-res Image As an example, this figure shows the association of VAMP1 to 'TUMOR.STAGE'. P value = 2.98e-07 with Spearman correlation analysis.

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

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

Table S19.  Basic characteristics of clinical feature: 'RADIATIONS.RADIATION.REGIMENINDICATION'

RADIATIONS.RADIATION.REGIMENINDICATION Labels N
  NO 14
  YES 249
     
  Significant markers N = 14
  Higher in YES 10
  Higher in NO 4
List of top 10 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

Table S20.  Get Full Table List of top 10 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

T(pos if higher in 'YES') ttestP Q AUC
ZNF642 5.83 1.825e-08 0.000317 0.6793
SLCO4C1 5.65 4.211e-08 0.000732 0.7352
PRELP -5.62 4.845e-08 0.000842 0.6604
MAT2B 5.72 6.515e-08 0.00113 0.5671
TRAPPC5 5.54 7.471e-08 0.0013 0.6277
MIIP -5.87 7.747e-08 0.00135 0.5703
ZNF506 5.64 2.418e-07 0.0042 0.5674
PELI1 -5.8 2.466e-07 0.00428 0.6434
LMX1B 5.43 2.576e-07 0.00447 0.6847
C12ORF62 6.19 4.856e-07 0.00843 0.7553

Figure S10.  Get High-res Image As an example, this figure shows the association of ZNF642 to 'RADIATIONS.RADIATION.REGIMENINDICATION'. P value = 1.83e-08 with T-test analysis.

Clinical variable #11: 'NUMBERPACKYEARSSMOKED'

No gene related to 'NUMBERPACKYEARSSMOKED'.

Table S21.  Basic characteristics of clinical feature: 'NUMBERPACKYEARSSMOKED'

NUMBERPACKYEARSSMOKED Mean (SD) 38.79 (26)
  Significant markers N = 0
Clinical variable #12: 'TOBACCOSMOKINGHISTORYINDICATOR'

28 genes related to 'TOBACCOSMOKINGHISTORYINDICATOR'.

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

TOBACCOSMOKINGHISTORYINDICATOR Labels N
  CURRENT REFORMED SMOKER FOR < OR = 15 YEARS 91
  CURRENT REFORMED SMOKER FOR > 15 YEARS 68
  CURRENT SMOKER 57
  LIFELONG NON-SMOKER 36
     
  Significant markers N = 28
List of top 10 genes differentially expressed by 'TOBACCOSMOKINGHISTORYINDICATOR'

Table S23.  Get Full Table List of top 10 genes differentially expressed by 'TOBACCOSMOKINGHISTORYINDICATOR'

ANOVA_P Q
SRM 1.116e-09 1.94e-05
GIT1 3.498e-09 6.08e-05
NME2 2.274e-08 0.000395
SNHG1 3.202e-08 0.000556
RPS8 3.753e-08 0.000652
NME1-NME2 4.235e-08 0.000736
ZC3HAV1L 8.09e-08 0.00141
TACC3 8.413e-08 0.00146
GAPDH 1.722e-07 0.00299
FAM128A 2.392e-07 0.00415

Figure S11.  Get High-res Image As an example, this figure shows the association of SRM to 'TOBACCOSMOKINGHISTORYINDICATOR'. P value = 1.12e-09 with ANOVA analysis.

Clinical variable #13: 'YEAROFTOBACCOSMOKINGONSET'

One gene related to 'YEAROFTOBACCOSMOKINGONSET'.

Table S24.  Basic characteristics of clinical feature: 'YEAROFTOBACCOSMOKINGONSET'

YEAROFTOBACCOSMOKINGONSET Mean (SD) 1964.9 (13)
  Significant markers N = 1
  pos. correlated 1
  neg. correlated 0
List of one gene significantly correlated to 'YEAROFTOBACCOSMOKINGONSET' by Spearman correlation test

Table S25.  Get Full Table List of one gene significantly correlated to 'YEAROFTOBACCOSMOKINGONSET' by Spearman correlation test

SpearmanCorr corrP Q
MYH14 0.3995 1.328e-06 0.0231

Figure S12.  Get High-res Image As an example, this figure shows the association of MYH14 to 'YEAROFTOBACCOSMOKINGONSET'. P value = 1.33e-06 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #14: 'COMPLETENESS.OF.RESECTION'

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

Table S26.  Basic characteristics of clinical feature: 'COMPLETENESS.OF.RESECTION'

COMPLETENESS.OF.RESECTION Labels N
  R0 126
  R1 7
  R2 1
  RX 9
     
  Significant markers N = 106
List of top 10 genes differentially expressed by 'COMPLETENESS.OF.RESECTION'

Table S27.  Get Full Table List of top 10 genes differentially expressed by 'COMPLETENESS.OF.RESECTION'

ANOVA_P Q
DDX52 1.993e-110 3.46e-106
MAN2A1 6.87e-85 1.19e-80
CCDC53 7.787e-85 1.35e-80
AFF1 1.276e-66 2.22e-62
ZNF619 5.577e-63 9.69e-59
ANKIB1 2.805e-61 4.87e-57
CDK13 2.678e-47 4.65e-43
CWC22 7.509e-46 1.3e-41
SLC6A16 5.063e-43 8.79e-39
HADHB 5.778e-39 1e-34

Figure S13.  Get High-res Image As an example, this figure shows the association of DDX52 to 'COMPLETENESS.OF.RESECTION'. P value = 1.99e-110 with ANOVA analysis.

Methods & Data
Input

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

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

  • Number of patients = 263

  • Number of genes = 17375

  • Number of clinical features = 14

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

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

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] Howell, D, Statistical Methods for Psychology. (5th ed.), Duxbury Press:324-5 (2002)
[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