Lung Adenocarcinoma: Correlation between gene methylation status and clinical features
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 17306 genes and 15 clinical features across 173 samples, statistically thresholded by Q value < 0.05, 9 clinical features related to at least one genes.

  • 8 genes correlated to 'Time to Death'.

    • ANO9 ,  ATP6V0A1 ,  LOC100144604 ,  HCP5 ,  TM4SF19 ,  ...

  • 18 genes correlated to 'GENDER'.

    • KIF4B ,  PPHLN1 ,  RNASEH2C ,  EIF4A1 ,  FAM35A ,  ...

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

    • WDR4

  • 110 genes correlated to 'HISTOLOGICAL.TYPE'.

    • GLTSCR2 ,  BCR ,  C8ORF42 ,  GAS2L3 ,  KRT39 ,  ...

  • 1 gene correlated to 'PATHOLOGY.T'.

    • GAPDH

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

    • C2ORF73 ,  C3ORF58 ,  YES1 ,  DENND2C ,  CYP2R1 ,  ...

  • 2 genes correlated to 'TUMOR.STAGE'.

    • PCDHGC4 ,  PCDHGC5

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

    • LYPLA2P1 ,  TRNP1 ,  GABARAPL3 ,  GPM6A ,  C3ORF47 ,  ...

  • 2 genes correlated to 'NEOADJUVANT.THERAPY'.

    • FXYD5 ,  OSTALPHA

  • No genes correlated to 'AGE', 'PATHOLOGY.N', '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=8 shorter survival N=4 longer survival N=4
AGE Spearman correlation test   N=0        
GENDER t test N=18 male N=6 female N=12
KARNOFSKY PERFORMANCE SCORE Spearman correlation test N=1 higher score N=1 lower score N=0
HISTOLOGICAL TYPE ANOVA test N=110        
PATHOLOGY T Spearman correlation test N=1 higher pT N=0 lower pT N=1
PATHOLOGY N Spearman correlation test   N=0        
PATHOLOGICSPREAD(M) ANOVA test N=19        
TUMOR STAGE Spearman correlation test N=2 higher stage N=2 lower stage N=0
RADIATIONS RADIATION REGIMENINDICATION t test N=8 yes N=3 no N=5
NEOADJUVANT THERAPY t test N=2 yes N=1 no N=1
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'

8 genes related to 'Time to Death'.

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

Time to Death Duration (Months) 0-224 (median=11.6)
  censored N = 102
  death N = 47
     
  Significant markers N = 8
  associated with shorter survival 4
  associated with longer survival 4
List of 8 genes significantly associated with 'Time to Death' by Cox regression test

Table S2.  Get Full Table List of 8 genes significantly associated with 'Time to Death' by Cox regression test

HazardRatio Wald_P Q C_index
ANO9 25001 4.82e-08 0.00083 0.666
ATP6V0A1 1101 4.327e-07 0.0075 0.6
LOC100144604 0 7.822e-07 0.014 0.339
HCP5 1801 1.08e-06 0.019 0.594
TM4SF19 0.02 1.149e-06 0.02 0.332
ASZ1 0 1.642e-06 0.028 0.378
RRAGD 211 2.371e-06 0.041 0.65
MAP7D1 0 2.437e-06 0.042 0.385

Figure S1.  Get High-res Image As an example, this figure shows the association of ANO9 to 'Time to Death'. four curves present the cumulative survival rates of 4 quartile subsets of patients. P value = 4.82e-08 with univariate Cox regression analysis using continuous log-2 expression values.

Clinical variable #2: 'AGE'

No gene related to 'AGE'.

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

AGE Mean (SD) 66.09 (9.8)
  Significant markers N = 0
Clinical variable #3: 'GENDER'

18 genes related to 'GENDER'.

Table S4.  Basic characteristics of clinical feature: 'GENDER'

GENDER Labels N
  FEMALE 99
  MALE 74
     
  Significant markers N = 18
  Higher in MALE 6
  Higher in FEMALE 12
List of top 10 genes differentially expressed by 'GENDER'

Table S5.  Get Full Table List of top 10 genes differentially expressed by 'GENDER'

T(pos if higher in 'MALE') ttestP Q AUC
KIF4B -10.42 2.01e-19 3.48e-15 0.8821
PPHLN1 -8.35 3.65e-14 6.32e-10 0.8225
RNASEH2C 7.49 3.633e-12 6.29e-08 0.7869
EIF4A1 -7.13 6.303e-11 1.09e-06 0.792
FAM35A -6.79 1.745e-10 3.02e-06 0.8069
GLUD1 -6.79 1.745e-10 3.02e-06 0.8069
FRG1B -6.82 2.125e-10 3.68e-06 0.7802
MACC1 5.63 7.604e-08 0.00132 0.7476
FUBP3 -5.47 1.835e-07 0.00317 0.7195
SFT2D2 5.16 6.818e-07 0.0118 0.7128

Figure S2.  Get High-res Image As an example, this figure shows the association of KIF4B to 'GENDER'. P value = 2.01e-19 with T-test analysis.

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

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

Table S6.  Basic characteristics of clinical feature: 'KARNOFSKY.PERFORMANCE.SCORE'

KARNOFSKY.PERFORMANCE.SCORE Mean (SD) 67.86 (38)
  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 S7.  Get Full Table List of one gene significantly correlated to 'KARNOFSKY.PERFORMANCE.SCORE' by Spearman correlation test

SpearmanCorr corrP Q
WDR4 0.934 1.035e-06 0.0179

Figure S3.  Get High-res Image As an example, this figure shows the association of WDR4 to 'KARNOFSKY.PERFORMANCE.SCORE'. P value = 1.03e-06 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #5: 'HISTOLOGICAL.TYPE'

110 genes related to 'HISTOLOGICAL.TYPE'.

Table S8.  Basic characteristics of clinical feature: 'HISTOLOGICAL.TYPE'

HISTOLOGICAL.TYPE Labels N
  LUNG ACINAR ADENOCARCINOMA 5
  LUNG ADENOCARCINOMA MIXED SUBTYPE 40
  LUNG ADENOCARCINOMA- NOT OTHERWISE SPECIFIED (NOS) 100
  LUNG BRONCHIOLOALVEOLAR CARCINOMA MUCINOUS 3
  LUNG BRONCHIOLOALVEOLAR CARCINOMA NONMUCINOUS 10
  LUNG MICROPAPILLARY ADENOCARCINOMA 2
  LUNG MUCINOUS ADENOCARCINOMA 1
  LUNG PAPILLARY ADENOCARCINOMA 8
  MUCINOUS (COLLOID) ADENOCARCINOMA 4
     
  Significant markers N = 110
List of top 10 genes differentially expressed by 'HISTOLOGICAL.TYPE'

Table S9.  Get Full Table List of top 10 genes differentially expressed by 'HISTOLOGICAL.TYPE'

ANOVA_P Q
GLTSCR2 7.078e-33 1.22e-28
BCR 8.671e-24 1.5e-19
C8ORF42 2.673e-20 4.63e-16
GAS2L3 1.123e-17 1.94e-13
KRT39 1.261e-16 2.18e-12
UBE2G1 8.172e-16 1.41e-11
SULF2 3.144e-15 5.44e-11
GPBAR1 1.792e-14 3.1e-10
LRRC66 5.806e-14 1e-09
MURC 8.076e-14 1.4e-09

Figure S4.  Get High-res Image As an example, this figure shows the association of GLTSCR2 to 'HISTOLOGICAL.TYPE'. P value = 7.08e-33 with ANOVA analysis.

Clinical variable #6: 'PATHOLOGY.T'

One gene related to 'PATHOLOGY.T'.

Table S10.  Basic characteristics of clinical feature: 'PATHOLOGY.T'

PATHOLOGY.T Mean (SD) 1.94 (0.82)
  N
  T1 50
  T2 96
  T3 13
  T4 13
     
  Significant markers N = 1
  pos. correlated 0
  neg. correlated 1
List of one gene significantly correlated to 'PATHOLOGY.T' by Spearman correlation test

Table S11.  Get Full Table List of one gene significantly correlated to 'PATHOLOGY.T' by Spearman correlation test

SpearmanCorr corrP Q
GAPDH -0.3518 2.219e-06 0.0384

Figure S5.  Get High-res Image As an example, this figure shows the association of GAPDH to 'PATHOLOGY.T'. P value = 2.22e-06 with Spearman correlation analysis.

Clinical variable #7: 'PATHOLOGY.N'

No gene related to 'PATHOLOGY.N'.

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

PATHOLOGY.N Mean (SD) 0.57 (0.79)
  N
  N0 105
  N1 32
  N2 32
     
  Significant markers N = 0
Clinical variable #8: 'PATHOLOGICSPREAD(M)'

19 genes related to 'PATHOLOGICSPREAD(M)'.

Table S13.  Basic characteristics of clinical feature: 'PATHOLOGICSPREAD(M)'

PATHOLOGICSPREAD(M) Labels N
  M0 111
  M1 6
  MX 51
     
  Significant markers N = 19
List of top 10 genes differentially expressed by 'PATHOLOGICSPREAD(M)'

Table S14.  Get Full Table List of top 10 genes differentially expressed by 'PATHOLOGICSPREAD(M)'

ANOVA_P Q
C2ORF73 3.731e-09 6.46e-05
C3ORF58 2.757e-08 0.000477
YES1 2.257e-07 0.00391
DENND2C 3.458e-07 0.00598
CYP2R1 4.835e-07 0.00837
C17ORF106 5.888e-07 0.0102
CSNK1G3 6.51e-07 0.0113
NOTCH2NL 7.121e-07 0.0123
FAM60A 1.062e-06 0.0184
USP12 1.085e-06 0.0188

Figure S6.  Get High-res Image As an example, this figure shows the association of C2ORF73 to 'PATHOLOGICSPREAD(M)'. P value = 3.73e-09 with ANOVA analysis.

Clinical variable #9: 'TUMOR.STAGE'

2 genes related to 'TUMOR.STAGE'.

Table S15.  Basic characteristics of clinical feature: 'TUMOR.STAGE'

TUMOR.STAGE Mean (SD) 1.77 (0.93)
  N
  Stage 1 89
  Stage 2 36
  Stage 3 36
  Stage 4 7
     
  Significant markers N = 2
  pos. correlated 2
  neg. correlated 0
List of 2 genes significantly correlated to 'TUMOR.STAGE' by Spearman correlation test

Table S16.  Get Full Table List of 2 genes significantly correlated to 'TUMOR.STAGE' by Spearman correlation test

SpearmanCorr corrP Q
PCDHGC4 0.362 1.425e-06 0.0247
PCDHGC5 0.362 1.425e-06 0.0247

Figure S7.  Get High-res Image As an example, this figure shows the association of PCDHGC4 to 'TUMOR.STAGE'. P value = 1.43e-06 with Spearman correlation analysis.

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

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

Table S17.  Basic characteristics of clinical feature: 'RADIATIONS.RADIATION.REGIMENINDICATION'

RADIATIONS.RADIATION.REGIMENINDICATION Labels N
  NO 12
  YES 161
     
  Significant markers N = 8
  Higher in YES 3
  Higher in NO 5
List of 8 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

Table S18.  Get Full Table List of 8 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

T(pos if higher in 'YES') ttestP Q AUC
LYPLA2P1 -5.76 1.457e-07 0.00252 0.647
TRNP1 -5.33 4.881e-07 0.00845 0.5471
GABARAPL3 -6.03 5.388e-07 0.00932 0.735
GPM6A 5.13 7.822e-07 0.0135 0.6537
C3ORF47 5.55 1.417e-06 0.0245 0.7164
CCDC91 -5.35 2.254e-06 0.039 0.6713
ARL6IP1 -5.76 2.355e-06 0.0407 0.7096
SLCO4C1 4.84 2.865e-06 0.0496 0.6812

Figure S8.  Get High-res Image As an example, this figure shows the association of LYPLA2P1 to 'RADIATIONS.RADIATION.REGIMENINDICATION'. P value = 1.46e-07 with T-test analysis.

Clinical variable #11: 'NEOADJUVANT.THERAPY'

2 genes related to 'NEOADJUVANT.THERAPY'.

Table S19.  Basic characteristics of clinical feature: 'NEOADJUVANT.THERAPY'

NEOADJUVANT.THERAPY Labels N
  NO 27
  YES 146
     
  Significant markers N = 2
  Higher in YES 1
  Higher in NO 1
List of 2 genes differentially expressed by 'NEOADJUVANT.THERAPY'

Table S20.  Get Full Table List of 2 genes differentially expressed by 'NEOADJUVANT.THERAPY'

T(pos if higher in 'YES') ttestP Q AUC
FXYD5 5.28 3.871e-07 0.0067 0.5553
OSTALPHA -4.91 2.256e-06 0.039 0.6824

Figure S9.  Get High-res Image As an example, this figure shows the association of FXYD5 to 'NEOADJUVANT.THERAPY'. P value = 3.87e-07 with T-test analysis.

Clinical variable #12: 'NUMBERPACKYEARSSMOKED'

No gene related to 'NUMBERPACKYEARSSMOKED'.

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

NUMBERPACKYEARSSMOKED Mean (SD) 38.49 (26)
  Significant markers N = 0
Clinical variable #13: 'STOPPEDSMOKINGYEAR'

No gene related to 'STOPPEDSMOKINGYEAR'.

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

STOPPEDSMOKINGYEAR Mean (SD) 1992.54 (14)
  Significant markers N = 0
Clinical variable #14: 'TOBACCOSMOKINGHISTORYINDICATOR'

No gene related to 'TOBACCOSMOKINGHISTORYINDICATOR'.

Table S23.  Basic characteristics of clinical feature: 'TOBACCOSMOKINGHISTORYINDICATOR'

TOBACCOSMOKINGHISTORYINDICATOR Labels N
  CURRENT REFORMED SMOKER FOR < OR = 15 YEARS 57
  CURRENT REFORMED SMOKER FOR > 15 YEARS 51
  CURRENT SMOKER 32
  LIFELONG NON-SMOKER 23
     
  Significant markers N = 0
Clinical variable #15: 'YEAROFTOBACCOSMOKINGONSET'

No gene related to 'YEAROFTOBACCOSMOKINGONSET'.

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

YEAROFTOBACCOSMOKINGONSET Mean (SD) 1961.99 (12)
  Significant markers N = 0
Methods & Data
Input

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

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

  • Number of patients = 173

  • Number of genes = 17306

  • Number of clinical features = 15

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)
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