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 17376 genes and 14 clinical features across 256 samples, statistically thresholded by Q value < 0.05, 12 clinical features related to at least one genes.

  • 19 genes correlated to 'Time to Death'.

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

  • 1 gene correlated to 'AGE'.

    • NETO2

  • 34 genes correlated to 'GENDER'.

    • CCNYL1 ,  KIF4B ,  EIF4A1 ,  RNASEH2C ,  FRG1B ,  ...

  • 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

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

    • FAM190A ,  CARD6 ,  PAPSS1

  • 1 gene correlated to 'TUMOR.STAGE'.

    • VAMP1

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

    • SLCO4C1 ,  ZNF642 ,  MIIP ,  TRAPPC5 ,  MAT2B ,  ...

  • 35 genes correlated to 'TOBACCOSMOKINGHISTORYINDICATOR'.

    • SRM ,  NME2 ,  NME1-NME2 ,  GIT1 ,  C14ORF115 ,  ...

  • 2 genes correlated to 'YEAROFTOBACCOSMOKINGONSET'.

    • MYH14 ,  AGR3

  • No genes correlated to 'NUMBERPACKYEARSSMOKED', and 'STOPPEDSMOKINGYEAR'.

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=1 older N=1 younger N=0
GENDER t test N=34 male N=5 female N=29
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=3        
TUMOR STAGE Spearman correlation test N=1 higher stage N=1 lower stage N=0
RADIATIONS RADIATION REGIMENINDICATION t test N=12 yes N=9 no N=3
NUMBERPACKYEARSSMOKED Spearman correlation test   N=0        
STOPPEDSMOKINGYEAR Spearman correlation test   N=0        
TOBACCOSMOKINGHISTORYINDICATOR ANOVA test N=35        
YEAROFTOBACCOSMOKINGONSET Spearman correlation test N=2 higher yearoftobaccosmokingonset N=2 lower yearoftobaccosmokingonset N=0
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=8.6)
  censored N = 167
  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 1.371e-08 0.00024 0.672
MARVELD1 0 1.462e-08 0.00025 0.323
LOC650368 0 4.436e-08 0.00077 0.339
LARP1 0 6.629e-08 0.0012 0.296
RRAGD 231 2.32e-07 0.004 0.634
APOBEC4 0 3.575e-07 0.0062 0.382
IBSP 0 4.606e-07 0.008 0.375
ZNF117 0 6.009e-07 0.01 0.392
SLC10A6 0 9.378e-07 0.016 0.385
MAP7D1 0 9.773e-07 0.017 0.41

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 = 1.37e-08 with univariate Cox regression analysis using continuous log-2 expression values.

Clinical variable #2: 'AGE'

One gene related to 'AGE'.

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

AGE Mean (SD) 65.4 (9.9)
  Significant markers N = 1
  pos. correlated 1
  neg. correlated 0
List of one gene significantly correlated to 'AGE' by Spearman correlation test

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

SpearmanCorr corrP Q
NETO2 0.3046 2.782e-06 0.0483

Figure S2.  Get High-res Image As an example, this figure shows the association of NETO2 to 'AGE'. P value = 2.78e-06 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #3: 'GENDER'

34 genes related to 'GENDER'.

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

GENDER Labels N
  FEMALE 140
  MALE 116
     
  Significant markers N = 34
  Higher in MALE 5
  Higher in FEMALE 29
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 -22.06 5.223e-57 9.08e-53 0.9547
KIF4B -11.88 6.341e-26 1.1e-21 0.8563
EIF4A1 -8.13 3.216e-14 5.59e-10 0.7837
RNASEH2C 7.93 7.074e-14 1.23e-09 0.751
FRG1B -6.95 3.797e-11 6.6e-07 0.7565
GPN1 -6.93 4.668e-11 8.11e-07 0.724
SPESP1 -6.45 7.72e-10 1.34e-05 0.7134
ZNF839 -6.31 1.29e-09 2.24e-05 0.7183
ATP5J 6.41 1.71e-09 2.97e-05 0.7337
GABPA 6.41 1.71e-09 2.97e-05 0.7337

Figure S3.  Get High-res Image As an example, this figure shows the association of CCNYL1 to 'GENDER'. P value = 5.22e-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 58
  LUNG ADENOCARCINOMA- NOT OTHERWISE SPECIFIED (NOS) 148
  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 8.24e-31 1.43e-26
GOPC 5.833e-27 1.01e-22
MURC 2.803e-26 4.87e-22
GNG10 7.498e-26 1.3e-21
KRT39 9.359e-22 1.63e-17
KAT5 4.986e-20 8.66e-16
MED17 2.766e-18 4.81e-14
BCR 3.411e-18 5.92e-14
GLTSCR2 2.675e-15 4.65e-11
CRISPLD2 3.018e-14 5.24e-10

Figure S5.  Get High-res Image As an example, this figure shows the association of USMG5 to 'HISTOLOGICAL.TYPE'. P value = 8.24e-31 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) 1.89 (0.77)
  N
  T1 77
  T2 143
  T3 20
  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 0.2929 2.03e-06 0.0353

Figure S6.  Get High-res Image As an example, this figure shows the association of KCNK12 to 'PATHOLOGY.T'. P value = 2.03e-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) 0.55 (0.77)
  N
  N0 156
  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 0.3086 6.804e-07 0.0118

Figure S7.  Get High-res Image As an example, this figure shows the association of VAMP1 to 'PATHOLOGY.N'. P value = 6.8e-07 with Spearman correlation analysis.

Clinical variable #8: 'PATHOLOGICSPREAD(M)'

3 genes related to 'PATHOLOGICSPREAD(M)'.

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

PATHOLOGICSPREAD(M) Labels N
  M0 164
  M1 11
  MX 74
     
  Significant markers N = 3
List of 3 genes differentially expressed by 'PATHOLOGICSPREAD(M)'

Table S16.  Get Full Table List of 3 genes differentially expressed by 'PATHOLOGICSPREAD(M)'

ANOVA_P Q
FAM190A 6.821e-07 0.0119
CARD6 8.796e-07 0.0153
PAPSS1 9.912e-07 0.0172

Figure S8.  Get High-res Image As an example, this figure shows the association of FAM190A to 'PATHOLOGICSPREAD(M)'. P value = 6.82e-07 with ANOVA analysis.

Clinical variable #9: 'TUMOR.STAGE'

One gene related to 'TUMOR.STAGE'.

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

TUMOR.STAGE Mean (SD) 1.76 (0.92)
  N
  Stage 1 132
  Stage 2 57
  Stage 3 50
  Stage 4 11
     
  Significant markers N = 1
  pos. correlated 1
  neg. correlated 0
List of one gene significantly correlated to 'TUMOR.STAGE' by Spearman correlation test

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

SpearmanCorr corrP Q
VAMP1 0.3075 7.091e-07 0.0123

Figure S9.  Get High-res Image As an example, this figure shows the association of VAMP1 to 'TUMOR.STAGE'. P value = 7.09e-07 with Spearman correlation analysis.

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

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

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

RADIATIONS.RADIATION.REGIMENINDICATION Labels N
  NO 14
  YES 242
     
  Significant markers N = 12
  Higher in YES 9
  Higher in NO 3
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
SLCO4C1 5.66 4.198e-08 0.00073 0.7411
ZNF642 5.66 4.329e-08 0.000752 0.678
MIIP -5.78 1.013e-07 0.00176 0.5673
TRAPPC5 5.47 1.088e-07 0.00189 0.6287
MAT2B 5.59 1.373e-07 0.00239 0.5694
PRELP -5.42 1.391e-07 0.00242 0.6588
ZNF506 5.67 1.95e-07 0.00339 0.5705
PELI1 -5.69 3.774e-07 0.00656 0.6423
C12ORF62 6.15 4.801e-07 0.00834 0.7547
RSAD2 5.93 7.42e-07 0.0129 0.7488

Figure S10.  Get High-res Image As an example, this figure shows the association of SLCO4C1 to 'RADIATIONS.RADIATION.REGIMENINDICATION'. P value = 4.2e-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) 38.39 (26)
  Significant markers N = 0
Clinical variable #12: 'STOPPEDSMOKINGYEAR'

No gene related to 'STOPPEDSMOKINGYEAR'.

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

STOPPEDSMOKINGYEAR Mean (SD) 1994.13 (13)
  Significant markers N = 0
Clinical variable #13: 'TOBACCOSMOKINGHISTORYINDICATOR'

35 genes related to 'TOBACCOSMOKINGHISTORYINDICATOR'.

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

TOBACCOSMOKINGHISTORYINDICATOR Labels N
  CURRENT REFORMED SMOKER FOR < OR = 15 YEARS 87
  CURRENT REFORMED SMOKER FOR > 15 YEARS 68
  CURRENT SMOKER 55
  LIFELONG NON-SMOKER 35
     
  Significant markers N = 35
List of top 10 genes differentially expressed by 'TOBACCOSMOKINGHISTORYINDICATOR'

Table S24.  Get Full Table List of top 10 genes differentially expressed by 'TOBACCOSMOKINGHISTORYINDICATOR'

ANOVA_P Q
SRM 1.738e-09 3.02e-05
NME2 4.423e-09 7.68e-05
NME1-NME2 2.54e-08 0.000441
GIT1 2.62e-08 0.000455
C14ORF115 3.016e-08 0.000524
ZC3HAV1L 3.293e-08 0.000572
LOR 7.905e-08 0.00137
CMTM5 9.735e-08 0.00169
RPS8 1.492e-07 0.00259
TACC3 1.694e-07 0.00294

Figure S11.  Get High-res Image As an example, this figure shows the association of SRM to 'TOBACCOSMOKINGHISTORYINDICATOR'. P value = 1.74e-09 with ANOVA analysis.

Clinical variable #14: 'YEAROFTOBACCOSMOKINGONSET'

2 genes related to 'YEAROFTOBACCOSMOKINGONSET'.

Table S25.  Basic characteristics of clinical feature: 'YEAROFTOBACCOSMOKINGONSET'

YEAROFTOBACCOSMOKINGONSET Mean (SD) 1964.67 (13)
  Significant markers N = 2
  pos. correlated 2
  neg. correlated 0
List of 2 genes significantly correlated to 'YEAROFTOBACCOSMOKINGONSET' by Spearman correlation test

Table S26.  Get Full Table List of 2 genes significantly correlated to 'YEAROFTOBACCOSMOKINGONSET' by Spearman correlation test

SpearmanCorr corrP Q
MYH14 0.4194 5.568e-07 0.00967
AGR3 0.415 7.537e-07 0.0131

Figure S12.  Get High-res Image As an example, this figure shows the association of MYH14 to 'YEAROFTOBACCOSMOKINGONSET'. P value = 5.57e-07 with Spearman correlation analysis. The straight line presents the best linear regression.

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 = 256

  • Number of genes = 17376

  • 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)
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