Correlation between RPPA expression and clinical features
Colorectal Adenocarcinoma (Primary solid tumor)
21 August 2015  |  analyses__2015_08_21
Maintainer Information
Citation Information
doi:10.7908/C1F18XW9
Maintained by Juok Cho (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2015): Correlation between RPPA expression and clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C1F18XW9
Overview
Introduction

This pipeline uses various statistical tests to identify RPPAs whose expression levels correlated to selected clinical features.

Summary

Testing the association between 208 genes and 13 clinical features across 488 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 11 clinical features related to at least one genes.

  • 1 gene correlated to 'DAYS_TO_DEATH_OR_LAST_FUP'.

    • EGFR|EGFR

  • 8 genes correlated to 'YEARS_TO_BIRTH'.

    • SRC|SRC ,  BID|BID ,  MET|C-MET_PY1235 ,  EGFR|EGFR ,  YAP1|YAP ,  ...

  • 16 genes correlated to 'TUMOR_TISSUE_SITE'.

    • BID|BID ,  IRS1|IRS1 ,  RAF1|C-RAF ,  ERBB3|HER3_PY1289 ,  SRC|SRC ,  ...

  • 30 genes correlated to 'PATHOLOGIC_STAGE'.

    • CASP7|CASPASE-7_CLEAVEDD198 ,  PIK3CA |PI3K-P110-ALPHA ,  YAP1|YAP ,  IRS1|IRS1 ,  DIRAS3|ARHI ,  ...

  • 30 genes correlated to 'PATHOLOGY_T_STAGE'.

    • SERPINE1|PAI-1 ,  ERRFI1|MIG-6 ,  SRC|SRC_PY527 ,  RB1|RB_PS807_S811 ,  EIF4E|EIF4E ,  ...

  • 30 genes correlated to 'PATHOLOGY_N_STAGE'.

    • IRS1|IRS1 ,  MYC|C-MYC ,  GAB2|GAB2 ,  EIF4E|EIF4E ,  CASP7|CASPASE-7_CLEAVEDD198 ,  ...

  • 30 genes correlated to 'PATHOLOGY_M_STAGE'.

    • CASP7|CASPASE-7_CLEAVEDD198 ,  RBM15|RBM15 ,  MAPK14|P38_MAPK ,  CCNE1|CYCLIN_E1 ,  PREX1|PREX1 ,  ...

  • 30 genes correlated to 'HISTOLOGICAL_TYPE'.

    • BID|BID ,  RAD50|RAD50 ,  RAF1|C-RAF ,  MRE11A|MRE11 ,  ERBB3|HER3_PY1289 ,  ...

  • 30 genes correlated to 'RESIDUAL_TUMOR'.

    • RBM15|RBM15 ,  EIF4G1|EIF4G ,  PEA15|PEA15 ,  ERBB2|HER2_PY1248 ,  TSC2|TUBERIN ,  ...

  • 30 genes correlated to 'NUMBER_OF_LYMPH_NODES'.

    • IRS1|IRS1 ,  GAB2|GAB2 ,  EIF4E|EIF4E ,  PXN|PAXILLIN ,  MYC|C-MYC ,  ...

  • 30 genes correlated to 'RACE'.

    • NRAS|N-RAS ,  PRKCB|PKC-PAN_BETAII_PS660 ,  MRE11A|MRE11 ,  ERBB2|HER2 ,  PREX1|PREX1 ,  ...

  • No genes correlated to 'GENDER', and 'RADIATION_THERAPY'.

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 P value < 0.05 and Q value < 0.3.

Clinical feature Statistical test Significant genes Associated with                 Associated with
DAYS_TO_DEATH_OR_LAST_FUP Cox regression test N=1 shorter survival N=1 longer survival N=0
YEARS_TO_BIRTH Spearman correlation test N=8 older N=3 younger N=5
TUMOR_TISSUE_SITE Wilcoxon test N=16 rectum N=16 colon N=0
PATHOLOGIC_STAGE Kruskal-Wallis test N=30        
PATHOLOGY_T_STAGE Spearman correlation test N=30 higher stage N=15 lower stage N=15
PATHOLOGY_N_STAGE Spearman correlation test N=30 higher stage N=15 lower stage N=15
PATHOLOGY_M_STAGE Wilcoxon test N=30 class1 N=30 class0 N=0
GENDER Wilcoxon test   N=0        
RADIATION_THERAPY Wilcoxon test   N=0        
HISTOLOGICAL_TYPE Kruskal-Wallis test N=30        
RESIDUAL_TUMOR Kruskal-Wallis test N=30        
NUMBER_OF_LYMPH_NODES Spearman correlation test N=30 higher number_of_lymph_nodes N=14 lower number_of_lymph_nodes N=16
RACE Kruskal-Wallis test N=30        
Clinical variable #1: 'DAYS_TO_DEATH_OR_LAST_FUP'

One gene related to 'DAYS_TO_DEATH_OR_LAST_FUP'.

Table S1.  Basic characteristics of clinical feature: 'DAYS_TO_DEATH_OR_LAST_FUP'

DAYS_TO_DEATH_OR_LAST_FUP Duration (Months) 0-140.4 (median=20)
  censored N = 389
  death N = 98
     
  Significant markers N = 1
  associated with shorter survival 1
  associated with longer survival 0
List of one gene differentially expressed by 'DAYS_TO_DEATH_OR_LAST_FUP'

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

HazardRatio Wald_P Q C_index
EGFR|EGFR 3.2 3.398e-05 0.0071 0.602
Clinical variable #2: 'YEARS_TO_BIRTH'

8 genes related to 'YEARS_TO_BIRTH'.

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

YEARS_TO_BIRTH Mean (SD) 66.56 (13)
  Significant markers N = 8
  pos. correlated 3
  neg. correlated 5
List of 8 genes differentially expressed by 'YEARS_TO_BIRTH'

Table S4.  Get Full Table List of 8 genes significantly correlated to 'YEARS_TO_BIRTH' by Spearman correlation test

SpearmanCorr corrP Q
SRC|SRC -0.1429 0.00157 0.12
BID|BID -0.1421 0.001671 0.12
MET|C-MET_PY1235 -0.1416 0.001732 0.12
EGFR|EGFR 0.1358 0.002678 0.139
YAP1|YAP -0.1296 0.004178 0.158
ESR1|ER-ALPHA_PS118 -0.1284 0.004545 0.158
MAP2K1|MEK1_PS217_S221 0.1251 0.005698 0.169
RB1|RB_PS807_S811 0.1168 0.009902 0.257
Clinical variable #3: 'TUMOR_TISSUE_SITE'

16 genes related to 'TUMOR_TISSUE_SITE'.

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

TUMOR_TISSUE_SITE Labels N
  COLON 357
  RECTUM 131
     
  Significant markers N = 16
  Higher in RECTUM 16
  Higher in COLON 0
List of top 10 genes differentially expressed by 'TUMOR_TISSUE_SITE'

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

W(pos if higher in 'RECTUM') wilcoxontestP Q AUC
BID|BID 29429 1.193e-05 0.00248 0.6293
IRS1|IRS1 28276 0.0003946 0.0277 0.6046
RAF1|C-RAF 28271 0.0004001 0.0277 0.6045
ERBB3|HER3_PY1289 27931 0.0009886 0.0514 0.5972
SRC|SRC 27551 0.00254 0.095 0.5891
BAD|BAD_PS112 19248 0.002742 0.095 0.5884
RPS6|S6 19435 0.004238 0.126 0.5844
JUN|C-JUN_PS73 19694 0.007535 0.196 0.5789
MYC|C-MYC 26994 0.008922 0.206 0.5772
KDR|VEGFR2 19998 0.01421 0.266 0.5724
Clinical variable #4: 'PATHOLOGIC_STAGE'

30 genes related to 'PATHOLOGIC_STAGE'.

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

PATHOLOGIC_STAGE Labels N
  STAGE I 75
  STAGE IA 1
  STAGE II 27
  STAGE IIA 148
  STAGE IIB 9
  STAGE IIC 2
  STAGE III 24
  STAGE IIIA 15
  STAGE IIIB 69
  STAGE IIIC 42
  STAGE IV 46
  STAGE IVA 20
  STAGE IVB 2
     
  Significant markers N = 30
List of top 10 genes differentially expressed by 'PATHOLOGIC_STAGE'

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

kruskal_wallis_P Q
CASP7|CASPASE-7_CLEAVEDD198 5.717e-06 0.000906
PIK3CA |PI3K-P110-ALPHA 8.714e-06 0.000906
YAP1|YAP 0.0002434 0.0159
IRS1|IRS1 0.0003373 0.0159
DIRAS3|ARHI 0.0003815 0.0159
PXN|PAXILLIN 0.0006688 0.0232
RB1|RB_PS807_S811 0.001026 0.0305
EGFR|EGFR_PY1173 0.002606 0.0565
BAK1|BAK 0.003296 0.0565
CDK1|CDK1_PY15 0.003349 0.0565
Clinical variable #5: 'PATHOLOGY_T_STAGE'

30 genes related to 'PATHOLOGY_T_STAGE'.

Table S9.  Basic characteristics of clinical feature: 'PATHOLOGY_T_STAGE'

PATHOLOGY_T_STAGE Mean (SD) 2.9 (0.6)
  N
  T1 11
  T2 81
  T3 339
  T4 55
     
  Significant markers N = 30
  pos. correlated 15
  neg. correlated 15
List of top 10 genes differentially expressed by 'PATHOLOGY_T_STAGE'

Table S10.  Get Full Table List of top 10 genes significantly correlated to 'PATHOLOGY_T_STAGE' by Spearman correlation test

SpearmanCorr corrP Q
SERPINE1|PAI-1 0.2013 7.742e-06 0.00161
ERRFI1|MIG-6 0.183 4.952e-05 0.00515
SRC|SRC_PY527 -0.1546 0.0006271 0.0357
RB1|RB_PS807_S811 -0.152 0.0007716 0.0357
EIF4E|EIF4E -0.1485 0.001022 0.0357
CDK1|CDK1_PY15 -0.1509 0.001183 0.0357
SRC|SRC_PY416 -0.1464 0.001212 0.0357
EIF4EBP1|4E-BP1_PT37_T46 -0.1437 0.001488 0.0357
SMAD1|SMAD1 -0.1432 0.001545 0.0357
GAB2|GAB2 0.1342 0.003038 0.0632
Clinical variable #6: 'PATHOLOGY_N_STAGE'

30 genes related to 'PATHOLOGY_N_STAGE'.

Table S11.  Basic characteristics of clinical feature: 'PATHOLOGY_N_STAGE'

PATHOLOGY_N_STAGE Mean (SD) 0.62 (0.78)
  N
  N0 274
  N1 122
  N2 89
     
  Significant markers N = 30
  pos. correlated 15
  neg. correlated 15
List of top 10 genes differentially expressed by 'PATHOLOGY_N_STAGE'

Table S12.  Get Full Table List of top 10 genes significantly correlated to 'PATHOLOGY_N_STAGE' by Spearman correlation test

SpearmanCorr corrP Q
IRS1|IRS1 0.2388 1.029e-07 2.14e-05
MYC|C-MYC 0.1918 2.122e-05 0.00221
GAB2|GAB2 0.1786 7.638e-05 0.004
EIF4E|EIF4E -0.1786 7.69e-05 0.004
CASP7|CASPASE-7_CLEAVEDD198 -0.1683 0.0001958 0.00814
PXN|PAXILLIN 0.1662 0.0002363 0.00819
BAX|BAX -0.1628 0.0003174 0.00943
PREX1|PREX1 -0.1582 0.0004686 0.0122
DVL3|DVL3 0.1516 0.0008073 0.0179
CCNE1|CYCLIN_E1 -0.1506 0.0008804 0.0179
Clinical variable #7: 'PATHOLOGY_M_STAGE'

30 genes related to 'PATHOLOGY_M_STAGE'.

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

PATHOLOGY_M_STAGE Labels N
  class0 367
  class1 67
     
  Significant markers N = 30
  Higher in class1 30
  Higher in class0 0
List of top 10 genes differentially expressed by 'PATHOLOGY_M_STAGE'

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

W(pos if higher in 'class1') wilcoxontestP Q AUC
CASP7|CASPASE-7_CLEAVEDD198 8400 3.715e-05 0.00773 0.6584
RBM15|RBM15 15513 0.0006532 0.0464 0.6309
MAPK14|P38_MAPK 9082 0.0006686 0.0464 0.6306
CCNE1|CYCLIN_E1 9234 0.001191 0.0619 0.6245
PREX1|PREX1 9404 0.002205 0.0917 0.6176
YBX1|YB-1 14829 0.007275 0.245 0.6031
IRS1|IRS1 14768 0.008809 0.245 0.6006
AKT1S1|PRAS40_PT246 14746 0.009429 0.245 0.5997
PXN|PAXILLIN 14685 0.01136 0.245 0.5972
MYC|C-MYC 14663 0.01214 0.245 0.5963
Clinical variable #8: 'GENDER'

No gene related to 'GENDER'.

Table S15.  Basic characteristics of clinical feature: 'GENDER'

GENDER Labels N
  FEMALE 233
  MALE 255
     
  Significant markers N = 0
Clinical variable #9: 'RADIATION_THERAPY'

No gene related to 'RADIATION_THERAPY'.

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

RADIATION_THERAPY Labels N
  NO 357
  YES 23
     
  Significant markers N = 0
Clinical variable #10: 'HISTOLOGICAL_TYPE'

30 genes related to 'HISTOLOGICAL_TYPE'.

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

HISTOLOGICAL_TYPE Labels N
  COLON ADENOCARCINOMA 312
  COLON MUCINOUS ADENOCARCINOMA 42
  RECTAL ADENOCARCINOMA 118
  RECTAL MUCINOUS ADENOCARCINOMA 10
     
  Significant markers N = 30
List of top 10 genes differentially expressed by 'HISTOLOGICAL_TYPE'

Table S18.  Get Full Table List of top 10 genes differentially expressed by 'HISTOLOGICAL_TYPE'

kruskal_wallis_P Q
BID|BID 3.683e-07 7.66e-05
RAD50|RAD50 1.637e-06 0.000134
RAF1|C-RAF 1.93e-06 0.000134
MRE11A|MRE11 3.188e-06 0.000166
ERBB3|HER3_PY1289 4.712e-06 0.000196
BAK1|BAK 1.99e-05 0.000636
TFRC|TFRC 2.14e-05 0.000636
SRC|SRC 0.0002213 0.00481
MET|C-MET_PY1235 0.0002442 0.00481
AR|AR 0.0002455 0.00481
Clinical variable #11: 'RESIDUAL_TUMOR'

30 genes related to 'RESIDUAL_TUMOR'.

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

RESIDUAL_TUMOR Labels N
  R0 363
  R1 2
  R2 29
  RX 19
     
  Significant markers N = 30
List of top 10 genes differentially expressed by 'RESIDUAL_TUMOR'

Table S20.  Get Full Table List of top 10 genes differentially expressed by 'RESIDUAL_TUMOR'

kruskal_wallis_P Q
RBM15|RBM15 2.572e-05 0.00535
EIF4G1|EIF4G 0.0003241 0.0337
PEA15|PEA15 0.0006644 0.0444
ERBB2|HER2_PY1248 0.0009054 0.0444
TSC2|TUBERIN 0.001439 0.0444
EGFR|EGFR_PY1068 0.001685 0.0444
MAPK14|P38_MAPK 0.00174 0.0444
PIK3CA |PI3K-P110-ALPHA 0.001946 0.0444
BRD4|BRD4 0.002008 0.0444
G6PD|G6PD 0.002342 0.0444
Clinical variable #12: 'NUMBER_OF_LYMPH_NODES'

30 genes related to 'NUMBER_OF_LYMPH_NODES'.

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

NUMBER_OF_LYMPH_NODES Mean (SD) 2.14 (4.6)
  Significant markers N = 30
  pos. correlated 14
  neg. correlated 16
List of top 10 genes differentially expressed by 'NUMBER_OF_LYMPH_NODES'

Table S22.  Get Full Table List of top 10 genes significantly correlated to 'NUMBER_OF_LYMPH_NODES' by Spearman correlation test

SpearmanCorr corrP Q
IRS1|IRS1 0.2724 2.854e-09 5.94e-07
GAB2|GAB2 0.2151 3.234e-06 0.000336
EIF4E|EIF4E -0.1872 5.352e-05 0.00286
PXN|PAXILLIN 0.1869 5.497e-05 0.00286
MYC|C-MYC 0.1728 0.0001968 0.00764
BAX|BAX -0.1714 0.0002203 0.00764
CASP7|CASPASE-7_CLEAVEDD198 -0.1685 0.0002823 0.00839
PREX1|PREX1 -0.162 0.0004858 0.0121
DVL3|DVL3 0.1611 0.0005233 0.0121
XRCC1|XRCC1 -0.1576 0.0006913 0.0144
Clinical variable #13: 'RACE'

30 genes related to 'RACE'.

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

RACE Labels N
  AMERICAN INDIAN OR ALASKA NATIVE 1
  ASIAN 12
  BLACK OR AFRICAN AMERICAN 51
  WHITE 246
     
  Significant markers N = 30
List of top 10 genes differentially expressed by 'RACE'

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

kruskal_wallis_P Q
NRAS|N-RAS 0.0003686 0.0506
PRKCB|PKC-PAN_BETAII_PS660 0.0007112 0.0506
MRE11A|MRE11 0.0007293 0.0506
ERBB2|HER2 0.001295 0.0673
PREX1|PREX1 0.002419 0.085
SMAD3|SMAD3 0.002529 0.085
BID|BID 0.003098 0.085
COPS5|JAB1 0.003268 0.085
AKT1S1|PRAS40_PT246 0.004435 0.0934
PEA15|PEA15_PS116 0.004492 0.0934
Methods & Data
Input

  • Expresson data file = COADREAD-TP.rppa.txt

  • Clinical data file = COADREAD-TP.merged_data.txt

  • Number of patients = 488

  • Number of genes = 208

  • Number of clinical features = 13

Selected clinical features

  • Further details on clinical features selected for this analysis, please find a documentation on selected CDEs (Clinical Data Elements). The first column of the file is a formula to convert values and the second column is a clinical parameter name.

  • Survival time data

    • Survival time data is a combined value of days_to_death and days_to_last_followup. For each patient, it creates a combined value 'days_to_death_or_last_fup' using conversion process below.

      • if 'vital_status'==1(dead), 'days_to_last_followup' is always NA. Thus, uses 'days_to_death' value for 'days_to_death_or_fup'

      • if 'vital_status'==0(alive),

        • if 'days_to_death'==NA & 'days_to_last_followup'!=NA, uses 'days_to_last_followup' value for 'days_to_death_or_fup'

        • if 'days_to_death'!=NA, excludes this case in survival analysis and report the case.

      • if 'vital_status'==NA,excludes this case in survival analysis and report the case.

    • cf. In certain diesase types such as SKCM, days_to_death parameter is replaced with time_from_specimen_dx or time_from_specimen_procurement_to_death .

  • This analysis excluded clinical variables that has only NA values.

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

Wilcoxon rank sum test (Mann-Whitney U test)

For two groups (mutant or wild-type) of continuous type of clinical data, wilcoxon rank sum test (Mann and Whitney, 1947) was applied to compare their mean difference using 'wilcox.test(continuous.clinical ~ as.factor(group), exact=FALSE)' function in R. This test is equivalent to the Mann-Whitney test.

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] Mann and Whitney, On a Test of Whether one of Two Random Variables is Stochastically Larger than the Other, Annals of Mathematical Statistics 18 (1), 50-60 (1947)
[4] 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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