Correlation between RPPA expression and clinical features
Colon Adenocarcinoma (Primary solid tumor)
21 August 2015  |  analyses__2015_08_21
Maintainer Information
Citation Information
doi:10.7908/C17P8XKZ
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/C17P8XKZ
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 12 clinical features across 357 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 10 clinical features related to at least one genes.

  • 1 gene correlated to 'DAYS_TO_DEATH_OR_LAST_FUP'.

    • EGFR|EGFR

  • 5 genes correlated to 'YEARS_TO_BIRTH'.

    • MYH11|MYH11 ,  SRC|SRC ,  MAP2K1|MEK1_PS217_S221 ,  EGFR|EGFR ,  RB1|RB_PS807_S811

  • 30 genes correlated to 'PATHOLOGIC_STAGE'.

    • CASP7|CASPASE-7_CLEAVEDD198 ,  YAP1|YAP ,  EGFR|EGFR ,  PREX1|PREX1 ,  PXN|PAXILLIN ,  ...

  • 30 genes correlated to 'PATHOLOGY_T_STAGE'.

    • ERRFI1|MIG-6 ,  SERPINE1|PAI-1 ,  SRC|SRC_PY527 ,  NOTCH1|NOTCH1 ,  RB1|RB_PS807_S811 ,  ...

  • 30 genes correlated to 'PATHOLOGY_N_STAGE'.

    • IRS1|IRS1 ,  PREX1|PREX1 ,  BCL2|BCL-2 ,  INPP4B|INPP4B ,  ARID1A|ARID1A ,  ...

  • 3 genes correlated to 'PATHOLOGY_M_STAGE'.

    • CASP7|CASPASE-7_CLEAVEDD198 ,  PREX1|PREX1 ,  CCNE1|CYCLIN_E1

  • 30 genes correlated to 'HISTOLOGICAL_TYPE'.

    • BAK1|BAK ,  MRE11A|MRE11 ,  TFRC|TFRC ,  MET|C-MET_PY1235 ,  RAD50|RAD50 ,  ...

  • 30 genes correlated to 'RESIDUAL_TUMOR'.

    • EIF4G1|EIF4G ,  RBM15|RBM15 ,  G6PD|G6PD ,  ANXA7|ANNEXIN_VII ,  PEA15|PEA15 ,  ...

  • 30 genes correlated to 'NUMBER_OF_LYMPH_NODES'.

    • IRS1|IRS1 ,  PREX1|PREX1 ,  GAB2|GAB2 ,  ARID1A|ARID1A ,  CASP7|CASPASE-7_CLEAVEDD198 ,  ...

  • 29 genes correlated to 'RACE'.

    • PRKCB|PKC-PAN_BETAII_PS660 ,  MRE11A|MRE11 ,  NRAS|N-RAS ,  CDKN1B|P27_PT157 ,  ERBB2|HER2 ,  ...

  • 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=5 older N=3 younger N=2
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=18 lower stage N=12
PATHOLOGY_M_STAGE Wilcoxon test N=3 class1 N=3 class0 N=0
GENDER Wilcoxon test   N=0        
RADIATION_THERAPY Wilcoxon test   N=0        
HISTOLOGICAL_TYPE Wilcoxon test N=30 colon mucinous adenocarcinoma N=30 colon adenocarcinoma N=0
RESIDUAL_TUMOR Kruskal-Wallis test N=30        
NUMBER_OF_LYMPH_NODES Spearman correlation test N=30 higher number_of_lymph_nodes N=18 lower number_of_lymph_nodes N=12
RACE Kruskal-Wallis test N=29        
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=21.8)
  censored N = 280
  death N = 76
     
  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 3.1 0.0001284 0.027 0.608
Clinical variable #2: 'YEARS_TO_BIRTH'

5 genes related to 'YEARS_TO_BIRTH'.

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

YEARS_TO_BIRTH Mean (SD) 66.98 (13)
  Significant markers N = 5
  pos. correlated 3
  neg. correlated 2
List of 5 genes differentially expressed by 'YEARS_TO_BIRTH'

Table S4.  Get Full Table List of 5 genes significantly correlated to 'YEARS_TO_BIRTH' by Spearman correlation test

SpearmanCorr corrP Q
MYH11|MYH11 -0.1702 0.00127 0.173
SRC|SRC -0.1661 0.001665 0.173
MAP2K1|MEK1_PS217_S221 0.1529 0.003823 0.178
EGFR|EGFR 0.1522 0.004006 0.178
RB1|RB_PS807_S811 0.151 0.00429 0.178
Clinical variable #3: 'PATHOLOGIC_STAGE'

30 genes related to 'PATHOLOGIC_STAGE'.

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

PATHOLOGIC_STAGE Labels N
  STAGE I 54
  STAGE IA 1
  STAGE II 20
  STAGE IIA 116
  STAGE IIB 8
  STAGE IIC 1
  STAGE III 18
  STAGE IIIA 7
  STAGE IIIB 49
  STAGE IIIC 33
  STAGE IV 30
  STAGE IVA 15
  STAGE IVB 2
     
  Significant markers N = 30
List of top 10 genes differentially expressed by 'PATHOLOGIC_STAGE'

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

kruskal_wallis_P Q
CASP7|CASPASE-7_CLEAVEDD198 5.299e-05 0.011
YAP1|YAP 0.0008224 0.0855
EGFR|EGFR 0.002484 0.111
PREX1|PREX1 0.002758 0.111
PXN|PAXILLIN 0.00333 0.111
IRS1|IRS1 0.003736 0.111
PRKAA1|AMPK_ALPHA 0.004045 0.111
NOTCH1|NOTCH1 0.004265 0.111
NRG1|HEREGULIN 0.006432 0.149
ERRFI1|MIG-6 0.007446 0.155
Clinical variable #4: 'PATHOLOGY_T_STAGE'

30 genes related to 'PATHOLOGY_T_STAGE'.

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

PATHOLOGY_T_STAGE Mean (SD) 2.93 (0.59)
  N
  T1 6
  T2 58
  T3 247
  T4 45
     
  Significant markers N = 30
  pos. correlated 15
  neg. correlated 15
List of top 10 genes differentially expressed by 'PATHOLOGY_T_STAGE'

Table S8.  Get Full Table List of top 10 genes significantly correlated to 'PATHOLOGY_T_STAGE' by Spearman correlation test

SpearmanCorr corrP Q
ERRFI1|MIG-6 0.2083 7.486e-05 0.0114
SERPINE1|PAI-1 0.2036 0.0001097 0.0114
SRC|SRC_PY527 -0.1574 0.002897 0.135
NOTCH1|NOTCH1 0.1572 0.002932 0.135
RB1|RB_PS807_S811 -0.1536 0.00367 0.135
SETD2|SETD2 0.1476 0.005272 0.135
CDKN1A|P21 0.147 0.005443 0.135
EIF4EBP1|4E-BP1_PT37_T46 -0.147 0.005451 0.135
CHEK2|CHK2 -0.1458 0.005835 0.135
EIF4E|EIF4E -0.1386 0.008821 0.176
Clinical variable #5: 'PATHOLOGY_N_STAGE'

30 genes related to 'PATHOLOGY_N_STAGE'.

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

PATHOLOGY_N_STAGE Mean (SD) 0.59 (0.77)
  N
  N0 209
  N1 85
  N2 63
     
  Significant markers N = 30
  pos. correlated 18
  neg. correlated 12
List of top 10 genes differentially expressed by 'PATHOLOGY_N_STAGE'

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

SpearmanCorr corrP Q
IRS1|IRS1 0.232 9.507e-06 0.00198
PREX1|PREX1 -0.2103 6.221e-05 0.00647
BCL2|BCL-2 -0.1691 0.00134 0.0929
INPP4B|INPP4B 0.1584 0.002688 0.112
ARID1A|ARID1A 0.1644 0.002699 0.112
CASP7|CASPASE-7_CLEAVEDD198 -0.155 0.003318 0.115
EIF4E|EIF4E -0.1501 0.004487 0.133
PXN|PAXILLIN 0.1446 0.006196 0.14
BAX|BAX -0.1435 0.006628 0.14
MYC|C-MYC 0.1432 0.006717 0.14
Clinical variable #6: 'PATHOLOGY_M_STAGE'

3 genes related to 'PATHOLOGY_M_STAGE'.

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

PATHOLOGY_M_STAGE Labels N
  class0 268
  class1 47
     
  Significant markers N = 3
  Higher in class1 3
  Higher in class0 0
List of 3 genes differentially expressed by 'PATHOLOGY_M_STAGE'

Table S12.  Get Full Table List of 3 genes differentially expressed by 'PATHOLOGY_M_STAGE'

W(pos if higher in 'class1') wilcoxontestP Q AUC
CASP7|CASPASE-7_CLEAVEDD198 4044 9.123e-05 0.019 0.6789
PREX1|PREX1 4200 0.0002706 0.0281 0.6666
CCNE1|CYCLIN_E1 4472 0.001526 0.106 0.645
Clinical variable #7: 'GENDER'

No gene related to 'GENDER'.

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

GENDER Labels N
  FEMALE 172
  MALE 185
     
  Significant markers N = 0
Clinical variable #8: 'RADIATION_THERAPY'

No gene related to 'RADIATION_THERAPY'.

Table S14.  Basic characteristics of clinical feature: 'RADIATION_THERAPY'

RADIATION_THERAPY Labels N
  NO 285
  YES 7
     
  Significant markers N = 0
Clinical variable #9: 'HISTOLOGICAL_TYPE'

30 genes related to 'HISTOLOGICAL_TYPE'.

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

HISTOLOGICAL_TYPE Labels N
  COLON ADENOCARCINOMA 312
  COLON MUCINOUS ADENOCARCINOMA 42
     
  Significant markers N = 30
  Higher in COLON MUCINOUS ADENOCARCINOMA 30
  Higher in COLON ADENOCARCINOMA 0
List of top 10 genes differentially expressed by 'HISTOLOGICAL_TYPE'

Table S16.  Get Full Table List of top 10 genes differentially expressed by 'HISTOLOGICAL_TYPE'

W(pos if higher in 'COLON MUCINOUS ADENOCARCINOMA') wilcoxontestP Q AUC
BAK1|BAK 9599 9.931e-07 0.000207 0.7325
MRE11A|MRE11 9507 2.083e-06 0.000217 0.7255
TFRC|TFRC 3779 8.471e-06 0.000587 0.7116
MET|C-MET_PY1235 9261 1.36e-05 0.000689 0.7067
RAD50|RAD50 3870 1.657e-05 0.000689 0.7047
PDK1|PDK1_PS241 3974 3.477e-05 0.00121 0.6967
HSPA1A|HSP70 9075 5.091e-05 0.00151 0.6925
AR|AR 9050 6.04e-05 0.00157 0.6906
SERPINE1|PAI-1 8979 9.73e-05 0.00221 0.6852
XRCC5|KU80 4138 0.000106 0.00221 0.6842
Clinical variable #10: 'RESIDUAL_TUMOR'

30 genes related to 'RESIDUAL_TUMOR'.

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

RESIDUAL_TUMOR Labels N
  R0 265
  R2 17
  RX 16
     
  Significant markers N = 30
List of top 10 genes differentially expressed by 'RESIDUAL_TUMOR'

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

kruskal_wallis_P Q
EIF4G1|EIF4G 5.118e-06 0.00106
RBM15|RBM15 3.987e-05 0.00306
G6PD|G6PD 4.418e-05 0.00306
ANXA7|ANNEXIN_VII 0.0001212 0.0063
PEA15|PEA15 0.0002046 0.00851
ERBB2|HER2_PY1248 0.0004395 0.0152
CDKN1B|P27 0.0005408 0.016
EGFR|EGFR_PY1068 0.0006152 0.016
ACVRL1|ACVRL1 0.000887 0.0186
TSC2|TUBERIN 0.0008963 0.0186
Clinical variable #11: 'NUMBER_OF_LYMPH_NODES'

30 genes related to 'NUMBER_OF_LYMPH_NODES'.

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

NUMBER_OF_LYMPH_NODES Mean (SD) 2.03 (4.4)
  Significant markers N = 30
  pos. correlated 18
  neg. correlated 12
List of top 10 genes differentially expressed by 'NUMBER_OF_LYMPH_NODES'

Table S20.  Get Full Table List of top 10 genes significantly correlated to 'NUMBER_OF_LYMPH_NODES' by Spearman correlation test

SpearmanCorr corrP Q
IRS1|IRS1 0.2641 9.4e-07 0.000196
PREX1|PREX1 -0.2083 0.000123 0.0128
GAB2|GAB2 0.1688 0.001933 0.111
ARID1A|ARID1A 0.1672 0.003094 0.111
CASP7|CASPASE-7_CLEAVEDD198 -0.16 0.003319 0.111
PXN|PAXILLIN 0.16 0.003327 0.111
INPP4B|INPP4B 0.158 0.003749 0.111
XRCC1|XRCC1 -0.1532 0.004945 0.129
BCL2|BCL-2 -0.1478 0.006747 0.143
EIF4E|EIF4E -0.1461 0.007379 0.143
Clinical variable #12: 'RACE'

29 genes related to 'RACE'.

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

RACE Labels N
  AMERICAN INDIAN OR ALASKA NATIVE 1
  ASIAN 11
  BLACK OR AFRICAN AMERICAN 47
  WHITE 181
     
  Significant markers N = 29
List of top 10 genes differentially expressed by 'RACE'

Table S22.  Get Full Table List of top 10 genes differentially expressed by 'RACE'

kruskal_wallis_P Q
PRKCB|PKC-PAN_BETAII_PS660 0.0001837 0.0382
MRE11A|MRE11 0.001595 0.127
NRAS|N-RAS 0.001839 0.127
CDKN1B|P27_PT157 0.002842 0.14
ERBB2|HER2 0.003366 0.14
PREX1|PREX1 0.004991 0.164
BID|BID 0.005819 0.164
AKT1S1|PRAS40_PT246 0.007531 0.164
PRKCA |PKC-ALPHA_PS657 0.008071 0.164
TP53|P53 0.008414 0.164
Methods & Data
Input

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

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

  • Number of patients = 357

  • Number of genes = 208

  • Number of clinical features = 12

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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