Correlation between RPPA expression and clinical features
Skin Cutaneous Melanoma (Metastatic)
28 January 2016  |  analyses__2016_01_28
Maintainer Information
Citation Information
doi:10.7908/C1ZC82BW
Maintained by Juok Cho (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2016): Correlation between RPPA expression and clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C1ZC82BW
Overview
Introduction

This pipeline uses various statistical tests to identify RPPAs whose expression levels correlated to selected clinical features. The input file "SKCM-TM.rppa.txt" is generated in the pipeline RPPA_AnnotateWithGene in the stddata run.

Summary

Testing the association between 208 genes and 14 clinical features across 262 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 9 clinical features related to at least one genes.

  • 30 genes correlated to 'TIME_FROM_SPECIMEN_DX_TO_DEATH_OR_LAST_FUP'.

    • CDKN1B|P27 ,  CDKN1B|P27_PT198 ,  IGFBP2|IGFBP2 ,  BCL2L11|BIM ,  KIT|C-KIT ,  ...

  • 30 genes correlated to 'DAYS_TO_DEATH_OR_LAST_FUP'.

    • CDKN1B|P27 ,  FOXO3|FOXO3A ,  YWHAZ|14-3-3_ZETA ,  MAPK1|ERK2 ,  ITGA2|CD49B ,  ...

  • 23 genes correlated to 'YEARS_TO_BIRTH'.

    • MAPK1|ERK2 ,  YWHAZ|14-3-3_ZETA ,  SHC1|SHC_PY317 ,  NOTCH1|NOTCH1 ,  CDK1|CDK1 ,  ...

  • 2 genes correlated to 'PATHOLOGIC_STAGE'.

    • SERPINE1|PAI-1 ,  TGM2|TRANSGLUTAMINASE

  • 10 genes correlated to 'PATHOLOGY_T_STAGE'.

    • MTOR|MTOR_PS2448 ,  ESR1|ER-ALPHA_PS118 ,  TP53BP1|53BP1 ,  TGM2|TRANSGLUTAMINASE ,  SMAD3|SMAD3 ,  ...

  • 3 genes correlated to 'PATHOLOGY_N_STAGE'.

    • TGM2|TRANSGLUTAMINASE ,  YWHAZ|14-3-3_ZETA ,  GATA3|GATA3

  • 1 gene correlated to 'MELANOMA_ULCERATION'.

    • SRC|SRC_PY416

  • 8 genes correlated to 'MELANOMA_PRIMARY_KNOWN'.

    • MTOR|MTOR_PS2448 ,  CDK1|CDK1_PY15 ,  SRC|SRC_PY527 ,  KIT|C-KIT ,  TSC2|TUBERIN_PT1462 ,  ...

  • 14 genes correlated to 'BRESLOW_THICKNESS'.

    • PRKCD|PKC-DELTA_PS664 ,  AXL|AXL ,  SYK|SYK ,  GSK3A GSK3B|GSK3-ALPHA-BETA ,  ASNS|ASNS ,  ...

  • No genes correlated to 'PATHOLOGY_M_STAGE', 'GENDER', 'RADIATION_THERAPY', 'RACE', and 'ETHNICITY'.

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
TIME_FROM_SPECIMEN_DX_TO_DEATH_OR_LAST_FUP Cox regression test N=30   N=NA   N=NA
DAYS_TO_DEATH_OR_LAST_FUP Cox regression test N=30   N=NA   N=NA
YEARS_TO_BIRTH Spearman correlation test N=23 older N=8 younger N=15
PATHOLOGIC_STAGE Kruskal-Wallis test N=2        
PATHOLOGY_T_STAGE Spearman correlation test N=10 higher stage N=4 lower stage N=6
PATHOLOGY_N_STAGE Spearman correlation test N=3 higher stage N=3 lower stage N=0
PATHOLOGY_M_STAGE Wilcoxon test   N=0        
MELANOMA_ULCERATION Wilcoxon test N=1 yes N=1 no N=0
MELANOMA_PRIMARY_KNOWN Wilcoxon test N=8 yes N=8 no N=0
BRESLOW_THICKNESS Spearman correlation test N=14 higher breslow_thickness N=6 lower breslow_thickness N=8
GENDER Wilcoxon test   N=0        
RADIATION_THERAPY Wilcoxon test   N=0        
RACE Wilcoxon test   N=0        
ETHNICITY Wilcoxon test   N=0        
Clinical variable #1: 'TIME_FROM_SPECIMEN_DX_TO_DEATH_OR_LAST_FUP'

30 genes related to 'TIME_FROM_SPECIMEN_DX_TO_DEATH_OR_LAST_FUP'.

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

TIME_FROM_SPECIMEN_DX_TO_DEATH_OR_LAST_FUP Duration (Months) 0.2-346.5 (median=47.4)
  censored N = 92
  death N = 93
     
  Significant markers N = 30
  associated with shorter survival NA
  associated with longer survival NA
List of top 10 genes differentially expressed by 'TIME_FROM_SPECIMEN_DX_TO_DEATH_OR_LAST_FUP'

Table S2.  Get Full Table List of top 10 genes significantly associated with 'Time from Specimen Diagnosis to Death' by Cox regression test. For the survival curves, it compared quantile intervals at c(0, 0.25, 0.50, 0.75, 1) and did not try survival analysis if there is only one interval.

logrank_P Q C_index
CDKN1B|P27 0.000163 0.034 0.374
CDKN1B|P27_PT198 0.000395 0.041 0.405
IGFBP2|IGFBP2 0.000993 0.058 0.389
BCL2L11|BIM 0.00112 0.058 0.368
KIT|C-KIT 0.00142 0.059 0.578
EIF4EBP1|4E-BP1_PT70 0.0017 0.059 0.587
MAPK8|JNK_PT183_PY185 0.00289 0.086 0.488
SERPINE1|PAI-1 0.00382 0.099 0.517
MAP2K1|MEK1_PS217_S221 0.00434 0.1 0.521
CHEK1|CHK1_PS345 0.00577 0.11 0.432
Clinical variable #2: 'DAYS_TO_DEATH_OR_LAST_FUP'

30 genes related to 'DAYS_TO_DEATH_OR_LAST_FUP'.

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

DAYS_TO_DEATH_OR_LAST_FUP Duration (Months) 0.2-369.9 (median=50.4)
  censored N = 128
  death N = 133
     
  Significant markers N = 30
  associated with shorter survival NA
  associated with longer survival NA
List of top 10 genes differentially expressed by 'DAYS_TO_DEATH_OR_LAST_FUP'

Table S4.  Get Full Table List of top 10 genes significantly associated with 'Time to Death' by Cox regression test. For the survival curves, it compared quantile intervals at c(0, 0.25, 0.50, 0.75, 1) and did not try survival analysis if there is only one interval.

logrank_P Q C_index
CDKN1B|P27 1.75e-07 3.7e-05 0.376
FOXO3|FOXO3A 1.68e-05 0.0017 0.417
YWHAZ|14-3-3_ZETA 0.000104 0.0072 0.618
MAPK1|ERK2 0.00019 0.0099 0.579
ITGA2|CD49B 0.0013 0.039 0.41
BCL2L11|BIM 0.00148 0.039 0.399
EIF4EBP1|4E-BP1_PT70 0.00148 0.039 0.567
NOTCH1|NOTCH1 0.00152 0.039 0.462
EEF2K|EEF2K 0.00194 0.045 0.535
MAPK8|JNK_PT183_PY185 0.00243 0.05 0.466
Clinical variable #3: 'YEARS_TO_BIRTH'

23 genes related to 'YEARS_TO_BIRTH'.

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

YEARS_TO_BIRTH Mean (SD) 56.13 (16)
  Significant markers N = 23
  pos. correlated 8
  neg. correlated 15
List of top 10 genes differentially expressed by 'YEARS_TO_BIRTH'

Table S6.  Get Full Table List of top 10 genes significantly correlated to 'YEARS_TO_BIRTH' by Spearman correlation test

SpearmanCorr corrP Q
MAPK1|ERK2 0.2315 0.0001862 0.0382
YWHAZ|14-3-3_ZETA 0.221 0.0003671 0.0382
SHC1|SHC_PY317 -0.2008 0.001235 0.0856
NOTCH1|NOTCH1 -0.1899 0.002278 0.118
CDK1|CDK1 0.1812 0.003623 0.133
EIF4EBP1|4E-BP1_PT70 0.1801 0.003845 0.133
CASP8|CASPASE-8 -0.1758 0.004793 0.142
IGFBP2|IGFBP2 -0.173 0.005511 0.143
AR|AR -0.161 0.00988 0.192
ITGA2|CD49B -0.1599 0.0104 0.192
Clinical variable #4: 'PATHOLOGIC_STAGE'

2 genes related to 'PATHOLOGIC_STAGE'.

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

PATHOLOGIC_STAGE Labels N
  I/II NOS 11
  STAGE 0 4
  STAGE I 18
  STAGE IA 13
  STAGE IB 19
  STAGE II 10
  STAGE IIA 10
  STAGE IIB 11
  STAGE IIC 9
  STAGE III 28
  STAGE IIIA 8
  STAGE IIIB 27
  STAGE IIIC 45
  STAGE IV 18
     
  Significant markers N = 2
List of 2 genes differentially expressed by 'PATHOLOGIC_STAGE'

Table S8.  Get Full Table List of 2 genes differentially expressed by 'PATHOLOGIC_STAGE'

kruskal_wallis_P Q
SERPINE1|PAI-1 0.0003747 0.0779
TGM2|TRANSGLUTAMINASE 0.001359 0.141
Clinical variable #5: 'PATHOLOGY_T_STAGE'

10 genes related to 'PATHOLOGY_T_STAGE'.

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

PATHOLOGY_T_STAGE Mean (SD) 2.39 (1.3)
  N
  T0 19
  T1 31
  T2 46
  T3 52
  T4 46
     
  Significant markers N = 10
  pos. correlated 4
  neg. correlated 6
List of 10 genes differentially expressed by 'PATHOLOGY_T_STAGE'

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

SpearmanCorr corrP Q
MTOR|MTOR_PS2448 0.2431 0.0006356 0.132
ESR1|ER-ALPHA_PS118 -0.2049 0.004156 0.289
TP53BP1|53BP1 -0.2002 0.005135 0.289
TGM2|TRANSGLUTAMINASE -0.1979 0.005678 0.289
SMAD3|SMAD3 -0.1868 0.009123 0.289
CCNE2|CYCLIN_E2 -0.182 0.01108 0.289
MAPK1 MAPK3|MAPK_PT202_Y204 0.1819 0.01113 0.289
GSK3A GSK3B|GSK3-ALPHA-BETA_PS21_S9 0.1801 0.01199 0.289
CASP7|CASPASE-7_CLEAVEDD198 -0.1789 0.01256 0.289
TSC2|TUBERIN_PT1462 0.1764 0.01388 0.289
Clinical variable #6: 'PATHOLOGY_N_STAGE'

3 genes related to 'PATHOLOGY_N_STAGE'.

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

PATHOLOGY_N_STAGE Mean (SD) 0.98 (1.1)
  N
  N0 113
  N1 43
  N2 33
  N3 38
     
  Significant markers N = 3
  pos. correlated 3
  neg. correlated 0
List of 3 genes differentially expressed by 'PATHOLOGY_N_STAGE'

Table S12.  Get Full Table List of 3 genes significantly correlated to 'PATHOLOGY_N_STAGE' by Spearman correlation test

SpearmanCorr corrP Q
TGM2|TRANSGLUTAMINASE 0.2622 6.352e-05 0.0132
YWHAZ|14-3-3_ZETA 0.1924 0.003608 0.259
GATA3|GATA3 0.1917 0.00374 0.259
Clinical variable #7: 'PATHOLOGY_M_STAGE'

No gene related to 'PATHOLOGY_M_STAGE'.

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

PATHOLOGY_M_STAGE Labels N
  class0 220
  class1 19
     
  Significant markers N = 0
Clinical variable #8: 'MELANOMA_ULCERATION'

One gene related to 'MELANOMA_ULCERATION'.

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

MELANOMA_ULCERATION Labels N
  NO 91
  YES 66
     
  Significant markers N = 1
  Higher in YES 1
  Higher in NO 0
List of one gene differentially expressed by 'MELANOMA_ULCERATION'

Table S15.  Get Full Table List of one gene differentially expressed by 'MELANOMA_ULCERATION'

W(pos if higher in 'YES') wilcoxontestP Q AUC
SRC|SRC_PY416 2105 0.001415 0.294 0.6495
Clinical variable #9: 'MELANOMA_PRIMARY_KNOWN'

8 genes related to 'MELANOMA_PRIMARY_KNOWN'.

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

MELANOMA_PRIMARY_KNOWN Labels N
  NO 39
  YES 223
     
  Significant markers N = 8
  Higher in YES 8
  Higher in NO 0
List of 8 genes differentially expressed by 'MELANOMA_PRIMARY_KNOWN'

Table S17.  Get Full Table List of 8 genes differentially expressed by 'MELANOMA_PRIMARY_KNOWN'

W(pos if higher in 'YES') wilcoxontestP Q AUC
MTOR|MTOR_PS2448 5803 0.0008673 0.108 0.6672
CDK1|CDK1_PY15 2593 0.001038 0.108 0.7056
SRC|SRC_PY527 5663 0.002615 0.168 0.6511
KIT|C-KIT 5635 0.003224 0.168 0.6479
TSC2|TUBERIN_PT1462 5541 0.006328 0.219 0.6371
FOXO3|FOXO3A_PS318_S321 5532 0.006735 0.219 0.6361
EIF4EBP1|4E-BP1_PT37_T46 5502 0.008268 0.219 0.6326
MAPK1 MAPK3|MAPK_PT202_Y204 5499 0.008437 0.219 0.6323
Clinical variable #10: 'BRESLOW_THICKNESS'

14 genes related to 'BRESLOW_THICKNESS'.

Table S18.  Basic characteristics of clinical feature: 'BRESLOW_THICKNESS'

BRESLOW_THICKNESS Mean (SD) 3.53 (4.8)
  Significant markers N = 14
  pos. correlated 6
  neg. correlated 8
List of top 10 genes differentially expressed by 'BRESLOW_THICKNESS'

Table S19.  Get Full Table List of top 10 genes significantly correlated to 'BRESLOW_THICKNESS' by Spearman correlation test

SpearmanCorr corrP Q
PRKCD|PKC-DELTA_PS664 -0.248 0.0008464 0.159
AXL|AXL -0.285 0.001531 0.159
SYK|SYK -0.2251 0.002522 0.175
GSK3A GSK3B|GSK3-ALPHA-BETA 0.2152 0.003909 0.186
ASNS|ASNS -0.2072 0.005525 0.186
IGFBP2|IGFBP2 -0.2041 0.006291 0.186
MAPK1|ERK2 0.2006 0.007262 0.186
AR|AR -0.1999 0.007463 0.186
PARK7|DJ-1 0.198 0.008064 0.186
YAP1|YAP 0.189 0.0115 0.235
Clinical variable #11: 'GENDER'

No gene related to 'GENDER'.

Table S20.  Basic characteristics of clinical feature: 'GENDER'

GENDER Labels N
  FEMALE 106
  MALE 156
     
  Significant markers N = 0
Clinical variable #12: 'RADIATION_THERAPY'

No gene related to 'RADIATION_THERAPY'.

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

RADIATION_THERAPY Labels N
  NO 228
  YES 34
     
  Significant markers N = 0
Clinical variable #13: 'RACE'

No gene related to 'RACE'.

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

RACE Labels N
  ASIAN 4
  WHITE 251
     
  Significant markers N = 0
Clinical variable #14: 'ETHNICITY'

No gene related to 'ETHNICITY'.

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

ETHNICITY Labels N
  HISPANIC OR LATINO 5
  NOT HISPANIC OR LATINO 252
     
  Significant markers N = 0
Methods & Data
Input

  • Expresson data file = SKCM-TM.rppa.txt

  • Clinical data file = SKCM-TM.merged_data.txt

  • Number of patients = 262

  • Number of genes = 208

  • Number of clinical features = 14

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, logrank test in univariate Cox regression analysis with proportional hazards model (Andersen and Gill 1982) was used to estimate the P values comparing quantile intervals using the 'coxph' function in R. Kaplan-Meier survival curves were plotted using quantile intervals at c(0, 0.25, 0.50, 0.75, 1). If there is only one interval group, it will not try survival analysis.

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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