Correlation between RPPA expression and clinical features
Skin Cutaneous Melanoma (Metastatic)
21 August 2015  |  analyses__2015_08_21
Maintainer Information
Citation Information
doi:10.7908/C1Z89BP1
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/C1Z89BP1
Overview
Introduction

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

Summary

Testing the association between 181 genes and 12 clinical features across 169 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 6 clinical features related to at least one genes.

  • 24 genes correlated to 'TIME_FROM_SPECIMEN_DX_TO_DEATH_OR_LAST_FUP'.

    • CDKN1B|P27_PT198 ,  CDKN1B|P27 ,  BCL2L11|BIM ,  MS4A1|CD20 ,  AKT1 AKT2 AKT3|AKT ,  ...

  • 30 genes correlated to 'DAYS_TO_DEATH_OR_LAST_FUP'.

    • CDKN1B|P27 ,  TIGAR|TIGAR ,  EEF2|EEF2 ,  BCL2L11|BIM ,  CDKN1B|P27_PT198 ,  ...

  • 12 genes correlated to 'YEARS_TO_BIRTH'.

    • MAPK1|ERK2 ,  FOXO3|FOXO3A ,  ITGA2|CD49B ,  PGR|PR ,  NRG1|HEREGULIN ,  ...

  • 2 genes correlated to 'PATHOLOGY_N_STAGE'.

    • TGM2|TRANSGLUTAMINASE ,  SMAD1|SMAD1

  • 15 genes correlated to 'MELANOMA_PRIMARY_KNOWN'.

    • TSC2|TUBERIN_PT1462 ,  TGM2|TRANSGLUTAMINASE ,  ARAF|A-RAF_PS299 ,  MAPK1 MAPK3|MAPK_PT202_Y204 ,  MTOR|MTOR_PS2448 ,  ...

  • 30 genes correlated to 'BRESLOW_THICKNESS'.

    • IGFBP2|IGFBP2 ,  ASNS|ASNS ,  SRC|SRC_PY416 ,  PRKCD|PKC-DELTA_PS664 ,  ESR1|ER-ALPHA ,  ...

  • No genes correlated to 'PATHOLOGIC_STAGE', 'PATHOLOGY_T_STAGE', 'PATHOLOGY_M_STAGE', 'MELANOMA_ULCERATION', '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
TIME_FROM_SPECIMEN_DX_TO_DEATH_OR_LAST_FUP Cox regression test N=24 shorter survival N=11 longer survival N=13
DAYS_TO_DEATH_OR_LAST_FUP Cox regression test N=30 shorter survival N=14 longer survival N=16
YEARS_TO_BIRTH Spearman correlation test N=12 older N=4 younger N=8
PATHOLOGIC_STAGE Kruskal-Wallis test   N=0        
PATHOLOGY_T_STAGE Spearman correlation test   N=0        
PATHOLOGY_N_STAGE Spearman correlation test N=2 higher stage N=1 lower stage N=1
PATHOLOGY_M_STAGE Wilcoxon test   N=0        
MELANOMA_ULCERATION Wilcoxon test   N=0        
MELANOMA_PRIMARY_KNOWN Wilcoxon test N=15 yes N=15 no N=0
BRESLOW_THICKNESS Spearman correlation test N=30 higher breslow_thickness N=13 lower breslow_thickness N=17
GENDER Wilcoxon test   N=0        
RADIATION_THERAPY Wilcoxon test   N=0        
Clinical variable #1: 'TIME_FROM_SPECIMEN_DX_TO_DEATH_OR_LAST_FUP'

24 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=53.2)
  censored N = 49
  death N = 71
     
  Significant markers N = 24
  associated with shorter survival 11
  associated with longer survival 13
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

HazardRatio Wald_P Q C_index
CDKN1B|P27_PT198 0.11 0.000614 0.062 0.37
CDKN1B|P27 0.16 0.0006899 0.062 0.369
BCL2L11|BIM 0.35 0.001797 0.11 0.384
MS4A1|CD20 0.23 0.007776 0.19 0.408
AKT1 AKT2 AKT3|AKT 1.9 0.007907 0.19 0.6
YAP1|YAP_PS127 1.68 0.008531 0.19 0.586
GSK3A GSK3B|GSK3_PS9 1.6 0.009187 0.19 0.578
ERBB3|HER3_PY1289 0.12 0.009706 0.19 0.381
MET|C-MET_PY1235 0.09 0.01021 0.19 0.389
TSC2|TUBERIN_PT1462 2 0.01038 0.19 0.568
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=56.6)
  censored N = 70
  death N = 98
     
  Significant markers N = 30
  associated with shorter survival 14
  associated with longer survival 16
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

HazardRatio Wald_P Q C_index
CDKN1B|P27 0.14 2.655e-05 0.0048 0.358
TIGAR|TIGAR 5.2 0.0004287 0.039 0.592
EEF2|EEF2 1.7 0.0007591 0.046 0.622
BCL2L11|BIM 0.44 0.001432 0.065 0.406
CDKN1B|P27_PT198 0.18 0.002274 0.082 0.426
ESR1|ER-ALPHA 0.39 0.006855 0.15 0.412
CCND1|CYCLIN_D1 3.1 0.007265 0.15 0.572
GSK3A GSK3B|GSK3-ALPHA-BETA 2.8 0.007568 0.15 0.583
CASP7|CASPASE-7_CLEAVEDD198 0.78 0.0084 0.15 0.413
RICTOR|RICTOR 0.55 0.008424 0.15 0.422
Clinical variable #3: 'YEARS_TO_BIRTH'

12 genes related to 'YEARS_TO_BIRTH'.

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

YEARS_TO_BIRTH Mean (SD) 55.28 (16)
  Significant markers N = 12
  pos. correlated 4
  neg. correlated 8
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 0.2653 0.0005526 0.1
FOXO3|FOXO3A -0.2366 0.00215 0.195
ITGA2|CD49B -0.2186 0.004672 0.229
PGR|PR -0.2166 0.005066 0.229
NRG1|HEREGULIN -0.2051 0.008042 0.254
IGFBP2|IGFBP2 -0.2038 0.008432 0.254
EIF4EBP1|4E-BP1_PT70 0.1995 0.00996 0.258
RB1|RB_PS807_S811 0.1889 0.01477 0.261
MAPK14|P38_MAPK 0.188 0.01526 0.261
ERBB2|HER2_PY1248 -0.1872 0.01572 0.261
Clinical variable #4: 'PATHOLOGIC_STAGE'

No gene related to 'PATHOLOGIC_STAGE'.

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

PATHOLOGIC_STAGE Labels N
  I OR II NOS 8
  STAGE 0 3
  STAGE I 15
  STAGE IA 8
  STAGE IB 17
  STAGE II 7
  STAGE IIA 5
  STAGE IIB 6
  STAGE IIC 4
  STAGE III 22
  STAGE IIIA 5
  STAGE IIIB 15
  STAGE IIIC 23
  STAGE IV 9
     
  Significant markers N = 0
Clinical variable #5: 'PATHOLOGY_T_STAGE'

No gene related to 'PATHOLOGY_T_STAGE'.

Table S8.  Basic characteristics of clinical feature: 'PATHOLOGY_T_STAGE'

PATHOLOGY_T_STAGE Mean (SD) 2.3 (1.3)
  N
  T0 15
  T1 21
  T2 37
  T3 28
  T4 31
     
  Significant markers N = 0
Clinical variable #6: 'PATHOLOGY_N_STAGE'

2 genes related to 'PATHOLOGY_N_STAGE'.

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

PATHOLOGY_N_STAGE Mean (SD) 0.84 (1.1)
  N
  N0 87
  N1 25
  N2 26
  N3 18
     
  Significant markers N = 2
  pos. correlated 1
  neg. correlated 1
List of 2 genes differentially expressed by 'PATHOLOGY_N_STAGE'

Table S10.  Get Full Table List of 2 genes significantly correlated to 'PATHOLOGY_N_STAGE' by Spearman correlation test

SpearmanCorr corrP Q
TGM2|TRANSGLUTAMINASE 0.3238 3.723e-05 0.00674
SMAD1|SMAD1 -0.2364 0.002972 0.269
Clinical variable #7: 'PATHOLOGY_M_STAGE'

No gene related to 'PATHOLOGY_M_STAGE'.

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

PATHOLOGY_M_STAGE Labels N
  class0 149
  class1 10
     
  Significant markers N = 0
Clinical variable #8: 'MELANOMA_ULCERATION'

No gene related to 'MELANOMA_ULCERATION'.

Table S12.  Basic characteristics of clinical feature: 'MELANOMA_ULCERATION'

MELANOMA_ULCERATION Labels N
  NO 65
  YES 37
     
  Significant markers N = 0
Clinical variable #9: 'MELANOMA_PRIMARY_KNOWN'

15 genes related to 'MELANOMA_PRIMARY_KNOWN'.

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

MELANOMA_PRIMARY_KNOWN Labels N
  NO 25
  YES 144
     
  Significant markers N = 15
  Higher in YES 15
  Higher in NO 0
List of top 10 genes differentially expressed by 'MELANOMA_PRIMARY_KNOWN'

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

W(pos if higher in 'YES') wilcoxontestP Q AUC
TSC2|TUBERIN_PT1462 2493 0.002166 0.206 0.6925
TGM2|TRANSGLUTAMINASE 1155 0.004319 0.206 0.6792
ARAF|A-RAF_PS299 2444 0.004379 0.206 0.6789
MAPK1 MAPK3|MAPK_PT202_Y204 2435 0.00496 0.206 0.6764
MTOR|MTOR_PS2448 2425 0.005686 0.206 0.6736
SRC|SRC_PY527 2411 0.006865 0.207 0.6697
AKT1 AKT2 AKT3|AKT_PS473 2351 0.01478 0.268 0.6531
FOXO3|FOXO3A_PS318_S321 2343 0.0163 0.268 0.6508
PDK1|PDK1_PS241 1260 0.0169 0.268 0.65
ERBB2|HER2_PY1248 1277 0.02069 0.268 0.6453
Clinical variable #10: 'BRESLOW_THICKNESS'

30 genes related to 'BRESLOW_THICKNESS'.

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

BRESLOW_THICKNESS Mean (SD) 3.38 (5.3)
  Significant markers N = 30
  pos. correlated 13
  neg. correlated 17
List of top 10 genes differentially expressed by 'BRESLOW_THICKNESS'

Table S16.  Get Full Table List of top 10 genes significantly correlated to 'BRESLOW_THICKNESS' by Spearman correlation test

SpearmanCorr corrP Q
IGFBP2|IGFBP2 -0.306 0.0007136 0.116
ASNS|ASNS -0.2919 0.001278 0.116
SRC|SRC_PY416 -0.2714 0.002826 0.133
PRKCD|PKC-DELTA_PS664 -0.2669 0.00334 0.133
ESR1|ER-ALPHA -0.2644 0.00367 0.133
MRE11A|MRE11 -0.2501 0.006092 0.156
EIF4EBP1|4E-BP1_PT70 0.2495 0.00622 0.156
GSK3A GSK3B|GSK3-ALPHA-BETA 0.2432 0.007693 0.156
ITGA2|CD49B -0.241 0.00828 0.156
AKT1 AKT2 AKT3|AKT 0.2399 0.008591 0.156
Clinical variable #11: 'GENDER'

No gene related to 'GENDER'.

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

GENDER Labels N
  FEMALE 64
  MALE 105
     
  Significant markers N = 0
Clinical variable #12: 'RADIATION_THERAPY'

No gene related to 'RADIATION_THERAPY'.

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

RADIATION_THERAPY Labels N
  NO 150
  YES 18
     
  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 = 169

  • Number of genes = 181

  • 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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