Correlation between RPPA expression and clinical features
Lung Squamous Cell Carcinoma (Primary solid tumor)
28 January 2016  |  analyses__2016_01_28
Maintainer Information
Citation Information
doi:10.7908/C1KS6QZS
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/C1KS6QZS
Overview
Introduction

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

Summary

Testing the association between 223 genes and 15 clinical features across 328 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 8 clinical features related to at least one genes.

  • 30 genes correlated to 'YEARS_TO_BIRTH'.

    • PCNA|PCNA ,  ERBB2|HER2_PY1248 ,  TSC2|TUBERIN_PT1462 ,  SRC|SRC_PY416 ,  CCNB1|CYCLIN_B1 ,  ...

  • 26 genes correlated to 'PATHOLOGIC_STAGE'.

    • MTOR|MTOR_PS2448 ,  MAPK1 MAPK3|MAPK_PT202_Y204 ,  CCND1|CYCLIN_D1 ,  RPS6|S6_PS235_S236 ,  JUN|C-JUN_PS73 ,  ...

  • 30 genes correlated to 'PATHOLOGY_T_STAGE'.

    • MTOR|MTOR_PS2448 ,  ITGA2|CD49B ,  MAPK1 MAPK3|MAPK_PT202_Y204 ,  BID|BID ,  PARP1|PARP-AB-3 ,  ...

  • 30 genes correlated to 'PATHOLOGY_N_STAGE'.

    • MAPK1 MAPK3|MAPK_PT202_Y204 ,  RPS6|S6_PS235_S236 ,  STAT3|STAT3_PY705 ,  MTOR|MTOR_PS2448 ,  PDCD4|PDCD4 ,  ...

  • 30 genes correlated to 'GENDER'.

    • PDCD1|PDCD1 ,  GAB2|GAB2 ,  PRKCB|PKC-PAN_BETAII_PS660 ,  GAPDH|GAPDH ,  ACACA|ACC1 ,  ...

  • 26 genes correlated to 'HISTOLOGICAL_TYPE'.

    • MSH2|MSH2 ,  SRSF1|SF2 ,  ARID1A|ARID1A ,  RAD51|RAD51 ,  PARP1|PARP1 ,  ...

  • 2 genes correlated to 'YEAR_OF_TOBACCO_SMOKING_ONSET'.

    • SRC|SRC_PY416 ,  ERRFI1|MIG-6

  • 1 gene correlated to 'RESIDUAL_TUMOR'.

    • GSK3A GSK3B|GSK3-ALPHA-BETA

  • No genes correlated to 'DAYS_TO_DEATH_OR_LAST_FUP', 'PATHOLOGY_M_STAGE', 'RADIATION_THERAPY', 'KARNOFSKY_PERFORMANCE_SCORE', 'NUMBER_PACK_YEARS_SMOKED', '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
DAYS_TO_DEATH_OR_LAST_FUP Cox regression test   N=0        
YEARS_TO_BIRTH Spearman correlation test N=30 older N=21 younger N=9
PATHOLOGIC_STAGE Kruskal-Wallis test N=26        
PATHOLOGY_T_STAGE Spearman correlation test N=30 higher stage N=16 lower stage N=14
PATHOLOGY_N_STAGE Spearman correlation test N=30 higher stage N=9 lower stage N=21
PATHOLOGY_M_STAGE Wilcoxon test   N=0        
GENDER Wilcoxon test N=30 male N=30 female N=0
RADIATION_THERAPY Wilcoxon test   N=0        
KARNOFSKY_PERFORMANCE_SCORE Spearman correlation test   N=0        
HISTOLOGICAL_TYPE Kruskal-Wallis test N=26        
NUMBER_PACK_YEARS_SMOKED Spearman correlation test   N=0        
YEAR_OF_TOBACCO_SMOKING_ONSET Spearman correlation test N=2 higher year_of_tobacco_smoking_onset N=1 lower year_of_tobacco_smoking_onset N=1
RESIDUAL_TUMOR Kruskal-Wallis test N=1        
RACE Kruskal-Wallis test   N=0        
ETHNICITY Wilcoxon test   N=0        
Clinical variable #1: 'DAYS_TO_DEATH_OR_LAST_FUP'

No 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) 0-173.8 (median=23)
  censored N = 190
  death N = 137
     
  Significant markers N = 0
Clinical variable #2: 'YEARS_TO_BIRTH'

30 genes related to 'YEARS_TO_BIRTH'.

Table S2.  Basic characteristics of clinical feature: 'YEARS_TO_BIRTH'

YEARS_TO_BIRTH Mean (SD) 67.05 (9)
  Significant markers N = 30
  pos. correlated 21
  neg. correlated 9
List of top 10 genes differentially expressed by 'YEARS_TO_BIRTH'

Table S3.  Get Full Table List of top 10 genes significantly correlated to 'YEARS_TO_BIRTH' by Spearman correlation test

SpearmanCorr corrP Q
PCNA|PCNA -0.2423 1.171e-05 0.00261
ERBB2|HER2_PY1248 0.2127 0.000126 0.0107
TSC2|TUBERIN_PT1462 0.2102 0.0001519 0.0107
SRC|SRC_PY416 0.207 0.0001924 0.0107
CCNB1|CYCLIN_B1 -0.1915 0.0005721 0.0176
FOXO3|FOXO3A_PS318_S321 0.1907 0.0006039 0.0176
RET|RET_PY905 0.2473 0.0006429 0.0176
AKT1 AKT2 AKT3|AKT_PS473 0.1876 0.0007465 0.0176
JUN|C-JUN_PS73 0.187 0.0007769 0.0176
AKT1S1|PRAS40_PT246 0.1867 0.0007903 0.0176
Clinical variable #3: 'PATHOLOGIC_STAGE'

26 genes related to 'PATHOLOGIC_STAGE'.

Table S4.  Basic characteristics of clinical feature: 'PATHOLOGIC_STAGE'

PATHOLOGIC_STAGE Labels N
  STAGE I 2
  STAGE IA 52
  STAGE IB 101
  STAGE II 3
  STAGE IIA 45
  STAGE IIB 62
  STAGE III 2
  STAGE IIIA 42
  STAGE IIIB 14
  STAGE IV 3
     
  Significant markers N = 26
List of top 10 genes differentially expressed by 'PATHOLOGIC_STAGE'

Table S5.  Get Full Table List of top 10 genes differentially expressed by 'PATHOLOGIC_STAGE'

kruskal_wallis_P Q
MTOR|MTOR_PS2448 6.274e-06 0.000744
MAPK1 MAPK3|MAPK_PT202_Y204 6.674e-06 0.000744
CCND1|CYCLIN_D1 0.0003246 0.0237
RPS6|S6_PS235_S236 0.0004256 0.0237
JUN|C-JUN_PS73 0.00139 0.0545
SRC|SRC_PY527 0.001468 0.0545
BAD|BAD_PS112 0.004504 0.131
SHC1|SHC_PY317 0.004716 0.131
KIT|C-KIT 0.007978 0.179
PDCD4|PDCD4 0.00859 0.179
Clinical variable #4: 'PATHOLOGY_T_STAGE'

30 genes related to 'PATHOLOGY_T_STAGE'.

Table S6.  Basic characteristics of clinical feature: 'PATHOLOGY_T_STAGE'

PATHOLOGY_T_STAGE Mean (SD) 2.03 (0.75)
  N
  T1 70
  T2 193
  T3 49
  T4 16
     
  Significant markers N = 30
  pos. correlated 16
  neg. correlated 14
List of top 10 genes differentially expressed by 'PATHOLOGY_T_STAGE'

Table S7.  Get Full Table List of top 10 genes significantly correlated to 'PATHOLOGY_T_STAGE' by Spearman correlation test

SpearmanCorr corrP Q
MTOR|MTOR_PS2448 -0.268 8.408e-07 0.000188
ITGA2|CD49B 0.2574 2.312e-06 0.000258
MAPK1 MAPK3|MAPK_PT202_Y204 -0.2286 2.916e-05 0.00217
BID|BID 0.2022 0.0002276 0.0127
PARP1|PARP-AB-3 0.2529 0.0003614 0.0137
TSC2|TUBERIN_PT1462 -0.1955 0.0003678 0.0137
SERPINE1|PAI-1 0.1926 0.0004507 0.0144
KIT|C-KIT -0.1876 0.0006367 0.0177
SYP|SYNAPTOPHYSIN -0.2395 0.0007475 0.0185
SRC|SRC_PY527 -0.1743 0.001527 0.031
Clinical variable #5: 'PATHOLOGY_N_STAGE'

30 genes related to 'PATHOLOGY_N_STAGE'.

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

PATHOLOGY_N_STAGE Mean (SD) 0.47 (0.7)
  N
  N0 205
  N1 89
  N2 26
  N3 4
     
  Significant markers N = 30
  pos. correlated 9
  neg. correlated 21
List of top 10 genes differentially expressed by 'PATHOLOGY_N_STAGE'

Table S9.  Get Full Table List of top 10 genes significantly correlated to 'PATHOLOGY_N_STAGE' by Spearman correlation test

SpearmanCorr corrP Q
MAPK1 MAPK3|MAPK_PT202_Y204 -0.2806 2.822e-07 6.29e-05
RPS6|S6_PS235_S236 -0.2382 1.466e-05 0.00163
STAT3|STAT3_PY705 -0.2233 5.011e-05 0.00372
MTOR|MTOR_PS2448 -0.2161 8.82e-05 0.00492
PDCD4|PDCD4 -0.2105 0.0001354 0.00604
MAP2K1|MEK1_PS217_S221 -0.2026 0.0002423 0.009
MAPK14|P38_PT180_Y182 -0.1724 0.001846 0.0577
PCNA|PCNA 0.1694 0.002217 0.0577
PARP1|PARP1 0.2638 0.002327 0.0577
RPS6|S6_PS240_S244 -0.1659 0.002743 0.0612
Clinical variable #6: 'PATHOLOGY_M_STAGE'

No gene related to 'PATHOLOGY_M_STAGE'.

Table S10.  Basic characteristics of clinical feature: 'PATHOLOGY_M_STAGE'

PATHOLOGY_M_STAGE Labels N
  class0 281
  class1 3
     
  Significant markers N = 0
Clinical variable #7: 'GENDER'

30 genes related to 'GENDER'.

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

GENDER Labels N
  FEMALE 80
  MALE 248
     
  Significant markers N = 30
  Higher in MALE 30
  Higher in FEMALE 0
List of top 10 genes differentially expressed by 'GENDER'

Table S12.  Get Full Table List of top 10 genes differentially expressed by 'GENDER'. 0 significant gene(s) located in sex chromosomes is(are) filtered out.

W(pos if higher in 'MALE') wilcoxontestP Q AUC
PDCD1|PDCD1 4827 0.0002569 0.0573 0.6747
GAB2|GAB2 7398 0.0006288 0.0672 0.6271
PRKCB|PKC-PAN_BETAII_PS660 7483 0.0009545 0.0672 0.6228
GAPDH|GAPDH 12267 0.001465 0.0672 0.6183
ACACA|ACC1 12261 0.001506 0.0672 0.618
MTOR|MTOR_PS2448 7683 0.002426 0.0787 0.6128
LCK|LCK 7687 0.00247 0.0787 0.6126
KIT|C-KIT 7812 0.00427 0.119 0.6062
SYK|SYK 7887 0.005854 0.145 0.6025
SQSTM1|P62-LCK-LIGAND 11914 0.006873 0.153 0.6005
Clinical variable #8: 'RADIATION_THERAPY'

No gene related to 'RADIATION_THERAPY'.

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

RADIATION_THERAPY Labels N
  NO 259
  YES 37
     
  Significant markers N = 0
Clinical variable #9: 'KARNOFSKY_PERFORMANCE_SCORE'

No gene related to 'KARNOFSKY_PERFORMANCE_SCORE'.

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

KARNOFSKY_PERFORMANCE_SCORE Mean (SD) 64.09 (40)
  Significant markers N = 0
Clinical variable #10: 'HISTOLOGICAL_TYPE'

26 genes related to 'HISTOLOGICAL_TYPE'.

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

HISTOLOGICAL_TYPE Labels N
  LUNG BASALOID SQUAMOUS CELL CARCINOMA 8
  LUNG PAPILLARY SQUAMOUS CELL CARICNOMA 4
  LUNG SQUAMOUS CELL CARCINOMA- NOT OTHERWISE SPECIFIED (NOS) 316
     
  Significant markers N = 26
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'

kruskal_wallis_P Q
MSH2|MSH2 0.002971 0.253
SRSF1|SF2 0.004413 0.253
ARID1A|ARID1A 0.005078 0.253
RAD51|RAD51 0.005374 0.253
PARP1|PARP1 0.008523 0.253
CHEK2|CHK2 0.009368 0.253
FN1|FIBRONECTIN 0.009522 0.253
KDR|VEGFR2 0.01141 0.253
BCL2L11|BIM 0.01265 0.253
TIGAR|TIGAR 0.01358 0.253
Clinical variable #11: 'NUMBER_PACK_YEARS_SMOKED'

No gene related to 'NUMBER_PACK_YEARS_SMOKED'.

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

NUMBER_PACK_YEARS_SMOKED Mean (SD) 50.5 (30)
  Significant markers N = 0
Clinical variable #12: 'YEAR_OF_TOBACCO_SMOKING_ONSET'

2 genes related to 'YEAR_OF_TOBACCO_SMOKING_ONSET'.

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

YEAR_OF_TOBACCO_SMOKING_ONSET Mean (SD) 1960.88 (12)
  Significant markers N = 2
  pos. correlated 1
  neg. correlated 1
List of 2 genes differentially expressed by 'YEAR_OF_TOBACCO_SMOKING_ONSET'

Table S19.  Get Full Table List of 2 genes significantly correlated to 'YEAR_OF_TOBACCO_SMOKING_ONSET' by Spearman correlation test

SpearmanCorr corrP Q
SRC|SRC_PY416 -0.2299 0.0007867 0.175
ERRFI1|MIG-6 0.2084 0.002407 0.268
Clinical variable #13: 'RESIDUAL_TUMOR'

One gene related to 'RESIDUAL_TUMOR'.

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

RESIDUAL_TUMOR Labels N
  R0 257
  R1 7
  R2 4
  RX 12
     
  Significant markers N = 1
List of one gene differentially expressed by 'RESIDUAL_TUMOR'

Table S21.  Get Full Table List of one gene differentially expressed by 'RESIDUAL_TUMOR'

kruskal_wallis_P Q
GSK3A GSK3B|GSK3-ALPHA-BETA 0.00122 0.272
Clinical variable #14: 'RACE'

No gene related to 'RACE'.

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

RACE Labels N
  ASIAN 6
  BLACK OR AFRICAN AMERICAN 19
  WHITE 242
     
  Significant markers N = 0
Clinical variable #15: 'ETHNICITY'

No gene related to 'ETHNICITY'.

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

ETHNICITY Labels N
  HISPANIC OR LATINO 4
  NOT HISPANIC OR LATINO 213
     
  Significant markers N = 0
Methods & Data
Input

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

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

  • Number of patients = 328

  • Number of genes = 223

  • Number of clinical features = 15

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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