Correlation between RPPA expression and clinical features
Lung Squamous Cell Carcinoma (Primary solid tumor)
02 April 2015  |  analyses__2015_04_02
Maintainer Information
Citation Information
doi:10.7908/C1D50M1D
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/C1D50M1D
Overview
Introduction

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

Summary

Testing the association between 174 genes and 14 clinical features across 195 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 8 clinical features related to at least one genes.

  • 5 genes correlated to 'DAYS_TO_DEATH_OR_LAST_FUP'.

    • CHEK2|CHK2-M-C ,  FOXO3|FOXO3A_PS318_S321-R-C ,  MSH6|MSH6-R-C ,  CDC2|CDK1-R-V ,  PGR|PR-R-V

  • 30 genes correlated to 'YEARS_TO_BIRTH'.

    • PCNA|PCNA-M-V ,  RAD51|RAD51-M-C ,  CCNE1|CYCLIN_E1-M-V ,  AKT1S1|PRAS40_PT246-R-V ,  WWTR1|TAZ_PS89-R-C ,  ...

  • 26 genes correlated to 'NEOPLASM_DISEASESTAGE'.

    • RPS6|S6_PS235_S236-R-V ,  FRAP1|MTOR_PS2448-R-C ,  RPS6KB1|P70S6K_PT389-R-V ,  MAPK1 MAPK3|MAPK_PT202_Y204-R-V ,  BID|BID-R-C ,  ...

  • 30 genes correlated to 'PATHOLOGY_T_STAGE'.

    • BID|BID-R-C ,  CD49|CD49B-M-V ,  DVL3|DVL3-R-V ,  IRS1|IRS1-R-V ,  FN1|FIBRONECTIN-R-C ,  ...

  • 8 genes correlated to 'PATHOLOGY_N_STAGE'.

    • MAPK1 MAPK3|MAPK_PT202_Y204-R-V ,  STAT3|STAT3_PY705-R-V ,  RPS6|S6_PS235_S236-R-V ,  MAP2K1|MEK1_PS217_S221-R-V ,  JUN|C-JUN_PS73-R-C ,  ...

  • 6 genes correlated to 'KARNOFSKY_PERFORMANCE_SCORE'.

    • CDC2|CDK1-R-V ,  FOXO3|FOXO3A-R-C ,  BIRC2 |CIAP-R-V ,  AKT1S1|PRAS40_PT246-R-V ,  JUN|C-JUN_PS73-R-C ,  ...

  • 10 genes correlated to 'HISTOLOGICAL_TYPE'.

    • ESR1|ER-ALPHA_PS118-R-V ,  NCOA3|AIB1-M-V ,  ARID1A|ARID1A-M-V ,  BCL2L11|BIM-R-V ,  EIF4EBP1|4E-BP1_PT70-R-C ,  ...

  • 7 genes correlated to 'YEAR_OF_TOBACCO_SMOKING_ONSET'.

    • CCNE1|CYCLIN_E1-M-V ,  PCNA|PCNA-M-V ,  SRC|SRC_PY416-R-C ,  CDC2|CDK1-R-V ,  ERBB2|HER2_PY1248-R-V ,  ...

  • No genes correlated to 'GENDER', 'RADIATIONS_RADIATION_REGIMENINDICATION', 'NUMBER_PACK_YEARS_SMOKED', 'COMPLETENESS_OF_RESECTION', '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=5 shorter survival N=3 longer survival N=2
YEARS_TO_BIRTH Spearman correlation test N=30 older N=23 younger N=7
NEOPLASM_DISEASESTAGE Kruskal-Wallis test N=26        
PATHOLOGY_T_STAGE Spearman correlation test N=30 higher stage N=17 lower stage N=13
PATHOLOGY_N_STAGE Spearman correlation test N=8 higher stage N=0 lower stage N=8
GENDER Wilcoxon test   N=0        
KARNOFSKY_PERFORMANCE_SCORE Spearman correlation test N=6 higher score N=2 lower score N=4
HISTOLOGICAL_TYPE Kruskal-Wallis test N=10        
RADIATIONS_RADIATION_REGIMENINDICATION Wilcoxon test   N=0        
NUMBER_PACK_YEARS_SMOKED Spearman correlation test   N=0        
YEAR_OF_TOBACCO_SMOKING_ONSET Spearman correlation test N=7 higher year_of_tobacco_smoking_onset N=4 lower year_of_tobacco_smoking_onset N=3
COMPLETENESS_OF_RESECTION Kruskal-Wallis test   N=0        
RACE Kruskal-Wallis test   N=0        
ETHNICITY Wilcoxon test   N=0        
Clinical variable #1: 'DAYS_TO_DEATH_OR_LAST_FUP'

5 genes 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) 0.1-174.1 (median=22.2)
  censored N = 110
  death N = 84
     
  Significant markers N = 5
  associated with shorter survival 3
  associated with longer survival 2
List of 5 genes differentially expressed by 'DAYS_TO_DEATH_OR_LAST_FUP'

Table S2.  Get Full Table List of 5 genes significantly associated with 'Time to Death' by Cox regression test

HazardRatio Wald_P Q C_index
CHEK2|CHK2-M-C 0.38 0.0002071 0.036 0.372
FOXO3|FOXO3A_PS318_S321-R-C 2.7 0.0008098 0.07 0.608
MSH6|MSH6-R-C 0.6 0.004187 0.22 0.369
CDC2|CDK1-R-V 2.8 0.005696 0.22 0.563
PGR|PR-R-V 3.8 0.006337 0.22 0.578
Clinical variable #2: 'YEARS_TO_BIRTH'

30 genes related to 'YEARS_TO_BIRTH'.

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

YEARS_TO_BIRTH Mean (SD) 67.41 (9.5)
  Significant markers N = 30
  pos. correlated 23
  neg. correlated 7
List of top 10 genes differentially expressed by 'YEARS_TO_BIRTH'

Table S4.  Get Full Table List of top 10 genes significantly correlated to 'YEARS_TO_BIRTH' by Spearman correlation test

SpearmanCorr corrP Q
PCNA|PCNA-M-V -0.3209 7.564e-06 0.00132
RAD51|RAD51-M-C -0.2743 0.0001453 0.0126
CCNE1|CYCLIN_E1-M-V -0.2539 0.0004545 0.0171
AKT1S1|PRAS40_PT246-R-V 0.2532 0.0004724 0.0171
WWTR1|TAZ_PS89-R-C -0.2509 0.0005325 0.0171
AKT1 AKT2 AKT3|AKT_PS473-R-V 0.249 0.0005899 0.0171
ERBB2|HER2_PY1248-R-V 0.2436 0.000782 0.0187
GAB2|GAB2-R-V 0.2417 0.0008595 0.0187
SRC|SRC_PY416-R-C 0.2393 0.0009739 0.0188
BAD|BAD_PS112-R-V 0.2356 0.001173 0.0204
Clinical variable #3: 'NEOPLASM_DISEASESTAGE'

26 genes related to 'NEOPLASM_DISEASESTAGE'.

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

NEOPLASM_DISEASESTAGE Labels N
  STAGE I 1
  STAGE IA 30
  STAGE IB 69
  STAGE II 1
  STAGE IIA 22
  STAGE IIB 34
  STAGE IIIA 23
  STAGE IIIB 13
     
  Significant markers N = 26
List of top 10 genes differentially expressed by 'NEOPLASM_DISEASESTAGE'

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) 1.98 (0.75)
  N
  T1 45
  T2 119
  T3 20
  T4 11
     
  Significant markers N = 30
  pos. correlated 17
  neg. correlated 13
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
BID|BID-R-C 0.2933 3.171e-05 0.00552
CD49|CD49B-M-V 0.2632 0.0002011 0.0127
DVL3|DVL3-R-V 0.2591 0.0002552 0.0127
IRS1|IRS1-R-V 0.2566 0.0002927 0.0127
FN1|FIBRONECTIN-R-C 0.2437 0.0005977 0.02
KDR|VEGFR2-R-V 0.2409 0.0006912 0.02
FRAP1|MTOR_PS2448-R-C -0.237 0.0008496 0.0207
HSPA1A|HSP70-R-C 0.2348 0.0009528 0.0207
RAD51|RAD51-M-C 0.202 0.004626 0.087
MRE11A|MRE11-R-C 0.1992 0.00525 0.087
Clinical variable #5: 'PATHOLOGY_N_STAGE'

8 genes related to 'PATHOLOGY_N_STAGE'.

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

PATHOLOGY_N_STAGE Mean (SD) 0.48 (0.74)
  N
  N0 124
  N1 49
  N2 16
  N3 4
     
  Significant markers N = 8
  pos. correlated 0
  neg. correlated 8
List of 8 genes differentially expressed by 'PATHOLOGY_N_STAGE'

Table S10.  Get Full Table List of 8 genes significantly correlated to 'PATHOLOGY_N_STAGE' by Spearman correlation test

SpearmanCorr corrP Q
MAPK1 MAPK3|MAPK_PT202_Y204-R-V -0.3132 9.235e-06 0.00161
STAT3|STAT3_PY705-R-V -0.2818 7.188e-05 0.00625
RPS6|S6_PS235_S236-R-V -0.2661 0.0001841 0.0107
MAP2K1|MEK1_PS217_S221-R-V -0.2351 0.0009964 0.0433
JUN|C-JUN_PS73-R-C -0.2215 0.001967 0.0684
CAV1|CAVEOLIN-1-R-V -0.2118 0.003101 0.0899
MAPK14|P38_PT180_Y182-R-V -0.2075 0.003781 0.094
FRAP1|MTOR_PS2448-R-C -0.2021 0.004828 0.105
Clinical variable #6: 'GENDER'

No gene related to 'GENDER'.

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

GENDER Labels N
  FEMALE 49
  MALE 146
     
  Significant markers N = 0
Clinical variable #7: 'KARNOFSKY_PERFORMANCE_SCORE'

6 genes related to 'KARNOFSKY_PERFORMANCE_SCORE'.

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

KARNOFSKY_PERFORMANCE_SCORE Mean (SD) 31.71 (40)
  Significant markers N = 6
  pos. correlated 2
  neg. correlated 4
List of 6 genes differentially expressed by 'KARNOFSKY_PERFORMANCE_SCORE'

Table S13.  Get Full Table List of 6 genes significantly correlated to 'KARNOFSKY_PERFORMANCE_SCORE' by Spearman correlation test

SpearmanCorr corrP Q
CDC2|CDK1-R-V -0.5483 0.0006498 0.104
FOXO3|FOXO3A-R-C 0.5254 0.001191 0.104
BIRC2 |CIAP-R-V 0.4989 0.002281 0.132
AKT1S1|PRAS40_PT246-R-V -0.4698 0.004403 0.192
JUN|C-JUN_PS73-R-C -0.4561 0.005888 0.205
EIF4EBP1|4E-BP1_PT37-R-V -0.4339 0.009215 0.267
Clinical variable #8: 'HISTOLOGICAL_TYPE'

10 genes related to 'HISTOLOGICAL_TYPE'.

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

HISTOLOGICAL_TYPE Labels N
  LUNG BASALOID SQUAMOUS CELL CARCINOMA 3
  LUNG PAPILLARY SQUAMOUS CELL CARICNOMA 2
  LUNG SQUAMOUS CELL CARCINOMA- NOT OTHERWISE SPECIFIED (NOS) 190
     
  Significant markers N = 10
List of 10 genes differentially expressed by 'HISTOLOGICAL_TYPE'

Table S15.  Get Full Table List of 10 genes differentially expressed by 'HISTOLOGICAL_TYPE'

kruskal_wallis_P Q
ESR1|ER-ALPHA_PS118-R-V 0.005054 0.28
NCOA3|AIB1-M-V 0.005094 0.28
ARID1A|ARID1A-M-V 0.005875 0.28
BCL2L11|BIM-R-V 0.0107 0.28
EIF4EBP1|4E-BP1_PT70-R-C 0.01185 0.28
CHEK2|CHK2-M-C 0.01291 0.28
CDKN1A|P21-R-C 0.01453 0.28
SMAD1|SMAD1-R-V 0.01483 0.28
KDR|VEGFR2-R-V 0.01553 0.28
CHEK1|CHK1-R-C 0.01607 0.28
Clinical variable #9: 'RADIATIONS_RADIATION_REGIMENINDICATION'

No gene related to 'RADIATIONS_RADIATION_REGIMENINDICATION'.

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

RADIATIONS_RADIATION_REGIMENINDICATION Labels N
  NO 10
  YES 185
     
  Significant markers N = 0
Clinical variable #10: '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) 51.69 (32)
  Significant markers N = 0
Clinical variable #11: 'YEAR_OF_TOBACCO_SMOKING_ONSET'

7 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) 1958.47 (12)
  Significant markers N = 7
  pos. correlated 4
  neg. correlated 3
List of 7 genes differentially expressed by 'YEAR_OF_TOBACCO_SMOKING_ONSET'

Table S19.  Get Full Table List of 7 genes significantly correlated to 'YEAR_OF_TOBACCO_SMOKING_ONSET' by Spearman correlation test

SpearmanCorr corrP Q
CCNE1|CYCLIN_E1-M-V 0.3444 5.623e-05 0.00978
PCNA|PCNA-M-V 0.2738 0.001551 0.122
SRC|SRC_PY416-R-C -0.2664 0.002104 0.122
CDC2|CDK1-R-V -0.2334 0.00731 0.284
ERBB2|HER2_PY1248-R-V -0.2279 0.008835 0.284
CCNB1|CYCLIN_B1-R-V 0.225 0.009781 0.284
MSH6|MSH6-R-C 0.2202 0.01149 0.286
Clinical variable #12: 'COMPLETENESS_OF_RESECTION'

No gene related to 'COMPLETENESS_OF_RESECTION'.

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

COMPLETENESS_OF_RESECTION Labels N
  R0 149
  R1 5
  R2 4
  RX 9
     
  Significant markers N = 0
Clinical variable #13: 'RACE'

No gene related to 'RACE'.

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

RACE Labels N
  ASIAN 3
  BLACK OR AFRICAN AMERICAN 9
  WHITE 147
     
  Significant markers N = 0
Clinical variable #14: 'ETHNICITY'

No gene related to 'ETHNICITY'.

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

ETHNICITY Labels N
  HISPANIC OR LATINO 4
  NOT HISPANIC OR LATINO 120
     
  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 = 195

  • Number of genes = 174

  • Number of clinical features = 14

Selected clinical features

  • For clinical features selected for this analysis and their value conozzle.versions, please find a documentation on selected CDEs .

  • 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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