Correlation between RPPA expression and clinical features
Pancreatic Adenocarcinoma (Primary solid tumor)
02 April 2015  |  analyses__2015_04_02
Maintainer Information
Citation Information
doi:10.7908/C1CJ8CK6
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/C1CJ8CK6
Overview
Introduction

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

Summary

Testing the association between 192 genes and 13 clinical features across 104 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 6 clinical features related to at least one genes.

  • 30 genes correlated to 'DAYS_TO_DEATH_OR_LAST_FUP'.

    • BAK1|BAK-R-E ,  SERPINE1|PAI-1-M-E ,  IGFBP2|IGFBP2-R-V ,  PRKAA1|AMPK_ALPHA-R-C ,  BID|BID-R-C ,  ...

  • 26 genes correlated to 'NEOPLASM_DISEASESTAGE'.

    • PXN|PAXILLIN-R-C ,  PRDX1|PRDX1-R-V ,  TSC2|TUBERIN-R-E ,  PARK7|DJ-1-R-E ,  ANXA7 |ANNEXIN_VII-M-V ,  ...

  • 30 genes correlated to 'PATHOLOGY_T_STAGE'.

    • ACVRL1|ACVRL1-R-C ,  TP53BP1|53BP1-R-E ,  CHEK2|CHK2_PT68-R-E ,  PXN|PAXILLIN-R-C ,  PRDX1|PRDX1-R-V ,  ...

  • 10 genes correlated to 'GENDER'.

    • MAPK14|P38-R-V ,  BAX|BAX-R-V ,  GAB2|GAB2-R-V ,  PXN|PAXILLIN-R-C ,  PREX1|PREX1-R-E ,  ...

  • 5 genes correlated to 'HISTOLOGICAL_TYPE'.

    • MSH2|MSH2-M-V ,  NOTCH1|NOTCH1-R-V ,  ERBB2|HER2_PY1248-R-C ,  MAPK9|JNK2-R-C ,  NFKB1|NF-KB-P65_PS536-R-C

  • 1 gene correlated to 'YEAR_OF_TOBACCO_SMOKING_ONSET'.

    • EGFR|EGFR-R-V

  • No genes correlated to 'YEARS_TO_BIRTH', 'PATHOLOGY_N_STAGE', 'PATHOLOGY_M_STAGE', 'NUMBER_PACK_YEARS_SMOKED', 'COMPLETENESS_OF_RESECTION', 'NUMBER_OF_LYMPH_NODES', and 'RACE'.

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=30 shorter survival N=20 longer survival N=10
YEARS_TO_BIRTH Spearman correlation test   N=0        
NEOPLASM_DISEASESTAGE Kruskal-Wallis test N=26        
PATHOLOGY_T_STAGE Spearman correlation test N=30 higher stage N=15 lower stage N=15
PATHOLOGY_N_STAGE Wilcoxon test   N=0        
PATHOLOGY_M_STAGE Wilcoxon test   N=0        
GENDER Wilcoxon test N=10 male N=10 female N=0
HISTOLOGICAL_TYPE Kruskal-Wallis test N=5        
NUMBER_PACK_YEARS_SMOKED Spearman correlation test   N=0        
YEAR_OF_TOBACCO_SMOKING_ONSET Spearman correlation test N=1 higher year_of_tobacco_smoking_onset N=0 lower year_of_tobacco_smoking_onset N=1
COMPLETENESS_OF_RESECTION Kruskal-Wallis test   N=0        
NUMBER_OF_LYMPH_NODES Spearman correlation test   N=0        
RACE Kruskal-Wallis test   N=0        
Clinical variable #1: 'DAYS_TO_DEATH_OR_LAST_FUP'

30 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) 0.1-71.7 (median=13.8)
  censored N = 46
  death N = 57
     
  Significant markers N = 30
  associated with shorter survival 20
  associated with longer survival 10
List of top 10 genes differentially expressed by 'DAYS_TO_DEATH_OR_LAST_FUP'

Table S2.  Get Full Table List of top 10 genes significantly associated with 'Time to Death' by Cox regression test

HazardRatio Wald_P Q C_index
BAK1|BAK-R-E 12 3.413e-05 0.0066 0.636
SERPINE1|PAI-1-M-E 1.84 0.0003022 0.023 0.597
IGFBP2|IGFBP2-R-V 0.48 0.0003528 0.023 0.346
PRKAA1|AMPK_ALPHA-R-C 0.14 0.001312 0.056 0.398
BID|BID-R-C 5.8 0.001952 0.056 0.606
FRAP1|MTOR_PS2448-R-C 0.19 0.002405 0.056 0.398
MRE11A|MRE11-R-C 6.2 0.002498 0.056 0.618
RAD51|RAD51-R-V 1.9 0.00306 0.056 0.617
MAPK9|JNK2-R-C 0.2 0.003179 0.056 0.394
EGFR|EGFR_PY1173-R-V 14 0.003237 0.056 0.609
Clinical variable #2: 'YEARS_TO_BIRTH'

No gene related to 'YEARS_TO_BIRTH'.

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

YEARS_TO_BIRTH Mean (SD) 65.98 (11)
  Significant markers N = 0
Clinical variable #3: 'NEOPLASM_DISEASESTAGE'

26 genes related to 'NEOPLASM_DISEASESTAGE'.

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

NEOPLASM_DISEASESTAGE Labels N
  STAGE IA 5
  STAGE IB 7
  STAGE IIA 15
  STAGE IIB 70
  STAGE III 5
  STAGE IV 2
     
  Significant markers N = 26
List of top 10 genes differentially expressed by 'NEOPLASM_DISEASESTAGE'

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

kruskal_wallis_P Q
PXN|PAXILLIN-R-C 0.0001793 0.0344
PRDX1|PRDX1-R-V 0.001407 0.135
TSC2|TUBERIN-R-E 0.002703 0.149
PARK7|DJ-1-R-E 0.0031 0.149
ANXA7 |ANNEXIN_VII-M-V 0.004171 0.149
TP53BP1|53BP1-R-E 0.005391 0.149
PEA15|PEA15_PS116-R-V 0.005927 0.149
STAT5A|STAT5-ALPHA-R-V 0.006869 0.149
RPS6KB1|P70S6K-R-V 0.007154 0.149
ACVRL1|ACVRL1-R-C 0.008118 0.149
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) 2.85 (0.57)
  N
  T1 6
  T2 8
  T3 86
  T4 4
     
  Significant markers N = 30
  pos. correlated 15
  neg. correlated 15
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
ACVRL1|ACVRL1-R-C 0.4101 1.533e-05 0.00294
TP53BP1|53BP1-R-E -0.3904 4.179e-05 0.00401
CHEK2|CHK2_PT68-R-E 0.3575 0.0001945 0.0125
PXN|PAXILLIN-R-C -0.3472 0.0003055 0.0144
PRDX1|PRDX1-R-V 0.3423 0.0003757 0.0144
RB1|RB_PS807_S811-R-V -0.3344 0.0005208 0.0167
CDKN1B|P27_PT198-R-V 0.3213 0.0008838 0.0202
EIF4EBP1|4E-BP1_PS65-R-V -0.3166 0.001058 0.0202
RAF1|C-RAF_PS338-R-E 0.3159 0.001089 0.0202
AKT1 AKT2 AKT3|AKT-R-V -0.3145 0.001149 0.0202
Clinical variable #5: 'PATHOLOGY_N_STAGE'

No gene related to 'PATHOLOGY_N_STAGE'.

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

PATHOLOGY_N_STAGE Labels N
  N0 27
  N1 76
     
  Significant markers N = 0
Clinical variable #6: 'PATHOLOGY_M_STAGE'

No gene related to 'PATHOLOGY_M_STAGE'.

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

PATHOLOGY_M_STAGE Labels N
  class0 47
  class1 2
     
  Significant markers N = 0
Clinical variable #7: 'GENDER'

10 genes related to 'GENDER'.

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

GENDER Labels N
  FEMALE 50
  MALE 54
     
  Significant markers N = 10
  Higher in MALE 10
  Higher in FEMALE 0
List of 10 genes differentially expressed by 'GENDER'

Table S11.  Get Full Table List of 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
MAPK14|P38-R-V 821 0.0005851 0.112 0.6959
BAX|BAX-R-V 859 0.001417 0.126 0.6819
GAB2|GAB2-R-V 1801 0.003379 0.126 0.667
PXN|PAXILLIN-R-C 1793 0.003991 0.126 0.6641
PREX1|PREX1-R-E 908 0.004074 0.126 0.6637
MAPK14|P38_PT180_Y182-R-V 909 0.004158 0.126 0.6633
EIF4E|EIF4E-R-V 914 0.004606 0.126 0.6615
TUBA1B|ACETYL-A-TUBULIN-LYS40-R-C 1763 0.007281 0.158 0.653
CHEK2|CHK2_PT68-R-E 938 0.007424 0.158 0.6526
YBX1|YB-1-R-V 1746 0.01008 0.194 0.6467
Clinical variable #8: 'HISTOLOGICAL_TYPE'

5 genes related to 'HISTOLOGICAL_TYPE'.

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

HISTOLOGICAL_TYPE Labels N
  PANCREAS-ADENOCARCINOMA DUCTAL TYPE 92
  PANCREAS-ADENOCARCINOMA-OTHER SUBTYPE 9
  PANCREAS-COLLOID (MUCINOUS NON-CYSTIC) CARCINOMA 2
     
  Significant markers N = 5
List of 5 genes differentially expressed by 'HISTOLOGICAL_TYPE'

Table S13.  Get Full Table List of 5 genes differentially expressed by 'HISTOLOGICAL_TYPE'

kruskal_wallis_P Q
MSH2|MSH2-M-V 0.003851 0.28
NOTCH1|NOTCH1-R-V 0.004332 0.28
ERBB2|HER2_PY1248-R-C 0.005777 0.28
MAPK9|JNK2-R-C 0.007142 0.28
NFKB1|NF-KB-P65_PS536-R-C 0.007279 0.28
Clinical variable #9: 'NUMBER_PACK_YEARS_SMOKED'

No gene related to 'NUMBER_PACK_YEARS_SMOKED'.

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

NUMBER_PACK_YEARS_SMOKED Mean (SD) 26.71 (17)
  Significant markers N = 0
Clinical variable #10: 'YEAR_OF_TOBACCO_SMOKING_ONSET'

One gene related to 'YEAR_OF_TOBACCO_SMOKING_ONSET'.

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

YEAR_OF_TOBACCO_SMOKING_ONSET Mean (SD) 1969.59 (13)
  Significant markers N = 1
  pos. correlated 0
  neg. correlated 1
List of one gene differentially expressed by 'YEAR_OF_TOBACCO_SMOKING_ONSET'

Table S16.  Get Full Table List of one gene significantly correlated to 'YEAR_OF_TOBACCO_SMOKING_ONSET' by Spearman correlation test

SpearmanCorr corrP Q
EGFR|EGFR-R-V -0.6661 0.0001492 0.0286
Clinical variable #11: 'COMPLETENESS_OF_RESECTION'

No gene related to 'COMPLETENESS_OF_RESECTION'.

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

COMPLETENESS_OF_RESECTION Labels N
  R0 61
  R1 32
  R2 1
  RX 2
     
  Significant markers N = 0
Clinical variable #12: 'NUMBER_OF_LYMPH_NODES'

No gene related to 'NUMBER_OF_LYMPH_NODES'.

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

NUMBER_OF_LYMPH_NODES Mean (SD) 2.94 (3.3)
  Significant markers N = 0
Clinical variable #13: 'RACE'

No gene related to 'RACE'.

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

RACE Labels N
  ASIAN 1
  BLACK OR AFRICAN AMERICAN 4
  WHITE 95
     
  Significant markers N = 0
Methods & Data
Input

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

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

  • Number of patients = 104

  • Number of genes = 192

  • Number of clinical features = 13

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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