Correlation between RPPA expression and clinical features
Head and Neck Squamous Cell Carcinoma (Primary solid tumor)
02 April 2015  |  analyses__2015_04_02
Maintainer Information
Citation Information
doi:10.7908/C1GX49M1
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/C1GX49M1
Overview
Introduction

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

Summary

Testing the association between 160 genes and 12 clinical features across 212 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 9 clinical features related to at least one genes.

  • 2 genes correlated to 'DAYS_TO_DEATH_OR_LAST_FUP'.

    • E2F1|E2F1-M-C ,  FN1|FIBRONECTIN-R-C

  • 26 genes correlated to 'NEOPLASM_DISEASESTAGE'.

    • ARID1A|ARID1A-M-V ,  RPS6|S6_PS240_S244-R-V ,  MAPK1 MAPK3|MAPK_PT202_Y204-R-V ,  CHGA|CHROMOGRANIN-A-N-TERM-R-E ,  MAP2K1|MEK1_PS217_S221-R-V ,  ...

  • 30 genes correlated to 'PATHOLOGY_T_STAGE'.

    • ARID1A|ARID1A-M-V ,  MAPK1 MAPK3|MAPK_PT202_Y204-R-V ,  RPS6|S6_PS240_S244-R-V ,  RPS6|S6_PS235_S236-R-V ,  AKT1 AKT2 AKT3|AKT_PS473-R-V ,  ...

  • 30 genes correlated to 'PATHOLOGY_N_STAGE'.

    • SRC|SRC_PY416-R-C ,  ANXA1|ANNEXIN_I-R-V ,  YAP1|YAP_PS127-R-C ,  MAPK9|JNK2-R-C ,  PRKCA |PKC-ALPHA_PS657-R-V ,  ...

  • 28 genes correlated to 'GENDER'.

    • YAP1|YAP_PS127-R-C ,  MAPK14|P38_PT180_Y182-R-V ,  MAPK1 MAPK3|MAPK_PT202_Y204-R-V ,  RPS6|S6_PS235_S236-R-V ,  BAD|BAD_PS112-R-V ,  ...

  • 29 genes correlated to 'RADIATIONS_RADIATION_REGIMENINDICATION'.

    • BCL2|BCL-2-M-V ,  COL6A1|COLLAGEN_VI-R-V ,  CDKN1B|P27_PT157-R-C ,  TTF1|TTF1-R-V ,  CDKN1B|P27_PT198-R-V ,  ...

  • 4 genes correlated to 'NUMBER_PACK_YEARS_SMOKED'.

    • TP63|P63-R-E ,  CHEK2|CHK2-M-C ,  EZH2|EZH2-R-C ,  CLDN7|CLAUDIN-7-R-V

  • 30 genes correlated to 'NUMBER_OF_LYMPH_NODES'.

    • ANXA1|ANNEXIN_I-R-V ,  SRC|SRC_PY416-R-C ,  YAP1|YAP_PS127-R-C ,  PRKCA |PKC-ALPHA_PS657-R-V ,  FN1|FIBRONECTIN-R-C ,  ...

  • 2 genes correlated to 'RACE'.

    • HSPA1A|HSP70-R-C ,  CDH2|N-CADHERIN-R-V

  • No genes correlated to 'YEARS_TO_BIRTH', 'YEAR_OF_TOBACCO_SMOKING_ONSET', 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=2 shorter survival N=2 longer survival N=0
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=17 lower stage N=13
PATHOLOGY_N_STAGE Spearman correlation test N=30 higher stage N=17 lower stage N=13
GENDER Wilcoxon test N=28 male N=28 female N=0
RADIATIONS_RADIATION_REGIMENINDICATION Wilcoxon test N=29 yes N=29 no N=0
NUMBER_PACK_YEARS_SMOKED Spearman correlation test N=4 higher number_pack_years_smoked N=4 lower number_pack_years_smoked N=0
YEAR_OF_TOBACCO_SMOKING_ONSET Spearman correlation test   N=0        
NUMBER_OF_LYMPH_NODES Spearman correlation test N=30 higher number_of_lymph_nodes N=14 lower number_of_lymph_nodes N=16
RACE Kruskal-Wallis test N=2        
ETHNICITY Wilcoxon test   N=0        
Clinical variable #1: 'DAYS_TO_DEATH_OR_LAST_FUP'

2 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) 0.1-211 (median=20.7)
  censored N = 92
  death N = 119
     
  Significant markers N = 2
  associated with shorter survival 2
  associated with longer survival 0
List of 2 genes differentially expressed by 'DAYS_TO_DEATH_OR_LAST_FUP'

Table S2.  Get Full Table List of 2 genes significantly associated with 'Time to Death' by Cox regression test

HazardRatio Wald_P Q C_index
E2F1|E2F1-M-C 3.6 0.00243 0.26 0.592
FN1|FIBRONECTIN-R-C 1.3 0.003276 0.26 0.599
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) 62.12 (12)
  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 I 9
  STAGE II 39
  STAGE III 31
  STAGE IVA 117
  STAGE IVB 4
     
  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 S6.  Basic characteristics of clinical feature: 'PATHOLOGY_T_STAGE'

PATHOLOGY_T_STAGE Mean (SD) 2.97 (0.97)
  N
  T1 13
  T2 59
  T3 53
  T4 79
     
  Significant markers N = 30
  pos. correlated 17
  neg. correlated 13
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
ARID1A|ARID1A-M-V 0.3335 1.095e-06 0.000175
MAPK1 MAPK3|MAPK_PT202_Y204-R-V -0.2974 1.558e-05 0.00106
RPS6|S6_PS240_S244-R-V -0.292 2.253e-05 0.00106
RPS6|S6_PS235_S236-R-V -0.2897 2.644e-05 0.00106
AKT1 AKT2 AKT3|AKT_PS473-R-V -0.2709 8.895e-05 0.00285
MAPK14|P38_PT180_Y182-R-V -0.2475 0.0003584 0.00956
SRC|SRC_PY527-R-V -0.2423 0.0004812 0.011
CCNB1|CYCLIN_B1-R-V 0.239 0.0005756 0.0115
CDC2|CDK1-R-V 0.2294 0.0009677 0.0172
EIF4EBP1|4E-BP1_PT37T46-R-V -0.2112 0.002422 0.0388
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) 1.09 (0.97)
  N
  N0 72
  N1 21
  N2 79
  N3 4
     
  Significant markers N = 30
  pos. correlated 17
  neg. correlated 13
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
SRC|SRC_PY416-R-C -0.3268 9.593e-06 0.00153
ANXA1|ANNEXIN_I-R-V -0.2868 0.0001137 0.0091
YAP1|YAP_PS127-R-C -0.2743 0.0002296 0.0122
MAPK9|JNK2-R-C 0.2675 0.0003315 0.0133
PRKCA |PKC-ALPHA_PS657-R-V 0.2574 0.0005621 0.0159
SRC|SRC_PY527-R-V -0.2556 0.0006167 0.0159
SYP|SYNAPTOPHYSIN-R-E 0.2532 0.0006964 0.0159
ERBB2|HER2_PY1248-R-V -0.2498 0.0008275 0.0165
LCN2|LCN2A-G-C -0.2283 0.002303 0.0409
PIK3R1 PIK3R2|PI3K-P85-R-V 0.2109 0.004957 0.075
Clinical variable #6: 'GENDER'

28 genes related to 'GENDER'.

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

GENDER Labels N
  FEMALE 62
  MALE 150
     
  Significant markers N = 28
  Higher in MALE 28
  Higher in FEMALE 0
List of top 10 genes differentially expressed by 'GENDER'

Table S11.  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
YAP1|YAP_PS127-R-C 2903 1.719e-05 0.00275 0.6878
MAPK14|P38_PT180_Y182-R-V 3126 0.000177 0.0142 0.6639
MAPK1 MAPK3|MAPK_PT202_Y204-R-V 3207 0.0003847 0.0205 0.6552
RPS6|S6_PS235_S236-R-V 3284 0.000777 0.026 0.6469
BAD|BAD_PS112-R-V 3289 0.0008123 0.026 0.6463
SRC|SRC_PY527-R-V 3354 0.00143 0.0381 0.6394
CLDN7|CLAUDIN-7-R-V 5874 0.002601 0.0579 0.6316
GSK3A GSK3B|GSK3-ALPHA-BETA_PS21_S9-R-V 3451 0.003179 0.0579 0.6289
SRC|SRC_PY416-R-C 3454 0.003256 0.0579 0.6286
AKT1S1|PRAS40_PT246-R-V 3484 0.004123 0.0614 0.6254
Clinical variable #7: 'RADIATIONS_RADIATION_REGIMENINDICATION'

29 genes related to 'RADIATIONS_RADIATION_REGIMENINDICATION'.

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

RADIATIONS_RADIATION_REGIMENINDICATION Labels N
  NO 61
  YES 151
     
  Significant markers N = 29
  Higher in YES 29
  Higher in NO 0
List of top 10 genes differentially expressed by 'RADIATIONS_RADIATION_REGIMENINDICATION'

Table S13.  Get Full Table List of top 10 genes differentially expressed by 'RADIATIONS_RADIATION_REGIMENINDICATION'

W(pos if higher in 'YES') wilcoxontestP Q AUC
BCL2|BCL-2-M-V 2759 4.985e-06 0.000798 0.7005
COL6A1|COLLAGEN_VI-R-V 3254 0.0008342 0.0667 0.6467
CDKN1B|P27_PT157-R-C 3373 0.002312 0.0915 0.6338
TTF1|TTF1-R-V 3390 0.002657 0.0915 0.632
CDKN1B|P27_PT198-R-V 3399 0.002858 0.0915 0.631
STK11|LKB1-M-C 3447 0.004185 0.0977 0.6258
LCK|LCK-R-V 3457 0.004523 0.0977 0.6247
PRKCD|PKC-DELTA_PS664-R-V 3467 0.004886 0.0977 0.6236
BCL2L11|BIM-R-V 3494 0.006002 0.102 0.6207
STMN1|STATHMIN-R-V 3518 0.007182 0.102 0.6181
Clinical variable #8: 'NUMBER_PACK_YEARS_SMOKED'

4 genes related to 'NUMBER_PACK_YEARS_SMOKED'.

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

NUMBER_PACK_YEARS_SMOKED Mean (SD) 48.45 (38)
  Significant markers N = 4
  pos. correlated 4
  neg. correlated 0
List of 4 genes differentially expressed by 'NUMBER_PACK_YEARS_SMOKED'

Table S15.  Get Full Table List of 4 genes significantly correlated to 'NUMBER_PACK_YEARS_SMOKED' by Spearman correlation test

SpearmanCorr corrP Q
TP63|P63-R-E 0.3599 0.0001209 0.0193
CHEK2|CHK2-M-C 0.3366 0.0003447 0.0276
EZH2|EZH2-R-C 0.2583 0.006683 0.297
CLDN7|CLAUDIN-7-R-V 0.2551 0.007419 0.297
Clinical variable #9: 'YEAR_OF_TOBACCO_SMOKING_ONSET'

No gene related to 'YEAR_OF_TOBACCO_SMOKING_ONSET'.

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

YEAR_OF_TOBACCO_SMOKING_ONSET Mean (SD) 1964.54 (12)
  Significant markers N = 0
Clinical variable #10: 'NUMBER_OF_LYMPH_NODES'

30 genes related to 'NUMBER_OF_LYMPH_NODES'.

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

NUMBER_OF_LYMPH_NODES Mean (SD) 2.86 (5.1)
  Significant markers N = 30
  pos. correlated 14
  neg. correlated 16
List of top 10 genes differentially expressed by 'NUMBER_OF_LYMPH_NODES'

Table S18.  Get Full Table List of top 10 genes significantly correlated to 'NUMBER_OF_LYMPH_NODES' by Spearman correlation test

SpearmanCorr corrP Q
ANXA1|ANNEXIN_I-R-V -0.3176 2.437e-05 0.0039
SRC|SRC_PY416-R-C -0.2914 0.0001158 0.00927
YAP1|YAP_PS127-R-C -0.2676 0.0004187 0.0208
PRKCA |PKC-ALPHA_PS657-R-V 0.2594 0.0006366 0.0208
FN1|FIBRONECTIN-R-C 0.2556 0.0007665 0.0208
SYP|SYNAPTOPHYSIN-R-E 0.2553 0.0007787 0.0208
AXL|AXL-M-C 0.2481 0.001105 0.0253
SRC|SRC_PY527-R-V -0.2371 0.001848 0.037
ERBB2|HER2_PY1248-R-V -0.2334 0.002189 0.0389
MAPK9|JNK2-R-C 0.2229 0.003483 0.0557
Clinical variable #11: 'RACE'

2 genes related to 'RACE'.

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

RACE Labels N
  AMERICAN INDIAN OR ALASKA NATIVE 1
  ASIAN 3
  BLACK OR AFRICAN AMERICAN 19
  WHITE 183
     
  Significant markers N = 2
List of 2 genes differentially expressed by 'RACE'

Table S20.  Get Full Table List of 2 genes differentially expressed by 'RACE'

kruskal_wallis_P Q
HSPA1A|HSP70-R-C 0.002213 0.282
CDH2|N-CADHERIN-R-V 0.003522 0.282
Clinical variable #12: 'ETHNICITY'

No gene related to 'ETHNICITY'.

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

ETHNICITY Labels N
  HISPANIC OR LATINO 13
  NOT HISPANIC OR LATINO 190
     
  Significant markers N = 0
Methods & Data
Input

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

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

  • Number of patients = 212

  • Number of genes = 160

  • Number of clinical features = 12

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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