Correlation between RPPA expression and clinical features
Colon Adenocarcinoma (Primary solid tumor)
21 April 2013  |  analyses__2013_04_21
Maintainer Information
Citation Information
doi:10.7908/C13F4MH5
Maintained by Juok Cho (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2013): Colon Adenocarcinoma (Primary solid tumor cohort) - 21 April 2013: Correlation between RPPA expression and clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C13F4MH5
Overview
Introduction

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

Summary

Testing the association between 171 genes and 11 clinical features across 331 samples, statistically thresholded by Q value < 0.05, 7 clinical features related to at least one genes.

  • 3 genes correlated to 'HISTOLOGICAL.TYPE'.

    • RAD50|RAD50-M-C ,  ANXA1|ANNEXIN_I-R-V ,  MRE11A|MRE11-R-C

  • 1 gene correlated to 'PATHOLOGY.T'.

    • PTGS2|COX-2-R-C

  • 1 gene correlated to 'PATHOLOGY.N'.

    • IRS1|IRS1-R-V

  • 1 gene correlated to 'PATHOLOGICSPREAD(M)'.

    • IGFBP2|IGFBP2-R-V

  • 3 genes correlated to 'RADIATIONS.RADIATION.REGIMENINDICATION'.

    • LCK|LCK-R-V ,  SETD2|SETD2-R-NA ,  PECAM1|CD31-M-V

  • 2 genes correlated to 'COMPLETENESS.OF.RESECTION'.

    • NCOA3|AIB1-M-V ,  EGFR|EGFR_PY1068-R-V

  • 1 gene correlated to 'NUMBER.OF.LYMPH.NODES'.

    • IRS1|IRS1-R-V

  • No genes correlated to 'Time to Death', 'AGE', 'GENDER', and 'TUMOR.STAGE'.

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 Q value < 0.05.

Clinical feature Statistical test Significant genes Associated with                 Associated with
Time to Death Cox regression test   N=0        
AGE Spearman correlation test   N=0        
GENDER t test   N=0        
HISTOLOGICAL TYPE t test N=3 colon mucinous adenocarcinoma N=2 colon adenocarcinoma N=1
PATHOLOGY T Spearman correlation test N=1 higher pT N=1 lower pT N=0
PATHOLOGY N Spearman correlation test N=1 higher pN N=1 lower pN N=0
PATHOLOGICSPREAD(M) ANOVA test N=1        
TUMOR STAGE Spearman correlation test   N=0        
RADIATIONS RADIATION REGIMENINDICATION t test N=3 yes N=2 no N=1
COMPLETENESS OF RESECTION ANOVA test N=2        
NUMBER OF LYMPH NODES Spearman correlation test N=1 higher number.of.lymph.nodes N=1 lower number.of.lymph.nodes N=0
Clinical variable #1: 'Time to Death'

No gene related to 'Time to Death'.

Table S1.  Basic characteristics of clinical feature: 'Time to Death'

Time to Death Duration (Months) 0.1-135.5 (median=8)
  censored N = 226
  death N = 40
     
  Significant markers N = 0
Clinical variable #2: 'AGE'

No gene related to 'AGE'.

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

AGE Mean (SD) 67.25 (13)
  Significant markers N = 0
Clinical variable #3: 'GENDER'

No gene related to 'GENDER'.

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

GENDER Labels N
  FEMALE 156
  MALE 175
     
  Significant markers N = 0
Clinical variable #4: 'HISTOLOGICAL.TYPE'

3 genes related to 'HISTOLOGICAL.TYPE'.

Table S4.  Basic characteristics of clinical feature: 'HISTOLOGICAL.TYPE'

HISTOLOGICAL.TYPE Labels N
  COLON ADENOCARCINOMA 290
  COLON MUCINOUS ADENOCARCINOMA 40
     
  Significant markers N = 3
  Higher in COLON MUCINOUS ADENOCARCINOMA 2
  Higher in COLON ADENOCARCINOMA 1
List of 3 genes differentially expressed by 'HISTOLOGICAL.TYPE'

Table S5.  Get Full Table List of 3 genes differentially expressed by 'HISTOLOGICAL.TYPE'

T(pos if higher in 'COLON MUCINOUS ADENOCARCINOMA') ttestP Q AUC
RAD50|RAD50-M-C -4.5 3.564e-05 0.0061 0.7039
ANXA1|ANNEXIN_I-R-V 3.9 0.0002585 0.044 0.689
MRE11A|MRE11-R-C 3.94 0.0002612 0.0441 0.6969

Figure S1.  Get High-res Image As an example, this figure shows the association of RAD50|RAD50-M-C to 'HISTOLOGICAL.TYPE'. P value = 3.56e-05 with T-test analysis.

Clinical variable #5: 'PATHOLOGY.T'

One gene related to 'PATHOLOGY.T'.

Table S6.  Basic characteristics of clinical feature: 'PATHOLOGY.T'

PATHOLOGY.T Mean (SD) 2.91 (0.6)
  N
  T0 1
  T1 5
  T2 53
  T3 232
  T4 37
     
  Significant markers N = 1
  pos. correlated 1
  neg. correlated 0
List of one gene significantly correlated to 'PATHOLOGY.T' by Spearman correlation test

Table S7.  Get Full Table List of one gene significantly correlated to 'PATHOLOGY.T' by Spearman correlation test

SpearmanCorr corrP Q
PTGS2|COX-2-R-C 0.2152 8.518e-05 0.0146

Figure S2.  Get High-res Image As an example, this figure shows the association of PTGS2|COX-2-R-C to 'PATHOLOGY.T'. P value = 8.52e-05 with Spearman correlation analysis.

Clinical variable #6: 'PATHOLOGY.N'

One gene related to 'PATHOLOGY.N'.

Table S8.  Basic characteristics of clinical feature: 'PATHOLOGY.N'

PATHOLOGY.N Mean (SD) 0.57 (0.76)
  N
  N0 196
  N1 80
  N2 54
     
  Significant markers N = 1
  pos. correlated 1
  neg. correlated 0
List of one gene significantly correlated to 'PATHOLOGY.N' by Spearman correlation test

Table S9.  Get Full Table List of one gene significantly correlated to 'PATHOLOGY.N' by Spearman correlation test

SpearmanCorr corrP Q
IRS1|IRS1-R-V 0.2101 0.0001205 0.0206

Figure S3.  Get High-res Image As an example, this figure shows the association of IRS1|IRS1-R-V to 'PATHOLOGY.N'. P value = 0.00012 with Spearman correlation analysis.

Clinical variable #7: 'PATHOLOGICSPREAD(M)'

One gene related to 'PATHOLOGICSPREAD(M)'.

Table S10.  Basic characteristics of clinical feature: 'PATHOLOGICSPREAD(M)'

PATHOLOGICSPREAD(M) Labels N
  M0 258
  M1 36
  M1A 6
  M1B 1
  MX 26
     
  Significant markers N = 1
List of one gene differentially expressed by 'PATHOLOGICSPREAD(M)'

Table S11.  Get Full Table List of one gene differentially expressed by 'PATHOLOGICSPREAD(M)'

ANOVA_P Q
IGFBP2|IGFBP2-R-V 0.000185 0.0316

Figure S4.  Get High-res Image As an example, this figure shows the association of IGFBP2|IGFBP2-R-V to 'PATHOLOGICSPREAD(M)'. P value = 0.000185 with ANOVA analysis.

Clinical variable #8: 'TUMOR.STAGE'

No gene related to 'TUMOR.STAGE'.

Table S12.  Basic characteristics of clinical feature: 'TUMOR.STAGE'

TUMOR.STAGE Mean (SD) 2.42 (0.9)
  N
  Stage 1 47
  Stage 2 135
  Stage 3 98
  Stage 4 43
     
  Significant markers N = 0
Clinical variable #9: 'RADIATIONS.RADIATION.REGIMENINDICATION'

3 genes related to 'RADIATIONS.RADIATION.REGIMENINDICATION'.

Table S13.  Basic characteristics of clinical feature: 'RADIATIONS.RADIATION.REGIMENINDICATION'

RADIATIONS.RADIATION.REGIMENINDICATION Labels N
  NO 3
  YES 328
     
  Significant markers N = 3
  Higher in YES 2
  Higher in NO 1
List of 3 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

Table S14.  Get Full Table List of 3 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

T(pos if higher in 'YES') ttestP Q AUC
LCK|LCK-R-V 9.75 1.296e-18 2.22e-16 0.6972
SETD2|SETD2-R-NA 5.51 9.342e-08 1.59e-05 0.5366
PECAM1|CD31-M-V -10.85 2.531e-07 4.28e-05 0.8049

Figure S5.  Get High-res Image As an example, this figure shows the association of LCK|LCK-R-V to 'RADIATIONS.RADIATION.REGIMENINDICATION'. P value = 1.3e-18 with T-test analysis.

Clinical variable #10: 'COMPLETENESS.OF.RESECTION'

2 genes related to 'COMPLETENESS.OF.RESECTION'.

Table S15.  Basic characteristics of clinical feature: 'COMPLETENESS.OF.RESECTION'

COMPLETENESS.OF.RESECTION Labels N
  R0 239
  R2 16
  RX 16
     
  Significant markers N = 2
List of 2 genes differentially expressed by 'COMPLETENESS.OF.RESECTION'

Table S16.  Get Full Table List of 2 genes differentially expressed by 'COMPLETENESS.OF.RESECTION'

ANOVA_P Q
NCOA3|AIB1-M-V 0.0001266 0.0217
EGFR|EGFR_PY1068-R-V 0.0002002 0.034

Figure S6.  Get High-res Image As an example, this figure shows the association of NCOA3|AIB1-M-V to 'COMPLETENESS.OF.RESECTION'. P value = 0.000127 with ANOVA analysis.

Clinical variable #11: 'NUMBER.OF.LYMPH.NODES'

One gene related to 'NUMBER.OF.LYMPH.NODES'.

Table S17.  Basic characteristics of clinical feature: 'NUMBER.OF.LYMPH.NODES'

NUMBER.OF.LYMPH.NODES Mean (SD) 1.96 (4.5)
  Significant markers N = 1
  pos. correlated 1
  neg. correlated 0
List of one gene significantly correlated to 'NUMBER.OF.LYMPH.NODES' by Spearman correlation test

Table S18.  Get Full Table List of one gene significantly correlated to 'NUMBER.OF.LYMPH.NODES' by Spearman correlation test

SpearmanCorr corrP Q
IRS1|IRS1-R-V 0.2401 1.865e-05 0.00319

Figure S7.  Get High-res Image As an example, this figure shows the association of IRS1|IRS1-R-V to 'NUMBER.OF.LYMPH.NODES'. P value = 1.86e-05 with Spearman correlation analysis. The straight line presents the best linear regression.

Methods & Data
Input

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

  • Clinical data file = COAD-TP.clin.merged.picked.txt

  • Number of patients = 331

  • Number of genes = 171

  • Number of clinical features = 11

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

Student's t-test analysis

For two-class clinical features, two-tailed Student's t test with unequal variance (Lehmann and Romano 2005) was applied to compare the log2-expression levels between the two clinical classes using 't.test' function in R

ANOVA analysis

For multi-class clinical features (ordinal or nominal), one-way analysis of variance (Howell 2002) was applied to compare the log2-expression levels between different clinical classes using 'anova' function in R

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

This is an experimental feature. The full results of the analysis summarized in this report can be downloaded from the TCGA Data Coordination Center.

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] Lehmann and Romano, Testing Statistical Hypotheses (3E ed.), New York: Springer. ISBN 0387988645 (2005)
[4] Howell, D, Statistical Methods for Psychology. (5th ed.), Duxbury Press:324-5 (2002)
[5] 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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