Correlation between RPPA expression and clinical features
Thyroid Adenocarcinoma (HistologicalType_Follicular)
01 July 2013  |  awg_thca__2013_07_01
Maintainer Information
Citation Information
Maintained by Juok Cho (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2013): Correlation between RPPA expression and clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C1WW7FSF
Overview
Introduction

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

Summary

Testing the association between 175 genes and 11 clinical features across 52 samples, statistically thresholded by Q value < 0.05, 2 clinical features related to at least one genes.

  • 1 gene correlated to 'RADIATIONEXPOSURE'.

    • AKT1S1|PRAS40_PT246-R-V

  • 1 gene correlated to 'NEOPLASM.DISEASESTAGE'.

    • RAF1|C-RAF_PS338-R-C

  • No genes correlated to 'AGE', 'GENDER', 'DISTANT.METASTASIS', 'EXTRATHYROIDAL.EXTENSION', 'LYMPH.NODE.METASTASIS', 'COMPLETENESS.OF.RESECTION', 'NUMBER.OF.LYMPH.NODES', 'MULTIFOCALITY', and 'TUMOR.SIZE'.

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
AGE Spearman correlation test   N=0        
GENDER t test   N=0        
RADIATIONEXPOSURE t test N=1 yes N=0 no N=1
DISTANT METASTASIS ANOVA test   N=0        
EXTRATHYROIDAL EXTENSION ANOVA test   N=0        
LYMPH NODE METASTASIS ANOVA test   N=0        
COMPLETENESS OF RESECTION ANOVA test   N=0        
NUMBER OF LYMPH NODES Spearman correlation test   N=0        
NEOPLASM DISEASESTAGE ANOVA test N=1        
MULTIFOCALITY t test   N=0        
TUMOR SIZE Spearman correlation test   N=0        
Clinical variable #1: 'AGE'

No gene related to 'AGE'.

Table S1.  Basic characteristics of clinical feature: 'AGE'

AGE Mean (SD) 51.62 (15)
  Significant markers N = 0
Clinical variable #2: 'GENDER'

No gene related to 'GENDER'.

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

GENDER Labels N
  FEMALE 40
  MALE 12
     
  Significant markers N = 0
Clinical variable #3: 'RADIATIONEXPOSURE'

One gene related to 'RADIATIONEXPOSURE'.

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

RADIATIONEXPOSURE Labels N
  NO 48
  YES 3
     
  Significant markers N = 1
  Higher in YES 0
  Higher in NO 1
List of one gene differentially expressed by 'RADIATIONEXPOSURE'

Table S4.  Get Full Table List of one gene differentially expressed by 'RADIATIONEXPOSURE'

T(pos if higher in 'YES') ttestP Q AUC
AKT1S1|PRAS40_PT246-R-V -5.7 5.56e-06 0.000973 0.8611

Figure S1.  Get High-res Image As an example, this figure shows the association of AKT1S1|PRAS40_PT246-R-V to 'RADIATIONEXPOSURE'. P value = 5.56e-06 with T-test analysis.

Clinical variable #4: 'DISTANT.METASTASIS'

No gene related to 'DISTANT.METASTASIS'.

Table S5.  Basic characteristics of clinical feature: 'DISTANT.METASTASIS'

DISTANT.METASTASIS Labels N
  M0 16
  M1 2
  MX 34
     
  Significant markers N = 0
Clinical variable #5: 'EXTRATHYROIDAL.EXTENSION'

No gene related to 'EXTRATHYROIDAL.EXTENSION'.

Table S6.  Basic characteristics of clinical feature: 'EXTRATHYROIDAL.EXTENSION'

EXTRATHYROIDAL.EXTENSION Labels N
  MINIMAL (T3) 6
  MODERATE/ADVANCED (T4A) 1
  NONE 45
     
  Significant markers N = 0
Clinical variable #6: 'LYMPH.NODE.METASTASIS'

No gene related to 'LYMPH.NODE.METASTASIS'.

Table S7.  Basic characteristics of clinical feature: 'LYMPH.NODE.METASTASIS'

LYMPH.NODE.METASTASIS Labels N
  N0 33
  N1 1
  N1A 3
  N1B 2
  NX 13
     
  Significant markers N = 0
Clinical variable #7: 'COMPLETENESS.OF.RESECTION'

No gene related to 'COMPLETENESS.OF.RESECTION'.

Table S8.  Basic characteristics of clinical feature: 'COMPLETENESS.OF.RESECTION'

COMPLETENESS.OF.RESECTION Labels N
  R0 44
  R1 2
  RX 6
     
  Significant markers N = 0
Clinical variable #8: 'NUMBER.OF.LYMPH.NODES'

No gene related to 'NUMBER.OF.LYMPH.NODES'.

Table S9.  Basic characteristics of clinical feature: 'NUMBER.OF.LYMPH.NODES'

NUMBER.OF.LYMPH.NODES Mean (SD) 0.66 (1.7)
  Value N
  0 32
  1 1
  4 2
  5 2
  6 1
     
  Significant markers N = 0
Clinical variable #9: 'NEOPLASM.DISEASESTAGE'

One gene related to 'NEOPLASM.DISEASESTAGE'.

Table S10.  Basic characteristics of clinical feature: 'NEOPLASM.DISEASESTAGE'

NEOPLASM.DISEASESTAGE Labels N
  STAGE I 23
  STAGE II 14
  STAGE III 10
  STAGE IVA 2
  STAGE IVC 2
     
  Significant markers N = 1
List of one gene differentially expressed by 'NEOPLASM.DISEASESTAGE'

Table S11.  Get Full Table List of one gene differentially expressed by 'NEOPLASM.DISEASESTAGE'

ANOVA_P Q
RAF1|C-RAF_PS338-R-C 4.582e-05 0.00802

Figure S2.  Get High-res Image As an example, this figure shows the association of RAF1|C-RAF_PS338-R-C to 'NEOPLASM.DISEASESTAGE'. P value = 4.58e-05 with ANOVA analysis.

Clinical variable #10: 'MULTIFOCALITY'

No gene related to 'MULTIFOCALITY'.

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

MULTIFOCALITY Labels N
  MULTIFOCAL 30
  UNIFOCAL 21
     
  Significant markers N = 0
Clinical variable #11: 'TUMOR.SIZE'

No gene related to 'TUMOR.SIZE'.

Table S13.  Basic characteristics of clinical feature: 'TUMOR.SIZE'

TUMOR.SIZE Mean (SD) 3.37 (1.5)
  Significant markers N = 0
Methods & Data
Input
  • Expresson data file = THCA-HistologicalType_Follicular.rppa.txt

  • Clinical data file = THCA-HistologicalType_Follicular.clin.merged.picked.txt

  • Number of patients = 52

  • Number of genes = 175

  • Number of clinical features = 11

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] Spearman, C, The proof and measurement of association between two things, Amer. J. Psychol 15:72-101 (1904)
[2] Lehmann and Romano, Testing Statistical Hypotheses (3E ed.), New York: Springer. ISBN 0387988645 (2005)
[3] Howell, D, Statistical Methods for Psychology. (5th ed.), Duxbury Press:324-5 (2002)
[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)