Correlation between RPPA expression and clinical features
Skin Cutaneous Melanoma (Metastatic)
15 July 2014  |  analyses__2014_07_15
Maintainer Information
Citation Information
doi:10.7908/C1CJ8C9M
Maintained by Juok Cho (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2014): Correlation between RPPA expression and clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C1CJ8C9M
Overview
Introduction

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

Summary

Testing the association between 181 genes and 12 clinical features across 169 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 6 clinical features related to at least one genes.

  • 6 genes correlated to 'Time from Specimen Diagnosis to Death'.

    • NA|LCK-R-V ,  NA|P27-R-V ,  NA|CASPASE-7_CLEAVEDD198-R-C ,  NA|SYK-M-V ,  NA|P27_PT198-R-V ,  ...

  • 3 genes correlated to 'Time to Death'.

    • NA|P27-R-V ,  NA|TIGAR-R-V ,  NA|EEF2-R-C

  • 1 gene correlated to 'AGE'.

    • NA|ERK2-R-E

  • 6 genes correlated to 'PRIMARY.SITE.OF.DISEASE'.

    • NA|KU80-R-C ,  NA|CASPASE-7_CLEAVEDD198-R-C ,  NA|YB-1-R-V ,  NA|XBP1-G-C ,  NA|LCK-R-V ,  ...

  • 1 gene correlated to 'PATHOLOGY.N.STAGE'.

    • NA|TRANSGLUTAMINASE-M-V

  • 2 genes correlated to 'BRESLOW.THICKNESS'.

    • NA|IGFBP2-R-V ,  NA|ASNS-R-V

  • No genes correlated to 'NEOPLASM.DISEASESTAGE', 'PATHOLOGY.T.STAGE', 'PATHOLOGY.M.STAGE', 'MELANOMA.ULCERATION', 'MELANOMA.PRIMARY.KNOWN', and 'GENDER'.

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
Time from Specimen Diagnosis to Death Cox regression test N=6 shorter survival N=1 longer survival N=5
Time to Death Cox regression test N=3 shorter survival N=2 longer survival N=1
AGE Spearman correlation test N=1 older N=1 younger N=0
PRIMARY SITE OF DISEASE Kruskal-Wallis test N=6        
NEOPLASM DISEASESTAGE Kruskal-Wallis test   N=0        
PATHOLOGY T STAGE Spearman correlation test   N=0        
PATHOLOGY N STAGE Spearman correlation test N=1 higher stage N=1 lower stage N=0
PATHOLOGY M STAGE Kruskal-Wallis test   N=0        
MELANOMA ULCERATION Wilcoxon test   N=0        
MELANOMA PRIMARY KNOWN Wilcoxon test   N=0        
BRESLOW THICKNESS Spearman correlation test N=2 higher breslow.thickness N=0 lower breslow.thickness N=2
GENDER Wilcoxon test   N=0        
Clinical variable #1: 'Time from Specimen Diagnosis to Death'

6 genes related to 'Time from Specimen Diagnosis to Death'.

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

Time from Specimen Diagnosis to Death Duration (Months) 0.2-124.3 (median=14.8)
  censored N = 72
  death N = 89
     
  Significant markers N = 6
  associated with shorter survival 1
  associated with longer survival 5
List of 6 genes differentially expressed by 'Time from Specimen Diagnosis to Death'

Table S2.  Get Full Table List of 6 genes significantly associated with 'Time from Specimen Diagnosis to Death' by Cox regression test

HazardRatio Wald_P Q C_index
NA|LCK-R-V 0.47 3.34e-05 0.006 0.371
NA|P27-R-V 0.14 7.794e-05 0.014 0.356
NA|CASPASE-7_CLEAVEDD198-R-C 0.68 7.996e-05 0.014 0.357
NA|SYK-M-V 0.63 0.0003307 0.059 0.385
NA|P27_PT198-R-V 0.13 0.000511 0.09 0.404
NA|4E-BP1_PS65-R-V 2.6 0.001191 0.21 0.596
Clinical variable #2: 'Time to Death'

3 genes related to 'Time to Death'.

Table S3.  Basic characteristics of clinical feature: 'Time to Death'

Time to Death Duration (Months) 0.2-357.4 (median=50.9)
  censored N = 75
  death N = 90
     
  Significant markers N = 3
  associated with shorter survival 2
  associated with longer survival 1
List of 3 genes differentially expressed by 'Time to Death'

Table S4.  Get Full Table List of 3 genes significantly associated with 'Time to Death' by Cox regression test

HazardRatio Wald_P Q C_index
NA|P27-R-V 0.14 5.799e-05 0.01 0.357
NA|TIGAR-R-V 5.9 0.0001912 0.034 0.595
NA|EEF2-R-C 1.73 0.0008728 0.16 0.629
Clinical variable #3: 'AGE'

One gene related to 'AGE'.

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

AGE Mean (SD) 55.28 (16)
  Significant markers N = 1
  pos. correlated 1
  neg. correlated 0
List of one gene differentially expressed by 'AGE'

Table S6.  Get Full Table List of one gene significantly correlated to 'AGE' by Spearman correlation test

SpearmanCorr corrP Q
NA|ERK2-R-E 0.2653 0.0005526 0.1
Clinical variable #4: 'PRIMARY.SITE.OF.DISEASE'

6 genes related to 'PRIMARY.SITE.OF.DISEASE'.

Table S7.  Basic characteristics of clinical feature: 'PRIMARY.SITE.OF.DISEASE'

PRIMARY.SITE.OF.DISEASE Labels N
  DISTANT METASTASIS 22
  PRIMARY TUMOR 1
  REGIONAL CUTANEOUS OR SUBCUTANEOUS TISSUE 31
  REGIONAL LYMPH NODE 114
     
  Significant markers N = 6
List of 6 genes differentially expressed by 'PRIMARY.SITE.OF.DISEASE'

Table S8.  Get Full Table List of 6 genes differentially expressed by 'PRIMARY.SITE.OF.DISEASE'

ANOVA_P Q
NA|KU80-R-C 2.806e-05 0.00508
NA|CASPASE-7_CLEAVEDD198-R-C 0.0003686 0.0664
NA|YB-1-R-V 0.0004223 0.0756
NA|XBP1-G-C 0.0007175 0.128
NA|LCK-R-V 0.0008404 0.149
NA|AR-R-V 0.001545 0.272
Clinical variable #5: 'NEOPLASM.DISEASESTAGE'

No gene related to 'NEOPLASM.DISEASESTAGE'.

Table S9.  Basic characteristics of clinical feature: 'NEOPLASM.DISEASESTAGE'

NEOPLASM.DISEASESTAGE Labels N
  I OR II NOS 8
  STAGE 0 3
  STAGE I 14
  STAGE IA 8
  STAGE IB 17
  STAGE II 7
  STAGE IIA 5
  STAGE IIB 6
  STAGE IIC 3
  STAGE III 20
  STAGE IIIA 5
  STAGE IIIB 15
  STAGE IIIC 27
  STAGE IV 9
     
  Significant markers N = 0
Clinical variable #6: 'PATHOLOGY.T.STAGE'

No gene related to 'PATHOLOGY.T.STAGE'.

Table S10.  Basic characteristics of clinical feature: 'PATHOLOGY.T.STAGE'

PATHOLOGY.T.STAGE Mean (SD) 2.3 (1.3)
  N
  0 15
  1 21
  2 37
  3 28
  4 31
     
  Significant markers N = 0
Clinical variable #7: 'PATHOLOGY.N.STAGE'

One gene related to 'PATHOLOGY.N.STAGE'.

Table S11.  Basic characteristics of clinical feature: 'PATHOLOGY.N.STAGE'

PATHOLOGY.N.STAGE Mean (SD) 0.88 (1.1)
  N
  0 85
  1 25
  2 25
  3 21
     
  Significant markers N = 1
  pos. correlated 1
  neg. correlated 0
List of one gene differentially expressed by 'PATHOLOGY.N.STAGE'

Table S12.  Get Full Table List of one gene significantly correlated to 'PATHOLOGY.N.STAGE' by Spearman correlation test

SpearmanCorr corrP Q
NA|TRANSGLUTAMINASE-M-V 0.3134 6.798e-05 0.0123
Clinical variable #8: 'PATHOLOGY.M.STAGE'

No gene related to 'PATHOLOGY.M.STAGE'.

Table S13.  Basic characteristics of clinical feature: 'PATHOLOGY.M.STAGE'

PATHOLOGY.M.STAGE Labels N
  M0 149
  M1 4
  M1A 2
  M1B 2
  M1C 2
     
  Significant markers N = 0
Clinical variable #9: 'MELANOMA.ULCERATION'

No gene related to 'MELANOMA.ULCERATION'.

Table S14.  Basic characteristics of clinical feature: 'MELANOMA.ULCERATION'

MELANOMA.ULCERATION Labels N
  NO 65
  YES 37
     
  Significant markers N = 0
Clinical variable #10: 'MELANOMA.PRIMARY.KNOWN'

No gene related to 'MELANOMA.PRIMARY.KNOWN'.

Table S15.  Basic characteristics of clinical feature: 'MELANOMA.PRIMARY.KNOWN'

MELANOMA.PRIMARY.KNOWN Labels N
  NO 25
  YES 144
     
  Significant markers N = 0
Clinical variable #11: 'BRESLOW.THICKNESS'

2 genes related to 'BRESLOW.THICKNESS'.

Table S16.  Basic characteristics of clinical feature: 'BRESLOW.THICKNESS'

BRESLOW.THICKNESS Mean (SD) 3.38 (5.3)
  Significant markers N = 2
  pos. correlated 0
  neg. correlated 2
List of 2 genes differentially expressed by 'BRESLOW.THICKNESS'

Table S17.  Get Full Table List of 2 genes significantly correlated to 'BRESLOW.THICKNESS' by Spearman correlation test

SpearmanCorr corrP Q
NA|IGFBP2-R-V -0.306 0.0007136 0.129
NA|ASNS-R-V -0.2919 0.001278 0.23
Clinical variable #12: 'GENDER'

No gene related to 'GENDER'.

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

GENDER Labels N
  FEMALE 64
  MALE 105
     
  Significant markers N = 0
Methods & Data
Input

  • Expresson data file = SKCM-TM.rppa.txt

  • Clinical data file = SKCM-TM.merged_data.txt

  • Number of patients = 169

  • Number of genes = 181

  • Number of clinical features = 12

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

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

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

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