Correlation between mRNAseq expression and clinical features
Skin Cutaneous Melanoma (Metastatic)
23 September 2013  |  analyses__2013_09_23
Maintainer Information
Citation Information
doi:10.7908/C1XG9PHP
Maintained by Juok Cho (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2013): Correlation between mRNAseq expression and clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C1XG9PHP
Overview
Introduction

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

Summary

Testing the association between 18091 genes and 11 clinical features across 241 samples, statistically thresholded by Q value < 0.05, 9 clinical features related to at least one genes.

  • 9 genes correlated to 'Time to Death'.

    • CCDC104|112942 ,  GATAD2A|54815 ,  ZNF25|219749 ,  MED7|9443 ,  PRKAR2B|5577 ,  ...

  • 8 genes correlated to 'AGE'.

    • ACOX2|8309 ,  MAOB|4129 ,  PHKA1|5255 ,  MGST2|4258 ,  CMBL|134147 ,  ...

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

    • TMEM156|80008 ,  EXOC3|11336 ,  CD38|952 ,  SLC3A1|6519 ,  POU2AF1|5450 ,  ...

  • 1 gene correlated to 'PATHOLOGY.T.STAGE'.

    • GBP4|115361

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

    • LRRC28|123355

  • 1 gene correlated to 'MELANOMA.ULCERATION'.

    • CDKL2|8999

  • 4 genes correlated to 'MELANOMA.PRIMARY.KNOWN'.

    • C4ORF36|132989 ,  FBXW12|285231 ,  C3ORF16|389161 ,  DEC1|50514

  • 5 genes correlated to 'BRESLOW.THICKNESS'.

    • REEP6|92840 ,  GBP4|115361 ,  C6ORF218|221718 ,  TNFSF13B|10673 ,  GCNT1|2650

  • 23 genes correlated to 'GENDER'.

    • ZFY|7544 ,  PRKY|5616 ,  XIST|7503 ,  RPS4Y1|6192 ,  DDX3Y|8653 ,  ...

  • No genes correlated to 'NEOPLASM.DISEASESTAGE', and 'PATHOLOGY.N.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=9 shorter survival N=1 longer survival N=8
AGE Spearman correlation test N=8 older N=0 younger N=8
PRIMARY SITE OF DISEASE ANOVA test N=52        
NEOPLASM DISEASESTAGE ANOVA test   N=0        
PATHOLOGY T STAGE Spearman correlation test N=1 higher stage N=0 lower stage N=1
PATHOLOGY N STAGE Spearman correlation test   N=0        
PATHOLOGY M STAGE ANOVA test N=1        
MELANOMA ULCERATION t test N=1 yes N=1 no N=0
MELANOMA PRIMARY KNOWN t test N=4 yes N=3 no N=1
BRESLOW THICKNESS Spearman correlation test N=5 higher breslow.thickness N=2 lower breslow.thickness N=3
GENDER t test N=23 male N=14 female N=9
Clinical variable #1: 'Time to Death'

9 genes related to 'Time to Death'.

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

Time to Death Duration (Months) 0.2-357.4 (median=48.9)
  censored N = 121
  death N = 114
     
  Significant markers N = 9
  associated with shorter survival 1
  associated with longer survival 8
List of 9 genes significantly associated with 'Time to Death' by Cox regression test

Table S2.  Get Full Table List of 9 genes significantly associated with 'Time to Death' by Cox regression test

HazardRatio Wald_P Q C_index
CCDC104|112942 0.54 3.334e-07 0.006 0.391
GATAD2A|54815 2.8 7.399e-07 0.013 0.634
ZNF25|219749 0.65 1.043e-06 0.019 0.378
MED7|9443 0.46 1.09e-06 0.02 0.394
PRKAR2B|5577 0.74 1.429e-06 0.026 0.369
METT5D1|196074 0.52 1.753e-06 0.032 0.39
C21ORF7|56911 0.7 1.901e-06 0.034 0.374
C11ORF58|10944 0.47 1.982e-06 0.036 0.416
C4ORF52|389203 0.72 2.01e-06 0.036 0.384

Figure S1.  Get High-res Image As an example, this figure shows the association of CCDC104|112942 to 'Time to Death'. four curves present the cumulative survival rates of 4 quartile subsets of patients. P value = 3.33e-07 with univariate Cox regression analysis using continuous log-2 expression values.

Clinical variable #2: 'AGE'

8 genes related to 'AGE'.

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

AGE Mean (SD) 55.53 (16)
  Significant markers N = 8
  pos. correlated 0
  neg. correlated 8
List of 8 genes significantly correlated to 'AGE' by Spearman correlation test

Table S4.  Get Full Table List of 8 genes significantly correlated to 'AGE' by Spearman correlation test

SpearmanCorr corrP Q
ACOX2|8309 -0.3627 8.835e-09 0.00016
MAOB|4129 -0.332 1.664e-07 0.00301
PHKA1|5255 -0.322 4.04e-07 0.00731
MGST2|4258 -0.3181 5.679e-07 0.0103
CMBL|134147 -0.3175 5.975e-07 0.0108
MCHR1|2847 -0.3043 2.113e-06 0.0382
FAM84B|157638 -0.3023 2.133e-06 0.0386
PPP1R1B|84152 -0.3151 2.299e-06 0.0416

Figure S2.  Get High-res Image As an example, this figure shows the association of ACOX2|8309 to 'AGE'. P value = 8.84e-09 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #3: 'PRIMARY.SITE.OF.DISEASE'

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

Table S5.  Basic characteristics of clinical feature: 'PRIMARY.SITE.OF.DISEASE'

PRIMARY.SITE.OF.DISEASE Labels N
  DISTANT METASTASIS 32
  PRIMARY TUMOR 1
  REGIONAL CUTANEOUS OR SUBCUTANEOUS TISSUE 49
  REGIONAL LYMPH NODE 158
     
  Significant markers N = 52
List of top 10 genes differentially expressed by 'PRIMARY.SITE.OF.DISEASE'

Table S6.  Get Full Table List of top 10 genes differentially expressed by 'PRIMARY.SITE.OF.DISEASE'

ANOVA_P Q
TMEM156|80008 1.703e-09 3.08e-05
EXOC3|11336 3.003e-09 5.43e-05
CD38|952 4.319e-09 7.81e-05
SLC3A1|6519 5.582e-09 0.000101
POU2AF1|5450 7.096e-09 0.000128
IGJ|3512 1.025e-08 0.000185
MYO7B|4648 1.316e-08 0.000238
FOXF1|2294 1.513e-08 0.000274
FCRL5|83416 1.804e-08 0.000326
MGC29506|51237 7.256e-08 0.00131

Figure S3.  Get High-res Image As an example, this figure shows the association of TMEM156|80008 to 'PRIMARY.SITE.OF.DISEASE'. P value = 1.7e-09 with ANOVA analysis.

Clinical variable #4: 'NEOPLASM.DISEASESTAGE'

No gene related to 'NEOPLASM.DISEASESTAGE'.

Table S7.  Basic characteristics of clinical feature: 'NEOPLASM.DISEASESTAGE'

NEOPLASM.DISEASESTAGE Labels N
  I OR II NOS 9
  STAGE 0 4
  STAGE I 20
  STAGE IA 10
  STAGE IB 22
  STAGE II 17
  STAGE IIA 10
  STAGE IIB 12
  STAGE IIC 9
  STAGE III 20
  STAGE IIIA 10
  STAGE IIIB 20
  STAGE IIIC 39
  STAGE IV 10
     
  Significant markers N = 0
Clinical variable #5: 'PATHOLOGY.T.STAGE'

One gene related to 'PATHOLOGY.T.STAGE'.

Table S8.  Basic characteristics of clinical feature: 'PATHOLOGY.T.STAGE'

PATHOLOGY.T.STAGE Mean (SD) 2.46 (1.2)
  N
  0 14
  1 28
  2 54
  3 46
  4 49
     
  Significant markers N = 1
  pos. correlated 0
  neg. correlated 1
List of one gene significantly correlated to 'PATHOLOGY.T.STAGE' by Spearman correlation test

Table S9.  Get Full Table List of one gene significantly correlated to 'PATHOLOGY.T.STAGE' by Spearman correlation test

SpearmanCorr corrP Q
GBP4|115361 -0.3504 6.723e-07 0.0122

Figure S4.  Get High-res Image As an example, this figure shows the association of GBP4|115361 to 'PATHOLOGY.T.STAGE'. P value = 6.72e-07 with Spearman correlation analysis.

Clinical variable #6: 'PATHOLOGY.N.STAGE'

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

Table S10.  Basic characteristics of clinical feature: 'PATHOLOGY.N.STAGE'

PATHOLOGY.N.STAGE Mean (SD) 0.8 (1.1)
  N
  0 127
  1 39
  2 27
  3 28
     
  Significant markers N = 0
Clinical variable #7: 'PATHOLOGY.M.STAGE'

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

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

PATHOLOGY.M.STAGE Labels N
  M0 212
  M1 3
  M1A 2
  M1B 2
  M1C 5
     
  Significant markers N = 1
List of one gene differentially expressed by 'PATHOLOGY.M.STAGE'

Table S12.  Get Full Table List of one gene differentially expressed by 'PATHOLOGY.M.STAGE'

ANOVA_P Q
LRRC28|123355 2.295e-07 0.00415

Figure S5.  Get High-res Image As an example, this figure shows the association of LRRC28|123355 to 'PATHOLOGY.M.STAGE'. P value = 2.3e-07 with ANOVA analysis.

Clinical variable #8: 'MELANOMA.ULCERATION'

One gene related to 'MELANOMA.ULCERATION'.

Table S13.  Basic characteristics of clinical feature: 'MELANOMA.ULCERATION'

MELANOMA.ULCERATION Labels N
  NO 91
  YES 61
     
  Significant markers N = 1
  Higher in YES 1
  Higher in NO 0
List of one gene differentially expressed by 'MELANOMA.ULCERATION'

Table S14.  Get Full Table List of one gene differentially expressed by 'MELANOMA.ULCERATION'

T(pos if higher in 'YES') ttestP Q AUC
CDKL2|8999 4.93 2.499e-06 0.0452 0.7222

Figure S6.  Get High-res Image As an example, this figure shows the association of CDKL2|8999 to 'MELANOMA.ULCERATION'. P value = 2.5e-06 with T-test analysis.

Clinical variable #9: 'MELANOMA.PRIMARY.KNOWN'

4 genes related to 'MELANOMA.PRIMARY.KNOWN'.

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

MELANOMA.PRIMARY.KNOWN Labels N
  NO 30
  YES 211
     
  Significant markers N = 4
  Higher in YES 3
  Higher in NO 1
List of 4 genes differentially expressed by 'MELANOMA.PRIMARY.KNOWN'

Table S16.  Get Full Table List of 4 genes differentially expressed by 'MELANOMA.PRIMARY.KNOWN'

T(pos if higher in 'YES') ttestP Q AUC
C4ORF36|132989 -5.96 1.271e-07 0.0023 0.7315
FBXW12|285231 5.81 5.576e-07 0.0101 0.7588
C3ORF16|389161 5.68 6.098e-07 0.011 0.7154
DEC1|50514 6.03 7.983e-07 0.0144 0.8127

Figure S7.  Get High-res Image As an example, this figure shows the association of C4ORF36|132989 to 'MELANOMA.PRIMARY.KNOWN'. P value = 1.27e-07 with T-test analysis.

Clinical variable #10: 'BRESLOW.THICKNESS'

5 genes related to 'BRESLOW.THICKNESS'.

Table S17.  Basic characteristics of clinical feature: 'BRESLOW.THICKNESS'

BRESLOW.THICKNESS Mean (SD) 3.55 (5.2)
  Significant markers N = 5
  pos. correlated 2
  neg. correlated 3
List of 5 genes significantly correlated to 'BRESLOW.THICKNESS' by Spearman correlation test

Table S18.  Get Full Table List of 5 genes significantly correlated to 'BRESLOW.THICKNESS' by Spearman correlation test

SpearmanCorr corrP Q
REEP6|92840 0.3768 1.853e-07 0.00335
GBP4|115361 -0.3679 3.752e-07 0.00679
C6ORF218|221718 0.3524 1.31e-06 0.0237
TNFSF13B|10673 -0.3473 1.778e-06 0.0322
GCNT1|2650 -0.3473 1.78e-06 0.0322

Figure S8.  Get High-res Image As an example, this figure shows the association of REEP6|92840 to 'BRESLOW.THICKNESS'. P value = 1.85e-07 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #11: 'GENDER'

23 genes related to 'GENDER'.

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

GENDER Labels N
  FEMALE 95
  MALE 146
     
  Significant markers N = 23
  Higher in MALE 14
  Higher in FEMALE 9
List of top 10 genes differentially expressed by 'GENDER'

Table S20.  Get Full Table List of top 10 genes differentially expressed by 'GENDER'

T(pos if higher in 'MALE') ttestP Q AUC
ZFY|7544 41.11 4.989e-102 9.02e-98 0.9989
PRKY|5616 34.16 8.426e-83 1.52e-78 0.9993
XIST|7503 -23.81 9.189e-61 1.66e-56 0.966
RPS4Y1|6192 34.36 1.502e-59 2.72e-55 1
DDX3Y|8653 39.18 4.11e-59 7.43e-55 1
EIF1AY|9086 41.07 3.554e-54 6.42e-50 1
CYORF15B|84663 37.11 2.303e-53 4.16e-49 1
KDM5D|8284 37.22 8.41e-49 1.52e-44 1
UTY|7404 32.5 3.013e-39 5.45e-35 1
TSIX|9383 -16.79 8.116e-39 1.47e-34 0.9605

Figure S9.  Get High-res Image As an example, this figure shows the association of ZFY|7544 to 'GENDER'. P value = 4.99e-102 with T-test analysis.

Methods & Data
Input

  • Expresson data file = SKCM-TM.uncv2.mRNAseq_RSEM_normalized_log2.txt

  • Clinical data file = SKCM-TM.clin.merged.picked.txt

  • Number of patients = 241

  • Number of genes = 18091

  • 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

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)
Copyright © 2013 Broad Institute TCGA GDAC as part of the TCGA Research Network. All rights reserved.
Made with Nozzle