Skin Cutaneous Melanoma: Correlation between mRNAseq expression and clinical features
(All_Metastatic cohort)
Maintained by Juok Cho (Broad Institute)
Overview
Introduction

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

Summary

Testing the association between 18090 genes and 7 clinical features across 171 samples, statistically thresholded by Q value < 0.05, 7 clinical features related to at least one genes.

  • 15 genes correlated to 'Time to Death'.

    • PPP3CB|5532 ,  RAB8B|51762 ,  ARPC5|10092 ,  BNIP2|663 ,  CYB5R4|51167 ,  ...

  • 5 genes correlated to 'AGE'.

    • ACOX2|8309 ,  MCHR1|2847 ,  TCEAL5|340543 ,  MAOB|4129 ,  PHKA1|5255

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

    • TMEM156|80008 ,  CD38|952 ,  P2RY10|27334 ,  IGJ|3512 ,  POU2AF1|5450 ,  ...

  • 18 genes correlated to 'GENDER'.

    • ZFY|7544 ,  PRKY|5616 ,  CYORF15B|84663 ,  RPS4Y1|6192 ,  XIST|7503 ,  ...

  • 4 genes correlated to 'DISTANT.METASTASIS'.

    • CLDN6|9074 ,  CXADRP3|440224 ,  PRPS1|5631 ,  LRRC28|123355

  • 6 genes correlated to 'LYMPH.NODE.METASTASIS'.

    • IHH|3549 ,  NPAS4|266743 ,  MUC6|4588 ,  AMY1A|276 ,  NXNL2|158046 ,  ...

  • 1 gene correlated to 'NEOPLASM.DISEASESTAGE'.

    • SLC34A2|10568

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=15 shorter survival N=0 longer survival N=15
AGE Spearman correlation test N=5 older N=0 younger N=5
PRIMARY SITE OF DISEASE ANOVA test N=55        
GENDER t test N=18 male N=14 female N=4
DISTANT METASTASIS ANOVA test N=4        
LYMPH NODE METASTASIS ANOVA test N=6        
NEOPLASM DISEASESTAGE ANOVA test N=1        
Clinical variable #1: 'Time to Death'

15 genes related to 'Time to Death'.

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

Time to Death Duration (Months) 0.1-98.8 (median=11.5)
  censored N = 42
  death N = 50
     
  Significant markers N = 15
  associated with shorter survival 0
  associated with longer survival 15
List of top 10 genes significantly associated with 'Time to Death' by Cox regression test

Table S2.  Get Full Table List of top 10 genes significantly associated with 'Time to Death' by Cox regression test

HazardRatio Wald_P Q C_index
PPP3CB|5532 0.29 2.046e-07 0.0037 0.335
RAB8B|51762 0.41 2.618e-07 0.0047 0.327
ARPC5|10092 0.26 3.142e-07 0.0057 0.306
BNIP2|663 0.3 4.798e-07 0.0087 0.309
CYB5R4|51167 0.58 7.129e-07 0.013 0.324
TLR1|7096 0.61 8.224e-07 0.015 0.299
LMBRD1|55788 0.4 1.099e-06 0.02 0.303
AGTPBP1|23287 0.49 1.401e-06 0.025 0.33
CD164|8763 0.48 2e-06 0.036 0.314
IBTK|25998 0.56 2.044e-06 0.037 0.324

Figure S1.  Get High-res Image As an example, this figure shows the association of PPP3CB|5532 to 'Time to Death'. four curves present the cumulative survival rates of 4 quartile subsets of patients. P value = 2.05e-07 with univariate Cox regression analysis using continuous log-2 expression values.

Clinical variable #2: 'AGE'

5 genes related to 'AGE'.

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

AGE Mean (SD) 56.07 (16)
  Significant markers N = 5
  pos. correlated 0
  neg. correlated 5
List of 5 genes significantly correlated to 'AGE' by Spearman correlation test

Table S4.  Get Full Table List of 5 genes significantly correlated to 'AGE' by Spearman correlation test

SpearmanCorr corrP Q
ACOX2|8309 -0.414 2e-08 0.000362
MCHR1|2847 -0.3914 1.43e-07 0.00259
TCEAL5|340543 -0.3816 2.828e-07 0.00512
MAOB|4129 -0.3667 8.702e-07 0.0157
PHKA1|5255 -0.3584 1.6e-06 0.0289

Figure S2.  Get High-res Image As an example, this figure shows the association of ACOX2|8309 to 'AGE'. P value = 2e-08 with Spearman correlation analysis. The straight line presents the best linear regression.

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

55 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 25
  PRIMARY TUMOR 1
  REGIONAL CUTANEOUS OR SUBCUTANEOUS TISSUE (INCLUDES SATELLITE AND IN-TRANSIT METASTASIS) 33
  REGIONAL LYMPH NODE 112
     
  Significant markers N = 55
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 8.12e-10 1.47e-05
CD38|952 2.456e-09 4.44e-05
P2RY10|27334 7.728e-09 0.00014
IGJ|3512 8.469e-09 0.000153
POU2AF1|5450 2.572e-08 0.000465
ADAM6|8755 4.595e-08 0.000831
FCRL3|115352 6.453e-08 0.00117
CD79A|973 6.921e-08 0.00125
FCRL5|83416 8.919e-08 0.00161
PRKCB|5579 1.015e-07 0.00183

Figure S3.  Get High-res Image As an example, this figure shows the association of TMEM156|80008 to 'PRIMARY.SITE.OF.DISEASE'. P value = 8.12e-10 with ANOVA analysis.

Clinical variable #4: 'GENDER'

18 genes related to 'GENDER'.

Table S7.  Basic characteristics of clinical feature: 'GENDER'

GENDER Labels N
  FEMALE 66
  MALE 105
     
  Significant markers N = 18
  Higher in MALE 14
  Higher in FEMALE 4
List of top 10 genes differentially expressed by 'GENDER'

Table S8.  Get Full Table List of top 10 genes differentially expressed by 'GENDER'

T(pos if higher in 'MALE') ttestP Q AUC
ZFY|7544 30.42 9.377e-67 1.7e-62 0.9914
PRKY|5616 26.47 2.425e-55 4.39e-51 0.9939
CYORF15B|84663 33.13 2.911e-53 5.26e-49 1
RPS4Y1|6192 29.46 5.202e-45 9.41e-41 1
XIST|7503 -19.63 4.961e-43 8.97e-39 0.9711
DDX3Y|8653 30.82 4.889e-42 8.84e-38 0.9976
KDM5D|8284 29.08 1.807e-36 3.27e-32 0.9921
EIF1AY|9086 28.78 3.519e-31 6.36e-27 0.9952
TSIX|9383 -15.1 5.704e-30 1.03e-25 0.9701
USP9Y|8287 25.67 1.282e-26 2.32e-22 0.999

Figure S4.  Get High-res Image As an example, this figure shows the association of ZFY|7544 to 'GENDER'. P value = 9.38e-67 with T-test analysis.

Clinical variable #5: 'DISTANT.METASTASIS'

4 genes related to 'DISTANT.METASTASIS'.

Table S9.  Basic characteristics of clinical feature: 'DISTANT.METASTASIS'

DISTANT.METASTASIS Labels N
  M0 148
  M1 2
  M1A 2
  M1B 2
  M1C 2
     
  Significant markers N = 4
List of 4 genes differentially expressed by 'DISTANT.METASTASIS'

Table S10.  Get Full Table List of 4 genes differentially expressed by 'DISTANT.METASTASIS'

ANOVA_P Q
CLDN6|9074 1.254e-09 2.27e-05
CXADRP3|440224 4.405e-08 0.000796
PRPS1|5631 1.462e-06 0.0264
LRRC28|123355 2.33e-06 0.0421

Figure S5.  Get High-res Image As an example, this figure shows the association of CLDN6|9074 to 'DISTANT.METASTASIS'. P value = 1.25e-09 with ANOVA analysis.

Clinical variable #6: 'LYMPH.NODE.METASTASIS'

6 genes related to 'LYMPH.NODE.METASTASIS'.

Table S11.  Basic characteristics of clinical feature: 'LYMPH.NODE.METASTASIS'

LYMPH.NODE.METASTASIS Labels N
  N0 95
  N1 2
  N1A 6
  N1B 16
  N2 1
  N2A 4
  N2B 10
  N2C 5
  N3 16
  NX 2
     
  Significant markers N = 6
List of 6 genes differentially expressed by 'LYMPH.NODE.METASTASIS'

Table S12.  Get Full Table List of 6 genes differentially expressed by 'LYMPH.NODE.METASTASIS'

ANOVA_P Q
IHH|3549 2.079e-11 3.76e-07
NPAS4|266743 1.613e-07 0.00292
MUC6|4588 8.804e-07 0.0159
AMY1A|276 9.125e-07 0.0165
NXNL2|158046 9.49e-07 0.0172
WBSCR17|64409 2.149e-06 0.0389

Figure S6.  Get High-res Image As an example, this figure shows the association of IHH|3549 to 'LYMPH.NODE.METASTASIS'. P value = 2.08e-11 with ANOVA analysis.

Clinical variable #7: 'NEOPLASM.DISEASESTAGE'

One gene related to 'NEOPLASM.DISEASESTAGE'.

Table S13.  Basic characteristics of clinical feature: 'NEOPLASM.DISEASESTAGE'

NEOPLASM.DISEASESTAGE Labels N
  I OR II NOS 4
  STAGE I 17
  STAGE IA 10
  STAGE IB 14
  STAGE II 19
  STAGE IIA 8
  STAGE IIB 10
  STAGE IIC 8
  STAGE III 9
  STAGE IIIA 5
  STAGE IIIB 17
  STAGE IIIC 23
  STAGE IV 6
     
  Significant markers N = 1
List of one gene differentially expressed by 'NEOPLASM.DISEASESTAGE'

Table S14.  Get Full Table List of one gene differentially expressed by 'NEOPLASM.DISEASESTAGE'

ANOVA_P Q
SLC34A2|10568 7.425e-07 0.0134

Figure S7.  Get High-res Image As an example, this figure shows the association of SLC34A2|10568 to 'NEOPLASM.DISEASESTAGE'. P value = 7.42e-07 with ANOVA analysis.

Methods & Data
Input

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

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

  • Number of patients = 171

  • Number of genes = 18090

  • Number of clinical features = 7

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

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] 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