Skin Cutaneous Melanoma: Correlation between mRNAseq expression and clinical features
(All_Samples 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 18094 genes and 8 clinical features across 198 samples, statistically thresholded by Q value < 0.05, 8 clinical features related to at least one genes.

  • 4 genes correlated to 'Time to Death'.

    • PRKAR2B|5577 ,  ZNF25|219749 ,  ARHGAP12|94134 ,  SATB1|6304

  • 5 genes correlated to 'AGE'.

    • ACOX2|8309 ,  PHKA1|5255 ,  MCHR1|2847 ,  CD200|4345 ,  PTGIS|5740

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

    • KRT17|3872 ,  C7|730 ,  TP53AIP1|63970 ,  S100A7|6278 ,  S100A2|6273 ,  ...

  • 20 genes correlated to 'GENDER'.

    • ZFY|7544 ,  CYORF15B|84663 ,  PRKY|5616 ,  RPS4Y1|6192 ,  DDX3Y|8653 ,  ...

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

    • KDM4C|23081 ,  ZFP90|146198 ,  AQP5|362 ,  LPP|4026 ,  EIF4G2|1982 ,  ...

  • 4 genes correlated to 'DISTANT.METASTASIS'.

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

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

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

  • 2 genes correlated to 'NEOPLASM.DISEASESTAGE'.

    • TNFSF11|8600 ,  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=4 shorter survival N=0 longer survival N=4
AGE Spearman correlation test N=5 older N=0 younger N=5
PRIMARY SITE OF DISEASE ANOVA test N=282        
GENDER t test N=20 male N=14 female N=6
RADIATIONS RADIATION REGIMENINDICATION t test N=89 yes N=51 no N=38
DISTANT METASTASIS ANOVA test N=4        
LYMPH NODE METASTASIS ANOVA test N=5        
NEOPLASM DISEASESTAGE ANOVA test N=2        
Clinical variable #1: 'Time to Death'

4 genes related to 'Time to Death'.

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

Time to Death Duration (Months) 0-357.4 (median=42.4)
  censored N = 97
  death N = 91
     
  Significant markers N = 4
  associated with shorter survival 0
  associated with longer survival 4
List of 4 genes significantly associated with 'Time to Death' by Cox regression test

Table S2.  Get Full Table List of 4 genes significantly associated with 'Time to Death' by Cox regression test

HazardRatio Wald_P Q C_index
PRKAR2B|5577 0.72 5.338e-07 0.0097 0.347
ZNF25|219749 0.65 1.216e-06 0.022 0.352
ARHGAP12|94134 0.64 1.589e-06 0.029 0.361
SATB1|6304 0.75 1.599e-06 0.029 0.355

Figure S1.  Get High-res Image As an example, this figure shows the association of PRKAR2B|5577 to 'Time to Death'. four curves present the cumulative survival rates of 4 quartile subsets of patients. P value = 5.34e-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) 56.64 (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 -0.4008 6.967e-09 0.000126
PHKA1|5255 -0.3887 2.143e-08 0.000388
MCHR1|2847 -0.3532 4.7e-07 0.0085
CD200|4345 -0.341 1.141e-06 0.0206
PTGIS|5740 -0.3334 2.038e-06 0.0369

Figure S2.  Get High-res Image As an example, this figure shows the association of ACOX2|8309 to 'AGE'. P value = 6.97e-09 with Spearman correlation analysis. The straight line presents the best linear regression.

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

282 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 27
  PRIMARY TUMOR 24
  REGIONAL CUTANEOUS OR SUBCUTANEOUS TISSUE (INCLUDES SATELLITE AND IN-TRANSIT METASTASIS) 35
  REGIONAL LYMPH NODE 112
     
  Significant markers N = 282
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
KRT17|3872 1.384e-16 2.5e-12
C7|730 3.95e-15 7.15e-11
TP53AIP1|63970 1.818e-13 3.29e-09
S100A7|6278 2.279e-13 4.12e-09
S100A2|6273 2.662e-13 4.82e-09
PLA2G4F|255189 3.899e-13 7.05e-09
SPRR1B|6699 4.954e-13 8.96e-09
SERPINB4|6318 8.095e-13 1.46e-08
FLG2|388698 8.443e-13 1.53e-08
KRT10|3858 8.65e-13 1.56e-08

Figure S3.  Get High-res Image As an example, this figure shows the association of KRT17|3872 to 'PRIMARY.SITE.OF.DISEASE'. P value = 1.38e-16 with ANOVA analysis.

Clinical variable #4: 'GENDER'

20 genes related to 'GENDER'.

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

GENDER Labels N
  FEMALE 75
  MALE 123
     
  Significant markers N = 20
  Higher in MALE 14
  Higher in FEMALE 6
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 32.67 6.143e-76 1.11e-71 0.9928
CYORF15B|84663 34.4 3.32e-65 6e-61 1
PRKY|5616 29 1.119e-63 2.02e-59 0.9951
RPS4Y1|6192 31.59 7.482e-50 1.35e-45 1
DDX3Y|8653 33.69 1.469e-49 2.66e-45 0.9982
XIST|7503 -20.9 1.219e-48 2.21e-44 0.9703
KDM5D|8284 31.86 4.122e-44 7.45e-40 0.9938
EIF1AY|9086 30.83 1.016e-36 1.84e-32 0.9959
TSIX|9383 -15.94 8.088e-34 1.46e-29 0.9642
USP9Y|8287 28.09 7.241e-33 1.31e-28 0.9993

Figure S4.  Get High-res Image As an example, this figure shows the association of ZFY|7544 to 'GENDER'. P value = 6.14e-76 with T-test analysis.

Clinical variable #5: 'RADIATIONS.RADIATION.REGIMENINDICATION'

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

Table S9.  Basic characteristics of clinical feature: 'RADIATIONS.RADIATION.REGIMENINDICATION'

RADIATIONS.RADIATION.REGIMENINDICATION Labels N
  NO 3
  YES 195
     
  Significant markers N = 89
  Higher in YES 51
  Higher in NO 38
List of top 10 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

Table S10.  Get Full Table List of top 10 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

T(pos if higher in 'YES') ttestP Q AUC
KDM4C|23081 -26.05 1.821e-46 2.95e-42 0.9846
ZFP90|146198 -13.86 1.316e-30 2.13e-26 0.8906
AQP5|362 15.48 5.885e-30 9.54e-26 0.9337
LPP|4026 -12.98 1.001e-26 1.62e-22 0.8393
EIF4G2|1982 -11.71 1.077e-22 1.75e-18 0.8598
TBC1D5|9779 -14.26 2.329e-22 3.77e-18 0.8957
HIST3H2A|92815 14.48 3.902e-21 6.32e-17 0.875
PSCA|8000 11.59 5.265e-21 8.53e-17 0.8048
GPI|2821 11.05 1.002e-20 1.62e-16 0.8137
DMRTA2|63950 11.41 2.895e-19 4.69e-15 0.8847

Figure S5.  Get High-res Image As an example, this figure shows the association of KDM4C|23081 to 'RADIATIONS.RADIATION.REGIMENINDICATION'. P value = 1.82e-46 with T-test analysis.

Clinical variable #6: 'DISTANT.METASTASIS'

4 genes related to 'DISTANT.METASTASIS'.

Table S11.  Basic characteristics of clinical feature: 'DISTANT.METASTASIS'

DISTANT.METASTASIS Labels N
  M0 172
  M1 2
  M1A 2
  M1B 2
  M1C 3
     
  Significant markers N = 4
List of 4 genes differentially expressed by 'DISTANT.METASTASIS'

Table S12.  Get Full Table List of 4 genes differentially expressed by 'DISTANT.METASTASIS'

ANOVA_P Q
CLDN6|9074 2.626e-09 4.75e-05
CXADRP3|440224 1.071e-07 0.00194
PRPS1|5631 6.116e-07 0.0111
LRRC28|123355 1.57e-06 0.0284

Figure S6.  Get High-res Image As an example, this figure shows the association of CLDN6|9074 to 'DISTANT.METASTASIS'. P value = 2.63e-09 with ANOVA analysis.

Clinical variable #7: 'LYMPH.NODE.METASTASIS'

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

Table S13.  Basic characteristics of clinical feature: 'LYMPH.NODE.METASTASIS'

LYMPH.NODE.METASTASIS Labels N
  N0 109
  N1 2
  N1A 7
  N1B 17
  N2 1
  N2A 5
  N2B 13
  N2C 6
  N3 18
  NX 5
     
  Significant markers N = 5
List of 5 genes differentially expressed by 'LYMPH.NODE.METASTASIS'

Table S14.  Get Full Table List of 5 genes differentially expressed by 'LYMPH.NODE.METASTASIS'

ANOVA_P Q
IHH|3549 8.61e-13 1.56e-08
NPAS4|266743 3.038e-08 0.00055
MUC6|4588 1.803e-07 0.00326
NXNL2|158046 7.127e-07 0.0129
AMY1A|276 1.49e-06 0.027

Figure S7.  Get High-res Image As an example, this figure shows the association of IHH|3549 to 'LYMPH.NODE.METASTASIS'. P value = 8.61e-13 with ANOVA analysis.

Clinical variable #8: 'NEOPLASM.DISEASESTAGE'

2 genes related to 'NEOPLASM.DISEASESTAGE'.

Table S15.  Basic characteristics of clinical feature: 'NEOPLASM.DISEASESTAGE'

NEOPLASM.DISEASESTAGE Labels N
  I OR II NOS 4
  STAGE I 17
  STAGE IA 10
  STAGE IB 15
  STAGE II 20
  STAGE IIA 9
  STAGE IIB 10
  STAGE IIC 22
  STAGE III 9
  STAGE IIIA 6
  STAGE IIIB 20
  STAGE IIIC 26
  STAGE IV 7
     
  Significant markers N = 2
List of 2 genes differentially expressed by 'NEOPLASM.DISEASESTAGE'

Table S16.  Get Full Table List of 2 genes differentially expressed by 'NEOPLASM.DISEASESTAGE'

ANOVA_P Q
TNFSF11|8600 2.946e-08 0.000533
SLC34A2|10568 6.71e-07 0.0121

Figure S8.  Get High-res Image As an example, this figure shows the association of TNFSF11|8600 to 'NEOPLASM.DISEASESTAGE'. P value = 2.95e-08 with ANOVA analysis.

Methods & Data
Input

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

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

  • Number of patients = 198

  • Number of genes = 18094

  • Number of clinical features = 8

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)
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