Skin Cutaneous Melanoma: Correlation between mRNAseq expression and clinical features
(Regional_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 18128 genes and 7 clinical features across 145 samples, statistically thresholded by Q value < 0.05, 6 clinical features related to at least one genes.

  • 2 genes correlated to 'Time to Death'.

    • NUDT7|283927 ,  PPP3CB|5532

  • 9 genes correlated to 'AGE'.

    • ACOX2|8309 ,  PHKA1|5255 ,  MCHR1|2847 ,  ETFB|2109 ,  MICALL2|79778 ,  ...

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

    • FCRL1|115350 ,  PIM2|11040 ,  C8ORF80|389643 ,  GP1BA|2811 ,  FLJ40330|645784 ,  ...

  • 17 genes correlated to 'GENDER'.

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

  • 2 genes correlated to 'DISTANT.METASTASIS'.

    • TMEM147|10430 ,  LRRC28|123355

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

    • IHH|3549 ,  C12ORF27|283460 ,  AMY1A|276 ,  NPAS4|266743 ,  MUC6|4588 ,  ...

  • No genes correlated to 'NEOPLASM.DISEASESTAGE'

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=2 shorter survival N=0 longer survival N=2
AGE Spearman correlation test N=9 older N=1 younger N=8
PRIMARY SITE OF DISEASE t test N=27 regional lymph node N=24 regional cutaneous or subcutaneous tissue (includes satellite and in-transit metastasis) N=3
GENDER t test N=17 male N=12 female N=5
DISTANT METASTASIS ANOVA test N=2        
LYMPH NODE METASTASIS ANOVA test N=8        
NEOPLASM DISEASESTAGE ANOVA test   N=0        
Clinical variable #1: 'Time to Death'

2 genes related to 'Time to Death'.

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

Time to Death Duration (Months) 1-98.8 (median=12.2)
  censored N = 37
  death N = 44
     
  Significant markers N = 2
  associated with shorter survival 0
  associated with longer survival 2
List of 2 genes significantly associated with 'Time to Death' by Cox regression test

Table S2.  Get Full Table List of 2 genes significantly associated with 'Time to Death' by Cox regression test

HazardRatio Wald_P Q C_index
NUDT7|283927 0.65 2.186e-06 0.04 0.287
PPP3CB|5532 0.29 2.627e-06 0.048 0.327

Figure S1.  Get High-res Image As an example, this figure shows the association of NUDT7|283927 to 'Time to Death'. four curves present the cumulative survival rates of 4 quartile subsets of patients. P value = 2.19e-06 with univariate Cox regression analysis using continuous log-2 expression values.

Clinical variable #2: 'AGE'

9 genes related to 'AGE'.

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

AGE Mean (SD) 55.98 (16)
  Significant markers N = 9
  pos. correlated 1
  neg. correlated 8
List of 9 genes significantly correlated to 'AGE' by Spearman correlation test

Table S4.  Get Full Table List of 9 genes significantly correlated to 'AGE' by Spearman correlation test

SpearmanCorr corrP Q
ACOX2|8309 -0.447 1.744e-08 0.000316
PHKA1|5255 -0.4088 3.31e-07 0.006
MCHR1|2847 -0.4056 4.173e-07 0.00756
ETFB|2109 -0.4041 4.632e-07 0.00839
MICALL2|79778 -0.4033 4.925e-07 0.00893
TCEAL5|340543 -0.3975 7.376e-07 0.0134
TENC1|23371 -0.3828 2.012e-06 0.0365
CDHR3|222256 0.3813 2.221e-06 0.0403
SYT12|91683 -0.3809 2.479e-06 0.0449

Figure S2.  Get High-res Image As an example, this figure shows the association of ACOX2|8309 to 'AGE'. P value = 1.74e-08 with Spearman correlation analysis. The straight line presents the best linear regression.

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

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

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

PRIMARY.SITE.OF.DISEASE Labels N
  REGIONAL CUTANEOUS OR SUBCUTANEOUS TISSUE (INCLUDES SATELLITE AND IN-TRANSIT METASTASIS) 33
  REGIONAL LYMPH NODE 112
     
  Significant markers N = 27
  Higher in REGIONAL LYMPH NODE 24
  Higher in REGIONAL CUTANEOUS OR SUBCUTANEOUS TISSUE (INCLUDES SATELLITE AND IN-TRANSIT METASTASIS) 3
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'

T(pos if higher in 'REGIONAL LYMPH NODE') ttestP Q AUC
FCRL1|115350 7.58 7.189e-11 1.3e-06 0.834
PIM2|11040 5.94 4.947e-08 0.000897 0.7546
C8ORF80|389643 5.98 8.127e-08 0.00147 0.7673
GP1BA|2811 5.81 8.605e-08 0.00156 0.7527
FLJ40330|645784 5.76 1.061e-07 0.00192 0.7603
FCER2|2208 5.81 1.274e-07 0.00231 0.745
AICDA|57379 5.87 1.292e-07 0.00234 0.7692
IGLL1|3543 6.22 1.591e-07 0.00288 0.8517
POU2AF1|5450 5.83 2.415e-07 0.00438 0.78
MS4A1|931 5.66 2.651e-07 0.0048 0.7563

Figure S3.  Get High-res Image As an example, this figure shows the association of FCRL1|115350 to 'PRIMARY.SITE.OF.DISEASE'. P value = 7.19e-11 with T-test analysis.

Clinical variable #4: 'GENDER'

17 genes related to 'GENDER'.

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

GENDER Labels N
  FEMALE 51
  MALE 94
     
  Significant markers N = 17
  Higher in MALE 12
  Higher in FEMALE 5
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 29.3 1.79e-58 3.24e-54 0.992
PRKY|5616 24.78 5.877e-44 1.06e-39 0.9947
XIST|7503 -18.99 1.671e-38 3.03e-34 0.9746
RPS4Y1|6192 27.49 2.187e-34 3.96e-30 1
CYORF15B|84663 32.09 2.239e-29 4.06e-25 1
DDX3Y|8653 27.41 2.752e-28 4.98e-24 0.9977
TSIX|9383 -13.99 3.375e-25 6.11e-21 0.9721
KDM5D|8284 25.85 1.524e-22 2.76e-18 0.992
TTTY15|64595 20.65 7.358e-20 1.33e-15 0.9884
EIF1AY|9086 25.96 2.075e-19 3.76e-15 0.9942

Figure S4.  Get High-res Image As an example, this figure shows the association of ZFY|7544 to 'GENDER'. P value = 1.79e-58 with T-test analysis.

Clinical variable #5: 'DISTANT.METASTASIS'

2 genes related to 'DISTANT.METASTASIS'.

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

DISTANT.METASTASIS Labels N
  M0 126
  M1 1
  M1A 2
  M1B 2
  M1C 1
     
  Significant markers N = 2
List of 2 genes differentially expressed by 'DISTANT.METASTASIS'

Table S10.  Get Full Table List of 2 genes differentially expressed by 'DISTANT.METASTASIS'

ANOVA_P Q
TMEM147|10430 9.087e-07 0.0164
LRRC28|123355 2.732e-06 0.0494

Figure S5.  Get High-res Image As an example, this figure shows the association of TMEM147|10430 to 'DISTANT.METASTASIS'. P value = 9.09e-07 with ANOVA analysis.

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

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

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

LYMPH.NODE.METASTASIS Labels N
  N0 77
  N1 2
  N1A 5
  N1B 12
  N2 1
  N2A 4
  N2B 10
  N2C 4
  N3 16
  NX 2
     
  Significant markers N = 8
List of 8 genes differentially expressed by 'LYMPH.NODE.METASTASIS'

Table S12.  Get Full Table List of 8 genes differentially expressed by 'LYMPH.NODE.METASTASIS'

ANOVA_P Q
IHH|3549 1.911e-11 3.46e-07
C12ORF27|283460 1.91e-09 3.46e-05
AMY1A|276 5.369e-08 0.000973
NPAS4|266743 6.016e-08 0.00109
MUC6|4588 7.43e-07 0.0135
NXNL2|158046 1.355e-06 0.0246
SCNN1G|6340 1.553e-06 0.0281
ESR1|2099 2.338e-06 0.0424

Figure S6.  Get High-res Image As an example, this figure shows the association of IHH|3549 to 'LYMPH.NODE.METASTASIS'. P value = 1.91e-11 with ANOVA analysis.

Clinical variable #7: 'NEOPLASM.DISEASESTAGE'

No gene related to 'NEOPLASM.DISEASESTAGE'.

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

NEOPLASM.DISEASESTAGE Labels N
  I OR II NOS 1
  STAGE I 16
  STAGE IA 8
  STAGE IB 13
  STAGE II 17
  STAGE IIA 7
  STAGE IIB 8
  STAGE IIC 4
  STAGE III 8
  STAGE IIIA 4
  STAGE IIIB 15
  STAGE IIIC 21
  STAGE IV 4
     
  Significant markers N = 0
Methods & Data
Input

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

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

  • Number of patients = 145

  • Number of genes = 18128

  • 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

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