Correlation between mRNAseq expression and clinical features
Skin Cutaneous Melanoma (Metastatic)
02 April 2015  |  analyses__2015_04_02
Maintainer Information
Citation Information
doi:10.7908/C1XD10S8
Maintained by Juok Cho (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2015): Correlation between mRNAseq expression and clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C1XD10S8
Overview
Introduction

This pipeline uses various statistical tests to identify mRNAs whose log2 expression levels correlated to selected clinical features.

Summary

Testing the association between 18067 genes and 14 clinical features across 359 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 8 clinical features related to at least one genes.

  • 30 genes correlated to 'YEARS_TO_BIRTH'.

    • CMBL|134147 ,  ACOX2|8309 ,  MGST2|4258 ,  NMNAT3|349565 ,  MAOB|4129 ,  ...

  • 30 genes correlated to 'PRIMARY_SITE_OF_DISEASE'.

    • PAX5|5079 ,  C7|730 ,  CR2|1380 ,  RBP5|83758 ,  SHISA3|152573 ,  ...

  • 1 gene correlated to 'NEOPLASM_DISEASESTAGE'.

    • RAI14|26064

  • 30 genes correlated to 'PATHOLOGY_T_STAGE'.

    • INHA|3623 ,  KYNU|8942 ,  POU5F1B|5462 ,  GSDMD|79792 ,  TNFSF13B|10673 ,  ...

  • 30 genes correlated to 'PATHOLOGY_N_STAGE'.

    • C12ORF62|84987 ,  RAI14|26064 ,  IL17RD|54756 ,  HIST1H1C|3006 ,  MAML3|55534 ,  ...

  • 9 genes correlated to 'MELANOMA_PRIMARY_KNOWN'.

    • DUSP5|1847 ,  ICOSLG|23308 ,  GPR183|1880 ,  ST6GALNAC3|256435 ,  GRIP2|80852 ,  ...

  • 30 genes correlated to 'BRESLOW_THICKNESS'.

    • C6ORF218|221718 ,  CRTAP|10491 ,  LOC100240735|100240735 ,  SLC7A8|23428 ,  ATP6V0A1|535 ,  ...

  • 5 genes correlated to 'GENDER'.

    • CYORF15A|246126 ,  HDHD1A|8226 ,  CYORF15B|84663 ,  NCRNA00183|554203 ,  CA5BP|340591

  • No genes correlated to 'TIME_FROM_SPECIMEN_DX_TO_DEATH_OR_LAST_FUP', 'DAYS_TO_DEATH_OR_LAST_FUP', 'PATHOLOGY_M_STAGE', 'MELANOMA_ULCERATION', 'RACE', and 'ETHNICITY'.

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_DX_TO_DEATH_OR_LAST_FUP Cox regression test   N=0        
DAYS_TO_DEATH_OR_LAST_FUP Cox regression test   N=0        
YEARS_TO_BIRTH Spearman correlation test N=30 older N=3 younger N=27
PRIMARY_SITE_OF_DISEASE Kruskal-Wallis test N=30        
NEOPLASM_DISEASESTAGE Kruskal-Wallis test N=1        
PATHOLOGY_T_STAGE Spearman correlation test N=30 higher stage N=6 lower stage N=24
PATHOLOGY_N_STAGE Spearman correlation test N=30 higher stage N=15 lower stage N=15
PATHOLOGY_M_STAGE Wilcoxon test   N=0        
MELANOMA_ULCERATION Wilcoxon test   N=0        
MELANOMA_PRIMARY_KNOWN Wilcoxon test N=9 yes N=9 no N=0
BRESLOW_THICKNESS Spearman correlation test N=30 higher breslow_thickness N=11 lower breslow_thickness N=19
GENDER Wilcoxon test N=5 male N=5 female N=0
RACE Kruskal-Wallis test   N=0        
ETHNICITY Wilcoxon test   N=0        
Clinical variable #1: 'TIME_FROM_SPECIMEN_DX_TO_DEATH_OR_LAST_FUP'

No gene related to 'TIME_FROM_SPECIMEN_DX_TO_DEATH_OR_LAST_FUP'.

Table S1.  Basic characteristics of clinical feature: 'TIME_FROM_SPECIMEN_DX_TO_DEATH_OR_LAST_FUP'

TIME_FROM_SPECIMEN_DX_TO_DEATH_OR_LAST_FUP Duration (Months) 0-346.5 (median=45.9)
  censored N = 121
  death N = 119
     
  Significant markers N = 0
Clinical variable #2: 'DAYS_TO_DEATH_OR_LAST_FUP'

No gene related to 'DAYS_TO_DEATH_OR_LAST_FUP'.

Table S2.  Basic characteristics of clinical feature: 'DAYS_TO_DEATH_OR_LAST_FUP'

DAYS_TO_DEATH_OR_LAST_FUP Duration (Months) 0.2-369.9 (median=50.9)
  censored N = 176
  death N = 182
     
  Significant markers N = 0
Clinical variable #3: 'YEARS_TO_BIRTH'

30 genes related to 'YEARS_TO_BIRTH'.

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

YEARS_TO_BIRTH Mean (SD) 56.21 (16)
  Significant markers N = 30
  pos. correlated 3
  neg. correlated 27
List of top 10 genes differentially expressed by 'YEARS_TO_BIRTH'

Table S4.  Get Full Table List of top 10 genes significantly correlated to 'YEARS_TO_BIRTH' by Spearman correlation test

SpearmanCorr corrP Q
CMBL|134147 -0.3339 1.379e-10 2.49e-06
ACOX2|8309 -0.2989 1.184e-08 0.000107
MGST2|4258 -0.2918 2.575e-08 0.000155
NMNAT3|349565 -0.2667 4.098e-07 0.00148
MAOB|4129 -0.2658 4.344e-07 0.00148
OR2A9P|441295 -0.2646 4.917e-07 0.00148
LOXL4|84171 -0.2576 9.964e-07 0.00257
FAM84B|157638 -0.2544 1.377e-06 0.00311
NOV|4856 0.253 1.583e-06 0.00318
ATP1B2|482 -0.2508 1.948e-06 0.00348
Clinical variable #4: 'PRIMARY_SITE_OF_DISEASE'

30 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 65
  PRIMARY TUMOR 5
  REGIONAL CUTANEOUS OR SUBCUTANEOUS TISSUE 72
  REGIONAL LYMPH NODE 216
     
  Significant markers N = 30
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'

kruskal_wallis_P Q
PAX5|5079 6.453e-12 7.13e-08
C7|730 7.895e-12 7.13e-08
CR2|1380 1.332e-11 8.02e-08
RBP5|83758 2.799e-11 1.12e-07
SHISA3|152573 3.115e-11 1.12e-07
MS4A1|931 3.731e-11 1.12e-07
CCL21|6366 6.915e-11 1.78e-07
FOXF1|2294 1.037e-10 2.34e-07
CXCR5|643 3.419e-10 6.86e-07
FCER2|2208 6.898e-10 1.25e-06
Clinical variable #5: 'NEOPLASM_DISEASESTAGE'

One gene related to 'NEOPLASM_DISEASESTAGE'.

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

NEOPLASM_DISEASESTAGE Labels N
  I OR II NOS 12
  STAGE 0 7
  STAGE I 28
  STAGE IA 18
  STAGE IB 27
  STAGE II 24
  STAGE IIA 14
  STAGE IIB 19
  STAGE IIC 12
  STAGE III 37
  STAGE IIIA 15
  STAGE IIIB 32
  STAGE IIIC 61
  STAGE IV 20
     
  Significant markers N = 1
List of one gene differentially expressed by 'NEOPLASM_DISEASESTAGE'

Table S8.  Get Full Table List of one gene differentially expressed by 'NEOPLASM_DISEASESTAGE'

kruskal_wallis_P Q
RAI14|26064 4.164e-07 0.00752
Clinical variable #6: 'PATHOLOGY_T_STAGE'

30 genes related to 'PATHOLOGY_T_STAGE'.

Table S9.  Basic characteristics of clinical feature: 'PATHOLOGY_T_STAGE'

PATHOLOGY_T_STAGE Mean (SD) 2.45 (1.2)
  N
  T0 23
  T1 41
  T2 72
  T3 77
  T4 69
     
  Significant markers N = 30
  pos. correlated 6
  neg. correlated 24
List of top 10 genes differentially expressed by 'PATHOLOGY_T_STAGE'

Table S10.  Get Full Table List of top 10 genes significantly correlated to 'PATHOLOGY_T_STAGE' by Spearman correlation test

SpearmanCorr corrP Q
INHA|3623 -0.2761 2.956e-06 0.0434
KYNU|8942 -0.266 5.933e-06 0.0434
POU5F1B|5462 -0.2675 9.324e-06 0.0434
GSDMD|79792 -0.2601 9.615e-06 0.0434
TNFSF13B|10673 -0.2554 1.467e-05 0.053
MLKL|197259 -0.2431 3.675e-05 0.0711
ARHGAP25|9938 -0.2429 3.75e-05 0.0711
FGL2|10875 -0.2417 4.095e-05 0.0711
LOXL4|84171 -0.2414 4.189e-05 0.0711
LOC148709|148709 0.2446 4.693e-05 0.0711
Clinical variable #7: 'PATHOLOGY_N_STAGE'

30 genes related to 'PATHOLOGY_N_STAGE'.

Table S11.  Basic characteristics of clinical feature: 'PATHOLOGY_N_STAGE'

PATHOLOGY_N_STAGE Mean (SD) 0.9 (1.1)
  N
  N0 169
  N1 64
  N2 38
  N3 49
     
  Significant markers N = 30
  pos. correlated 15
  neg. correlated 15
List of top 10 genes differentially expressed by 'PATHOLOGY_N_STAGE'

Table S12.  Get Full Table List of top 10 genes significantly correlated to 'PATHOLOGY_N_STAGE' by Spearman correlation test

SpearmanCorr corrP Q
C12ORF62|84987 0.2841 2.358e-07 0.00426
RAI14|26064 -0.2529 4.623e-06 0.0363
IL17RD|54756 -0.247 7.775e-06 0.0363
HIST1H1C|3006 0.2465 8.135e-06 0.0363
MAML3|55534 -0.2441 1.004e-05 0.0363
PTPRG|5793 -0.2385 1.618e-05 0.0487
RNF168|165918 -0.2364 1.934e-05 0.0499
TMEM208|29100 0.2277 3.931e-05 0.0812
CHCHD10|400916 0.2272 4.096e-05 0.0812
MTMR12|54545 -0.226 4.494e-05 0.0812
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
  class0 314
  class1 21
     
  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 132
  YES 89
     
  Significant markers N = 0
Clinical variable #10: 'MELANOMA_PRIMARY_KNOWN'

9 genes related to 'MELANOMA_PRIMARY_KNOWN'.

Table S15.  Basic characteristics of clinical feature: 'MELANOMA_PRIMARY_KNOWN'

MELANOMA_PRIMARY_KNOWN Labels N
  NO 44
  YES 314
     
  Significant markers N = 9
  Higher in YES 9
  Higher in NO 0
List of 9 genes differentially expressed by 'MELANOMA_PRIMARY_KNOWN'

Table S16.  Get Full Table List of 9 genes differentially expressed by 'MELANOMA_PRIMARY_KNOWN'

W(pos if higher in 'YES') wilcoxontestP Q AUC
DUSP5|1847 4089 1.165e-05 0.172 0.704
ICOSLG|23308 4158.5 1.904e-05 0.172 0.699
GPR183|1880 4275 4.227e-05 0.222 0.6906
ST6GALNAC3|256435 9499 5.593e-05 0.222 0.6875
GRIP2|80852 3988 6.151e-05 0.222 0.6875
TMPRSS9|360200 3774 7.512e-05 0.226 0.6891
C5AR1|728 4389 8.952e-05 0.231 0.6823
AXIN2|8313 9373 0.0001264 0.285 0.6784
ANKRD52|283373 9352 0.0001443 0.29 0.6769
Clinical variable #11: 'BRESLOW_THICKNESS'

30 genes related to 'BRESLOW_THICKNESS'.

Table S17.  Basic characteristics of clinical feature: 'BRESLOW_THICKNESS'

BRESLOW_THICKNESS Mean (SD) 3.48 (4.7)
  Significant markers N = 30
  pos. correlated 11
  neg. correlated 19
List of top 10 genes differentially expressed by 'BRESLOW_THICKNESS'

Table S18.  Get Full Table List of top 10 genes significantly correlated to 'BRESLOW_THICKNESS' by Spearman correlation test

SpearmanCorr corrP Q
C6ORF218|221718 0.3025 6.345e-07 0.00613
CRTAP|10491 0.2963 9.965e-07 0.00613
LOC100240735|100240735 -0.3012 1.569e-06 0.00613
SLC7A8|23428 0.2903 1.683e-06 0.00613
ATP6V0A1|535 0.2902 1.696e-06 0.00613
FCRL6|343413 -0.2891 2.327e-06 0.00701
TNFSF13B|10673 -0.2847 2.815e-06 0.00712
HNRNPD|3184 -0.2816 3.511e-06 0.00712
PTMA|5757 -0.2814 3.548e-06 0.00712
ASF1A|25842 -0.2717 7.808e-06 0.0114
Clinical variable #12: 'GENDER'

5 genes related to 'GENDER'.

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

GENDER Labels N
  FEMALE 135
  MALE 224
     
  Significant markers N = 5
  Higher in MALE 5
  Higher in FEMALE 0
List of 5 genes differentially expressed by 'GENDER'

Table S20.  Get Full Table List of 5 genes differentially expressed by 'GENDER'. 25 significant gene(s) located in sex chromosomes is(are) filtered out.

W(pos if higher in 'MALE') wilcoxontestP Q AUC
CYORF15A|246126 6265 7.748e-18 1.08e-14 0.9989
HDHD1A|8226 8081 1.471e-13 1.66e-10 0.7328
CYORF15B|84663 3799 8.119e-12 7.72e-09 0.9976
NCRNA00183|554203 8665 1.23e-11 1.11e-08 0.7135
CA5BP|340591 9924 4.904e-08 3.28e-05 0.6718
Clinical variable #13: 'RACE'

No gene related to 'RACE'.

Table S21.  Basic characteristics of clinical feature: 'RACE'

RACE Labels N
  ASIAN 5
  BLACK OR AFRICAN AMERICAN 1
  WHITE 345
     
  Significant markers N = 0
Clinical variable #14: 'ETHNICITY'

No gene related to 'ETHNICITY'.

Table S22.  Basic characteristics of clinical feature: 'ETHNICITY'

ETHNICITY Labels N
  HISPANIC OR LATINO 7
  NOT HISPANIC OR LATINO 345
     
  Significant markers N = 0
Methods & Data
Input

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

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

  • Number of patients = 359

  • Number of genes = 18067

  • Number of clinical features = 14

Selected clinical features

  • For clinical features selected for this analysis and their value conozzle.versions, please find a documentation on selected CDEs .

  • Survival time data

    • Survival time data is a combined value of days_to_death and days_to_last_followup. For each patient, it creates a combined value 'days_to_death_or_last_fup' using conversion process below.

      • if 'vital_status'==1(dead), 'days_to_last_followup' is always NA. Thus, uses 'days_to_death' value for 'days_to_death_or_fup'

      • if 'vital_status'==0(alive),

        • if 'days_to_death'==NA & 'days_to_last_followup'!=NA, uses 'days_to_last_followup' value for 'days_to_death_or_fup'

        • if 'days_to_death'!=NA, excludes this case in survival analysis and report the case.

      • if 'vital_status'==NA,excludes this case in survival analysis and report the case.

    • cf. In certain diesase types such as SKCM, days_to_death parameter is replaced with time_from_specimen_dx or time_from_specimen_procurement_to_death .

  • This analysis excluded clinical variables that has only NA values.

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

Wilcoxon rank sum test (Mann-Whitney U test)

For two groups (mutant or wild-type) of continuous type of clinical data, wilcoxon rank sum test (Mann and Whitney, 1947) was applied to compare their mean difference using 'wilcox.test(continuous.clinical ~ as.factor(group), exact=FALSE)' function in R. This test is equivalent to the Mann-Whitney test.

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] Mann and Whitney, On a Test of Whether one of Two Random Variables is Stochastically Larger than the Other, Annals of Mathematical Statistics 18 (1), 50-60 (1947)
[4] 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 © 2015 Broad Institute TCGA GDAC as part of the TCGA Research Network. All rights reserved.
Made with Nozzle