Correlation between mRNAseq expression and clinical features
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 18215 genes and 12 clinical features across 389 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 9 clinical features related to at least one genes.

  • 30 genes correlated to 'DAYS_TO_DEATH_OR_LAST_FUP'.

    • GSDMB|55876 ,  LOC91316|91316 ,  TIA1|7072 ,  EHBP1|23301 ,  ORMDL1|94101 ,  ...

  • 30 genes correlated to 'YEARS_TO_BIRTH'.

    • FAM111A|63901 ,  PLA2G5|5322 ,  CXCL12|6387 ,  APLNR|187 ,  PLN|5350 ,  ...

  • 30 genes correlated to 'NEOPLASM_DISEASESTAGE'.

    • SFRP2|6423 ,  COL10A1|1300 ,  CTHRC1|115908 ,  SSC5D|284297 ,  SFRP4|6424 ,  ...

  • 30 genes correlated to 'PATHOLOGY_T_STAGE'.

    • LRIG1|26018 ,  CCDC80|151887 ,  CTHRC1|115908 ,  SSC5D|284297 ,  SFRP4|6424 ,  ...

  • 30 genes correlated to 'PATHOLOGY_N_STAGE'.

    • IL1R1|3554 ,  MESP1|55897 ,  C15ORF48|84419 ,  PEA15|8682 ,  GFPT1|2673 ,  ...

  • 9 genes correlated to 'GENDER'.

    • HDHD1A|8226 ,  CYORF15A|246126 ,  CYORF15B|84663 ,  NCRNA00183|554203 ,  PHF7|51533 ,  ...

  • 30 genes correlated to 'KARNOFSKY_PERFORMANCE_SCORE'.

    • APBB1IP|54518 ,  DGKA|1606 ,  S1PR3|1903 ,  LOC283070|283070 ,  MRAS|22808 ,  ...

  • 30 genes correlated to 'NUMBER_OF_LYMPH_NODES'.

    • GDPD3|79153 ,  IL1R1|3554 ,  MCEE|84693 ,  SLC44A2|57153 ,  MAL|4118 ,  ...

  • 30 genes correlated to 'RACE'.

    • CALU|813 ,  XKR9|389668 ,  SEC23A|10484 ,  WFIKKN1|117166 ,  TXNRD1|7296 ,  ...

  • No genes correlated to 'PATHOLOGY_M_STAGE', 'NUMBER_PACK_YEARS_SMOKED', 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
DAYS_TO_DEATH_OR_LAST_FUP Cox regression test N=30 shorter survival N=5 longer survival N=25
YEARS_TO_BIRTH Spearman correlation test N=30 older N=22 younger N=8
NEOPLASM_DISEASESTAGE Kruskal-Wallis test N=30        
PATHOLOGY_T_STAGE Spearman correlation test N=30 higher stage N=30 lower stage N=0
PATHOLOGY_N_STAGE Spearman correlation test N=30 higher stage N=22 lower stage N=8
PATHOLOGY_M_STAGE Wilcoxon test   N=0        
GENDER Wilcoxon test N=9 male N=9 female N=0
KARNOFSKY_PERFORMANCE_SCORE Spearman correlation test N=30 higher score N=18 lower score N=12
NUMBER_PACK_YEARS_SMOKED Spearman correlation test   N=0        
NUMBER_OF_LYMPH_NODES Spearman correlation test N=30 higher number_of_lymph_nodes N=27 lower number_of_lymph_nodes N=3
RACE Kruskal-Wallis test N=30        
ETHNICITY Wilcoxon test   N=0        
Clinical variable #1: 'DAYS_TO_DEATH_OR_LAST_FUP'

30 genes related to 'DAYS_TO_DEATH_OR_LAST_FUP'.

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

DAYS_TO_DEATH_OR_LAST_FUP Duration (Months) 0.1-166 (median=15.6)
  censored N = 234
  death N = 154
     
  Significant markers N = 30
  associated with shorter survival 5
  associated with longer survival 25
List of top 10 genes differentially expressed by 'DAYS_TO_DEATH_OR_LAST_FUP'

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
GSDMB|55876 0.72 1.044e-09 1.9e-05 0.356
LOC91316|91316 0.62 8.032e-08 5e-04 0.38
TIA1|7072 0.51 1.152e-07 5e-04 0.367
EHBP1|23301 1.8 1.553e-07 5e-04 0.621
ORMDL1|94101 0.39 2.054e-07 5e-04 0.374
TMEM109|79073 2.1 2.058e-07 5e-04 0.61
C6ORF115|58527 0.59 2.124e-07 5e-04 0.384
FER1L4|80307 0.87 2.176e-07 5e-04 0.382
TRIM38|10475 0.59 2.795e-07 0.00057 0.377
CNKSR1|10256 0.78 3.491e-07 0.00064 0.411
Clinical variable #2: '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) 67.74 (11)
  Significant markers N = 30
  pos. correlated 22
  neg. correlated 8
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
FAM111A|63901 -0.2731 4.579e-08 0.000834
PLA2G5|5322 0.2528 5.723e-07 0.00482
CXCL12|6387 0.2454 9.932e-07 0.00482
APLNR|187 0.2428 1.296e-06 0.00482
PLN|5350 0.243 1.596e-06 0.00482
FGF7|2252 0.2401 1.722e-06 0.00482
LRRC49|54839 -0.2367 2.432e-06 0.00482
HAS1|3036 0.2485 2.521e-06 0.00482
ITGA7|3679 0.2359 2.635e-06 0.00482
PRICKLE1|144165 0.2358 2.645e-06 0.00482
Clinical variable #3: 'NEOPLASM_DISEASESTAGE'

30 genes related to 'NEOPLASM_DISEASESTAGE'.

Table S5.  Basic characteristics of clinical feature: 'NEOPLASM_DISEASESTAGE'

NEOPLASM_DISEASESTAGE Labels N
  STAGE I 4
  STAGE II 125
  STAGE III 127
  STAGE IV 128
     
  Significant markers N = 30
List of top 10 genes differentially expressed by 'NEOPLASM_DISEASESTAGE'

Table S6.  Get Full Table List of top 10 genes differentially expressed by 'NEOPLASM_DISEASESTAGE'

kruskal_wallis_P Q
SFRP2|6423 1.379e-14 2.51e-10
COL10A1|1300 1.342e-13 6.23e-10
CTHRC1|115908 1.587e-13 6.23e-10
SSC5D|284297 1.599e-13 6.23e-10
SFRP4|6424 1.709e-13 6.23e-10
COL6A3|1293 3.33e-13 1.01e-09
ISLR|3671 4.633e-13 1.21e-09
CCDC80|151887 7.481e-13 1.7e-09
COL1A1|1277 9.739e-13 1.97e-09
FNDC1|84624 1.257e-12 2.16e-09
Clinical variable #4: 'PATHOLOGY_T_STAGE'

30 genes related to 'PATHOLOGY_T_STAGE'.

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

PATHOLOGY_T_STAGE Mean (SD) 2.79 (0.72)
  N
  T0 2
  T1 3
  T2 116
  T3 183
  T4 53
     
  Significant markers N = 30
  pos. correlated 30
  neg. correlated 0
List of top 10 genes differentially expressed by 'PATHOLOGY_T_STAGE'

Table S8.  Get Full Table List of top 10 genes significantly correlated to 'PATHOLOGY_T_STAGE' by Spearman correlation test

SpearmanCorr corrP Q
LRIG1|26018 0.3337 9.804e-11 1.09e-06
CCDC80|151887 0.3323 1.194e-10 1.09e-06
CTHRC1|115908 0.3242 3.527e-10 2.12e-06
SSC5D|284297 0.3221 4.645e-10 2.12e-06
SFRP4|6424 0.3194 1.203e-09 3.75e-06
WISP1|8840 0.3141 1.361e-09 3.75e-06
FNDC1|84624 0.3154 1.591e-09 3.75e-06
LRRN2|10446 0.3156 1.647e-09 3.75e-06
VCAN|1462 0.3107 1.993e-09 3.82e-06
IGF1|3479 0.3103 2.098e-09 3.82e-06
Clinical variable #5: 'PATHOLOGY_N_STAGE'

30 genes related to 'PATHOLOGY_N_STAGE'.

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

PATHOLOGY_N_STAGE Mean (SD) 0.62 (0.9)
  N
  N0 225
  N1 41
  N2 75
  N3 8
     
  Significant markers N = 30
  pos. correlated 22
  neg. correlated 8
List of top 10 genes differentially expressed by 'PATHOLOGY_N_STAGE'

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

SpearmanCorr corrP Q
IL1R1|3554 0.3062 5.181e-09 9.44e-05
MESP1|55897 0.2879 5.439e-08 0.000417
C15ORF48|84419 0.2838 6.87e-08 0.000417
PEA15|8682 0.2793 1.131e-07 0.000486
GFPT1|2673 0.2777 1.335e-07 0.000486
SULT1C2|6819 -0.2837 1.729e-07 0.000525
ISLR|3671 0.2708 2.794e-07 0.000612
COPG|22820 0.2695 3.192e-07 0.000612
P4HA3|283208 0.2691 3.334e-07 0.000612
MCEE|84693 0.269 3.362e-07 0.000612
Clinical variable #6: 'PATHOLOGY_M_STAGE'

No gene related to 'PATHOLOGY_M_STAGE'.

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

PATHOLOGY_M_STAGE Labels N
  class0 189
  class1 10
     
  Significant markers N = 0
Clinical variable #7: 'GENDER'

9 genes related to 'GENDER'.

Table S12.  Basic characteristics of clinical feature: 'GENDER'

GENDER Labels N
  FEMALE 101
  MALE 288
     
  Significant markers N = 9
  Higher in MALE 9
  Higher in FEMALE 0
List of 9 genes differentially expressed by 'GENDER'

Table S13.  Get Full Table List of 9 genes differentially expressed by 'GENDER'. 21 significant gene(s) located in sex chromosomes is(are) filtered out.

W(pos if higher in 'MALE') wilcoxontestP Q AUC
HDHD1A|8226 8178 7.289e-11 1.11e-07 0.7179
CYORF15A|246126 3725 1.226e-09 1.49e-06 0.9984
CYORF15B|84663 3453 4.71e-09 5.05e-06 0.9991
NCRNA00183|554203 9913 1.913e-06 0.00145 0.6592
PHF7|51533 19084 3.029e-06 0.00212 0.6561
ORC5L|5001 10135 5.785e-06 0.0039 0.6516
CARD10|29775 10160 6.532e-06 0.00425 0.6507
DDX43|55510 13925 2.887e-05 0.0181 0.6537
RAF1|5894 18593 3.129e-05 0.0185 0.6392
Clinical variable #8: 'KARNOFSKY_PERFORMANCE_SCORE'

30 genes related to 'KARNOFSKY_PERFORMANCE_SCORE'.

Table S14.  Basic characteristics of clinical feature: 'KARNOFSKY_PERFORMANCE_SCORE'

KARNOFSKY_PERFORMANCE_SCORE Mean (SD) 82.66 (14)
  Significant markers N = 30
  pos. correlated 18
  neg. correlated 12
List of top 10 genes differentially expressed by 'KARNOFSKY_PERFORMANCE_SCORE'

Table S15.  Get Full Table List of top 10 genes significantly correlated to 'KARNOFSKY_PERFORMANCE_SCORE' by Spearman correlation test

SpearmanCorr corrP Q
APBB1IP|54518 0.5117 1.245e-09 2.27e-05
DGKA|1606 -0.4826 1.378e-08 0.000126
S1PR3|1903 0.4748 2.533e-08 0.000154
LOC283070|283070 -0.4435 2.481e-07 0.000954
MRAS|22808 0.4428 2.618e-07 0.000954
SLC9A1|6548 -0.4385 3.513e-07 0.00098
ANXA3|306 0.4375 3.767e-07 0.00098
IL18R1|8809 0.4337 4.861e-07 0.00111
MMD|23531 0.4284 6.9e-07 0.0014
ZNF658|26149 -0.4229 9.896e-07 0.0018
Clinical variable #9: 'NUMBER_PACK_YEARS_SMOKED'

No gene related to 'NUMBER_PACK_YEARS_SMOKED'.

Table S16.  Basic characteristics of clinical feature: 'NUMBER_PACK_YEARS_SMOKED'

NUMBER_PACK_YEARS_SMOKED Mean (SD) 38.91 (54)
  Significant markers N = 0
Clinical variable #10: 'NUMBER_OF_LYMPH_NODES'

30 genes related to 'NUMBER_OF_LYMPH_NODES'.

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

NUMBER_OF_LYMPH_NODES Mean (SD) 2.03 (6.9)
  Significant markers N = 30
  pos. correlated 27
  neg. correlated 3
List of top 10 genes differentially expressed by 'NUMBER_OF_LYMPH_NODES'

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

SpearmanCorr corrP Q
GDPD3|79153 0.3113 1.048e-07 0.00148
IL1R1|3554 0.303 2.34e-07 0.00148
MCEE|84693 0.3026 2.438e-07 0.00148
SLC44A2|57153 0.2995 3.261e-07 0.00148
MAL|4118 0.2947 5.667e-07 0.00206
ANXA9|8416 0.2831 1.475e-06 0.00448
PRSS27|83886 0.2765 2.636e-06 0.00547
WWC1|23286 0.2742 3.194e-06 0.00547
KCNG1|3755 0.2742 3.206e-06 0.00547
PRR15L|79170 0.2769 3.268e-06 0.00547
Clinical variable #11: 'RACE'

30 genes related to 'RACE'.

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

RACE Labels N
  ASIAN 43
  BLACK OR AFRICAN AMERICAN 22
  WHITE 308
     
  Significant markers N = 30
List of top 10 genes differentially expressed by 'RACE'

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

kruskal_wallis_P Q
CALU|813 1.053e-11 1.92e-07
XKR9|389668 2.958e-11 2.69e-07
SEC23A|10484 7.726e-11 3.11e-07
WFIKKN1|117166 8.867e-11 3.11e-07
TXNRD1|7296 1.076e-10 3.11e-07
JMJD7-PLA2G4B|8681 1.211e-10 3.11e-07
ZFPM1|161882 1.361e-10 3.11e-07
CLIC4|25932 1.365e-10 3.11e-07
LOX|4015 2.584e-10 5.1e-07
BAG2|9532 2.949e-10 5.1e-07
Clinical variable #12: 'ETHNICITY'

No gene related to 'ETHNICITY'.

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

ETHNICITY Labels N
  HISPANIC OR LATINO 8
  NOT HISPANIC OR LATINO 351
     
  Significant markers N = 0
Methods & Data
Input

  • Expresson data file = BLCA-TP.uncv2.mRNAseq_RSEM_normalized_log2.txt

  • Clinical data file = BLCA-TP.merged_data.txt

  • Number of patients = 389

  • Number of genes = 18215

  • Number of clinical features = 12

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.

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)
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