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 23365 genes and 12 clinical features across 274 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 11 clinical features related to at least one genes.

  • 30 genes correlated to 'DAYS_TO_DEATH_OR_LAST_FUP'.

    • LOC100506178|100506178_CALCULATED ,  BC038245|?_CALCULATED ,  SLC52A3|113278_CALCULATED ,  PAPPA2|60676_CALCULATED ,  PRR5-ARHGAP8|553158_CALCULATED ,  ...

  • 30 genes correlated to 'YEARS_TO_BIRTH'.

    • TMEM240|339453_CALCULATED ,  PEX7|5191_CALCULATED ,  CXCL1|2919_CALCULATED ,  KIAA0845|?_CALCULATED ,  TMEM132C|92293_CALCULATED ,  ...

  • 30 genes correlated to 'PATHOLOGIC_STAGE'.

    • GNB4|59345_CALCULATED ,  FMO2|2327_CALCULATED ,  METAZOA_SRP|?|35OF109_CALCULATED ,  DDX6|1656_CALCULATED ,  ANKRD11|29123_CALCULATED ,  ...

  • 30 genes correlated to 'PATHOLOGY_T_STAGE'.

    • SNTB2|6645_CALCULATED ,  GNB4|59345_CALCULATED ,  PPP1R12A|4659_CALCULATED ,  NEXN|91624_CALCULATED ,  YIPF3|25844_CALCULATED ,  ...

  • 30 genes correlated to 'PATHOLOGY_N_STAGE'.

    • DYNC2H1|79659_CALCULATED ,  YPEL2|388403_CALCULATED ,  BX538254|?_CALCULATED ,  ABCA6|23460_CALCULATED ,  FAM13B|51306_CALCULATED ,  ...

  • 1 gene correlated to 'PATHOLOGY_M_STAGE'.

    • HEATR7A|727957|1OF2_CALCULATED

  • 1 gene correlated to 'GENDER'.

    • AY927613|?_CALCULATED

  • 30 genes correlated to 'HISTOLOGICAL_TYPE'.

    • MFAP5|8076_CALCULATED ,  FRMD6|122786_CALCULATED ,  VIM|7431_CALCULATED ,  GEM|2669_CALCULATED ,  ZFPM2|23414_CALCULATED ,  ...

  • 30 genes correlated to 'RESIDUAL_TUMOR'.

    • ZBTB3|79842_CALCULATED ,  GLTSCR1|29998_CALCULATED ,  METAZOA_SRP|?|35OF109_CALCULATED ,  HIATL2|84278_CALCULATED ,  ZNF865|100507290_CALCULATED ,  ...

  • 30 genes correlated to 'NUMBER_OF_LYMPH_NODES'.

    • BX538254|?_CALCULATED ,  ABCA6|23460_CALCULATED ,  DTX1|1840_CALCULATED ,  YPEL2|388403_CALCULATED ,  SIGLEC6|946_CALCULATED ,  ...

  • 30 genes correlated to 'RACE'.

    • AK055746|?_CALCULATED ,  RGPD4|285190_CALCULATED ,  SIRPB2|284759_CALCULATED ,  NPIPL2|440348_CALCULATED ,  PSPHP1|8781_CALCULATED ,  ...

  • No genes correlated to 'RADIATION_THERAPY'

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=13 longer survival N=17
YEARS_TO_BIRTH Spearman correlation test N=30 older N=19 younger N=11
PATHOLOGIC_STAGE Kruskal-Wallis test N=30        
PATHOLOGY_T_STAGE Spearman correlation test N=30 higher stage N=27 lower stage N=3
PATHOLOGY_N_STAGE Spearman correlation test N=30 higher stage N=24 lower stage N=6
PATHOLOGY_M_STAGE Wilcoxon test N=1 class1 N=1 class0 N=0
GENDER Wilcoxon test N=1 male N=1 female N=0
RADIATION_THERAPY Wilcoxon test   N=0        
HISTOLOGICAL_TYPE Kruskal-Wallis test N=30        
RESIDUAL_TUMOR Kruskal-Wallis test N=30        
NUMBER_OF_LYMPH_NODES Spearman correlation test N=30 higher number_of_lymph_nodes N=28 lower number_of_lymph_nodes N=2
RACE Kruskal-Wallis test N=30        
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) 0-105.1 (median=13.8)
  censored N = 189
  death N = 84
     
  Significant markers N = 30
  associated with shorter survival 13
  associated with longer survival 17
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
LOC100506178|100506178_CALCULATED 1.37 5.407e-06 0.11 0.64
BC038245|?_CALCULATED 0.68 1.778e-05 0.11 0.386
SLC52A3|113278_CALCULATED 0.69 1.814e-05 0.11 0.367
PAPPA2|60676_CALCULATED 1.2 2.284e-05 0.11 0.615
PRR5-ARHGAP8|553158_CALCULATED 0.58 3.225e-05 0.11 0.372
FOLR2|2350_CALCULATED 1.42 3.31e-05 0.11 0.629
SLC5A10|125206_CALCULATED 0.53 3.544e-05 0.11 0.379
PLCXD3|345557_CALCULATED 1.22 4.374e-05 0.11 0.619
MYB|4602_CALCULATED 0.75 4.628e-05 0.11 0.393
ETV2|2116_CALCULATED 0.61 5.581e-05 0.11 0.374
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) 65.75 (11)
  Significant markers N = 30
  pos. correlated 19
  neg. correlated 11
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
TMEM240|339453_CALCULATED -0.3261 4.955e-08 0.000837
PEX7|5191_CALCULATED 0.3223 7.164e-08 0.000837
CXCL1|2919_CALCULATED 0.3086 2.674e-07 0.00185
KIAA0845|?_CALCULATED -0.3068 3.17e-07 0.00185
TMEM132C|92293_CALCULATED -0.3152 5.57e-07 0.00247
CRTAP|10491_CALCULATED -0.2992 6.334e-07 0.00247
SPTBN4|57731_CALCULATED -0.2932 1.08e-06 0.00258
SNORD52|26797_CALCULATED 0.2936 1.093e-06 0.00258
PSMB1|5689_CALCULATED 0.2922 1.181e-06 0.00258
FGFR1OP|11116_CALCULATED 0.2918 1.226e-06 0.00258
Clinical variable #3: 'PATHOLOGIC_STAGE'

30 genes related to 'PATHOLOGIC_STAGE'.

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

PATHOLOGIC_STAGE Labels N
  STAGE I 2
  STAGE IA 10
  STAGE IB 27
  STAGE II 23
  STAGE IIA 29
  STAGE IIB 44
  STAGE III 3
  STAGE IIIA 42
  STAGE IIIB 30
  STAGE IIIC 23
  STAGE IV 25
     
  Significant markers N = 30
List of top 10 genes differentially expressed by 'PATHOLOGIC_STAGE'

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) 2.92 (0.86)
  N
  T1 13
  T2 70
  T3 107
  T4 75
     
  Significant markers N = 30
  pos. correlated 27
  neg. correlated 3
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
SNTB2|6645_CALCULATED 0.4443 3.028e-14 7.08e-10
GNB4|59345_CALCULATED 0.4124 2.661e-12 2.31e-08
PPP1R12A|4659_CALCULATED 0.4115 2.962e-12 2.31e-08
NEXN|91624_CALCULATED 0.3926 3.391e-11 1.98e-07
YIPF3|25844_CALCULATED -0.379 1.775e-10 8.29e-07
CALD1|800_CALCULATED 0.3747 2.932e-10 1.14e-06
KCNE4|23704_CALCULATED 0.3698 5.198e-10 1.6e-06
SGTB|54557_CALCULATED 0.3691 5.621e-10 1.6e-06
OSTM1|28962_CALCULATED 0.3682 6.218e-10 1.6e-06
PLN|5350_CALCULATED 0.3671 7.115e-10 1.6e-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) 1.2 (1.1)
  N
  N0 91
  N1 76
  N2 46
  N3 49
     
  Significant markers N = 30
  pos. correlated 24
  neg. correlated 6
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
DYNC2H1|79659_CALCULATED 0.2881 2.108e-06 0.0174
YPEL2|388403_CALCULATED 0.2878 2.175e-06 0.0174
BX538254|?_CALCULATED 0.2851 2.73e-06 0.0174
ABCA6|23460_CALCULATED 0.284 2.986e-06 0.0174
FAM13B|51306_CALCULATED 0.2802 4.083e-06 0.0191
IL6ST|3572_CALCULATED 0.2738 6.908e-06 0.0223
C1ORF150|148823_CALCULATED 0.2748 8.465e-06 0.0223
DTX1|1840_CALCULATED 0.2659 1.285e-05 0.0223
EIF4EBP1|1978_CALCULATED -0.2659 1.291e-05 0.0223
C5ORF46|389336_CALCULATED -0.2852 1.397e-05 0.0223
Clinical variable #6: 'PATHOLOGY_M_STAGE'

One gene related to 'PATHOLOGY_M_STAGE'.

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

PATHOLOGY_M_STAGE Labels N
  class0 243
  class1 18
     
  Significant markers N = 1
  Higher in class1 1
  Higher in class0 0
List of one gene differentially expressed by 'PATHOLOGY_M_STAGE'

Table S12.  Get Full Table List of one gene differentially expressed by 'PATHOLOGY_M_STAGE'

W(pos if higher in 'class1') wilcoxontestP Q AUC
HEATR7A|727957|1OF2_CALCULATED 823 1.023e-05 0.239 0.8118
Clinical variable #7: 'GENDER'

One gene related to 'GENDER'.

Table S13.  Basic characteristics of clinical feature: 'GENDER'

GENDER Labels N
  FEMALE 103
  MALE 171
     
  Significant markers N = 1
  Higher in MALE 1
  Higher in FEMALE 0
List of one gene differentially expressed by 'GENDER'

Table S14.  Get Full Table List of one gene differentially expressed by 'GENDER'. 29 significant gene(s) located in sex chromosomes is(are) filtered out.

W(pos if higher in 'MALE') wilcoxontestP Q AUC
AY927613|?_CALCULATED 5226 1.751e-08 1.52e-05 0.7033
Clinical variable #8: 'RADIATION_THERAPY'

No gene related to 'RADIATION_THERAPY'.

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

RADIATION_THERAPY Labels N
  NO 203
  YES 26
     
  Significant markers N = 0
Clinical variable #9: 'HISTOLOGICAL_TYPE'

30 genes related to 'HISTOLOGICAL_TYPE'.

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

HISTOLOGICAL_TYPE Labels N
  STOMACH ADENOCARCINOMA DIFFUSE TYPE 51
  STOMACH ADENOCARCINOMA NOT OTHERWISE SPECIFIED (NOS) 130
  STOMACH INTESTINAL ADENOCARCINOMA NOT OTHERWISE SPECIFIED (NOS) 34
  STOMACH INTESTINAL ADENOCARCINOMA TUBULAR TYPE 36
  STOMACH ADENOCARCINOMA SIGNET RING TYPE 1
  STOMACH INTESTINAL ADENOCARCINOMA MUCINOUS TYPE 14
  STOMACH INTESTINAL ADENOCARCINOMA PAPILLARY TYPE 5
     
  Significant markers N = 30
List of top 10 genes differentially expressed by 'HISTOLOGICAL_TYPE'

Clinical variable #10: 'RESIDUAL_TUMOR'

30 genes related to 'RESIDUAL_TUMOR'.

Table S18.  Basic characteristics of clinical feature: 'RESIDUAL_TUMOR'

RESIDUAL_TUMOR Labels N
  R0 217
  R1 9
  R2 10
  RX 22
     
  Significant markers N = 30
List of top 10 genes differentially expressed by 'RESIDUAL_TUMOR'

Clinical variable #11: 'NUMBER_OF_LYMPH_NODES'

30 genes related to 'NUMBER_OF_LYMPH_NODES'.

Table S20.  Basic characteristics of clinical feature: 'NUMBER_OF_LYMPH_NODES'

NUMBER_OF_LYMPH_NODES Mean (SD) 4.84 (7.1)
  Significant markers N = 30
  pos. correlated 28
  neg. correlated 2
List of top 10 genes differentially expressed by 'NUMBER_OF_LYMPH_NODES'

Table S21.  Get Full Table List of top 10 genes significantly correlated to 'NUMBER_OF_LYMPH_NODES' by Spearman correlation test

SpearmanCorr corrP Q
BX538254|?_CALCULATED 0.2983 2.812e-06 0.0404
ABCA6|23460_CALCULATED 0.2862 7.265e-06 0.0404
DTX1|1840_CALCULATED 0.2829 9.316e-06 0.0404
YPEL2|388403_CALCULATED 0.2815 1.034e-05 0.0404
SIGLEC6|946_CALCULATED 0.2807 1.103e-05 0.0404
GPR20|2843_CALCULATED 0.2798 1.175e-05 0.0404
NFASC|23114_CALCULATED 0.2781 1.334e-05 0.0404
C1ORF150|148823_CALCULATED 0.2797 1.467e-05 0.0404
GHRL|51738_CALCULATED 0.276 1.557e-05 0.0404
GLIS3|169792_CALCULATED 0.2739 1.826e-05 0.0427
Clinical variable #12: 'RACE'

30 genes related to 'RACE'.

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

RACE Labels N
  ASIAN 73
  BLACK OR AFRICAN AMERICAN 4
  WHITE 156
     
  Significant markers N = 30
List of top 10 genes differentially expressed by 'RACE'

Methods & Data
Input

  • Expresson data file = STAD-TP.mRNAseq_RPKM_log2.txt

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

  • Number of patients = 274

  • Number of genes = 23365

  • Number of clinical features = 12

Selected clinical features

  • Further details on clinical features selected for this analysis, please find a documentation on selected CDEs (Clinical Data Elements). The first column of the file is a formula to convert values and the second column is a clinical parameter name.

  • 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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