Correlation between mRNAseq expression and clinical features
Pancreatic Adenocarcinoma (Primary solid tumor)
02 April 2015  |  analyses__2015_04_02
Maintainer Information
Citation Information
doi:10.7908/C17S7MVG
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/C17S7MVG
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 18475 genes and 14 clinical features across 167 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 'DAYS_TO_DEATH_OR_LAST_FUP'.

    • ACTL6A|86 ,  MUM1|84939 ,  USP20|10868 ,  INSIG2|51141 ,  ARMC10|83787 ,  ...

  • 30 genes correlated to 'YEARS_TO_BIRTH'.

    • ABI2|10152 ,  MOSC1|64757 ,  BCORL1|63035 ,  UQCRC2|7385 ,  TANC2|26115 ,  ...

  • 18 genes correlated to 'NEOPLASM_DISEASESTAGE'.

    • GPR157|80045 ,  HAR1B|768097 ,  ZFP36L1|677 ,  FGFBP3|143282 ,  SLC25A17|10478 ,  ...

  • 30 genes correlated to 'PATHOLOGY_T_STAGE'.

    • EFCAB2|84288 ,  STK33|65975 ,  CHST10|9486 ,  VPS26B|112936 ,  DUSP15|128853 ,  ...

  • 1 gene correlated to 'PATHOLOGY_N_STAGE'.

    • GABARAPL2|11345

  • 5 genes correlated to 'GENDER'.

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

  • 30 genes correlated to 'HISTOLOGICAL_TYPE'.

    • NUP93|9688 ,  EIF2S1|1965 ,  TOLLIP|54472 ,  SLC38A5|92745 ,  WFIKKN1|117166 ,  ...

  • 1 gene correlated to 'NUMBER_PACK_YEARS_SMOKED'.

    • HIST2H2AB|317772

  • No genes correlated to 'PATHOLOGY_M_STAGE', 'YEAR_OF_TOBACCO_SMOKING_ONSET', 'COMPLETENESS_OF_RESECTION', 'NUMBER_OF_LYMPH_NODES', '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
DAYS_TO_DEATH_OR_LAST_FUP Cox regression test N=30 shorter survival N=16 longer survival N=14
YEARS_TO_BIRTH Spearman correlation test N=30 older N=17 younger N=13
NEOPLASM_DISEASESTAGE Kruskal-Wallis test N=18        
PATHOLOGY_T_STAGE Spearman correlation test N=30 higher stage N=1 lower stage N=29
PATHOLOGY_N_STAGE Wilcoxon test N=1 n1 N=1 n0 N=0
PATHOLOGY_M_STAGE Wilcoxon test   N=0        
GENDER Wilcoxon test N=5 male N=5 female N=0
HISTOLOGICAL_TYPE Kruskal-Wallis test N=30        
NUMBER_PACK_YEARS_SMOKED Spearman correlation test N=1 higher number_pack_years_smoked N=1 lower number_pack_years_smoked N=0
YEAR_OF_TOBACCO_SMOKING_ONSET Spearman correlation test   N=0        
COMPLETENESS_OF_RESECTION Kruskal-Wallis test   N=0        
NUMBER_OF_LYMPH_NODES Spearman correlation test   N=0        
RACE Kruskal-Wallis test   N=0        
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) 0.1-84.1 (median=14)
  censored N = 82
  death N = 84
     
  Significant markers N = 30
  associated with shorter survival 16
  associated with longer survival 14
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
ACTL6A|86 6 3.554e-08 0.00045 0.662
MUM1|84939 0.29 1.31e-07 0.00045 0.338
USP20|10868 0.23 1.391e-07 0.00045 0.337
INSIG2|51141 2.6 1.675e-07 0.00045 0.67
ARMC10|83787 5.3 1.681e-07 0.00045 0.643
TRIM67|440730 0.56 1.91e-07 0.00045 0.345
KPNA4|3840 4.9 2.075e-07 0.00045 0.635
MET|4233 1.81 2.137e-07 0.00045 0.667
SPRN|503542 0.49 2.209e-07 0.00045 0.364
THSD1P1|374500 0.35 3.531e-07 0.00063 0.364
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) 64.62 (11)
  Significant markers N = 30
  pos. correlated 17
  neg. correlated 13
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
ABI2|10152 -0.3675 1.033e-06 0.0191
MOSC1|64757 0.3507 3.371e-06 0.0311
BCORL1|63035 -0.3234 2.015e-05 0.0979
UQCRC2|7385 0.318 2.821e-05 0.0979
TANC2|26115 -0.317 2.993e-05 0.0979
CACNG4|27092 -0.316 3.181e-05 0.0979
MRPL1|65008 0.3084 5.006e-05 0.0991
PSMB8|5696 0.3082 5.093e-05 0.0991
RRS1|23212 0.3081 5.1e-05 0.0991
VARS|7407 0.305 6.119e-05 0.0991
Clinical variable #3: 'NEOPLASM_DISEASESTAGE'

18 genes related to 'NEOPLASM_DISEASESTAGE'.

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

NEOPLASM_DISEASESTAGE Labels N
  STAGE I 1
  STAGE IA 6
  STAGE IB 13
  STAGE IIA 25
  STAGE IIB 114
  STAGE III 4
  STAGE IV 3
     
  Significant markers N = 18
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
GPR157|80045 4.038e-05 0.255
HAR1B|768097 4.483e-05 0.255
ZFP36L1|677 5.75e-05 0.255
FGFBP3|143282 6.901e-05 0.255
SLC25A17|10478 9.023e-05 0.255
NUDT9|53343 9.862e-05 0.255
PIGY|84992 0.0001119 0.255
C15ORF26|161502 0.0001252 0.255
METTL10|399818 0.0001517 0.255
C10ORF88|80007 0.0001594 0.255
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) 2.8 (0.55)
  N
  T1 8
  T2 21
  T3 134
  T4 3
     
  Significant markers N = 30
  pos. correlated 1
  neg. correlated 29
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
EFCAB2|84288 -0.3638 1.451e-06 0.0142
STK33|65975 -0.364 1.535e-06 0.0142
CHST10|9486 -0.345 5.322e-06 0.027
VPS26B|112936 -0.3436 5.849e-06 0.027
DUSP15|128853 -0.3339 1.104e-05 0.0284
QDPR|5860 -0.331 1.326e-05 0.0284
GPR27|2850 -0.3374 1.454e-05 0.0284
BEX1|55859 -0.325 1.931e-05 0.0284
CDK20|23552 -0.3248 1.964e-05 0.0284
LOC401127|401127 -0.3236 2.238e-05 0.0284
Clinical variable #5: 'PATHOLOGY_N_STAGE'

One gene related to 'PATHOLOGY_N_STAGE'.

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

PATHOLOGY_N_STAGE Labels N
  N0 44
  N1 119
     
  Significant markers N = 1
  Higher in N1 1
  Higher in N0 0
List of one gene differentially expressed by 'PATHOLOGY_N_STAGE'

Table S10.  Get Full Table List of one gene differentially expressed by 'PATHOLOGY_N_STAGE'

W(pos if higher in 'N1') wilcoxontestP Q AUC
GABARAPL2|11345 1429 8.875e-06 0.164 0.7271
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 75
  class1 3
     
  Significant markers N = 0
Clinical variable #7: 'GENDER'

5 genes related to 'GENDER'.

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

GENDER Labels N
  FEMALE 75
  MALE 92
     
  Significant markers N = 5
  Higher in MALE 5
  Higher in FEMALE 0
List of 5 genes differentially expressed by 'GENDER'

Table S13.  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
NCRNA00183|554203 1109 5.057e-14 7.79e-11 0.8393
HDHD1A|8226 1409 5.196e-11 5.65e-08 0.7958
CYORF15B|84663 1467 2.659e-10 2.46e-07 0.9966
CYORF15A|246126 1092 4.039e-08 2.87e-05 0.9891
CA5BP|340591 1780 7.807e-08 5.34e-05 0.742
Clinical variable #8: 'HISTOLOGICAL_TYPE'

30 genes related to 'HISTOLOGICAL_TYPE'.

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

HISTOLOGICAL_TYPE Labels N
  PANCREAS-ADENOCARCINOMA DUCTAL TYPE 139
  PANCREAS-ADENOCARCINOMA-OTHER SUBTYPE 22
  PANCREAS-COLLOID (MUCINOUS NON-CYSTIC) CARCINOMA 4
  PANCREAS-UNDIFFERENTIATED CARCINOMA 1
     
  Significant markers N = 30
List of top 10 genes differentially expressed by 'HISTOLOGICAL_TYPE'

Table S15.  Get Full Table List of top 10 genes differentially expressed by 'HISTOLOGICAL_TYPE'

kruskal_wallis_P Q
NUP93|9688 1.182e-06 0.0202
EIF2S1|1965 3.255e-06 0.0202
TOLLIP|54472 3.929e-06 0.0202
SLC38A5|92745 4.947e-06 0.0202
WFIKKN1|117166 1.109e-05 0.0202
KCNJ3|3760 1.114e-05 0.0202
RRAS2|22800 1.138e-05 0.0202
BZRAP1|9256 1.219e-05 0.0202
GPR132|29933 1.243e-05 0.0202
SEZ6L2|26470 1.38e-05 0.0202
Clinical variable #9: 'NUMBER_PACK_YEARS_SMOKED'

One gene related to 'NUMBER_PACK_YEARS_SMOKED'.

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

NUMBER_PACK_YEARS_SMOKED Mean (SD) 26.45 (18)
  Significant markers N = 1
  pos. correlated 1
  neg. correlated 0
List of one gene differentially expressed by 'NUMBER_PACK_YEARS_SMOKED'

Table S17.  Get Full Table List of one gene significantly correlated to 'NUMBER_PACK_YEARS_SMOKED' by Spearman correlation test

SpearmanCorr corrP Q
HIST2H2AB|317772 0.8049 2.417e-07 0.00447
Clinical variable #10: 'YEAR_OF_TOBACCO_SMOKING_ONSET'

No gene related to 'YEAR_OF_TOBACCO_SMOKING_ONSET'.

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

YEAR_OF_TOBACCO_SMOKING_ONSET Mean (SD) 1970.67 (13)
  Significant markers N = 0
Clinical variable #11: 'COMPLETENESS_OF_RESECTION'

No gene related to 'COMPLETENESS_OF_RESECTION'.

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

COMPLETENESS_OF_RESECTION Labels N
  R0 103
  R1 51
  R2 2
  RX 4
     
  Significant markers N = 0
Clinical variable #12: 'NUMBER_OF_LYMPH_NODES'

No gene related to 'NUMBER_OF_LYMPH_NODES'.

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

NUMBER_OF_LYMPH_NODES Mean (SD) 3.01 (3.5)
  Significant markers N = 0
Clinical variable #13: 'RACE'

No gene related to 'RACE'.

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

RACE Labels N
  ASIAN 3
  BLACK OR AFRICAN AMERICAN 6
  WHITE 154
     
  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 3
  NOT HISPANIC OR LATINO 130
     
  Significant markers N = 0
Methods & Data
Input

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

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

  • Number of patients = 167

  • Number of genes = 18475

  • 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)
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