Correlation between mRNAseq expression and clinical features
Breast Invasive Carcinoma (Primary solid tumor)
28 January 2016  |  analyses__2016_01_28
Maintainer Information
Citation Information
doi:10.7908/C17H1HX3
Maintained by Juok Cho (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2016): Correlation between mRNAseq expression and clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C17H1HX3
Overview
Introduction

This pipeline uses various statistical tests to identify mRNAs whose log2 expression levels correlated to selected clinical features. The input file "BRCA-TP.uncv2.mRNAseq_RSEM_normalized_log2.txt" is generated in the pipeline mRNAseq_Preprocess in the stddata run.

Summary

Testing the association between 18296 genes and 12 clinical features across 1093 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'.

    • PGK1|5230 ,  TFPI2|7980 ,  IGJ|3512 ,  FAM159A|348378 ,  PCMT1|5110 ,  ...

  • 30 genes correlated to 'YEARS_TO_BIRTH'.

    • ESR1|2099 ,  DSC2|1824 ,  TMEFF1|8577 ,  FAT2|2196 ,  LRFN5|145581 ,  ...

  • 30 genes correlated to 'PATHOLOGIC_STAGE'.

    • C18ORF34|374864 ,  MMRN1|22915 ,  CCL14|6358 ,  ABCA9|10350 ,  ZFP36|7538 ,  ...

  • 30 genes correlated to 'PATHOLOGY_T_STAGE'.

    • ZMYM6|9204 ,  ERMN|57471 ,  ARAF|369 ,  NDNL2|56160 ,  ZBTB1|22890 ,  ...

  • 30 genes correlated to 'PATHOLOGY_N_STAGE'.

    • SVEP1|79987 ,  HTR2B|3357 ,  NR2F2|7026 ,  HMSD|284293 ,  CERCAM|51148 ,  ...

  • 1 gene correlated to 'PATHOLOGY_M_STAGE'.

    • RBM25|58517

  • 24 genes correlated to 'GENDER'.

    • FAM104A|84923 ,  CSNK1D|1453 ,  SLC39A11|201266 ,  GINS2|51659 ,  ASS1|445 ,  ...

  • 30 genes correlated to 'RADIATION_THERAPY'.

    • SIRPB2|284759 ,  CLSTN1|22883 ,  ANKRD37|353322 ,  TAS2R1|50834 ,  SRGN|5552 ,  ...

  • 30 genes correlated to 'HISTOLOGICAL_TYPE'.

    • CDH1|999 ,  RAPGEF3|10411 ,  LTBP4|8425 ,  TENC1|23371 ,  AVPR2|554 ,  ...

  • 30 genes correlated to 'NUMBER_OF_LYMPH_NODES'.

    • POU4F1|5457 ,  HMSD|284293 ,  PODN|127435 ,  SNED1|25992 ,  CERCAM|51148 ,  ...

  • 30 genes correlated to 'RACE'.

    • CRYBB2|1415 ,  CROCCL1|84809 ,  FAM3A|60343 ,  LRRC37A2|474170 ,  C14ORF167|55449 ,  ...

  • No genes correlated to '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   N=NA   N=NA
YEARS_TO_BIRTH Spearman correlation test N=30 older N=2 younger N=28
PATHOLOGIC_STAGE Kruskal-Wallis test N=30        
PATHOLOGY_T_STAGE Spearman correlation test N=30 higher stage N=4 lower stage N=26
PATHOLOGY_N_STAGE Spearman correlation test N=30 higher stage N=20 lower stage N=10
PATHOLOGY_M_STAGE Wilcoxon test N=1 class1 N=1 class0 N=0
GENDER Wilcoxon test N=24 male N=24 female N=0
RADIATION_THERAPY Wilcoxon test N=30 yes N=30 no N=0
HISTOLOGICAL_TYPE Kruskal-Wallis test N=30        
NUMBER_OF_LYMPH_NODES Spearman correlation test N=30 higher number_of_lymph_nodes N=23 lower number_of_lymph_nodes N=7
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) 0-282.9 (median=28.3)
  censored N = 940
  death N = 152
     
  Significant markers N = 30
  associated with shorter survival NA
  associated with longer survival NA
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. For the survival curves, it compared quantile intervals at c(0, 0.25, 0.50, 0.75, 1) and did not try survival analysis if there is only one interval.

logrank_P Q C_index
PGK1|5230 1.69e-07 0.0031 0.665
TFPI2|7980 1.97e-05 0.12 0.419
IGJ|3512 2.01e-05 0.12 0.376
FAM159A|348378 3.17e-05 0.15 0.423
PCMT1|5110 6.59e-05 0.21 0.629
NACAD|23148 8.04e-05 0.21 0.406
CEBPD|1052 9.49e-05 0.21 0.432
IRF2|3660 0.000108 0.21 0.382
CAMK4|814 0.000113 0.21 0.401
IL27RA|9466 0.000132 0.21 0.434
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) 58.59 (13)
  Significant markers N = 30
  pos. correlated 2
  neg. correlated 28
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
ESR1|2099 0.3475 5.945e-32 1.09e-27
DSC2|1824 -0.2677 3.787e-19 3.46e-15
TMEFF1|8577 -0.2568 1.072e-17 6.54e-14
FAT2|2196 -0.2469 2.176e-16 7.21e-13
LRFN5|145581 -0.2486 2.9e-16 7.21e-13
DZIP1|22873 -0.2455 2.951e-16 7.21e-13
ASTN1|460 -0.2526 3.032e-16 7.21e-13
ZNF521|25925 -0.2448 3.587e-16 7.21e-13
RELN|5649 -0.248 3.954e-16 7.21e-13
LAMA1|284217 -0.2442 4.402e-16 7.21e-13
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 90
  STAGE IA 85
  STAGE IB 6
  STAGE II 6
  STAGE IIA 358
  STAGE IIB 256
  STAGE III 2
  STAGE IIIA 156
  STAGE IIIB 27
  STAGE IIIC 65
  STAGE IV 20
  STAGE X 14
     
  Significant markers N = 30
List of top 10 genes differentially expressed by 'PATHOLOGIC_STAGE'

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

kruskal_wallis_P Q
C18ORF34|374864 1.572e-07 0.00135
MMRN1|22915 1.834e-07 0.00135
CCL14|6358 3.176e-07 0.00135
ABCA9|10350 3.48e-07 0.00135
ZFP36|7538 4.607e-07 0.00135
C16ORF89|146556 5.129e-07 0.00135
SVEP1|79987 5.175e-07 0.00135
DARC|2532 1.194e-06 0.00273
FOS|2353 1.404e-06 0.00276
MFAP4|4239 1.509e-06 0.00276
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) 1.94 (0.73)
  N
  T1 279
  T2 633
  T3 138
  T4 40
     
  Significant markers N = 30
  pos. correlated 4
  neg. correlated 26
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
ZMYM6|9204 -0.1775 3.62e-09 6.62e-05
ERMN|57471 -0.1665 3.363e-08 0.000207
ARAF|369 0.1662 3.398e-08 0.000207
NDNL2|56160 -0.1625 6.81e-08 0.000311
ZBTB1|22890 -0.1613 8.573e-08 0.000314
RBM10|8241 0.1587 1.396e-07 0.000401
IKZF4|64375 -0.1582 1.534e-07 0.000401
SEMA3D|223117 -0.1564 2.253e-07 0.000449
MMP10|4319 -0.158 2.344e-07 0.000449
CLEC5A|23601 -0.1556 2.453e-07 0.000449
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) 0.78 (0.91)
  N
  N0 515
  N1 361
  N2 120
  N3 77
     
  Significant markers N = 30
  pos. correlated 20
  neg. correlated 10
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
SVEP1|79987 0.1606 1.247e-07 0.000897
HTR2B|3357 0.1591 1.609e-07 0.000897
NR2F2|7026 0.1591 1.618e-07 0.000897
HMSD|284293 -0.2052 2.244e-07 0.000897
CERCAM|51148 0.1567 2.464e-07 0.000897
NUDT4|11163 0.1556 3.013e-07 0.000897
F2R|2149 0.1549 3.432e-07 0.000897
SNED1|25992 0.1518 5.887e-07 0.00135
PODN|127435 0.1507 7.04e-07 0.00143
TTC22|55001 -0.1479 1.391e-06 0.00208
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 903
  class1 22
     
  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
RBM25|58517 4534 1.3e-05 0.238 0.7718
Clinical variable #7: 'GENDER'

24 genes related to 'GENDER'.

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

GENDER Labels N
  FEMALE 1081
  MALE 12
     
  Significant markers N = 24
  Higher in MALE 24
  Higher in FEMALE 0
List of top 10 genes differentially expressed by 'GENDER'

Table S14.  Get Full Table List of top 10 genes differentially expressed by 'GENDER'. 6 significant gene(s) located in sex chromosomes is(are) filtered out.

W(pos if higher in 'MALE') wilcoxontestP Q AUC
FAM104A|84923 11804 1.01e-06 0.00369 0.91
CSNK1D|1453 11608 2.483e-06 0.00757 0.8949
SLC39A11|201266 11496 4.095e-06 0.00996 0.8862
GINS2|51659 11482 4.356e-06 0.00996 0.8851
ASS1|445 1539 5.401e-06 0.011 0.8814
DHRS2|10202 11255 8.125e-06 0.014 0.8741
ST6GAL1|6480 1663 9.226e-06 0.014 0.8718
MRPS23|51649 11291 9.961e-06 0.014 0.8704
PYY|5697 8155 9.97e-06 0.014 0.8713
MSMB|4477 10516 1.115e-05 0.0143 0.8685
Clinical variable #8: 'RADIATION_THERAPY'

30 genes related to 'RADIATION_THERAPY'.

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

RADIATION_THERAPY Labels N
  NO 445
  YES 553
     
  Significant markers N = 30
  Higher in YES 30
  Higher in NO 0
List of top 10 genes differentially expressed by 'RADIATION_THERAPY'

Table S16.  Get Full Table List of top 10 genes differentially expressed by 'RADIATION_THERAPY'

W(pos if higher in 'YES') wilcoxontestP Q AUC
SIRPB2|284759 144137.5 2.402e-06 0.0392 0.5868
CLSTN1|22883 102779 7.577e-06 0.0392 0.5823
ANKRD37|353322 103005 9.56e-06 0.0392 0.5814
TAS2R1|50834 10338 1.009e-05 0.0392 0.6391
SRGN|5552 142968 1.072e-05 0.0392 0.581
CD300E|342510 91457 1.808e-05 0.0509 0.5885
IFT27|11020 103899 2.344e-05 0.0509 0.5778
ANKRD54|129138 104039 2.688e-05 0.0509 0.5772
DNAL4|10126 104044 2.701e-05 0.0509 0.5772
HTR2B|3357 142011 2.781e-05 0.0509 0.5771
Clinical variable #9: 'HISTOLOGICAL_TYPE'

30 genes related to 'HISTOLOGICAL_TYPE'.

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

HISTOLOGICAL_TYPE Labels N
  INFILTRATING CARCINOMA NOS 1
  INFILTRATING DUCTAL CARCINOMA 782
  INFILTRATING LOBULAR CARCINOMA 203
  MEDULLARY CARCINOMA 6
  METAPLASTIC CARCINOMA 9
  MIXED HISTOLOGY (PLEASE SPECIFY) 29
  MUCINOUS CARCINOMA 17
  OTHER, SPECIFY 45
     
  Significant markers N = 30
List of top 10 genes differentially expressed by 'HISTOLOGICAL_TYPE'

Table S18.  Get Full Table List of top 10 genes differentially expressed by 'HISTOLOGICAL_TYPE'

kruskal_wallis_P Q
CDH1|999 7.354e-69 1.35e-64
RAPGEF3|10411 6.194e-48 5.67e-44
LTBP4|8425 2.934e-46 1.79e-42
TENC1|23371 8.671e-46 3.97e-42
AVPR2|554 1.615e-45 5.91e-42
PSMD12|5718 4.784e-45 1.46e-41
ADAM33|80332 6.954e-45 1.82e-41
CSE1L|1434 2.637e-43 6.03e-40
USHBP1|83878 5.213e-43 1.06e-39
PLAC9|219348 1.197e-42 2.04e-39
Clinical variable #10: 'NUMBER_OF_LYMPH_NODES'

30 genes related to 'NUMBER_OF_LYMPH_NODES'.

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

NUMBER_OF_LYMPH_NODES Mean (SD) 2.37 (4.6)
  Significant markers N = 30
  pos. correlated 23
  neg. correlated 7
List of top 10 genes differentially expressed by 'NUMBER_OF_LYMPH_NODES'

Table S20.  Get Full Table List of top 10 genes significantly correlated to 'NUMBER_OF_LYMPH_NODES' by Spearman correlation test

SpearmanCorr corrP Q
POU4F1|5457 -0.2344 5.985e-08 0.00066
HMSD|284293 -0.2282 7.213e-08 0.00066
PODN|127435 0.1718 1.465e-07 0.000893
SNED1|25992 0.17 1.989e-07 0.00091
CERCAM|51148 0.1653 4.26e-07 0.00156
CD1A|909 -0.1692 6.002e-07 0.00183
NUDT4|11163 0.158 1.371e-06 0.00316
HTR2B|3357 0.158 1.381e-06 0.00316
LRRC32|2615 0.1539 2.571e-06 0.00523
SLC1A7|6512 0.1537 3.139e-06 0.00524
Clinical variable #11: 'RACE'

30 genes related to 'RACE'.

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

RACE Labels N
  AMERICAN INDIAN OR ALASKA NATIVE 1
  ASIAN 61
  BLACK OR AFRICAN AMERICAN 183
  WHITE 753
     
  Significant markers N = 30
List of top 10 genes differentially expressed by 'RACE'

Table S22.  Get Full Table List of top 10 genes differentially expressed by 'RACE'

kruskal_wallis_P Q
CRYBB2|1415 3.938e-37 7.2e-33
CROCCL1|84809 2.144e-35 1.96e-31
FAM3A|60343 5.163e-35 3.15e-31
LRRC37A2|474170 8.184e-33 3.74e-29
C14ORF167|55449 1.775e-31 6.49e-28
LOC90784|90784 2.707e-30 8.26e-27
TSPO|706 7.427e-29 1.94e-25
TRABD|80305 1e-28 2.27e-25
NSUN5P1|155400 1.209e-28 2.27e-25
MEIS3P1|4213 1.239e-28 2.27e-25
Clinical variable #12: 'ETHNICITY'

No gene related to 'ETHNICITY'.

Table S23.  Basic characteristics of clinical feature: 'ETHNICITY'

ETHNICITY Labels N
  HISPANIC OR LATINO 39
  NOT HISPANIC OR LATINO 880
     
  Significant markers N = 0
Methods & Data
Input

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

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

  • Number of patients = 1093

  • Number of genes = 18296

  • 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, logrank test in univariate Cox regression analysis with proportional hazards model (Andersen and Gill 1982) was used to estimate the P values comparing quantile intervals using the 'coxph' function in R. Kaplan-Meier survival curves were plotted using quantile intervals at c(0, 0.25, 0.50, 0.75, 1). If there is only one interval group, it will not try survival analysis.

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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