Correlation between mRNA expression and clinical features
Breast Invasive Carcinoma (Primary solid tumor)
17 October 2014  |  analyses__2014_10_17
Maintainer Information
Citation Information
doi:10.7908/C11Z437X
Maintained by TCGA GDAC Team (Broad Institute/MD Anderson Cancer Center/Harvard Medical School)
Cite as Broad Institute TCGA Genome Data Analysis Center (2014): Correlation between mRNA expression and clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C11Z437X
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 17814 genes and 12 clinical features across 526 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 8 clinical features related to at least one genes.

  • 641 genes correlated to 'AGE'.

    • ESR1 ,  CNTNAP3 ,  KRT17 ,  C20ORF42 ,  MAGED4B ,  ...

  • 10 genes correlated to 'NEOPLASM.DISEASESTAGE'.

    • OR4D1 ,  RANBP2 ,  RPL11 ,  RWDD3 ,  GIPR ,  ...

  • 53 genes correlated to 'PATHOLOGY.T.STAGE'.

    • RBBP5 ,  PPP2R5D ,  TMEM81 ,  CCNF ,  TBRG4 ,  ...

  • 39 genes correlated to 'PATHOLOGY.N.STAGE'.

    • RWDD3 ,  RPL5 ,  HIST1H2AG ,  PBX1 ,  LRP6 ,  ...

  • 341 genes correlated to 'HISTOLOGICAL.TYPE'.

    • CDH1 ,  GLTSCR2 ,  ADRM1 ,  PPIL1 ,  ALG3 ,  ...

  • 3 genes correlated to 'RADIATIONS.RADIATION.REGIMENINDICATION'.

    • SETD7 ,  FBXL10 ,  LOC285398

  • 8 genes correlated to 'NUMBER.OF.LYMPH.NODES'.

    • CSDE1 ,  RWDD3 ,  BCAR1 ,  DDX20 ,  STS ,  ...

  • 50 genes correlated to 'RACE'.

    • PSPH ,  CRYBB2 ,  IL27 ,  PRSS36 ,  RAI16 ,  ...

  • No genes correlated to 'Time to Death', 'PATHOLOGY.M.STAGE', 'GENDER', 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 to Death Cox regression test   N=0        
AGE Spearman correlation test N=641 older N=255 younger N=386
NEOPLASM DISEASESTAGE Kruskal-Wallis test N=10        
PATHOLOGY T STAGE Spearman correlation test N=53 higher stage N=39 lower stage N=14
PATHOLOGY N STAGE Spearman correlation test N=39 higher stage N=20 lower stage N=19
PATHOLOGY M STAGE Kruskal-Wallis test   N=0        
GENDER Wilcoxon test   N=0        
HISTOLOGICAL TYPE Kruskal-Wallis test N=341        
RADIATIONS RADIATION REGIMENINDICATION Wilcoxon test N=3 yes N=3 no N=0
NUMBER OF LYMPH NODES Spearman correlation test N=8 higher number.of.lymph.nodes N=4 lower number.of.lymph.nodes N=4
RACE Kruskal-Wallis test N=50        
ETHNICITY Wilcoxon test   N=0        
Clinical variable #1: 'Time to Death'

No gene related to 'Time to Death'.

Table S1.  Basic characteristics of clinical feature: 'Time to Death'

Time to Death Duration (Months) 0.1-234.3 (median=29)
  censored N = 438
  death N = 73
     
  Significant markers N = 0
Clinical variable #2: 'AGE'

641 genes related to 'AGE'.

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

AGE Mean (SD) 58.08 (13)
  Significant markers N = 641
  pos. correlated 255
  neg. correlated 386
List of top 10 genes differentially expressed by 'AGE'

Table S3.  Get Full Table List of top 10 genes significantly correlated to 'AGE' by Spearman correlation test

SpearmanCorr corrP Q
ESR1 0.4214 8.331e-24 1.48e-19
CNTNAP3 -0.3013 2.261e-12 4.03e-08
KRT17 -0.2952 6.472e-12 1.15e-07
C20ORF42 -0.2947 7.018e-12 1.25e-07
MAGED4B -0.2913 1.245e-11 2.22e-07
FOXD2 0.2907 1.391e-11 2.48e-07
KLK6 -0.2892 1.784e-11 3.18e-07
SYT8 -0.2882 2.11e-11 3.76e-07
SOSTDC1 -0.2879 2.195e-11 3.91e-07
PPP1R14C -0.2873 2.438e-11 4.34e-07
Clinical variable #3: 'NEOPLASM.DISEASESTAGE'

10 genes related to 'NEOPLASM.DISEASESTAGE'.

Table S4.  Basic characteristics of clinical feature: 'NEOPLASM.DISEASESTAGE'

NEOPLASM.DISEASESTAGE Labels N
  STAGE I 46
  STAGE IA 37
  STAGE IB 6
  STAGE IIA 185
  STAGE IIB 110
  STAGE IIIA 77
  STAGE IIIB 15
  STAGE IIIC 19
  STAGE IV 14
  STAGE TIS 1
  STAGE X 16
     
  Significant markers N = 10
List of 10 genes differentially expressed by 'NEOPLASM.DISEASESTAGE'

Table S5.  Get Full Table List of 10 genes differentially expressed by 'NEOPLASM.DISEASESTAGE'

ANOVA_P Q
OR4D1 1.066e-06 0.019
RANBP2 2.435e-06 0.0434
RPL11 3.235e-06 0.0576
RWDD3 6.828e-06 0.122
GIPR 1.257e-05 0.224
CHST5 1.341e-05 0.239
LOC51252 1.413e-05 0.252
FAM131C 1.571e-05 0.28
MGC40574 1.596e-05 0.284
FRMD1 1.642e-05 0.292
Clinical variable #4: 'PATHOLOGY.T.STAGE'

53 genes related to 'PATHOLOGY.T.STAGE'.

Table S6.  Basic characteristics of clinical feature: 'PATHOLOGY.T.STAGE'

PATHOLOGY.T.STAGE Mean (SD) 1.93 (0.72)
  N
  1 133
  2 311
  3 59
  4 20
     
  Significant markers N = 53
  pos. correlated 39
  neg. correlated 14
List of top 10 genes differentially expressed by 'PATHOLOGY.T.STAGE'

Table S7.  Get Full Table List of top 10 genes significantly correlated to 'PATHOLOGY.T.STAGE' by Spearman correlation test

SpearmanCorr corrP Q
RBBP5 0.2759 1.374e-10 2.45e-06
PPP2R5D 0.2371 4.053e-08 0.000722
TMEM81 0.2324 7.583e-08 0.00135
CCNF 0.2287 1.236e-07 0.0022
TBRG4 0.226 1.748e-07 0.00311
TMEM63B 0.2251 1.974e-07 0.00352
SEPT10 -0.2198 3.856e-07 0.00687
RWDD3 -0.2176 5.027e-07 0.00895
ZBED5 -0.2165 5.779e-07 0.0103
RRM2 0.2125 9.338e-07 0.0166
Clinical variable #5: 'PATHOLOGY.N.STAGE'

39 genes related to 'PATHOLOGY.N.STAGE'.

Table S8.  Basic characteristics of clinical feature: 'PATHOLOGY.N.STAGE'

PATHOLOGY.N.STAGE Mean (SD) 0.74 (0.88)
  N
  0 255
  1 170
  2 61
  3 29
     
  Significant markers N = 39
  pos. correlated 20
  neg. correlated 19
List of top 10 genes differentially expressed by 'PATHOLOGY.N.STAGE'

Table S9.  Get Full Table List of top 10 genes significantly correlated to 'PATHOLOGY.N.STAGE' by Spearman correlation test

SpearmanCorr corrP Q
RWDD3 -0.2537 5.268e-09 9.38e-05
RPL5 -0.2316 1.062e-07 0.00189
HIST1H2AG 0.2272 1.866e-07 0.00332
PBX1 0.2181 5.796e-07 0.0103
LRP6 -0.2169 6.674e-07 0.0119
SRD5A2L 0.2124 1.149e-06 0.0205
C11ORF80 0.2118 1.239e-06 0.0221
RBBP8 -0.2094 1.638e-06 0.0292
CALM1 0.2088 1.749e-06 0.0311
ZMYM4 -0.2079 1.949e-06 0.0347
Clinical variable #6: 'PATHOLOGY.M.STAGE'

No gene related to 'PATHOLOGY.M.STAGE'.

Table S10.  Basic characteristics of clinical feature: 'PATHOLOGY.M.STAGE'

PATHOLOGY.M.STAGE Labels N
  CM0 (I+) 2
  M0 495
  M1 15
  MX 14
     
  Significant markers N = 0
Clinical variable #7: 'GENDER'

No gene related to 'GENDER'.

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

GENDER Labels N
  FEMALE 520
  MALE 6
     
  Significant markers N = 0
Clinical variable #8: 'HISTOLOGICAL.TYPE'

341 genes related to 'HISTOLOGICAL.TYPE'.

Table S12.  Basic characteristics of clinical feature: 'HISTOLOGICAL.TYPE'

HISTOLOGICAL.TYPE Labels N
  INFILTRATING DUCTAL CARCINOMA 448
  INFILTRATING LOBULAR CARCINOMA 41
  MEDULLARY CARCINOMA 1
  MIXED HISTOLOGY (PLEASE SPECIFY) 12
  MUCINOUS CARCINOMA 2
  OTHER SPECIFY 21
     
  Significant markers N = 341
List of top 10 genes differentially expressed by 'HISTOLOGICAL.TYPE'

Table S13.  Get Full Table List of top 10 genes differentially expressed by 'HISTOLOGICAL.TYPE'

ANOVA_P Q
CDH1 3.005e-17 5.35e-13
GLTSCR2 3.981e-10 7.09e-06
ADRM1 4.47e-10 7.96e-06
PPIL1 9.746e-10 1.74e-05
ALG3 3.424e-09 6.1e-05
MGC7036 8.706e-09 0.000155
C6ORF129 8.992e-09 0.00016
C10ORF56 1.014e-08 0.000181
CIRBP 1.046e-08 0.000186
HSPC171 1.129e-08 0.000201
Clinical variable #9: 'RADIATIONS.RADIATION.REGIMENINDICATION'

3 genes related to 'RADIATIONS.RADIATION.REGIMENINDICATION'.

Table S14.  Basic characteristics of clinical feature: 'RADIATIONS.RADIATION.REGIMENINDICATION'

RADIATIONS.RADIATION.REGIMENINDICATION Labels N
  NO 168
  YES 358
     
  Significant markers N = 3
  Higher in YES 3
  Higher in NO 0
List of 3 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

Table S15.  Get Full Table List of 3 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

W(pos if higher in 'YES') wilcoxontestP Q AUC
SETD7 37238 1.039e-05 0.185 0.6191
FBXL10 22908.5 1.046e-05 0.186 0.6191
LOC285398 37086 1.593e-05 0.284 0.6166
Clinical variable #10: 'NUMBER.OF.LYMPH.NODES'

8 genes related to 'NUMBER.OF.LYMPH.NODES'.

Table S16.  Basic characteristics of clinical feature: 'NUMBER.OF.LYMPH.NODES'

NUMBER.OF.LYMPH.NODES Mean (SD) 1.82 (3.5)
  Significant markers N = 8
  pos. correlated 4
  neg. correlated 4
List of 8 genes differentially expressed by 'NUMBER.OF.LYMPH.NODES'

Table S17.  Get Full Table List of 8 genes significantly correlated to 'NUMBER.OF.LYMPH.NODES' by Spearman correlation test

SpearmanCorr corrP Q
CSDE1 -0.2357 1.48e-06 0.0264
RWDD3 -0.2285 3.122e-06 0.0556
BCAR1 0.2248 4.548e-06 0.081
DDX20 -0.2229 5.451e-06 0.0971
STS 0.218 8.857e-06 0.158
SH3GL1 0.2135 1.368e-05 0.244
HIST1H2AG 0.2127 1.471e-05 0.262
ACY1L2 -0.2118 1.601e-05 0.285
Clinical variable #11: 'RACE'

50 genes related to 'RACE'.

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

RACE Labels N
  AMERICAN INDIAN OR ALASKA NATIVE 1
  ASIAN 34
  BLACK OR AFRICAN AMERICAN 40
  WHITE 361
     
  Significant markers N = 50
List of top 10 genes differentially expressed by 'RACE'

Table S19.  Get Full Table List of top 10 genes differentially expressed by 'RACE'

ANOVA_P Q
PSPH 2.725e-16 4.85e-12
CRYBB2 1.187e-13 2.11e-09
IL27 8.988e-11 1.6e-06
PRSS36 1.012e-10 1.8e-06
RAI16 1.656e-10 2.95e-06
DPF2 1.832e-09 3.26e-05
UTS2 2.16e-09 3.85e-05
CRCT1 1.266e-08 0.000225
MAB21L2 1.302e-08 0.000232
TNMD 2.08e-08 0.00037
Clinical variable #12: 'ETHNICITY'

No gene related to 'ETHNICITY'.

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

ETHNICITY Labels N
  HISPANIC OR LATINO 7
  NOT HISPANIC OR LATINO 372
     
  Significant markers N = 0
Methods & Data
Input

  • Expresson data file = BRCA-TP.medianexp.txt

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

  • Number of patients = 526

  • Number of genes = 17814

  • Number of clinical features = 12

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

ANOVA analysis

For multi-class clinical features (ordinal or nominal), one-way analysis of variance (Howell 2002) was applied to compare the log2-expression levels between different clinical classes using 'anova' function in R

Student's t-test analysis

For two-class clinical features, two-tailed Student's t test with unequal variance (Lehmann and Romano 2005) was applied to compare the log2-expression levels between the two clinical classes using 't.test' function in R

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] Howell, D, Statistical Methods for Psychology. (5th ed.), Duxbury Press:324-5 (2002)
[4] Lehmann and Romano, Testing Statistical Hypotheses (3E ed.), New York: Springer. ISBN 0387988645 (2005)
[5] 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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