Correlation between mRNA expression and clinical features
Breast Invasive Carcinoma (Primary solid tumor)
16 April 2014  |  analyses__2014_04_16
Maintainer Information
Citation Information
doi:10.7908/C1GQ6WB5
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/C1GQ6WB5
Overview
Introduction

This pipeline uses various statistical tests to identify mRNAs whose expression levels correlated to selected clinical features.

Summary

Testing the association between 17814 genes and 10 clinical features across 526 samples, statistically thresholded by Q value < 0.05, 8 clinical features related to at least one genes.

  • 390 genes correlated to 'AGE'.

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

  • 23 genes correlated to 'NEOPLASM.DISEASESTAGE'.

    • NGFB ,  OR1M1 ,  PRKACG ,  OR6K3 ,  C20ORF71 ,  ...

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

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

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

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

  • 1 gene correlated to 'PATHOLOGY.M.STAGE'.

    • GBF1

  • 5 genes correlated to 'GENDER'.

    • TMEM16C ,  CACNG1 ,  MAPK4 ,  GSTA2 ,  P11

  • 173 genes correlated to 'HISTOLOGICAL.TYPE'.

    • CDH1 ,  NRAP ,  MGC32805 ,  MAGEC3 ,  OR8D4 ,  ...

  • 1 gene correlated to 'NUMBER.OF.LYMPH.NODES'.

    • CSDE1

  • No genes correlated to 'Time to Death', and 'RADIATIONS.RADIATION.REGIMENINDICATION'.

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 Q value < 0.05.

Clinical feature Statistical test Significant genes Associated with                 Associated with
Time to Death Cox regression test   N=0        
AGE Spearman correlation test N=390 older N=132 younger N=258
NEOPLASM DISEASESTAGE ANOVA test N=23        
PATHOLOGY T STAGE Spearman correlation test N=17 higher stage N=14 lower stage N=3
PATHOLOGY N STAGE Spearman correlation test N=12 higher stage N=5 lower stage N=7
PATHOLOGY M STAGE ANOVA test N=1        
GENDER t test N=5 male N=1 female N=4
HISTOLOGICAL TYPE ANOVA test N=173        
RADIATIONS RADIATION REGIMENINDICATION t test   N=0        
NUMBER OF LYMPH NODES Spearman correlation test N=1 higher number.of.lymph.nodes N=0 lower number.of.lymph.nodes N=1
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=27.2)
  censored N = 439
  death N = 72
     
  Significant markers N = 0
Clinical variable #2: 'AGE'

390 genes related to 'AGE'.

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

AGE Mean (SD) 58.08 (13)
  Significant markers N = 390
  pos. correlated 132
  neg. correlated 258
List of top 10 genes significantly correlated to 'AGE' by Spearman correlation test

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

Figure S1.  Get High-res Image As an example, this figure shows the association of ESR1 to 'AGE'. P value = 8.33e-24 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #3: 'NEOPLASM.DISEASESTAGE'

23 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 = 23
List of top 10 genes differentially expressed by 'NEOPLASM.DISEASESTAGE'

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

ANOVA_P Q
NGFB 6.944e-23 1.24e-18
OR1M1 5.74e-21 1.02e-16
PRKACG 9.067e-15 1.62e-10
OR6K3 2.261e-13 4.03e-09
C20ORF71 1.376e-12 2.45e-08
IFNA7 5.787e-12 1.03e-07
GPR52 7.664e-11 1.36e-06
TAS2R40 2.946e-10 5.25e-06
SEBOX 4.855e-10 8.65e-06
UNQ9368 1.209e-09 2.15e-05

Figure S2.  Get High-res Image As an example, this figure shows the association of NGFB to 'NEOPLASM.DISEASESTAGE'. P value = 6.94e-23 with ANOVA analysis.

Clinical variable #4: 'PATHOLOGY.T.STAGE'

17 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 = 17
  pos. correlated 14
  neg. correlated 3
List of top 10 genes significantly correlated to 'PATHOLOGY.T.STAGE' by Spearman correlation test

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

Figure S3.  Get High-res Image As an example, this figure shows the association of RBBP5 to 'PATHOLOGY.T.STAGE'. P value = 1.37e-10 with Spearman correlation analysis.

Clinical variable #5: 'PATHOLOGY.N.STAGE'

12 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 = 12
  pos. correlated 5
  neg. correlated 7
List of top 10 genes significantly correlated to 'PATHOLOGY.N.STAGE' by Spearman correlation test

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

Figure S4.  Get High-res Image As an example, this figure shows the association of RWDD3 to 'PATHOLOGY.N.STAGE'. P value = 5.27e-09 with Spearman correlation analysis.

Clinical variable #6: 'PATHOLOGY.M.STAGE'

One 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 496
  M1 14
  MX 14
     
  Significant markers N = 1
List of one gene differentially expressed by 'PATHOLOGY.M.STAGE'

Table S11.  Get Full Table List of one gene differentially expressed by 'PATHOLOGY.M.STAGE'

ANOVA_P Q
GBF1 2.538e-06 0.0452

Figure S5.  Get High-res Image As an example, this figure shows the association of GBF1 to 'PATHOLOGY.M.STAGE'. P value = 2.54e-06 with ANOVA analysis.

Clinical variable #7: 'GENDER'

5 genes related to 'GENDER'.

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

GENDER Labels N
  FEMALE 520
  MALE 6
     
  Significant markers N = 5
  Higher in MALE 1
  Higher in FEMALE 4
List of 5 genes differentially expressed by 'GENDER'

Table S13.  Get Full Table List of 5 genes differentially expressed by 'GENDER'

T(pos if higher in 'MALE') ttestP Q AUC
TMEM16C -16.03 1.122e-14 2e-10 0.9324
CACNG1 20.22 7.307e-10 1.3e-05 0.9625
MAPK4 -11.19 1.03e-09 1.83e-05 0.8146
GSTA2 -11.42 5.015e-07 0.00893 0.8657
P11 -7.66 6.366e-07 0.0113 0.6862

Figure S6.  Get High-res Image As an example, this figure shows the association of TMEM16C to 'GENDER'. P value = 1.12e-14 with T-test analysis.

Clinical variable #8: 'HISTOLOGICAL.TYPE'

173 genes related to 'HISTOLOGICAL.TYPE'.

Table S14.  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 = 173
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'

ANOVA_P Q
CDH1 1.473e-43 2.62e-39
NRAP 6.64e-13 1.18e-08
MGC32805 2.781e-12 4.95e-08
MAGEC3 5.062e-12 9.02e-08
OR8D4 2.022e-11 3.6e-07
ADAD1 1.73e-10 3.08e-06
GLTSCR2 1.991e-10 3.55e-06
PPIL1 2.571e-10 4.58e-06
C1QTNF7 5.544e-10 9.87e-06
GLRA1 2.81e-09 5e-05

Figure S7.  Get High-res Image As an example, this figure shows the association of CDH1 to 'HISTOLOGICAL.TYPE'. P value = 1.47e-43 with ANOVA analysis.

Clinical variable #9: 'RADIATIONS.RADIATION.REGIMENINDICATION'

No gene related to 'RADIATIONS.RADIATION.REGIMENINDICATION'.

Table S16.  Basic characteristics of clinical feature: 'RADIATIONS.RADIATION.REGIMENINDICATION'

RADIATIONS.RADIATION.REGIMENINDICATION Labels N
  NO 168
  YES 358
     
  Significant markers N = 0
Clinical variable #10: 'NUMBER.OF.LYMPH.NODES'

One gene related to 'NUMBER.OF.LYMPH.NODES'.

Table S17.  Basic characteristics of clinical feature: 'NUMBER.OF.LYMPH.NODES'

NUMBER.OF.LYMPH.NODES Mean (SD) 1.82 (3.5)
  Significant markers N = 1
  pos. correlated 0
  neg. correlated 1
List of one gene significantly correlated to 'NUMBER.OF.LYMPH.NODES' by Spearman correlation test

Table S18.  Get Full Table List of one gene significantly correlated to 'NUMBER.OF.LYMPH.NODES' by Spearman correlation test

SpearmanCorr corrP Q
CSDE1 -0.2357 1.48e-06 0.0264

Figure S8.  Get High-res Image As an example, this figure shows the association of CSDE1 to 'NUMBER.OF.LYMPH.NODES'. P value = 1.48e-06 with Spearman correlation analysis. The straight line presents the best linear regression.

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 = 10

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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