Correlation between mRNAseq expression and clinical features
Breast Invasive Carcinoma (Primary solid tumor)
23 September 2013  |  analyses__2013_09_23
Maintainer Information
Citation Information
doi:10.7908/C1JM27X0
Maintained by Juok Cho (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2013): Correlation between mRNAseq expression and clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C1JM27X0
Overview
Introduction

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

Summary

Testing the association between 18282 genes and 10 clinical features across 953 samples, statistically thresholded by Q value < 0.05, 10 clinical features related to at least one genes.

  • 4 genes correlated to 'Time to Death'.

    • NFKBIA|4792 ,  PGK1|5230 ,  DIP2B|57609 ,  PARP3|10039

  • 958 genes correlated to 'AGE'.

    • ESR1|2099 ,  TMEFF1|8577 ,  DSC2|1824 ,  LRFN5|145581 ,  TFPI2|7980 ,  ...

  • 42 genes correlated to 'NEOPLASM.DISEASESTAGE'.

    • ABCA10|10349 ,  MMRN1|22915 ,  SDPR|8436 ,  GRRP1|79927 ,  LHFP|10186 ,  ...

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

    • NDNL2|56160 ,  ZMYM6|9204 ,  ERMN|57471 ,  C14ORF139|79686 ,  SELE|6401 ,  ...

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

    • HMSD|284293 ,  DAAM1|23002 ,  NR2F2|7026 ,  SNED1|25992 ,  RGS4|5999 ,  ...

  • 113 genes correlated to 'PATHOLOGY.M.STAGE'.

    • PPIAL4G|644591 ,  CCDC130|81576 ,  NACA2|342538 ,  HOOK2|29911 ,  EXD3|54932 ,  ...

  • 19 genes correlated to 'GENDER'.

    • NLGN4Y|22829 ,  ZFY|7544 ,  PRKY|5616 ,  SYT9|143425 ,  GSTA1|2938 ,  ...

  • 5610 genes correlated to 'HISTOLOGICAL.TYPE'.

    • CDH1|999 ,  RAPGEF3|10411 ,  USHBP1|83878 ,  AVPR2|554 ,  PSMD14|10213 ,  ...

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

    • PCDH17|27253 ,  SELO|83642

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

    • HMSD|284293 ,  SNED1|25992 ,  POU4F1|5457 ,  NUDT4|11163

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=4 shorter survival N=2 longer survival N=2
AGE Spearman correlation test N=958 older N=258 younger N=700
NEOPLASM DISEASESTAGE ANOVA test N=42        
PATHOLOGY T STAGE Spearman correlation test N=27 higher stage N=4 lower stage N=23
PATHOLOGY N STAGE Spearman correlation test N=11 higher stage N=10 lower stage N=1
PATHOLOGY M STAGE ANOVA test N=113        
GENDER t test N=19 male N=8 female N=11
HISTOLOGICAL TYPE ANOVA test N=5610        
RADIATIONS RADIATION REGIMENINDICATION t test N=2 yes N=1 no N=1
NUMBER OF LYMPH NODES Spearman correlation test N=4 higher number.of.lymph.nodes N=2 lower number.of.lymph.nodes N=2
Clinical variable #1: 'Time to Death'

4 genes related to 'Time to Death'.

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

Time to Death Duration (Months) 0-234.2 (median=21.6)
  censored N = 788
  death N = 111
     
  Significant markers N = 4
  associated with shorter survival 2
  associated with longer survival 2
List of 4 genes significantly associated with 'Time to Death' by Cox regression test

Table S2.  Get Full Table List of 4 genes significantly associated with 'Time to Death' by Cox regression test

HazardRatio Wald_P Q C_index
NFKBIA|4792 0.42 1.919e-07 0.0035 0.359
PGK1|5230 1.97 6.694e-07 0.012 0.675
DIP2B|57609 2.4 1.175e-06 0.021 0.595
PARP3|10039 0.6 2.465e-06 0.045 0.355

Figure S1.  Get High-res Image As an example, this figure shows the association of NFKBIA|4792 to 'Time to Death'. four curves present the cumulative survival rates of 4 quartile subsets of patients. P value = 1.92e-07 with univariate Cox regression analysis using continuous log-2 expression values.

Clinical variable #2: 'AGE'

958 genes related to 'AGE'.

Table S3.  Basic characteristics of clinical feature: 'AGE'

AGE Mean (SD) 58.42 (13)
  Significant markers N = 958
  pos. correlated 258
  neg. correlated 700
List of top 10 genes significantly correlated to 'AGE' by Spearman correlation test

Table S4.  Get Full Table List of top 10 genes significantly correlated to 'AGE' by Spearman correlation test

SpearmanCorr corrP Q
ESR1|2099 0.3537 2.249e-29 4.11e-25
TMEFF1|8577 -0.2642 1.218e-16 2.23e-12
DSC2|1824 -0.2567 9.213e-16 1.68e-11
LRFN5|145581 -0.2594 1.004e-15 1.84e-11
TFPI2|7980 -0.2547 2.096e-15 3.83e-11
DZIP1|22873 -0.2532 2.325e-15 4.25e-11
LAMA1|284217 -0.2414 4.759e-14 8.7e-10
DIO2|1734 -0.2411 4.988e-14 9.12e-10
ZNF521|25925 -0.2404 5.874e-14 1.07e-09
FMO1|2326 -0.2401 6.741e-14 1.23e-09

Figure S2.  Get High-res Image As an example, this figure shows the association of ESR1|2099 to 'AGE'. P value = 2.25e-29 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #3: 'NEOPLASM.DISEASESTAGE'

42 genes related to 'NEOPLASM.DISEASESTAGE'.

Table S5.  Basic characteristics of clinical feature: 'NEOPLASM.DISEASESTAGE'

NEOPLASM.DISEASESTAGE Labels N
  STAGE I 77
  STAGE IA 72
  STAGE IB 11
  STAGE II 9
  STAGE IIA 324
  STAGE IIB 217
  STAGE III 2
  STAGE IIIA 130
  STAGE IIIB 25
  STAGE IIIC 52
  STAGE IV 15
  STAGE TIS 1
  STAGE X 17
     
  Significant markers N = 42
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'

ANOVA_P Q
ABCA10|10349 6.45e-09 0.000118
MMRN1|22915 9.189e-09 0.000168
SDPR|8436 1.485e-08 0.000271
GRRP1|79927 2.23e-08 0.000408
LHFP|10186 3.917e-08 0.000716
ABCA9|10350 5.658e-08 0.00103
SPARCL1|8404 5.694e-08 0.00104
PGGT1B|5229 6.837e-08 0.00125
C7|730 1.543e-07 0.00282
ADCY4|196883 2.343e-07 0.00428

Figure S3.  Get High-res Image As an example, this figure shows the association of ABCA10|10349 to 'NEOPLASM.DISEASESTAGE'. P value = 6.45e-09 with ANOVA analysis.

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

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

Table S7.  Basic characteristics of clinical feature: 'PATHOLOGY.T.STAGE'

PATHOLOGY.T.STAGE Mean (SD) 1.93 (0.72)
  N
  1 251
  2 552
  3 113
  4 34
     
  Significant markers N = 27
  pos. correlated 4
  neg. correlated 23
List of top 10 genes significantly correlated to 'PATHOLOGY.T.STAGE' by Spearman correlation test

Table S8.  Get Full Table List of top 10 genes significantly correlated to 'PATHOLOGY.T.STAGE' by Spearman correlation test

SpearmanCorr corrP Q
NDNL2|56160 -0.1768 4.147e-08 0.000758
ZMYM6|9204 -0.1755 5.156e-08 0.000943
ERMN|57471 -0.1717 1.052e-07 0.00192
C14ORF139|79686 -0.1653 2.991e-07 0.00547
SELE|6401 -0.1646 3.412e-07 0.00624
TLR10|81793 -0.1639 3.882e-07 0.00709
CNN3|1266 -0.1633 4.164e-07 0.00761
ZNF167|55888 -0.1613 5.892e-07 0.0108
KIAA1217|56243 -0.1609 6.234e-07 0.0114
CCND2|894 -0.1605 6.614e-07 0.0121

Figure S4.  Get High-res Image As an example, this figure shows the association of NDNL2|56160 to 'PATHOLOGY.T.STAGE'. P value = 4.15e-08 with Spearman correlation analysis.

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

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

Table S9.  Basic characteristics of clinical feature: 'PATHOLOGY.N.STAGE'

PATHOLOGY.N.STAGE Mean (SD) 0.77 (0.9)
  N
  0 450
  1 319
  2 106
  3 63
     
  Significant markers N = 11
  pos. correlated 10
  neg. correlated 1
List of top 10 genes significantly correlated to 'PATHOLOGY.N.STAGE' by Spearman correlation test

Table S10.  Get Full Table List of top 10 genes significantly correlated to 'PATHOLOGY.N.STAGE' by Spearman correlation test

SpearmanCorr corrP Q
HMSD|284293 -0.2446 7.513e-09 0.000137
DAAM1|23002 0.1665 2.946e-07 0.00539
NR2F2|7026 0.1661 3.139e-07 0.00574
SNED1|25992 0.1637 4.618e-07 0.00844
RGS4|5999 0.1628 5.399e-07 0.00987
F2R|2149 0.1624 5.714e-07 0.0104
NUDT4|11163 0.1612 6.907e-07 0.0126
SVEP1|79987 0.1606 7.762e-07 0.0142
HTR2B|3357 0.1599 8.57e-07 0.0157
BAHD1|22893 0.1541 2.129e-06 0.0389

Figure S5.  Get High-res Image As an example, this figure shows the association of HMSD|284293 to 'PATHOLOGY.N.STAGE'. P value = 7.51e-09 with Spearman correlation analysis.

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

113 genes related to 'PATHOLOGY.M.STAGE'.

Table S11.  Basic characteristics of clinical feature: 'PATHOLOGY.M.STAGE'

PATHOLOGY.M.STAGE Labels N
  CM0 (I+) 2
  M0 828
  M1 15
  MX 108
     
  Significant markers N = 113
List of top 10 genes differentially expressed by 'PATHOLOGY.M.STAGE'

Table S12.  Get Full Table List of top 10 genes differentially expressed by 'PATHOLOGY.M.STAGE'

ANOVA_P Q
PPIAL4G|644591 4.859e-12 8.88e-08
CCDC130|81576 1.217e-11 2.23e-07
NACA2|342538 9.321e-11 1.7e-06
HOOK2|29911 1.071e-10 1.96e-06
EXD3|54932 4.874e-10 8.91e-06
MAP2K7|5609 8.595e-10 1.57e-05
VENTX|27287 9.357e-10 1.71e-05
NEURL2|140825 1.226e-09 2.24e-05
ID2B|84099 1.894e-09 3.46e-05
AKAP8|10270 9.463e-09 0.000173

Figure S6.  Get High-res Image As an example, this figure shows the association of PPIAL4G|644591 to 'PATHOLOGY.M.STAGE'. P value = 4.86e-12 with ANOVA analysis.

Clinical variable #7: 'GENDER'

19 genes related to 'GENDER'.

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

GENDER Labels N
  FEMALE 943
  MALE 10
     
  Significant markers N = 19
  Higher in MALE 8
  Higher in FEMALE 11
List of top 10 genes differentially expressed by 'GENDER'

Table S14.  Get Full Table List of top 10 genes differentially expressed by 'GENDER'

T(pos if higher in 'MALE') ttestP Q AUC
NLGN4Y|22829 40.73 3.978e-13 7.16e-09 1
ZFY|7544 36.08 1.318e-11 2.37e-07 1
PRKY|5616 30.19 3.251e-11 5.85e-07 1
SYT9|143425 13.68 2.925e-10 5.27e-06 0.7979
GSTA1|2938 -16.78 1.851e-08 0.000333 0.8942
MYH16|84176 -12.43 1.112e-07 0.002 0.8488
RND2|8153 11.12 1.119e-07 0.00202 0.8371
SUMF2|25870 -8.63 1.561e-07 0.00281 0.7338
RIMS4|140730 11.55 1.641e-07 0.00295 0.8772
HTR4|3360 -12.63 2.078e-07 0.00374 0.8039

Figure S7.  Get High-res Image As an example, this figure shows the association of NLGN4Y|22829 to 'GENDER'. P value = 3.98e-13 with T-test analysis.

Clinical variable #8: 'HISTOLOGICAL.TYPE'

5610 genes related to 'HISTOLOGICAL.TYPE'.

Table S15.  Basic characteristics of clinical feature: 'HISTOLOGICAL.TYPE'

HISTOLOGICAL.TYPE Labels N
  INFILTRATING CARCINOMA NOS 1
  INFILTRATING DUCTAL CARCINOMA 711
  INFILTRATING LOBULAR CARCINOMA 152
  MEDULLARY CARCINOMA 5
  MIXED HISTOLOGY (PLEASE SPECIFY) 27
  MUCINOUS CARCINOMA 14
  OTHER SPECIFY 42
     
  Significant markers N = 5610
List of top 10 genes differentially expressed by 'HISTOLOGICAL.TYPE'

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

ANOVA_P Q
CDH1|999 2.645e-95 4.84e-91
RAPGEF3|10411 1.135e-43 2.07e-39
USHBP1|83878 3.691e-41 6.75e-37
AVPR2|554 9.55e-39 1.75e-34
PSMD14|10213 2.076e-37 3.8e-33
KANK3|256949 5.224e-37 9.55e-33
MUSTN1|389125 9.243e-37 1.69e-32
MUC2|4583 1.022e-36 1.87e-32
BTG2|7832 1.796e-36 3.28e-32
GPIHBP1|338328 2.139e-36 3.91e-32

Figure S8.  Get High-res Image As an example, this figure shows the association of CDH1|999 to 'HISTOLOGICAL.TYPE'. P value = 2.64e-95 with ANOVA analysis.

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

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

Table S17.  Basic characteristics of clinical feature: 'RADIATIONS.RADIATION.REGIMENINDICATION'

RADIATIONS.RADIATION.REGIMENINDICATION Labels N
  NO 231
  YES 722
     
  Significant markers N = 2
  Higher in YES 1
  Higher in NO 1
List of 2 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

Table S18.  Get Full Table List of 2 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

T(pos if higher in 'YES') ttestP Q AUC
PCDH17|27253 -4.99 8.475e-07 0.0155 0.5922
SELO|83642 4.9 1.306e-06 0.0239 0.5949

Figure S9.  Get High-res Image As an example, this figure shows the association of PCDH17|27253 to 'RADIATIONS.RADIATION.REGIMENINDICATION'. P value = 8.47e-07 with T-test analysis.

Clinical variable #10: 'NUMBER.OF.LYMPH.NODES'

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

Table S19.  Basic characteristics of clinical feature: 'NUMBER.OF.LYMPH.NODES'

NUMBER.OF.LYMPH.NODES Mean (SD) 2.32 (4.6)
  Significant markers N = 4
  pos. correlated 2
  neg. correlated 2
List of 4 genes significantly correlated to 'NUMBER.OF.LYMPH.NODES' by Spearman correlation test

Table S20.  Get Full Table List of 4 genes significantly correlated to 'NUMBER.OF.LYMPH.NODES' by Spearman correlation test

SpearmanCorr corrP Q
HMSD|284293 -0.267 3.955e-09 7.23e-05
SNED1|25992 0.1798 3.11e-07 0.00568
POU4F1|5457 -0.2276 1.297e-06 0.0237
NUDT4|11163 0.1691 1.536e-06 0.0281

Figure S10.  Get High-res Image As an example, this figure shows the association of HMSD|284293 to 'NUMBER.OF.LYMPH.NODES'. P value = 3.96e-09 with Spearman correlation analysis. The straight line presents the best linear regression.

Methods & Data
Input

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

  • Clinical data file = BRCA-TP.clin.merged.picked.txt

  • Number of patients = 953

  • Number of genes = 18282

  • 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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