Correlation between mRNAseq expression and clinical features
Breast Invasive Carcinoma (Primary solid tumor)
21 April 2013  |  analyses__2013_04_21
Maintainer Information
Citation Information
doi:10.7908/C1V985ZK
Maintained by Juok Cho (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2013): Breast Invasive Carcinoma (Primary solid tumor cohort) - 21 April 2013: Correlation between mRNAseq expression and clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C1V985ZK
Overview
Introduction

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

Summary

Testing the association between 18256 genes and 8 clinical features across 837 samples, statistically thresholded by Q value < 0.05, 5 clinical features related to at least one genes.

  • 4 genes correlated to 'Time to Death'.

    • DIP2B|57609 ,  PGK1|5230 ,  CAND1|55832 ,  IRF2|3660

  • 677 genes correlated to 'AGE'.

    • ESR1|2099 ,  LRFN5|145581 ,  TFPI2|7980 ,  TMEFF1|8577 ,  SOBP|55084 ,  ...

  • 18 genes correlated to 'GENDER'.

    • NLGN4Y|22829 ,  ZFY|7544 ,  PRKY|5616 ,  C7ORF10|79783 ,  SYT9|143425 ,  ...

  • 8 genes correlated to 'LYMPH.NODE.METASTASIS'.

    • BTBD10|84280 ,  POLR2B|5431 ,  SPPL3|121665 ,  C19ORF21|126353 ,  SRP72|6731 ,  ...

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

    • HMSD|284293 ,  FITM2|128486

  • No genes correlated to 'RADIATIONS.RADIATION.REGIMENINDICATION', 'DISTANT.METASTASIS', and 'NEOPLASM.DISEASESTAGE'.

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=3 longer survival N=1
AGE Spearman correlation test N=677 older N=160 younger N=517
GENDER t test N=18 male N=8 female N=10
RADIATIONS RADIATION REGIMENINDICATION t test   N=0        
DISTANT METASTASIS ANOVA test   N=0        
LYMPH NODE METASTASIS ANOVA test N=8        
NUMBER OF LYMPH NODES Spearman correlation test N=2 higher number.of.lymph.nodes N=1 lower number.of.lymph.nodes N=1
NEOPLASM DISEASESTAGE ANOVA test   N=0        
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) 0-223.4 (median=18.6)
  censored N = 686
  death N = 94
     
  Significant markers N = 4
  associated with shorter survival 3
  associated with longer survival 1
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
DIP2B|57609 2.9 1.586e-07 0.0029 0.635
PGK1|5230 2 1.65e-06 0.03 0.686
CAND1|55832 2.1 1.653e-06 0.03 0.629
IRF2|3660 0.28 1.982e-06 0.036 0.329

Figure S1.  Get High-res Image As an example, this figure shows the association of DIP2B|57609 to 'Time to Death'. four curves present the cumulative survival rates of 4 quartile subsets of patients. P value = 1.59e-07 with univariate Cox regression analysis using continuous log-2 expression values.

Clinical variable #2: 'AGE'

677 genes related to 'AGE'.

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

AGE Mean (SD) 58.2 (13)
  Significant markers N = 677
  pos. correlated 160
  neg. correlated 517
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 0.3531 6.013e-26 1.1e-21
LRFN5|145581 -0.2685 5.841e-15 1.07e-10
TFPI2|7980 -0.2659 6.947e-15 1.27e-10
TMEFF1|8577 -0.2543 8.372e-14 1.53e-09
SOBP|55084 -0.252 1.415e-13 2.58e-09
DBX2|440097 -0.2691 2.696e-13 4.92e-09
DZIP1|22873 -0.2449 6.958e-13 1.27e-08
PCDH18|54510 -0.2448 7.198e-13 1.31e-08
RELN|5649 -0.2466 8.742e-13 1.6e-08
FXYD6|53826 -0.2408 1.723e-12 3.14e-08

Figure S2.  Get High-res Image As an example, this figure shows the association of ESR1|2099 to 'AGE'. P value = 6.01e-26 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #3: 'GENDER'

18 genes related to 'GENDER'.

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

GENDER Labels N
  FEMALE 828
  MALE 9
     
  Significant markers N = 18
  Higher in MALE 8
  Higher in FEMALE 10
List of top 10 genes differentially expressed by 'GENDER'

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

T(pos if higher in 'MALE') ttestP Q AUC
NLGN4Y|22829 41.21 2.344e-12 4.21e-08 1
ZFY|7544 41.98 1.809e-11 3.25e-07 1
PRKY|5616 27.63 6.148e-10 1.1e-05 1
C7ORF10|79783 8.69 3.317e-09 5.96e-05 0.6638
SYT9|143425 12.45 6.607e-09 0.000119 0.794
GSTA1|2938 -16 9.561e-09 0.000172 0.8833
MMP11|4320 11.07 1.628e-08 0.000292 0.7465
RND2|8153 12.29 2.69e-08 0.000483 0.8335
SNORA74B|677841 -11.94 9.946e-08 0.00179 0.8348
HTR4|3360 -12.07 1.118e-07 0.00201 0.7909

Figure S3.  Get High-res Image As an example, this figure shows the association of NLGN4Y|22829 to 'GENDER'. P value = 2.34e-12 with T-test analysis.

Clinical variable #4: 'RADIATIONS.RADIATION.REGIMENINDICATION'

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

Table S7.  Basic characteristics of clinical feature: 'RADIATIONS.RADIATION.REGIMENINDICATION'

RADIATIONS.RADIATION.REGIMENINDICATION Labels N
  NO 209
  YES 628
     
  Significant markers N = 0
Clinical variable #5: 'DISTANT.METASTASIS'

No gene related to 'DISTANT.METASTASIS'.

Table S8.  Basic characteristics of clinical feature: 'DISTANT.METASTASIS'

DISTANT.METASTASIS Labels N
  CM0 (I+) 2
  M0 621
  M1 9
  MX 67
     
  Significant markers N = 0
Clinical variable #6: 'LYMPH.NODE.METASTASIS'

8 genes related to 'LYMPH.NODE.METASTASIS'.

Table S9.  Basic characteristics of clinical feature: 'LYMPH.NODE.METASTASIS'

LYMPH.NODE.METASTASIS Labels N
  N0 220
  N0 (I+) 13
  N0 (I-) 87
  N0 (MOL+) 1
  N1 84
  N1A 109
  N1B 26
  N1C 2
  N1MI 20
  N2 42
  N2A 45
  N3 12
  N3A 27
  N3B 1
  NX 10
     
  Significant markers N = 8
List of 8 genes differentially expressed by 'LYMPH.NODE.METASTASIS'

Table S10.  Get Full Table List of 8 genes differentially expressed by 'LYMPH.NODE.METASTASIS'

ANOVA_P Q
BTBD10|84280 8.892e-14 1.62e-09
POLR2B|5431 4.148e-09 7.57e-05
SPPL3|121665 2.033e-07 0.00371
C19ORF21|126353 5.823e-07 0.0106
SRP72|6731 6.716e-07 0.0123
ZNF837|116412 7.758e-07 0.0142
FAM128B|80097 1.419e-06 0.0259
PXT1|222659 2.166e-06 0.0395

Figure S4.  Get High-res Image As an example, this figure shows the association of BTBD10|84280 to 'LYMPH.NODE.METASTASIS'. P value = 8.89e-14 with ANOVA analysis.

Clinical variable #7: 'NUMBER.OF.LYMPH.NODES'

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

Table S11.  Basic characteristics of clinical feature: 'NUMBER.OF.LYMPH.NODES'

NUMBER.OF.LYMPH.NODES Mean (SD) 2.16 (4.3)
  Significant markers N = 2
  pos. correlated 1
  neg. correlated 1
List of 2 genes significantly correlated to 'NUMBER.OF.LYMPH.NODES' by Spearman correlation test

Table S12.  Get Full Table List of 2 genes significantly correlated to 'NUMBER.OF.LYMPH.NODES' by Spearman correlation test

SpearmanCorr corrP Q
HMSD|284293 -0.2591 9.257e-08 0.00169
FITM2|128486 0.1796 1.867e-06 0.0341

Figure S5.  Get High-res Image As an example, this figure shows the association of HMSD|284293 to 'NUMBER.OF.LYMPH.NODES'. P value = 9.26e-08 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #8: 'NEOPLASM.DISEASESTAGE'

No gene related to 'NEOPLASM.DISEASESTAGE'.

Table S13.  Basic characteristics of clinical feature: 'NEOPLASM.DISEASESTAGE'

NEOPLASM.DISEASESTAGE Labels N
  STAGE I 68
  STAGE IA 44
  STAGE IB 3
  STAGE II 8
  STAGE IIA 240
  STAGE IIB 160
  STAGE III 2
  STAGE IIIA 100
  STAGE IIIB 20
  STAGE IIIC 32
  STAGE IV 9
  STAGE X 12
     
  Significant markers N = 0
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 = 837

  • Number of genes = 18256

  • Number of clinical features = 8

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

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

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

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

This is an experimental feature. The full results of the analysis summarized in this report can be downloaded from the TCGA Data Coordination Center.

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