Correlation between mRNAseq expression and clinical features
Overview
Introduction

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

Summary

Testing the association between 18284 genes and 10 clinical features across 969 samples, statistically thresholded by Q value < 0.05, 9 clinical features related to at least one genes.

  • 1056 genes correlated to 'AGE'.

    • ESR1|2099 ,  TMEFF1|8577 ,  DSC2|1824 ,  LRFN5|145581 ,  DZIP1|22873 ,  ...

  • 64 genes correlated to 'NEOPLASM.DISEASESTAGE'.

    • ABCA10|10349 ,  SDPR|8436 ,  LHFP|10186 ,  MMRN1|22915 ,  ABCA9|10350 ,  ...

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

    • ZMYM6|9204 ,  ERMN|57471 ,  NDNL2|56160 ,  TLR10|81793 ,  CNN3|1266 ,  ...

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

    • HMSD|284293 ,  NR2F2|7026 ,  F2R|2149 ,  HTR2B|3357 ,  SNED1|25992 ,  ...

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

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

  • 19 genes correlated to 'GENDER'.

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

  • 5541 genes correlated to 'HISTOLOGICAL.TYPE'.

    • CDH1|999 ,  RAPGEF3|10411 ,  USHBP1|83878 ,  AVPR2|554 ,  BTG2|7832 ,  ...

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

    • SELO|83642 ,  KIF20B|9585 ,  FAM100A|124402 ,  NACA2|342538 ,  RING1|6015 ,  ...

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

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

  • No genes correlated to 'Time to Death'

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=1056 older N=271 younger N=785
NEOPLASM DISEASESTAGE ANOVA test N=64        
PATHOLOGY T STAGE Spearman correlation test N=35 higher stage N=5 lower stage N=30
PATHOLOGY N STAGE Spearman correlation test N=13 higher stage N=11 lower stage N=2
PATHOLOGY M STAGE ANOVA test N=392        
GENDER t test N=19 male N=8 female N=11
HISTOLOGICAL TYPE ANOVA test N=5541        
RADIATIONS RADIATION REGIMENINDICATION t test N=241 yes N=105 no N=136
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'

No gene related to 'Time to Death'.

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

Time to Death Duration (Months) 0-234.2 (median=21.8)
  censored N = 819
  death N = 113
     
  Significant markers N = 0
Clinical variable #2: 'AGE'

1056 genes related to 'AGE'.

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

AGE Mean (SD) 58.53 (13)
  Significant markers N = 1056
  pos. correlated 271
  neg. correlated 785
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|2099 0.3543 6.093e-30 1.11e-25
TMEFF1|8577 -0.2673 2.874e-17 5.25e-13
DSC2|1824 -0.2622 1.192e-16 2.18e-12
LRFN5|145581 -0.263 2.224e-16 4.07e-12
DZIP1|22873 -0.2594 2.593e-16 4.74e-12
TFPI2|7980 -0.2562 8.332e-16 1.52e-11
ZNF521|25925 -0.2491 3.91e-15 7.15e-11
PCDH18|54510 -0.2439 1.486e-14 2.72e-10
IGSF10|285313 -0.2427 2.219e-14 4.06e-10
FMO1|2326 -0.241 3.341e-14 6.11e-10

Figure S1.  Get High-res Image As an example, this figure shows the association of ESR1|2099 to 'AGE'. P value = 6.09e-30 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #3: 'NEOPLASM.DISEASESTAGE'

64 genes related to 'NEOPLASM.DISEASESTAGE'.

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

NEOPLASM.DISEASESTAGE Labels N
  STAGE I 78
  STAGE IA 75
  STAGE IB 10
  STAGE II 9
  STAGE IIA 326
  STAGE IIB 221
  STAGE III 2
  STAGE IIIA 134
  STAGE IIIB 27
  STAGE IIIC 53
  STAGE IV 15
  STAGE TIS 1
  STAGE X 17
     
  Significant markers N = 64
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
ABCA10|10349 3.56e-09 6.51e-05
SDPR|8436 4.071e-09 7.44e-05
LHFP|10186 4.323e-09 7.9e-05
MMRN1|22915 6.235e-09 0.000114
ABCA9|10350 1.219e-08 0.000223
SPARCL1|8404 1.483e-08 0.000271
GRRP1|79927 3.216e-08 0.000588
C7|730 7.389e-08 0.00135
ADCY4|196883 7.592e-08 0.00139
USHBP1|83878 7.718e-08 0.00141

Figure S2.  Get High-res Image As an example, this figure shows the association of ABCA10|10349 to 'NEOPLASM.DISEASESTAGE'. P value = 3.56e-09 with ANOVA analysis.

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

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

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

PATHOLOGY.T.STAGE Mean (SD) 1.93 (0.73)
  N
  1 254
  2 561
  3 115
  4 36
     
  Significant markers N = 35
  pos. correlated 5
  neg. correlated 30
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
ZMYM6|9204 -0.1792 2.055e-08 0.000376
ERMN|57471 -0.1723 7.386e-08 0.00135
NDNL2|56160 -0.1695 1.166e-07 0.00213
TLR10|81793 -0.167 1.844e-07 0.00337
CNN3|1266 -0.1653 2.368e-07 0.00433
C14ORF139|79686 -0.1646 2.702e-07 0.00494
ZNF167|55888 -0.1641 2.966e-07 0.00542
SELE|6401 -0.1626 3.809e-07 0.00696
PTGER3|5733 -0.1611 4.795e-07 0.00876
CCND2|894 -0.1605 5.311e-07 0.00971

Figure S3.  Get High-res Image As an example, this figure shows the association of ZMYM6|9204 to 'PATHOLOGY.T.STAGE'. P value = 2.06e-08 with Spearman correlation analysis.

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

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

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

PATHOLOGY.N.STAGE Mean (SD) 0.77 (0.9)
  N
  0 456
  1 325
  2 108
  3 64
     
  Significant markers N = 13
  pos. correlated 11
  neg. correlated 2
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
HMSD|284293 -0.2395 1.214e-08 0.000222
NR2F2|7026 0.1725 8.34e-08 0.00152
F2R|2149 0.1647 3.192e-07 0.00584
HTR2B|3357 0.1632 4.045e-07 0.00739
SNED1|25992 0.1626 4.493e-07 0.00821
RGS4|5999 0.1622 4.794e-07 0.00876
SVEP1|79987 0.1612 5.763e-07 0.0105
NUDT4|11163 0.1604 6.493e-07 0.0119
DAAM1|23002 0.16 6.864e-07 0.0125
HS6ST3|266722 0.1551 1.981e-06 0.0362

Figure S4.  Get High-res Image As an example, this figure shows the association of HMSD|284293 to 'PATHOLOGY.N.STAGE'. P value = 1.21e-08 with Spearman correlation analysis.

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

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

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

PATHOLOGY.M.STAGE Labels N
  CM0 (I+) 2
  M0 837
  M1 15
  MX 115
     
  Significant markers N = 392
List of top 10 genes differentially expressed by 'PATHOLOGY.M.STAGE'

Table S11.  Get Full Table List of top 10 genes differentially expressed by 'PATHOLOGY.M.STAGE'

ANOVA_P Q
CCDC130|81576 9.25e-15 1.69e-10
NACA2|342538 7.486e-14 1.37e-09
HOOK2|29911 3.976e-13 7.27e-09
PPIAL4G|644591 1.295e-12 2.37e-08
EXD3|54932 2.468e-12 4.51e-08
CNOT4|4850 9.861e-12 1.8e-07
NEURL2|140825 1.649e-11 3.01e-07
VENTX|27287 2.888e-11 5.28e-07
ID2B|84099 4.482e-11 8.19e-07
FBXW9|84261 4.767e-11 8.71e-07

Figure S5.  Get High-res Image As an example, this figure shows the association of CCDC130|81576 to 'PATHOLOGY.M.STAGE'. P value = 9.25e-15 with ANOVA analysis.

Clinical variable #7: 'GENDER'

19 genes related to 'GENDER'.

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

GENDER Labels N
  FEMALE 959
  MALE 10
     
  Significant markers N = 19
  Higher in MALE 8
  Higher in FEMALE 11
List of top 10 genes differentially expressed by 'GENDER'

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

T(pos if higher in 'MALE') ttestP Q AUC
NLGN4Y|22829 40.76 4.186e-13 7.54e-09 1
ZFY|7544 36.03 1.327e-11 2.39e-07 1
PRKY|5616 30.22 3.381e-11 6.09e-07 1
SYT9|143425 13.7 3.291e-10 5.93e-06 0.7977
GSTA1|2938 -16.89 1.907e-08 0.000343 0.895
MYH16|84176 -12.46 1.273e-07 0.00229 0.8501
RND2|8153 10.97 1.321e-07 0.00238 0.8317
SUMF2|25870 -8.75 1.375e-07 0.00248 0.7352
RIMS4|140730 11.53 1.723e-07 0.0031 0.8754
HTR4|3360 -12.66 2.192e-07 0.00395 0.8049

Figure S6.  Get High-res Image As an example, this figure shows the association of NLGN4Y|22829 to 'GENDER'. P value = 4.19e-13 with T-test analysis.

Clinical variable #8: 'HISTOLOGICAL.TYPE'

5541 genes related to 'HISTOLOGICAL.TYPE'.

Table S14.  Basic characteristics of clinical feature: 'HISTOLOGICAL.TYPE'

HISTOLOGICAL.TYPE Labels N
  INFILTRATING CARCINOMA NOS 1
  INFILTRATING DUCTAL CARCINOMA 722
  INFILTRATING LOBULAR CARCINOMA 155
  MEDULLARY CARCINOMA 5
  MIXED HISTOLOGY (PLEASE SPECIFY) 28
  MUCINOUS CARCINOMA 14
  OTHER SPECIFY 43
     
  Significant markers N = 5541
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|999 1.808e-94 3.31e-90
RAPGEF3|10411 1.37e-43 2.5e-39
USHBP1|83878 4.104e-41 7.5e-37
AVPR2|554 7.779e-39 1.42e-34
BTG2|7832 9.211e-38 1.68e-33
PSMD14|10213 2.362e-37 4.32e-33
MUSTN1|389125 4.069e-37 7.44e-33
MUC2|4583 1.041e-36 1.9e-32
LRRC70|100130733 2.34e-36 4.28e-32
GPIHBP1|338328 2.416e-36 4.41e-32

Figure S7.  Get High-res Image As an example, this figure shows the association of CDH1|999 to 'HISTOLOGICAL.TYPE'. P value = 1.81e-94 with ANOVA analysis.

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

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

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

RADIATIONS.RADIATION.REGIMENINDICATION Labels N
  NO 282
  YES 687
     
  Significant markers N = 241
  Higher in YES 105
  Higher in NO 136
List of top 10 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

Table S17.  Get Full Table List of top 10 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

T(pos if higher in 'YES') ttestP Q AUC
SELO|83642 6.49 1.709e-10 3.12e-06 0.6208
KIF20B|9585 -6.49 1.729e-10 3.16e-06 0.6172
FAM100A|124402 6.28 6.551e-10 1.2e-05 0.6126
NACA2|342538 6.08 2.004e-09 3.66e-05 0.5957
RING1|6015 6.05 2.657e-09 4.86e-05 0.6126
BAZ1B|9031 -5.99 3.676e-09 6.72e-05 0.6092
C1ORF86|199990 5.96 4.187e-09 7.65e-05 0.6044
C19ORF6|91304 5.96 4.205e-09 7.69e-05 0.5983
SLC39A5|283375 5.99 4.383e-09 8.01e-05 0.626
DMPK|1760 5.93 5.16e-09 9.43e-05 0.6136

Figure S8.  Get High-res Image As an example, this figure shows the association of SELO|83642 to 'RADIATIONS.RADIATION.REGIMENINDICATION'. P value = 1.71e-10 with T-test analysis.

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

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

Table S18.  Basic characteristics of clinical feature: 'NUMBER.OF.LYMPH.NODES'

NUMBER.OF.LYMPH.NODES Mean (SD) 2.31 (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 S19.  Get Full Table List of 4 genes significantly correlated to 'NUMBER.OF.LYMPH.NODES' by Spearman correlation test

SpearmanCorr corrP Q
HMSD|284293 -0.2603 7.98e-09 0.000146
SNED1|25992 0.1804 2.467e-07 0.00451
POU4F1|5457 -0.2313 7.266e-07 0.0133
NUDT4|11163 0.1645 2.62e-06 0.0479

Figure S9.  Get High-res Image As an example, this figure shows the association of HMSD|284293 to 'NUMBER.OF.LYMPH.NODES'. P value = 7.98e-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.merged_data.txt

  • Number of patients = 969

  • Number of genes = 18284

  • 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.

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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