Correlation between mRNAseq expression and clinical features
Uterine Corpus Endometrioid Carcinoma (Primary solid tumor)
15 July 2014  |  analyses__2014_07_15
Maintainer Information
Citation Information
Maintained by Juok Cho (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2014): Correlation between mRNAseq expression and clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C1JQ0ZTM
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 18555 genes and 7 clinical features across 488 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 5 clinical features related to at least one genes.

  • 21 genes correlated to 'Time to Death'.

    • CD3EAP|10849 ,  SRD5A1|6715 ,  SCGB2A1|4246 ,  JMJD7-PLA2G4B|8681 ,  DKC1|1736 ,  ...

  • 664 genes correlated to 'AGE'.

    • DIO2|1734 ,  FAM107A|11170 ,  PTCH1|5727 ,  S100A1|6271 ,  NR2F6|2063 ,  ...

  • 4726 genes correlated to 'HISTOLOGICAL.TYPE'.

    • KIAA1324|57535 ,  L1CAM|3897 ,  FOXA2|3170 ,  PPAP2C|8612 ,  HIF3A|64344 ,  ...

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

    • RPL23AP82|284942 ,  RPL23AP7|118433 ,  LOC341056|341056 ,  UBE2MP1|606551 ,  EDARADD|128178 ,  ...

  • 69 genes correlated to 'RACE'.

    • SORD|6652 ,  PPIL3|53938 ,  ACTB|60 ,  LOC90784|90784 ,  NOTCH2NL|388677 ,  ...

  • No genes correlated to 'COMPLETENESS.OF.RESECTION', 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=21 shorter survival N=16 longer survival N=5
AGE Spearman correlation test N=664 older N=401 younger N=263
HISTOLOGICAL TYPE Kruskal-Wallis test N=4726        
RADIATIONS RADIATION REGIMENINDICATION Wilcoxon test N=100 yes N=100 no N=0
COMPLETENESS OF RESECTION Kruskal-Wallis test   N=0        
RACE Kruskal-Wallis test N=69        
ETHNICITY Wilcoxon test   N=0        
Clinical variable #1: 'Time to Death'

21 genes related to 'Time to Death'.

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

Time to Death Duration (Months) 0-191.8 (median=22.7)
  censored N = 426
  death N = 60
     
  Significant markers N = 21
  associated with shorter survival 16
  associated with longer survival 5
List of top 10 genes differentially expressed by 'Time to Death'

Table S2.  Get Full Table List of top 10 genes significantly associated with 'Time to Death' by Cox regression test

HazardRatio Wald_P Q C_index
CD3EAP|10849 2.8 4.005e-09 7.4e-05 0.678
SRD5A1|6715 2.6 5.841e-08 0.0011 0.669
SCGB2A1|4246 0.85 1.986e-06 0.037 0.304
JMJD7-PLA2G4B|8681 0.5 3.887e-06 0.072 0.33
DKC1|1736 2.6 4.175e-06 0.077 0.691
GOLGA7|51125 2.4 4.23e-06 0.078 0.638
MGAT4A|11320 1.61 4.696e-06 0.087 0.672
KIAA1324|57535 0.86 4.891e-06 0.091 0.337
CPS1|1373 1.26 5.822e-06 0.11 0.641
MRPL15|29088 2.4 7.032e-06 0.13 0.642
Clinical variable #2: 'AGE'

664 genes related to 'AGE'.

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

AGE Mean (SD) 63.7 (11)
  Significant markers N = 664
  pos. correlated 401
  neg. correlated 263
List of top 10 genes differentially expressed by 'AGE'

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

SpearmanCorr corrP Q
DIO2|1734 -0.3771 6.657e-18 1.24e-13
FAM107A|11170 0.3409 1.024e-14 1.9e-10
PTCH1|5727 -0.3351 3.064e-14 5.68e-10
S100A1|6271 0.3345 3.383e-14 6.28e-10
NR2F6|2063 0.3215 3.585e-13 6.65e-09
HIF3A|64344 0.3237 3.823e-13 7.09e-09
SPTBN4|57731 0.318 6.936e-13 1.29e-08
DUSP9|1852 0.3288 8.862e-13 1.64e-08
MGAT4A|11320 0.3133 1.499e-12 2.78e-08
HRASLS|57110 0.3239 1.504e-12 2.79e-08
Clinical variable #3: 'HISTOLOGICAL.TYPE'

4726 genes related to 'HISTOLOGICAL.TYPE'.

Table S5.  Basic characteristics of clinical feature: 'HISTOLOGICAL.TYPE'

HISTOLOGICAL.TYPE Labels N
  ENDOMETRIOID ENDOMETRIAL ADENOCARCINOMA 370
  MIXED SEROUS AND ENDOMETRIOID 19
  SEROUS ENDOMETRIAL ADENOCARCINOMA 99
     
  Significant markers N = 4726
List of top 10 genes differentially expressed by 'HISTOLOGICAL.TYPE'

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

ANOVA_P Q
KIAA1324|57535 2.103e-38 3.9e-34
L1CAM|3897 4.376e-38 8.12e-34
FOXA2|3170 2.664e-36 4.94e-32
PPAP2C|8612 5.16e-36 9.57e-32
HIF3A|64344 5.193e-36 9.63e-32
SLC6A12|6539 9.731e-35 1.81e-30
IL20RA|53832 9.972e-35 1.85e-30
TFF3|7033 3.197e-34 5.93e-30
CDKN1A|1026 9.645e-34 1.79e-29
SPDEF|25803 1.681e-33 3.12e-29
Clinical variable #4: 'RADIATIONS.RADIATION.REGIMENINDICATION'

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

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

RADIATIONS.RADIATION.REGIMENINDICATION Labels N
  NO 137
  YES 351
     
  Significant markers N = 100
  Higher in YES 100
  Higher in NO 0
List of top 10 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

Table S8.  Get Full Table List of top 10 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

W(pos if higher in 'YES') wilcoxontestP Q AUC
RPL23AP82|284942 14317 3.706e-12 6.88e-08 0.7023
RPL23AP7|118433 14517 1.01e-11 1.87e-07 0.6981
LOC341056|341056 15113 1.779e-10 3.3e-06 0.6857
UBE2MP1|606551 15723.5 2.795e-09 5.19e-05 0.673
EDARADD|128178 15777 3.527e-09 6.54e-05 0.6719
POTEE|445582 15556 5.884e-09 0.000109 0.6699
UBE2NL|389898 15526.5 7.531e-09 0.00014 0.6691
TPI1P3|728402 14842 8.41e-09 0.000156 0.6698
LOC100130932|100130932 16003 9.273e-09 0.000172 0.6672
PGAM4|441531 16066 1.209e-08 0.000224 0.6659
Clinical variable #5: 'COMPLETENESS.OF.RESECTION'

No gene related to 'COMPLETENESS.OF.RESECTION'.

Table S9.  Basic characteristics of clinical feature: 'COMPLETENESS.OF.RESECTION'

COMPLETENESS.OF.RESECTION Labels N
  R0 337
  R1 22
  R2 17
  RX 29
     
  Significant markers N = 0
Clinical variable #6: 'RACE'

69 genes related to 'RACE'.

Table S10.  Basic characteristics of clinical feature: 'RACE'

RACE Labels N
  AMERICAN INDIAN OR ALASKA NATIVE 4
  ASIAN 19
  BLACK OR AFRICAN AMERICAN 74
  NATIVE HAWAIIAN OR OTHER PACIFIC ISLANDER 9
  WHITE 357
     
  Significant markers N = 69
List of top 10 genes differentially expressed by 'RACE'

Table S11.  Get Full Table List of top 10 genes differentially expressed by 'RACE'

ANOVA_P Q
SORD|6652 8.397e-12 1.56e-07
PPIL3|53938 1.311e-11 2.43e-07
ACTB|60 2.691e-10 4.99e-06
LOC90784|90784 3.191e-10 5.92e-06
NOTCH2NL|388677 5.702e-10 1.06e-05
UTS2|10911 3.443e-09 6.39e-05
LRRC37A2|474170 4.905e-09 9.1e-05
DHRS4L1|728635 1.347e-08 0.00025
APH1A|51107 1.385e-08 0.000257
CNN2|1265 1.991e-08 0.000369
Clinical variable #7: 'ETHNICITY'

No gene related to 'ETHNICITY'.

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

ETHNICITY Labels N
  HISPANIC OR LATINO 13
  NOT HISPANIC OR LATINO 337
     
  Significant markers N = 0
Methods & Data
Input
  • Expresson data file = UCEC-TP.uncv2.mRNAseq_RSEM_normalized_log2.txt

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

  • Number of patients = 488

  • Number of genes = 18555

  • Number of clinical features = 7

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)