Brain Lower Grade Glioma: Correlation between mRNAseq expression and clinical features
Maintained by Juok Cho (Broad Institute)
Overview
Introduction

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

Summary

Testing the association between 18308 genes and 6 clinical features across 110 samples, statistically thresholded by Q value < 0.05, 5 clinical features related to at least one genes.

  • 100 genes correlated to 'Time to Death'.

    • PGAM1|5223 ,  CBARA1|10367 ,  CCNY|219771 ,  PPA1|5464 ,  CUEDC2|79004 ,  ...

  • 13 genes correlated to 'AGE'.

    • TRMT2B|79979 ,  SAR1A|56681 ,  NBL1|4681 ,  CCNY|219771 ,  CDC123|8872 ,  ...

  • 23 genes correlated to 'GENDER'.

    • XIST|7503 ,  ZFY|7544 ,  PRKY|5616 ,  RPS4Y1|6192 ,  KDM5D|8284 ,  ...

  • 1138 genes correlated to 'HISTOLOGICAL.TYPE'.

    • AK2|204 ,  LRRC42|115353 ,  TXNDC12|51060 ,  ZNF691|51058 ,  TMEM69|51249 ,  ...

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

    • C9ORF93|203238 ,  LMBRD2|92255 ,  SLC25A46|91137 ,  ZDHHC21|340481 ,  POLR2J|5439 ,  ...

  • No genes correlated to 'KARNOFSKY.PERFORMANCE.SCORE'

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=100 shorter survival N=24 longer survival N=76
AGE Spearman correlation test N=13 older N=1 younger N=12
GENDER t test N=23 male N=15 female N=8
KARNOFSKY PERFORMANCE SCORE Spearman correlation test   N=0        
HISTOLOGICAL TYPE ANOVA test N=1138        
RADIATIONS RADIATION REGIMENINDICATION t test N=31 yes N=20 no N=11
Clinical variable #1: 'Time to Death'

100 genes related to 'Time to Death'.

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

Time to Death Duration (Months) 0-211.2 (median=19)
  censored N = 69
  death N = 41
     
  Significant markers N = 100
  associated with shorter survival 24
  associated with longer survival 76
List of top 10 genes significantly associated with 'Time to Death' by Cox regression test

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
PGAM1|5223 0.15 6.68e-09 0.00012 0.214
CBARA1|10367 0.12 7.695e-09 0.00014 0.257
CCNY|219771 0.07 1e-08 0.00018 0.226
PPA1|5464 0.14 1.253e-08 0.00023 0.25
CUEDC2|79004 0.08 1.67e-08 0.00031 0.261
ZRANB1|54764 0.13 1.819e-08 0.00033 0.223
CGREF1|10669 0.4 2.253e-08 0.00041 0.308
ARL3|403 0.15 2.536e-08 0.00046 0.209
SLITRK5|26050 0.33 2.869e-08 0.00052 0.284
LOC254559|254559 0.5 3.272e-08 6e-04 0.283

Figure S1.  Get High-res Image As an example, this figure shows the association of PGAM1|5223 to 'Time to Death'. four curves present the cumulative survival rates of 4 quartile subsets of patients. P value = 6.68e-09 with univariate Cox regression analysis using continuous log-2 expression values.

Clinical variable #2: 'AGE'

13 genes related to 'AGE'.

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

AGE Mean (SD) 42.95 (13)
  Significant markers N = 13
  pos. correlated 1
  neg. correlated 12
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
TRMT2B|79979 0.4893 5.819e-08 0.00107
SAR1A|56681 -0.4886 6.138e-08 0.00112
NBL1|4681 -0.4805 1.079e-07 0.00198
CCNY|219771 -0.4796 1.149e-07 0.0021
CDC123|8872 -0.4768 1.393e-07 0.00255
RBM17|84991 -0.4692 2.339e-07 0.00428
DTX4|23220 -0.4663 2.834e-07 0.00519
MKX|283078 -0.4592 4.509e-07 0.00825
LOC100128292|100128292 -0.4565 5.363e-07 0.00981
OTUD1|220213 -0.4491 8.621e-07 0.0158

Figure S2.  Get High-res Image As an example, this figure shows the association of TRMT2B|79979 to 'AGE'. P value = 5.82e-08 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #3: 'GENDER'

23 genes related to 'GENDER'.

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

GENDER Labels N
  FEMALE 50
  MALE 60
     
  Significant markers N = 23
  Higher in MALE 15
  Higher in FEMALE 8
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
XIST|7503 -39.21 5.231e-63 9.57e-59 1
ZFY|7544 47.2 2.525e-59 4.62e-55 1
PRKY|5616 25.31 2.249e-43 4.12e-39 0.9996
RPS4Y1|6192 38.96 4.013e-42 7.34e-38 1
KDM5D|8284 52.17 6.693e-39 1.22e-34 1
NLGN4Y|22829 24.17 1.097e-37 2.01e-33 0.9966
TSIX|9383 -20.98 9.775e-37 1.79e-32 1
USP9Y|8287 45.68 8.53e-33 1.56e-28 1
DDX3Y|8653 46.36 4.11e-32 7.52e-28 1
EIF1AY|9086 44.86 4.043e-19 7.4e-15 1

Figure S3.  Get High-res Image As an example, this figure shows the association of XIST|7503 to 'GENDER'. P value = 5.23e-63 with T-test analysis.

Clinical variable #4: 'KARNOFSKY.PERFORMANCE.SCORE'

No gene related to 'KARNOFSKY.PERFORMANCE.SCORE'.

Table S7.  Basic characteristics of clinical feature: 'KARNOFSKY.PERFORMANCE.SCORE'

KARNOFSKY.PERFORMANCE.SCORE Mean (SD) 88.62 (11)
  Score N
  50 2
  70 3
  80 10
  90 27
  100 16
     
  Significant markers N = 0
Clinical variable #5: 'HISTOLOGICAL.TYPE'

1138 genes related to 'HISTOLOGICAL.TYPE'.

Table S8.  Basic characteristics of clinical feature: 'HISTOLOGICAL.TYPE'

HISTOLOGICAL.TYPE Labels N
  ASTROCYTOMA 36
  OLIGOASTROCYTOMA 27
  OLIGODENDROGLIOMA 46
     
  Significant markers N = 1138
List of top 10 genes differentially expressed by 'HISTOLOGICAL.TYPE'

Table S9.  Get Full Table List of top 10 genes differentially expressed by 'HISTOLOGICAL.TYPE'

ANOVA_P Q
AK2|204 1.386e-15 2.54e-11
LRRC42|115353 4.533e-15 8.3e-11
TXNDC12|51060 4.792e-15 8.77e-11
ZNF691|51058 1.226e-14 2.24e-10
TMEM69|51249 2.538e-14 4.65e-10
FPGT|8790 5.019e-14 9.19e-10
ADPRHL2|54936 5.25e-14 9.61e-10
TAF12|6883 5.598e-14 1.02e-09
TRAPPC3|27095 5.733e-14 1.05e-09
CAP1|10487 6.023e-14 1.1e-09

Figure S4.  Get High-res Image As an example, this figure shows the association of AK2|204 to 'HISTOLOGICAL.TYPE'. P value = 1.39e-15 with ANOVA analysis.

Clinical variable #6: 'RADIATIONS.RADIATION.REGIMENINDICATION'

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

Table S10.  Basic characteristics of clinical feature: 'RADIATIONS.RADIATION.REGIMENINDICATION'

RADIATIONS.RADIATION.REGIMENINDICATION Labels N
  NO 66
  YES 44
     
  Significant markers N = 31
  Higher in YES 20
  Higher in NO 11
List of top 10 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

Table S11.  Get Full Table List of top 10 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

T(pos if higher in 'YES') ttestP Q AUC
C9ORF93|203238 5.95 3.383e-08 0.000619 0.8034
LMBRD2|92255 5.89 4.679e-08 0.000857 0.7837
SLC25A46|91137 5.64 1.444e-07 0.00264 0.7738
ZDHHC21|340481 5.59 1.753e-07 0.00321 0.7855
POLR2J|5439 -5.61 1.786e-07 0.00327 0.7724
TTBK2|146057 5.54 2.397e-07 0.00439 0.7824
ZNHIT1|10467 -5.46 3.39e-07 0.0062 0.77
ADAM22|53616 5.43 3.525e-07 0.00645 0.7769
PTPN4|5775 5.37 4.716e-07 0.00863 0.7603
MYCBP2|23077 5.3 6.736e-07 0.0123 0.7534

Figure S5.  Get High-res Image As an example, this figure shows the association of C9ORF93|203238 to 'RADIATIONS.RADIATION.REGIMENINDICATION'. P value = 3.38e-08 with T-test analysis.

Methods & Data
Input

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

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

  • Number of patients = 110

  • Number of genes = 18308

  • Number of clinical features = 6

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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