Correlation between mRNAseq expression and clinical features
Sarcoma (Primary solid tumor)
28 January 2016  |  analyses__2016_01_28
Maintainer Information
Citation Information
doi:10.7908/C180523M
Maintained by Juok Cho (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2016): Correlation between mRNAseq expression and clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C180523M
Overview
Introduction

This pipeline uses various statistical tests to identify mRNAs whose log2 expression levels correlated to selected clinical features. The input file "SARC-TP.uncv2.mRNAseq_RSEM_normalized_log2.txt" is generated in the pipeline mRNAseq_Preprocess in the stddata run.

Summary

Testing the association between 18187 genes and 9 clinical features across 259 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 8 clinical features related to at least one genes.

  • 30 genes correlated to 'DAYS_TO_DEATH_OR_LAST_FUP'.

    • SERBP1|26135 ,  DHRS12|79758 ,  B3GALT4|8705 ,  NUDCD1|84955 ,  WDR43|23160 ,  ...

  • 30 genes correlated to 'YEARS_TO_BIRTH'.

    • KTI12|112970 ,  VASN|114990 ,  MBD5|55777 ,  NANS|54187 ,  BAZ2B|29994 ,  ...

  • 30 genes correlated to 'TUMOR_TISSUE_SITE'.

    • MEIS1|4211 ,  FOXF1|2294 ,  TBX15|6913 ,  C7|730 ,  MEIS2|4212 ,  ...

  • 9 genes correlated to 'GENDER'.

    • CYORF15B|84663 ,  NCRNA00183|554203 ,  CYORF15A|246126 ,  DBF4B|80174 ,  HDHD1A|8226 ,  ...

  • 30 genes correlated to 'RADIATION_THERAPY'.

    • EFTUD2|9343 ,  MAPK10|5602 ,  TBX15|6913 ,  SNX8|29886 ,  IER5L|389792 ,  ...

  • 30 genes correlated to 'HISTOLOGICAL_TYPE'.

    • DAB2|1601 ,  TPM2|7169 ,  PAPSS2|9060 ,  SPEG|10290 ,  ADD3|120 ,  ...

  • 30 genes correlated to 'RESIDUAL_TUMOR'.

    • RELL2|285613 ,  FAM57A|79850 ,  BRD7|29117 ,  SFRS1|6426 ,  PABPC1L|80336 ,  ...

  • 1 gene correlated to 'RACE'.

    • LOC441869|441869

  • No genes correlated to '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
DAYS_TO_DEATH_OR_LAST_FUP Cox regression test N=30   N=NA   N=NA
YEARS_TO_BIRTH Spearman correlation test N=30 older N=9 younger N=21
TUMOR_TISSUE_SITE Kruskal-Wallis test N=30        
GENDER Wilcoxon test N=9 male N=9 female N=0
RADIATION_THERAPY Wilcoxon test N=30 yes N=30 no N=0
HISTOLOGICAL_TYPE Kruskal-Wallis test N=30        
RESIDUAL_TUMOR Kruskal-Wallis test N=30        
RACE Kruskal-Wallis test N=1        
ETHNICITY Wilcoxon test   N=0        
Clinical variable #1: 'DAYS_TO_DEATH_OR_LAST_FUP'

30 genes related to 'DAYS_TO_DEATH_OR_LAST_FUP'.

Table S1.  Basic characteristics of clinical feature: 'DAYS_TO_DEATH_OR_LAST_FUP'

DAYS_TO_DEATH_OR_LAST_FUP Duration (Months) 0.5-188.2 (median=31)
  censored N = 160
  death N = 98
     
  Significant markers N = 30
  associated with shorter survival NA
  associated with longer survival NA
List of top 10 genes differentially expressed by 'DAYS_TO_DEATH_OR_LAST_FUP'

Table S2.  Get Full Table List of top 10 genes significantly associated with 'Time to Death' by Cox regression test. For the survival curves, it compared quantile intervals at c(0, 0.25, 0.50, 0.75, 1) and did not try survival analysis if there is only one interval.

logrank_P Q C_index
SERBP1|26135 2.89e-08 0.00053 0.655
DHRS12|79758 5.55e-07 0.005 0.332
B3GALT4|8705 1.07e-06 0.0065 0.31
NUDCD1|84955 1.63e-06 0.0074 0.626
WDR43|23160 3.8e-06 0.012 0.626
HNRNPR|10236 4.08e-06 0.012 0.646
TARDBP|23435 4.76e-06 0.012 0.689
GNL3|26354 6.02e-06 0.012 0.63
NUDT7|283927 6.54e-06 0.012 0.369
ALKBH7|84266 7.33e-06 0.012 0.449
Clinical variable #2: 'YEARS_TO_BIRTH'

30 genes related to 'YEARS_TO_BIRTH'.

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

YEARS_TO_BIRTH Mean (SD) 60.72 (15)
  Significant markers N = 30
  pos. correlated 9
  neg. correlated 21
List of top 10 genes differentially expressed by 'YEARS_TO_BIRTH'

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

SpearmanCorr corrP Q
KTI12|112970 0.3686 1.009e-09 1.84e-05
VASN|114990 0.358 3.219e-09 2.93e-05
MBD5|55777 -0.351 6.772e-09 3.72e-05
NANS|54187 0.3488 8.571e-09 3.72e-05
BAZ2B|29994 -0.3451 1.261e-08 3.72e-05
MARCO|8685 0.3504 1.331e-08 3.72e-05
NDRG2|57447 -0.3438 1.431e-08 3.72e-05
ZMYM2|7750 -0.3407 1.972e-08 4.03e-05
ALS2CR8|79800 -0.3406 1.994e-08 4.03e-05
UAP1|6675 0.3342 3.782e-08 6.65e-05
Clinical variable #3: 'TUMOR_TISSUE_SITE'

30 genes related to 'TUMOR_TISSUE_SITE'.

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

TUMOR_TISSUE_SITE Labels N
  CHEST - BREAST 1
  CHEST - CHEST WALL 7
  CHEST - LUNG/PLEURA 2
  CHEST - MEDIASTINUM 1
  CHEST - OTHER (PLEASE SPECIFY 2
  GYNECOLOGICAL - OVARY 1
  GYNECOLOGICAL - UTERUS 29
  HEAD AND NECK - HEAD 2
  HEAD AND NECK - NECK 1
  HEAD AND NECK - OTHER (PLEASE SPECIFY 2
  LOWER ABDOMINAL/PELVIC - BLADDER 1
  LOWER ABDOMINAL/PELVIC - OTHER (PLEASE SPECIFY 2
  LOWER ABDOMINAL/PELVIC - PELVIC 11
  LOWER ABDOMINAL/PELVIC - SPERMATIC CORD 2
  LOWER EXTREMITY - FOOT/ANKLE 4
  LOWER EXTREMITY - GROIN 2
  LOWER EXTREMITY - LOWER LEG/CALF 17
  LOWER EXTREMITY - OTHER (PLEASE SPECIFY 5
  LOWER EXTREMITY - THIGH/KNEE 45
  RETROPERITONEUM/UPPER ABDOMINAL - COLON 4
  RETROPERITONEUM/UPPER ABDOMINAL - GASTRIC 2
  RETROPERITONEUM/UPPER ABDOMINAL - INTRAABDOMINAL 5
  RETROPERITONEUM/UPPER ABDOMINAL - KIDNEY 8
  RETROPERITONEUM/UPPER ABDOMINAL - OTHER (PLEASE SPECIFY 2
  RETROPERITONEUM/UPPER ABDOMINAL - PANCREAS 1
  RETROPERITONEUM/UPPER ABDOMINAL - RETROPERITONEUM 72
  RETROPERITONEUM/UPPER ABDOMINAL - SMALL INTESTINES 3
  SUPERFICIAL TRUNK - ABDOMINAL WALL 2
  SUPERFICIAL TRUNK - BACK 5
  SUPERFICIAL TRUNK - BUTTOCK 4
  SUPERFICIAL TRUNK - FLANK 1
  UPPER EXTREMITY - SHOULDER/AXILLA 7
  UPPER EXTREMITY - UPPER ARM/ELBOW 5
     
  Significant markers N = 30
List of top 10 genes differentially expressed by 'TUMOR_TISSUE_SITE'

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

kruskal_wallis_P Q
MEIS1|4211 3.315e-13 6.03e-09
FOXF1|2294 6.889e-11 5.81e-07
TBX15|6913 1.078e-10 5.81e-07
C7|730 1.564e-10 5.81e-07
MEIS2|4212 1.596e-10 5.81e-07
PBX1|5087 5.788e-10 1.75e-06
HOXC4|3221 3.39e-09 8.81e-06
KCNH2|3757 4.007e-09 9.11e-06
LONRF2|164832 4.894e-09 9.89e-06
C10ORF55|414236 7.298e-09 1.33e-05
Clinical variable #4: 'GENDER'

9 genes related to 'GENDER'.

Table S7.  Basic characteristics of clinical feature: 'GENDER'

GENDER Labels N
  FEMALE 141
  MALE 118
     
  Significant markers N = 9
  Higher in MALE 9
  Higher in FEMALE 0
List of 9 genes differentially expressed by 'GENDER'

Table S8.  Get Full Table List of 9 genes differentially expressed by 'GENDER'. 21 significant gene(s) located in sex chromosomes is(are) filtered out.

W(pos if higher in 'MALE') wilcoxontestP Q AUC
CYORF15B|84663 3296 3.103e-16 4.7e-13 0.9976
NCRNA00183|554203 3728 2.079e-14 2.7e-11 0.7759
CYORF15A|246126 2596 1.093e-13 1.33e-10 1
DBF4B|80174 4651 1.007e-09 9.15e-07 0.7205
HDHD1A|8226 4732 2.323e-09 2.01e-06 0.7156
CA5BP|340591 4842 7.029e-09 5.56e-06 0.709
CBX1|10951 4953 2.078e-08 1.45e-05 0.7023
MYST2|11143 4982 2.744e-08 1.85e-05 0.7006
TYRO3|7301 5024 4.086e-08 2.65e-05 0.698
Clinical variable #5: 'RADIATION_THERAPY'

30 genes related to 'RADIATION_THERAPY'.

Table S9.  Basic characteristics of clinical feature: 'RADIATION_THERAPY'

RADIATION_THERAPY Labels N
  NO 179
  YES 74
     
  Significant markers N = 30
  Higher in YES 30
  Higher in NO 0
List of top 10 genes differentially expressed by 'RADIATION_THERAPY'

Table S10.  Get Full Table List of top 10 genes differentially expressed by 'RADIATION_THERAPY'

W(pos if higher in 'YES') wilcoxontestP Q AUC
EFTUD2|9343 9542 3.552e-08 0.000646 0.7204
MAPK10|5602 3916 4.07e-07 0.00247 0.7027
TBX15|6913 9247 7.246e-07 0.00247 0.6981
SNX8|29886 9246 7.317e-07 0.00247 0.698
IER5L|389792 9241 7.681e-07 0.00247 0.6976
KIAA2022|340533 3503 8.564e-07 0.00247 0.7031
MYOCD|93649 3072 9.5e-07 0.00247 0.7083
SLC24A3|57419 3992 1.291e-06 0.00284 0.6945
PGM5|5239 4068 1.405e-06 0.00284 0.6929
S100A10|6281 9137 2.066e-06 0.00376 0.6898
Clinical variable #6: 'HISTOLOGICAL_TYPE'

30 genes related to 'HISTOLOGICAL_TYPE'.

Table S11.  Basic characteristics of clinical feature: 'HISTOLOGICAL_TYPE'

HISTOLOGICAL_TYPE Labels N
  DEDIFFERENTIATED LIPOSARCOMA 58
  DESMOID TUMOR 2
  GIANT CELL 'MFH' / UNDIFFERENTIATED PLEOMORPHIC SARCOMA WITH GIANT CELLS 1
  LEIOMYOSARCOMA (LMS) 104
  MALIGNANT PERIPHERAL NERVE SHEATH TUMORS (MPNST) 9
  MYXOFIBROSARCOMA 25
  PLEOMORPHIC 'MFH' / UNDIFFERENTIATED PLEOMORPHIC SARCOMA 29
  SARCOMA; SYNOVIAL; POORLY DIFFERENTIATED 2
  SYNOVIAL SARCOMA - BIPHASIC 2
  SYNOVIAL SARCOMA - MONOPHASIC 6
  UNDIFFERENTIATED PLEOMORPHIC SARCOMA (UPS) 21
     
  Significant markers N = 30
List of top 10 genes differentially expressed by 'HISTOLOGICAL_TYPE'

Table S12.  Get Full Table List of top 10 genes differentially expressed by 'HISTOLOGICAL_TYPE'

kruskal_wallis_P Q
DAB2|1601 1.398e-27 1.43e-23
TPM2|7169 1.569e-27 1.43e-23
PAPSS2|9060 6.096e-27 3.7e-23
SPEG|10290 2.292e-26 1.04e-22
ADD3|120 2.295e-25 8.35e-22
RBM24|221662 3.837e-25 1.16e-21
ACTG2|72 4.773e-25 1.24e-21
JPH2|57158 7.237e-25 1.63e-21
SORBS1|10580 8.052e-25 1.63e-21
LOC728264|728264 1.179e-24 2.14e-21
Clinical variable #7: 'RESIDUAL_TUMOR'

30 genes related to 'RESIDUAL_TUMOR'.

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

RESIDUAL_TUMOR Labels N
  R0 154
  R1 69
  R2 9
  RX 26
     
  Significant markers N = 30
List of top 10 genes differentially expressed by 'RESIDUAL_TUMOR'

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

kruskal_wallis_P Q
RELL2|285613 1.432e-06 0.026
FAM57A|79850 1.209e-05 0.0663
BRD7|29117 1.337e-05 0.0663
SFRS1|6426 1.816e-05 0.0663
PABPC1L|80336 2.495e-05 0.0663
SNX21|90203 2.686e-05 0.0663
TMTC1|83857 3.124e-05 0.0663
THAP11|57215 4.164e-05 0.0663
CLEC4G|339390 4.345e-05 0.0663
UBE2O|63893 4.382e-05 0.0663
Clinical variable #8: 'RACE'

One gene related to 'RACE'.

Table S15.  Basic characteristics of clinical feature: 'RACE'

RACE Labels N
  ASIAN 6
  BLACK OR AFRICAN AMERICAN 18
  WHITE 226
     
  Significant markers N = 1
List of one gene differentially expressed by 'RACE'

Table S16.  Get Full Table List of one gene differentially expressed by 'RACE'

kruskal_wallis_P Q
LOC441869|441869 1.325e-05 0.241
Clinical variable #9: 'ETHNICITY'

No gene related to 'ETHNICITY'.

Table S17.  Basic characteristics of clinical feature: 'ETHNICITY'

ETHNICITY Labels N
  HISPANIC OR LATINO 5
  NOT HISPANIC OR LATINO 222
     
  Significant markers N = 0
Methods & Data
Input

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

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

  • Number of patients = 259

  • Number of genes = 18187

  • Number of clinical features = 9

Selected clinical features

  • Further details on clinical features selected for this analysis, please find a documentation on selected CDEs (Clinical Data Elements). The first column of the file is a formula to convert values and the second column is a clinical parameter name.

  • Survival time data

    • Survival time data is a combined value of days_to_death and days_to_last_followup. For each patient, it creates a combined value 'days_to_death_or_last_fup' using conversion process below.

      • if 'vital_status'==1(dead), 'days_to_last_followup' is always NA. Thus, uses 'days_to_death' value for 'days_to_death_or_fup'

      • if 'vital_status'==0(alive),

        • if 'days_to_death'==NA & 'days_to_last_followup'!=NA, uses 'days_to_last_followup' value for 'days_to_death_or_fup'

        • if 'days_to_death'!=NA, excludes this case in survival analysis and report the case.

      • if 'vital_status'==NA,excludes this case in survival analysis and report the case.

    • cf. In certain diesase types such as SKCM, days_to_death parameter is replaced with time_from_specimen_dx or time_from_specimen_procurement_to_death .

  • This analysis excluded clinical variables that has only NA values.

Survival analysis

For survival clinical features, logrank test in univariate Cox regression analysis with proportional hazards model (Andersen and Gill 1982) was used to estimate the P values comparing quantile intervals using the 'coxph' function in R. Kaplan-Meier survival curves were plotted using quantile intervals at c(0, 0.25, 0.50, 0.75, 1). If there is only one interval group, it will not try survival analysis.

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

Wilcoxon rank sum test (Mann-Whitney U test)

For two groups (mutant or wild-type) of continuous type of clinical data, wilcoxon rank sum test (Mann and Whitney, 1947) was applied to compare their mean difference using 'wilcox.test(continuous.clinical ~ as.factor(group), exact=FALSE)' function in R. This test is equivalent to the Mann-Whitney test.

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] Mann and Whitney, On a Test of Whether one of Two Random Variables is Stochastically Larger than the Other, Annals of Mathematical Statistics 18 (1), 50-60 (1947)
[4] 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)
Copyright © 2016 Broad Institute TCGA GDAC as part of the TCGA Research Network. All rights reserved.
Made with Nozzle