Correlation between mRNAseq expression and clinical features
Lung Adenocarcinoma (Primary solid tumor)
23 May 2013  |  analyses__2013_05_23
Maintainer Information
Citation Information
doi:10.7908/C14X55VS
Maintained by Juok Cho (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2013): Correlation between mRNAseq expression and clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C14X55VS
Overview
Introduction

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

Summary

Testing the association between 18310 genes and 12 clinical features across 354 samples, statistically thresholded by Q value < 0.05, 7 clinical features related to at least one genes.

  • 6 genes correlated to 'Time to Death'.

    • ESYT3|83850 ,  UCN2|90226 ,  PPP1R3G|648791 ,  B3GNT8|374907 ,  LOC645166|645166 ,  ...

  • 3 genes correlated to 'AGE'.

    • HSD17B2|3294 ,  GPR15|2838 ,  AHRR|57491

  • 85 genes correlated to 'GENDER'.

    • PRKY|5616 ,  ZFY|7544 ,  RPS4Y1|6192 ,  XIST|7503 ,  DDX3Y|8653 ,  ...

  • 30 genes correlated to 'HISTOLOGICAL.TYPE'.

    • CREB3L3|84699 ,  A4GNT|51146 ,  REG4|83998 ,  MIA|8190 ,  CRH|1392 ,  ...

  • 2 genes correlated to 'YEAROFTOBACCOSMOKINGONSET'.

    • GPR15|2838 ,  ENTPD3|956

  • 53 genes correlated to 'DISTANT.METASTASIS'.

    • CUL4A|8451 ,  AMFR|267 ,  SEZ6|124925 ,  DCUN1D2|55208 ,  PROZ|8858 ,  ...

  • 1 gene correlated to 'LYMPH.NODE.METASTASIS'.

    • AKR1D1|6718

  • No genes correlated to 'KARNOFSKY.PERFORMANCE.SCORE', 'RADIATIONS.RADIATION.REGIMENINDICATION', 'NUMBERPACKYEARSSMOKED', 'COMPLETENESS.OF.RESECTION', 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=6 shorter survival N=3 longer survival N=3
AGE Spearman correlation test N=3 older N=1 younger N=2
GENDER t test N=85 male N=29 female N=56
KARNOFSKY PERFORMANCE SCORE Spearman correlation test   N=0        
HISTOLOGICAL TYPE ANOVA test N=30        
RADIATIONS RADIATION REGIMENINDICATION t test   N=0        
NUMBERPACKYEARSSMOKED Spearman correlation test   N=0        
YEAROFTOBACCOSMOKINGONSET Spearman correlation test N=2 higher yearoftobaccosmokingonset N=1 lower yearoftobaccosmokingonset N=1
DISTANT METASTASIS ANOVA test N=53        
LYMPH NODE METASTASIS ANOVA test N=1        
COMPLETENESS OF RESECTION ANOVA test   N=0        
NEOPLASM DISEASESTAGE ANOVA test   N=0        
Clinical variable #1: 'Time to Death'

6 genes related to 'Time to Death'.

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

Time to Death Duration (Months) 0-224 (median=9.4)
  censored N = 236
  death N = 83
     
  Significant markers N = 6
  associated with shorter survival 3
  associated with longer survival 3
List of 6 genes significantly associated with 'Time to Death' by Cox regression test

Table S2.  Get Full Table List of 6 genes significantly associated with 'Time to Death' by Cox regression test

HazardRatio Wald_P Q C_index
ESYT3|83850 0.72 1.342e-07 0.0025 0.368
UCN2|90226 1.36 3.136e-07 0.0057 0.638
PPP1R3G|648791 1.54 5.393e-07 0.0099 0.66
B3GNT8|374907 0.71 9.262e-07 0.017 0.334
LOC645166|645166 1.5 1.473e-06 0.027 0.652
MYLIP|29116 0.51 1.735e-06 0.032 0.354

Figure S1.  Get High-res Image As an example, this figure shows the association of ESYT3|83850 to 'Time to Death'. four curves present the cumulative survival rates of 4 quartile subsets of patients. P value = 1.34e-07 with univariate Cox regression analysis using continuous log-2 expression values.

Clinical variable #2: 'AGE'

3 genes related to 'AGE'.

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

AGE Mean (SD) 65.2 (9.8)
  Significant markers N = 3
  pos. correlated 1
  neg. correlated 2
List of 3 genes significantly correlated to 'AGE' by Spearman correlation test

Table S4.  Get Full Table List of 3 genes significantly correlated to 'AGE' by Spearman correlation test

SpearmanCorr corrP Q
HSD17B2|3294 0.2704 1.068e-06 0.0196
GPR15|2838 -0.2676 2.494e-06 0.0457
AHRR|57491 -0.2582 2.67e-06 0.0489

Figure S2.  Get High-res Image As an example, this figure shows the association of HSD17B2|3294 to 'AGE'. P value = 1.07e-06 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #3: 'GENDER'

85 genes related to 'GENDER'.

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

GENDER Labels N
  FEMALE 191
  MALE 163
     
  Significant markers N = 85
  Higher in MALE 29
  Higher in FEMALE 56
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
PRKY|5616 45.81 3.572e-142 6.54e-138 0.9994
ZFY|7544 53.94 1.054e-117 1.93e-113 0.998
RPS4Y1|6192 49.02 1.536e-97 2.81e-93 0.9967
XIST|7503 -36.21 1.936e-86 3.54e-82 0.9809
DDX3Y|8653 46.36 2.005e-66 3.67e-62 0.9976
KDM5D|8284 39.96 2.039e-51 3.73e-47 0.9984
NLGN4Y|22829 27.19 2.454e-50 4.49e-46 0.9914
USP9Y|8287 39.66 1.149e-48 2.1e-44 0.9996
TSIX|9383 -18.52 4.287e-36 7.84e-32 0.9721
UTY|7404 27.19 4.833e-26 8.84e-22 0.9959

Figure S3.  Get High-res Image As an example, this figure shows the association of PRKY|5616 to 'GENDER'. P value = 3.57e-142 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) 75.86 (32)
  Significant markers N = 0
Clinical variable #5: 'HISTOLOGICAL.TYPE'

30 genes related to 'HISTOLOGICAL.TYPE'.

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

HISTOLOGICAL.TYPE Labels N
  LUNG ACINAR ADENOCARCINOMA 10
  LUNG ADENOCARCINOMA MIXED SUBTYPE 75
  LUNG ADENOCARCINOMA- NOT OTHERWISE SPECIFIED (NOS) 214
  LUNG BRONCHIOLOALVEOLAR CARCINOMA MUCINOUS 4
  LUNG BRONCHIOLOALVEOLAR CARCINOMA NONMUCINOUS 17
  LUNG CLEAR CELL ADENOCARCINOMA 2
  LUNG MICROPAPILLARY ADENOCARCINOMA 3
  LUNG MUCINOUS ADENOCARCINOMA 2
  LUNG PAPILLARY ADENOCARCINOMA 17
  LUNG SOLID PATTERN PREDOMINANT ADENOCARCINOMA 3
  MUCINOUS (COLLOID) CARCINOMA 7
     
  Significant markers N = 30
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
CREB3L3|84699 7.21e-12 1.32e-07
A4GNT|51146 1.532e-11 2.81e-07
REG4|83998 2.013e-10 3.68e-06
MIA|8190 3.384e-09 6.19e-05
CRH|1392 4.05e-09 7.41e-05
ELOVL5|60481 5.324e-09 9.75e-05
DPCR1|135656 7.733e-09 0.000142
FER1L6|654463 9.555e-09 0.000175
DNAH14|127602 2.68e-08 0.000491
LRRC66|339977 3.51e-08 0.000642

Figure S4.  Get High-res Image As an example, this figure shows the association of CREB3L3|84699 to 'HISTOLOGICAL.TYPE'. P value = 7.21e-12 with ANOVA analysis.

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

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

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

RADIATIONS.RADIATION.REGIMENINDICATION Labels N
  NO 17
  YES 337
     
  Significant markers N = 0
Clinical variable #7: 'NUMBERPACKYEARSSMOKED'

No gene related to 'NUMBERPACKYEARSSMOKED'.

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

NUMBERPACKYEARSSMOKED Mean (SD) 41.04 (27)
  Significant markers N = 0
Clinical variable #8: 'YEAROFTOBACCOSMOKINGONSET'

2 genes related to 'YEAROFTOBACCOSMOKINGONSET'.

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

YEAROFTOBACCOSMOKINGONSET Mean (SD) 1965 (13)
  Significant markers N = 2
  pos. correlated 1
  neg. correlated 1
List of 2 genes significantly correlated to 'YEAROFTOBACCOSMOKINGONSET' by Spearman correlation test

Table S13.  Get Full Table List of 2 genes significantly correlated to 'YEAROFTOBACCOSMOKINGONSET' by Spearman correlation test

SpearmanCorr corrP Q
GPR15|2838 0.365 7.932e-07 0.0145
ENTPD3|956 -0.3493 1.097e-06 0.0201

Figure S5.  Get High-res Image As an example, this figure shows the association of GPR15|2838 to 'YEAROFTOBACCOSMOKINGONSET'. P value = 7.93e-07 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #9: 'DISTANT.METASTASIS'

53 genes related to 'DISTANT.METASTASIS'.

Table S14.  Basic characteristics of clinical feature: 'DISTANT.METASTASIS'

DISTANT.METASTASIS Labels N
  M0 242
  M1 17
  M1A 1
  M1B 3
  MX 87
     
  Significant markers N = 53
List of top 10 genes differentially expressed by 'DISTANT.METASTASIS'

Table S15.  Get Full Table List of top 10 genes differentially expressed by 'DISTANT.METASTASIS'

ANOVA_P Q
CUL4A|8451 5.538e-11 1.01e-06
AMFR|267 1.429e-09 2.62e-05
SEZ6|124925 3.019e-09 5.53e-05
DCUN1D2|55208 3.594e-09 6.58e-05
PROZ|8858 4.698e-09 8.6e-05
MGMT|4255 6.505e-09 0.000119
SLC35F2|54733 6.883e-09 0.000126
MLL5|55904 1.02e-08 0.000187
C3ORF42|84657 4.222e-08 0.000773
TMCO3|55002 4.42e-08 0.000809

Figure S6.  Get High-res Image As an example, this figure shows the association of CUL4A|8451 to 'DISTANT.METASTASIS'. P value = 5.54e-11 with ANOVA analysis.

Clinical variable #10: 'LYMPH.NODE.METASTASIS'

One gene related to 'LYMPH.NODE.METASTASIS'.

Table S16.  Basic characteristics of clinical feature: 'LYMPH.NODE.METASTASIS'

LYMPH.NODE.METASTASIS Labels N
  N0 218
  N1 71
  N2 55
  N3 1
  NX 7
     
  Significant markers N = 1
List of one gene differentially expressed by 'LYMPH.NODE.METASTASIS'

Table S17.  Get Full Table List of one gene differentially expressed by 'LYMPH.NODE.METASTASIS'

ANOVA_P Q
AKR1D1|6718 1.059e-08 0.000194

Figure S7.  Get High-res Image As an example, this figure shows the association of AKR1D1|6718 to 'LYMPH.NODE.METASTASIS'. P value = 1.06e-08 with ANOVA analysis.

Clinical variable #11: 'COMPLETENESS.OF.RESECTION'

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

Table S18.  Basic characteristics of clinical feature: 'COMPLETENESS.OF.RESECTION'

COMPLETENESS.OF.RESECTION Labels N
  R0 213
  R1 9
  R2 4
  RX 12
     
  Significant markers N = 0
Clinical variable #12: 'NEOPLASM.DISEASESTAGE'

No gene related to 'NEOPLASM.DISEASESTAGE'.

Table S19.  Basic characteristics of clinical feature: 'NEOPLASM.DISEASESTAGE'

NEOPLASM.DISEASESTAGE Labels N
  STAGE I 2
  STAGE IA 82
  STAGE IB 103
  STAGE IIA 28
  STAGE IIB 51
  STAGE IIIA 55
  STAGE IIIB 10
  STAGE IV 21
     
  Significant markers N = 0
Methods & Data
Input

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

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

  • Number of patients = 354

  • Number of genes = 18310

  • Number of clinical features = 12

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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