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 18529 genes and 14 clinical features across 316 samples, statistically thresholded by Q value < 0.05, 9 clinical features related to at least one genes.

  • 4 genes correlated to 'AGE'.

    • PRSS12|8492 ,  GLB1L|79411 ,  SLC35D2|11046 ,  RHBDD1|84236

  • 30 genes correlated to 'GENDER'.

    • XIST|7503 ,  PRKY|5616 ,  ZFY|7544 ,  RPS4Y1|6192 ,  TSIX|9383 ,  ...

  • 38 genes correlated to 'HISTOLOGICAL.TYPE'.

    • SNIP1|79753 ,  SF3A3|10946 ,  PCMTD2|55251 ,  XIAP|331 ,  UTP11L|51118 ,  ...

  • 20 genes correlated to 'PATHOLOGY.T'.

    • GDF10|2662 ,  ADH1B|125 ,  CNR1|1268 ,  ATP1A2|477 ,  SFTPC|6440 ,  ...

  • 12 genes correlated to 'PATHOLOGICSPREAD(M)'.

    • DEDD|9191 ,  TMCO1|54499 ,  PEX19|5824 ,  SDHC|6391 ,  POU2F1|5451 ,  ...

  • 2 genes correlated to 'TUMOR.STAGE'.

    • TXNDC6|347736 ,  SLC6A13|6540

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

    • FLJ36000|284124 ,  MYT1L|23040 ,  RNF186|54546 ,  C7ORF34|135927 ,  PCDH11Y|83259 ,  ...

  • 1 gene correlated to 'YEAROFTOBACCOSMOKINGONSET'.

    • DUS1L|64118

  • 2 genes correlated to 'COMPLETENESS.OF.RESECTION'.

    • RNF113B|140432 ,  NARF|26502

  • No genes correlated to 'Time to Death', 'KARNOFSKY.PERFORMANCE.SCORE', 'PATHOLOGY.N', 'NUMBERPACKYEARSSMOKED', and 'TOBACCOSMOKINGHISTORYINDICATOR'.

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=4 older N=3 younger N=1
GENDER t test N=30 male N=11 female N=19
KARNOFSKY PERFORMANCE SCORE Spearman correlation test   N=0        
HISTOLOGICAL TYPE ANOVA test N=38        
PATHOLOGY T Spearman correlation test N=20 higher pT N=1 lower pT N=19
PATHOLOGY N Spearman correlation test   N=0        
PATHOLOGICSPREAD(M) ANOVA test N=12        
TUMOR STAGE Spearman correlation test N=2 higher stage N=0 lower stage N=2
RADIATIONS RADIATION REGIMENINDICATION t test N=6 yes N=6 no N=0
NUMBERPACKYEARSSMOKED Spearman correlation test   N=0        
TOBACCOSMOKINGHISTORYINDICATOR ANOVA test   N=0        
YEAROFTOBACCOSMOKINGONSET Spearman correlation test N=1 higher yearoftobaccosmokingonset N=1 lower yearoftobaccosmokingonset N=0
COMPLETENESS OF RESECTION ANOVA test 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) 0-173.8 (median=13.1)
  censored N = 182
  death N = 117
     
  Significant markers N = 0
Clinical variable #2: 'AGE'

4 genes related to 'AGE'.

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

AGE Mean (SD) 67.31 (8.6)
  Significant markers N = 4
  pos. correlated 3
  neg. correlated 1
List of 4 genes significantly correlated to 'AGE' by Spearman correlation test

Table S3.  Get Full Table List of 4 genes significantly correlated to 'AGE' by Spearman correlation test

SpearmanCorr corrP Q
PRSS12|8492 0.3516 2.305e-10 4.27e-06
GLB1L|79411 0.2715 1.323e-06 0.0245
SLC35D2|11046 -0.2689 1.677e-06 0.0311
RHBDD1|84236 0.2671 1.976e-06 0.0366

Figure S1.  Get High-res Image As an example, this figure shows the association of PRSS12|8492 to 'AGE'. P value = 2.3e-10 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #3: 'GENDER'

30 genes related to 'GENDER'.

Table S4.  Basic characteristics of clinical feature: 'GENDER'

GENDER Labels N
  FEMALE 80
  MALE 236
     
  Significant markers N = 30
  Higher in MALE 11
  Higher in FEMALE 19
List of top 10 genes differentially expressed by 'GENDER'

Table S5.  Get Full Table List of top 10 genes differentially expressed by 'GENDER'

T(pos if higher in 'MALE') ttestP Q AUC
XIST|7503 -32.41 1.183e-85 2.19e-81 0.9703
PRKY|5616 23.21 1.025e-47 1.9e-43 0.9786
ZFY|7544 28.69 9.98e-42 1.85e-37 0.9872
RPS4Y1|6192 29.06 1.677e-40 3.11e-36 0.987
TSIX|9383 -14.77 3.687e-32 6.83e-28 0.9363
DDX3Y|8653 22.08 1.49e-25 2.76e-21 0.9801
NLGN4Y|22829 17.24 5.791e-23 1.07e-18 0.9737
KDM5D|8284 16.66 7.972e-17 1.48e-12 0.9657
USP9Y|8287 14.16 6.485e-14 1.2e-09 0.9644
CYORF15A|246126 13.08 3.08e-12 5.7e-08 0.9607

Figure S2.  Get High-res Image As an example, this figure shows the association of XIST|7503 to 'GENDER'. P value = 1.18e-85 with T-test analysis.

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

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

Table S6.  Basic characteristics of clinical feature: 'KARNOFSKY.PERFORMANCE.SCORE'

KARNOFSKY.PERFORMANCE.SCORE Mean (SD) 27.36 (39)
  Significant markers N = 0
Clinical variable #5: 'HISTOLOGICAL.TYPE'

38 genes related to 'HISTOLOGICAL.TYPE'.

Table S7.  Basic characteristics of clinical feature: 'HISTOLOGICAL.TYPE'

HISTOLOGICAL.TYPE Labels N
  LUNG BASALOID SQUAMOUS CELL CARCINOMA 7
  LUNG PAPILLARY SQUAMOUS CELL CARCINOMA 1
  LUNG PAPILLARY SQUAMOUS CELL CARICNOMA 1
  LUNG SMALL CELL SQUAMOUS CELL CARCINOMA 1
  LUNG SQUAMOUS CELL CARCINOMA- NOT OTHERWISE SPECIFIED (NOS) 306
     
  Significant markers N = 38
List of top 10 genes differentially expressed by 'HISTOLOGICAL.TYPE'

Table S8.  Get Full Table List of top 10 genes differentially expressed by 'HISTOLOGICAL.TYPE'

ANOVA_P Q
SNIP1|79753 1.589e-23 2.94e-19
SF3A3|10946 3.752e-22 6.95e-18
PCMTD2|55251 2.118e-21 3.92e-17
XIAP|331 3.029e-19 5.61e-15
UTP11L|51118 3.302e-18 6.12e-14
GNL2|29889 1.68e-15 3.11e-11
INPP5B|3633 2.613e-15 4.84e-11
C1ORF109|54955 9.671e-15 1.79e-10
MEAF6|64769 5.153e-14 9.54e-10
MTMR10|54893 1.402e-13 2.6e-09

Figure S3.  Get High-res Image As an example, this figure shows the association of SNIP1|79753 to 'HISTOLOGICAL.TYPE'. P value = 1.59e-23 with ANOVA analysis.

Clinical variable #6: 'PATHOLOGY.T'

20 genes related to 'PATHOLOGY.T'.

Table S9.  Basic characteristics of clinical feature: 'PATHOLOGY.T'

PATHOLOGY.T Mean (SD) 1.97 (0.75)
  N
  T1 76
  T2 190
  T3 33
  T4 17
     
  Significant markers N = 20
  pos. correlated 1
  neg. correlated 19
List of top 10 genes significantly correlated to 'PATHOLOGY.T' by Spearman correlation test

Table S10.  Get Full Table List of top 10 genes significantly correlated to 'PATHOLOGY.T' by Spearman correlation test

SpearmanCorr corrP Q
GDF10|2662 -0.3048 5.043e-08 0.000934
ADH1B|125 -0.2938 1.309e-07 0.00242
CNR1|1268 -0.2926 1.347e-07 0.0025
ATP1A2|477 -0.2944 1.492e-07 0.00276
SFTPC|6440 -0.2888 1.897e-07 0.00351
GPR44|11251 -0.2846 2.674e-07 0.00495
AGER|177 -0.2843 2.736e-07 0.00507
AQP4|361 -0.2754 7.437e-07 0.0138
CACNA2D2|9254 -0.2729 8.401e-07 0.0156
MGC87042|256227 0.2722 8.98e-07 0.0166

Figure S4.  Get High-res Image As an example, this figure shows the association of GDF10|2662 to 'PATHOLOGY.T'. P value = 5.04e-08 with Spearman correlation analysis.

Clinical variable #7: 'PATHOLOGY.N'

No gene related to 'PATHOLOGY.N'.

Table S11.  Basic characteristics of clinical feature: 'PATHOLOGY.N'

PATHOLOGY.N Mean (SD) 0.49 (0.71)
  N
  N0 195
  N1 89
  N2 25
  N3 5
     
  Significant markers N = 0
Clinical variable #8: 'PATHOLOGICSPREAD(M)'

12 genes related to 'PATHOLOGICSPREAD(M)'.

Table S12.  Basic characteristics of clinical feature: 'PATHOLOGICSPREAD(M)'

PATHOLOGICSPREAD(M) Labels N
  M0 279
  M1 4
  MX 27
     
  Significant markers N = 12
List of top 10 genes differentially expressed by 'PATHOLOGICSPREAD(M)'

Table S13.  Get Full Table List of top 10 genes differentially expressed by 'PATHOLOGICSPREAD(M)'

ANOVA_P Q
DEDD|9191 1.517e-09 2.81e-05
TMCO1|54499 4.57e-09 8.47e-05
PEX19|5824 2.135e-08 0.000396
SDHC|6391 8.808e-08 0.00163
POU2F1|5451 1.223e-07 0.00227
PEX2|5828 1.303e-07 0.00241
B4GALT3|8703 2.082e-07 0.00386
TAC3|6866 4.458e-07 0.00826
TOMM40L|84134 6.131e-07 0.0114
IMPA1|3612 7.309e-07 0.0135

Figure S5.  Get High-res Image As an example, this figure shows the association of DEDD|9191 to 'PATHOLOGICSPREAD(M)'. P value = 1.52e-09 with ANOVA analysis.

Clinical variable #9: 'TUMOR.STAGE'

2 genes related to 'TUMOR.STAGE'.

Table S14.  Basic characteristics of clinical feature: 'TUMOR.STAGE'

TUMOR.STAGE Mean (SD) 1.7 (0.82)
  N
  Stage 1 161
  Stage 2 87
  Stage 3 60
  Stage 4 4
     
  Significant markers N = 2
  pos. correlated 0
  neg. correlated 2
List of 2 genes significantly correlated to 'TUMOR.STAGE' by Spearman correlation test

Table S15.  Get Full Table List of 2 genes significantly correlated to 'TUMOR.STAGE' by Spearman correlation test

SpearmanCorr corrP Q
TXNDC6|347736 -0.2766 9.229e-07 0.0171
SLC6A13|6540 -0.2757 2.6e-06 0.0482

Figure S6.  Get High-res Image As an example, this figure shows the association of TXNDC6|347736 to 'TUMOR.STAGE'. P value = 9.23e-07 with Spearman correlation analysis.

Clinical variable #10: 'RADIATIONS.RADIATION.REGIMENINDICATION'

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

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

RADIATIONS.RADIATION.REGIMENINDICATION Labels N
  NO 10
  YES 306
     
  Significant markers N = 6
  Higher in YES 6
  Higher in NO 0
List of 6 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

Table S17.  Get Full Table List of 6 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

T(pos if higher in 'YES') ttestP Q AUC
FLJ36000|284124 10.68 5.151e-10 9.51e-06 0.875
MYT1L|23040 6.79 6.431e-10 1.19e-05 0.7994
RNF186|54546 6.76 1.588e-09 2.93e-05 0.8038
C7ORF34|135927 7.41 1.406e-08 0.00026 0.7969
PCDH11Y|83259 9.09 5.662e-07 0.0105 0.896
GAGE12J|729396 7.58 6.66e-07 0.0123 0.7573

Figure S7.  Get High-res Image As an example, this figure shows the association of FLJ36000|284124 to 'RADIATIONS.RADIATION.REGIMENINDICATION'. P value = 5.15e-10 with T-test analysis.

Clinical variable #11: 'NUMBERPACKYEARSSMOKED'

No gene related to 'NUMBERPACKYEARSSMOKED'.

Table S18.  Basic characteristics of clinical feature: 'NUMBERPACKYEARSSMOKED'

NUMBERPACKYEARSSMOKED Mean (SD) 52.72 (33)
  Significant markers N = 0
Clinical variable #12: 'TOBACCOSMOKINGHISTORYINDICATOR'

No gene related to 'TOBACCOSMOKINGHISTORYINDICATOR'.

Table S19.  Basic characteristics of clinical feature: 'TOBACCOSMOKINGHISTORYINDICATOR'

TOBACCOSMOKINGHISTORYINDICATOR Labels N
  CURRENT REFORMED SMOKER FOR < OR = 15 YEARS 152
  CURRENT REFORMED SMOKER FOR > 15 YEARS 72
  CURRENT SMOKER 71
  LIFELONG NON-SMOKER 14
     
  Significant markers N = 0
Clinical variable #13: 'YEAROFTOBACCOSMOKINGONSET'

One gene related to 'YEAROFTOBACCOSMOKINGONSET'.

Table S20.  Basic characteristics of clinical feature: 'YEAROFTOBACCOSMOKINGONSET'

YEAROFTOBACCOSMOKINGONSET Mean (SD) 1958.81 (12)
  Significant markers N = 1
  pos. correlated 1
  neg. correlated 0
List of one gene significantly correlated to 'YEAROFTOBACCOSMOKINGONSET' by Spearman correlation test

Table S21.  Get Full Table List of one gene significantly correlated to 'YEAROFTOBACCOSMOKINGONSET' by Spearman correlation test

SpearmanCorr corrP Q
DUS1L|64118 0.3406 4.49e-07 0.00832

Figure S8.  Get High-res Image As an example, this figure shows the association of DUS1L|64118 to 'YEAROFTOBACCOSMOKINGONSET'. P value = 4.49e-07 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #14: 'COMPLETENESS.OF.RESECTION'

2 genes related to 'COMPLETENESS.OF.RESECTION'.

Table S22.  Basic characteristics of clinical feature: 'COMPLETENESS.OF.RESECTION'

COMPLETENESS.OF.RESECTION Labels N
  R0 250
  R1 6
  R2 4
  RX 16
     
  Significant markers N = 2
List of 2 genes differentially expressed by 'COMPLETENESS.OF.RESECTION'

Table S23.  Get Full Table List of 2 genes differentially expressed by 'COMPLETENESS.OF.RESECTION'

ANOVA_P Q
RNF113B|140432 6.64e-12 1.23e-07
NARF|26502 1.73e-06 0.0321

Figure S9.  Get High-res Image As an example, this figure shows the association of RNF113B|140432 to 'COMPLETENESS.OF.RESECTION'. P value = 6.64e-12 with ANOVA analysis.

Methods & Data
Input

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

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

  • Number of patients = 316

  • Number of genes = 18529

  • Number of clinical features = 14

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.

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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