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 18313 genes and 13 clinical features across 435 samples, statistically thresholded by Q value < 0.05, 11 clinical features related to at least one genes.

  • 9 genes correlated to 'Time to Death'.

    • MYLIP|29116 ,  ESYT3|83850 ,  PPP1R3G|648791 ,  VEGFC|7424 ,  FAM117A|81558 ,  ...

  • 19 genes correlated to 'AGE'.

    • AHRR|57491 ,  GPR15|2838 ,  C11ORF84|144097 ,  CYP1A1|1543 ,  PLA1A|51365 ,  ...

  • 2 genes correlated to 'NEOPLASM.DISEASESTAGE'.

    • FAM117A|81558 ,  ZNF540|163255

  • 45 genes correlated to 'PATHOLOGY.T.STAGE'.

    • C14ORF139|79686 ,  ST8SIA1|6489 ,  RASGRP2|10235 ,  FAM125B|89853 ,  PPP1R16B|26051 ,  ...

  • 14 genes correlated to 'PATHOLOGY.N.STAGE'.

    • DAPK2|23604 ,  LRRC37A2|474170 ,  ZNF483|158399 ,  RCOR3|55758 ,  DBH|1621 ,  ...

  • 56 genes correlated to 'PATHOLOGY.M.STAGE'.

    • CUL4A|8451 ,  AMFR|267 ,  DCUN1D2|55208 ,  SLC35F2|54733 ,  PROZ|8858 ,  ...

  • 114 genes correlated to 'GENDER'.

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

  • 43 genes correlated to 'HISTOLOGICAL.TYPE'.

    • CREB3L3|84699 ,  REG4|83998 ,  A4GNT|51146 ,  MIA|8190 ,  DPCR1|135656 ,  ...

  • 1 gene correlated to 'RADIATIONS.RADIATION.REGIMENINDICATION'.

    • PGAM2|5224

  • 3 genes correlated to 'YEAROFTOBACCOSMOKINGONSET'.

    • GPR15|2838 ,  HIST1H4E|8367 ,  HIST1H2BG|8339

  • 1 gene correlated to 'COMPLETENESS.OF.RESECTION'.

    • PAX2|5076

  • No genes correlated to 'KARNOFSKY.PERFORMANCE.SCORE', and 'NUMBERPACKYEARSSMOKED'.

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=9 shorter survival N=6 longer survival N=3
AGE Spearman correlation test N=19 older N=11 younger N=8
NEOPLASM DISEASESTAGE ANOVA test N=2        
PATHOLOGY T STAGE Spearman correlation test N=45 higher stage N=2 lower stage N=43
PATHOLOGY N STAGE Spearman correlation test N=14 higher stage N=2 lower stage N=12
PATHOLOGY M STAGE ANOVA test N=56        
GENDER t test N=114 male N=33 female N=81
KARNOFSKY PERFORMANCE SCORE Spearman correlation test   N=0        
HISTOLOGICAL TYPE ANOVA test N=43        
RADIATIONS RADIATION REGIMENINDICATION t test N=1 yes N=1 no N=0
NUMBERPACKYEARSSMOKED Spearman correlation test   N=0        
YEAROFTOBACCOSMOKINGONSET Spearman correlation test N=3 higher yearoftobaccosmokingonset N=3 lower yearoftobaccosmokingonset N=0
COMPLETENESS OF RESECTION ANOVA test N=1        
Clinical variable #1: 'Time to Death'

9 genes related to 'Time to Death'.

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

Time to Death Duration (Months) 0-224 (median=12.2)
  censored N = 292
  death N = 110
     
  Significant markers N = 9
  associated with shorter survival 6
  associated with longer survival 3
List of 9 genes significantly associated with 'Time to Death' by Cox regression test

Table S2.  Get Full Table List of 9 genes significantly associated with 'Time to Death' by Cox regression test

HazardRatio Wald_P Q C_index
MYLIP|29116 0.51 5.158e-08 0.00094 0.339
ESYT3|83850 0.77 5.709e-07 0.01 0.368
PPP1R3G|648791 1.46 7.181e-07 0.013 0.652
VEGFC|7424 1.45 8.347e-07 0.015 0.626
FAM117A|81558 0.53 1.109e-06 0.02 0.361
KRT6A|3853 1.13 1.296e-06 0.024 0.665
FUT4|2526 1.74 1.7e-06 0.031 0.643
DKK1|22943 1.15 1.781e-06 0.033 0.691
KRT6B|3854 1.15 2.175e-06 0.04 0.669

Figure S1.  Get High-res Image As an example, this figure shows the association of MYLIP|29116 to 'Time to Death'. four curves present the cumulative survival rates of 4 quartile subsets of patients. P value = 5.16e-08 with univariate Cox regression analysis using continuous log-2 expression values.

Clinical variable #2: 'AGE'

19 genes related to 'AGE'.

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

AGE Mean (SD) 65.39 (9.8)
  Significant markers N = 19
  pos. correlated 11
  neg. correlated 8
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
AHRR|57491 -0.2788 1.248e-08 0.000229
GPR15|2838 -0.2752 5.362e-08 0.000982
C11ORF84|144097 -0.2544 2.18e-07 0.00399
CYP1A1|1543 -0.3088 2.756e-07 0.00505
PLA1A|51365 0.2475 4.732e-07 0.00866
METTL7B|196410 0.2442 6.756e-07 0.0124
MAT2B|27430 0.2439 6.962e-07 0.0127
CCNG1|900 0.2427 7.912e-07 0.0145
PYCR1|5831 -0.2424 8.17e-07 0.015
TMEM37|140738 0.2409 9.655e-07 0.0177

Figure S2.  Get High-res Image As an example, this figure shows the association of AHRR|57491 to 'AGE'. P value = 1.25e-08 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #3: 'NEOPLASM.DISEASESTAGE'

2 genes related to 'NEOPLASM.DISEASESTAGE'.

Table S5.  Basic characteristics of clinical feature: 'NEOPLASM.DISEASESTAGE'

NEOPLASM.DISEASESTAGE Labels N
  STAGE I 3
  STAGE IA 107
  STAGE IB 128
  STAGE IIA 39
  STAGE IIB 61
  STAGE IIIA 63
  STAGE IIIB 11
  STAGE IV 22
     
  Significant markers N = 2
List of 2 genes differentially expressed by 'NEOPLASM.DISEASESTAGE'

Table S6.  Get Full Table List of 2 genes differentially expressed by 'NEOPLASM.DISEASESTAGE'

ANOVA_P Q
FAM117A|81558 2.286e-07 0.00419
ZNF540|163255 3.29e-07 0.00602

Figure S3.  Get High-res Image As an example, this figure shows the association of FAM117A|81558 to 'NEOPLASM.DISEASESTAGE'. P value = 2.29e-07 with ANOVA analysis.

Clinical variable #4: 'PATHOLOGY.T.STAGE'

45 genes related to 'PATHOLOGY.T.STAGE'.

Table S7.  Basic characteristics of clinical feature: 'PATHOLOGY.T.STAGE'

PATHOLOGY.T.STAGE Mean (SD) 1.86 (0.74)
  N
  1 134
  2 243
  3 38
  4 18
     
  Significant markers N = 45
  pos. correlated 2
  neg. correlated 43
List of top 10 genes significantly correlated to 'PATHOLOGY.T.STAGE' by Spearman correlation test

Table S8.  Get Full Table List of top 10 genes significantly correlated to 'PATHOLOGY.T.STAGE' by Spearman correlation test

SpearmanCorr corrP Q
C14ORF139|79686 -0.277 4.537e-09 8.31e-05
ST8SIA1|6489 -0.2613 3.414e-08 0.000625
RASGRP2|10235 -0.2597 4.179e-08 0.000765
FAM125B|89853 -0.2548 7.639e-08 0.0014
PPP1R16B|26051 -0.2492 1.495e-07 0.00274
MAL|4118 -0.2478 1.762e-07 0.00323
GP1BA|2811 -0.2504 1.816e-07 0.00332
CCL19|6363 -0.2468 2.044e-07 0.00374
MAP4K1|11184 -0.246 2.179e-07 0.00399
MS4A1|931 -0.2447 2.595e-07 0.00475

Figure S4.  Get High-res Image As an example, this figure shows the association of C14ORF139|79686 to 'PATHOLOGY.T.STAGE'. P value = 4.54e-09 with Spearman correlation analysis.

Clinical variable #5: 'PATHOLOGY.N.STAGE'

14 genes related to 'PATHOLOGY.N.STAGE'.

Table S9.  Basic characteristics of clinical feature: 'PATHOLOGY.N.STAGE'

PATHOLOGY.N.STAGE Mean (SD) 0.52 (0.77)
  N
  0 275
  1 83
  2 65
  3 2
     
  Significant markers N = 14
  pos. correlated 2
  neg. correlated 12
List of top 10 genes significantly correlated to 'PATHOLOGY.N.STAGE' by Spearman correlation test

Table S10.  Get Full Table List of top 10 genes significantly correlated to 'PATHOLOGY.N.STAGE' by Spearman correlation test

SpearmanCorr corrP Q
DAPK2|23604 -0.2531 1.238e-07 0.00227
LRRC37A2|474170 -0.2484 2.13e-07 0.0039
ZNF483|158399 -0.2471 2.479e-07 0.00454
RCOR3|55758 -0.2464 2.694e-07 0.00493
DBH|1621 -0.2436 4.937e-07 0.00904
LOC729020|729020 0.2404 5.309e-07 0.00972
ARID4A|5926 -0.2381 6.832e-07 0.0125
MASP2|10747 -0.2383 6.896e-07 0.0126
EPM2AIP1|9852 -0.2322 1.304e-06 0.0239
ACSS1|84532 -0.2299 1.67e-06 0.0306

Figure S5.  Get High-res Image As an example, this figure shows the association of DAPK2|23604 to 'PATHOLOGY.N.STAGE'. P value = 1.24e-07 with Spearman correlation analysis.

Clinical variable #6: 'PATHOLOGY.M.STAGE'

56 genes related to 'PATHOLOGY.M.STAGE'.

Table S11.  Basic characteristics of clinical feature: 'PATHOLOGY.M.STAGE'

PATHOLOGY.M.STAGE Labels N
  M0 298
  M1 18
  M1A 1
  M1B 3
  MX 111
     
  Significant markers N = 56
List of top 10 genes differentially expressed by 'PATHOLOGY.M.STAGE'

Table S12.  Get Full Table List of top 10 genes differentially expressed by 'PATHOLOGY.M.STAGE'

ANOVA_P Q
CUL4A|8451 4.194e-12 7.68e-08
AMFR|267 1.316e-09 2.41e-05
DCUN1D2|55208 1.708e-09 3.13e-05
SLC35F2|54733 1.769e-09 3.24e-05
PROZ|8858 1.338e-08 0.000245
TMCO3|55002 1.382e-08 0.000253
LAMP1|3916 2.477e-08 0.000453
SEZ6|124925 2.945e-08 0.000539
TFDP1|7027 3.855e-08 0.000706
ZNF37B|100129482 5.273e-08 0.000965

Figure S6.  Get High-res Image As an example, this figure shows the association of CUL4A|8451 to 'PATHOLOGY.M.STAGE'. P value = 4.19e-12 with ANOVA analysis.

Clinical variable #7: 'GENDER'

114 genes related to 'GENDER'.

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

GENDER Labels N
  FEMALE 234
  MALE 201
     
  Significant markers N = 114
  Higher in MALE 33
  Higher in FEMALE 81
List of top 10 genes differentially expressed by 'GENDER'

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

T(pos if higher in 'MALE') ttestP Q AUC
PRKY|5616 51.09 1.289e-174 2.36e-170 0.9996
ZFY|7544 61.41 7.313e-153 1.34e-148 0.9982
RPS4Y1|6192 57.25 6.989e-133 1.28e-128 0.9973
XIST|7503 -40.21 9.197e-110 1.68e-105 0.9788
DDX3Y|8653 56.16 2.892e-95 5.29e-91 0.998
USP9Y|8287 50.47 1.148e-81 2.1e-77 0.9997
KDM5D|8284 51.1 1.644e-81 3.01e-77 0.9991
NLGN4Y|22829 30.26 6.903e-61 1.26e-56 0.9918
UTY|7404 36.89 1.02e-43 1.87e-39 0.997
TSIX|9383 -18.9 1.828e-41 3.34e-37 0.9575

Figure S7.  Get High-res Image As an example, this figure shows the association of PRKY|5616 to 'GENDER'. P value = 1.29e-174 with T-test analysis.

Clinical variable #8: 'KARNOFSKY.PERFORMANCE.SCORE'

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

Table S15.  Basic characteristics of clinical feature: 'KARNOFSKY.PERFORMANCE.SCORE'

KARNOFSKY.PERFORMANCE.SCORE Mean (SD) 83.97 (23)
  Significant markers N = 0
Clinical variable #9: 'HISTOLOGICAL.TYPE'

43 genes related to 'HISTOLOGICAL.TYPE'.

Table S16.  Basic characteristics of clinical feature: 'HISTOLOGICAL.TYPE'

HISTOLOGICAL.TYPE Labels N
  LUNG ACINAR ADENOCARCINOMA 13
  LUNG ADENOCARCINOMA MIXED SUBTYPE 88
  LUNG ADENOCARCINOMA- NOT OTHERWISE SPECIFIED (NOS) 277
  LUNG BRONCHIOLOALVEOLAR CARCINOMA MUCINOUS 4
  LUNG BRONCHIOLOALVEOLAR CARCINOMA NONMUCINOUS 18
  LUNG CLEAR CELL ADENOCARCINOMA 2
  LUNG MICROPAPILLARY ADENOCARCINOMA 3
  LUNG MUCINOUS ADENOCARCINOMA 2
  LUNG PAPILLARY ADENOCARCINOMA 17
  LUNG SOLID PATTERN PREDOMINANT ADENOCARCINOMA 4
  MUCINOUS (COLLOID) CARCINOMA 7
     
  Significant markers N = 43
List of top 10 genes differentially expressed by 'HISTOLOGICAL.TYPE'

Table S17.  Get Full Table List of top 10 genes differentially expressed by 'HISTOLOGICAL.TYPE'

ANOVA_P Q
CREB3L3|84699 4.283e-12 7.84e-08
REG4|83998 7.231e-12 1.32e-07
A4GNT|51146 1.568e-11 2.87e-07
MIA|8190 1.001e-09 1.83e-05
DPCR1|135656 3.101e-09 5.68e-05
DNAH14|127602 1.285e-08 0.000235
FER1L6|654463 1.285e-08 0.000235
CA2|760 1.791e-08 0.000328
BTNL8|79908 2.162e-08 0.000396
SOX10|6663 2.648e-08 0.000485

Figure S8.  Get High-res Image As an example, this figure shows the association of CREB3L3|84699 to 'HISTOLOGICAL.TYPE'. P value = 4.28e-12 with ANOVA analysis.

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

One gene related to 'RADIATIONS.RADIATION.REGIMENINDICATION'.

Table S18.  Basic characteristics of clinical feature: 'RADIATIONS.RADIATION.REGIMENINDICATION'

RADIATIONS.RADIATION.REGIMENINDICATION Labels N
  NO 20
  YES 415
     
  Significant markers N = 1
  Higher in YES 1
  Higher in NO 0
List of one gene differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

Table S19.  Get Full Table List of one gene differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

T(pos if higher in 'YES') ttestP Q AUC
PGAM2|5224 6.73 2.927e-07 0.00536 0.7651

Figure S9.  Get High-res Image As an example, this figure shows the association of PGAM2|5224 to 'RADIATIONS.RADIATION.REGIMENINDICATION'. P value = 2.93e-07 with T-test analysis.

Clinical variable #11: 'NUMBERPACKYEARSSMOKED'

No gene related to 'NUMBERPACKYEARSSMOKED'.

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

NUMBERPACKYEARSSMOKED Mean (SD) 42.13 (28)
  Significant markers N = 0
Clinical variable #12: 'YEAROFTOBACCOSMOKINGONSET'

3 genes related to 'YEAROFTOBACCOSMOKINGONSET'.

Table S21.  Basic characteristics of clinical feature: 'YEAROFTOBACCOSMOKINGONSET'

YEAROFTOBACCOSMOKINGONSET Mean (SD) 1964.97 (12)
  Significant markers N = 3
  pos. correlated 3
  neg. correlated 0
List of 3 genes significantly correlated to 'YEAROFTOBACCOSMOKINGONSET' by Spearman correlation test

Table S22.  Get Full Table List of 3 genes significantly correlated to 'YEAROFTOBACCOSMOKINGONSET' by Spearman correlation test

SpearmanCorr corrP Q
GPR15|2838 0.3183 1.284e-06 0.0235
HIST1H4E|8367 0.3363 2.374e-06 0.0435
HIST1H2BG|8339 0.3084 2.415e-06 0.0442

Figure S10.  Get High-res Image As an example, this figure shows the association of GPR15|2838 to 'YEAROFTOBACCOSMOKINGONSET'. P value = 1.28e-06 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #13: 'COMPLETENESS.OF.RESECTION'

One gene related to 'COMPLETENESS.OF.RESECTION'.

Table S23.  Basic characteristics of clinical feature: 'COMPLETENESS.OF.RESECTION'

COMPLETENESS.OF.RESECTION Labels N
  R0 297
  R1 10
  R2 4
  RX 15
     
  Significant markers N = 1
List of one gene differentially expressed by 'COMPLETENESS.OF.RESECTION'

Table S24.  Get Full Table List of one gene differentially expressed by 'COMPLETENESS.OF.RESECTION'

ANOVA_P Q
PAX2|5076 1.017e-06 0.0186

Figure S11.  Get High-res Image As an example, this figure shows the association of PAX2|5076 to 'COMPLETENESS.OF.RESECTION'. P value = 1.02e-06 with ANOVA analysis.

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 = 435

  • Number of genes = 18313

  • Number of clinical features = 13

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.

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)
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