Correlation between RPPA expression and clinical features
Overview
Introduction

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

Summary

Testing the association between 160 genes and 13 clinical features across 181 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 3 clinical features related to at least one genes.

  • 2 genes correlated to 'NEOPLASM.DISEASESTAGE'.

    • NA|ASNS-R-V ,  NA|PRAS40_PT246-R-V

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

    • NA|P70S6K-R-V ,  NA|ACC1-R-C ,  NA|CYCLIN_B1-R-V ,  NA|MAPK_PT202_Y204-R-V

  • 1 gene correlated to 'GENDER'.

    • NA|CLAUDIN-7-R-V

  • No genes correlated to 'Time to Death', 'AGE', 'PATHOLOGY.N.STAGE', 'PATHOLOGY.M.STAGE', 'KARNOFSKY.PERFORMANCE.SCORE', 'HISTOLOGICAL.TYPE', 'RADIATIONS.RADIATION.REGIMENINDICATION', 'NUMBERPACKYEARSSMOKED', 'COMPLETENESS.OF.RESECTION', and 'RACE'.

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
Time to Death Cox regression test   N=0        
AGE Spearman correlation test   N=0        
NEOPLASM DISEASESTAGE Kruskal-Wallis test N=2        
PATHOLOGY T STAGE Spearman correlation test N=4 higher stage N=3 lower stage N=1
PATHOLOGY N STAGE Spearman correlation test   N=0        
PATHOLOGY M STAGE Kruskal-Wallis test   N=0        
GENDER Wilcoxon test N=1 male N=1 female N=0
KARNOFSKY PERFORMANCE SCORE Spearman correlation test   N=0        
HISTOLOGICAL TYPE Kruskal-Wallis test   N=0        
RADIATIONS RADIATION REGIMENINDICATION Wilcoxon test   N=0        
NUMBERPACKYEARSSMOKED Spearman correlation test   N=0        
COMPLETENESS OF RESECTION Kruskal-Wallis test   N=0        
RACE Kruskal-Wallis test   N=0        
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 (Years) 2-2370 (median=741)
  censored N = 112
  death N = 43
     
  Significant markers N = 0
Clinical variable #2: 'AGE'

No gene related to 'AGE'.

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

AGE Mean (SD) 65.48 (9.6)
  Significant markers N = 0
Clinical variable #3: 'NEOPLASM.DISEASESTAGE'

2 genes related to 'NEOPLASM.DISEASESTAGE'.

Table S3.  Basic characteristics of clinical feature: 'NEOPLASM.DISEASESTAGE'

NEOPLASM.DISEASESTAGE Labels N
  STAGE I 1
  STAGE IA 41
  STAGE IB 52
  STAGE IIA 15
  STAGE IIB 25
  STAGE IIIA 33
  STAGE IIIB 7
  STAGE IV 7
     
  Significant markers N = 2
List of 2 genes differentially expressed by 'NEOPLASM.DISEASESTAGE'

Table S4.  Get Full Table List of 2 genes differentially expressed by 'NEOPLASM.DISEASESTAGE'

ANOVA_P Q
NA|ASNS-R-V 0.0004387 0.0702
NA|PRAS40_PT246-R-V 0.0006063 0.0964
Clinical variable #4: 'PATHOLOGY.T.STAGE'

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

Table S5.  Basic characteristics of clinical feature: 'PATHOLOGY.T.STAGE'

PATHOLOGY.T.STAGE Mean (SD) 1.94 (0.77)
  N
  1 47
  2 108
  3 13
  4 12
     
  Significant markers N = 4
  pos. correlated 3
  neg. correlated 1
List of 4 genes differentially expressed by 'PATHOLOGY.T.STAGE'

Table S6.  Get Full Table List of 4 genes significantly correlated to 'PATHOLOGY.T.STAGE' by Spearman correlation test

SpearmanCorr corrP Q
NA|P70S6K-R-V 0.2593 0.0004406 0.0705
NA|ACC1-R-C 0.2518 0.0006516 0.104
NA|CYCLIN_B1-R-V 0.2426 0.001035 0.164
NA|MAPK_PT202_Y204-R-V -0.2322 0.001706 0.268
Clinical variable #5: 'PATHOLOGY.N.STAGE'

No gene related to 'PATHOLOGY.N.STAGE'.

Table S7.  Basic characteristics of clinical feature: 'PATHOLOGY.N.STAGE'

PATHOLOGY.N.STAGE Mean (SD) 0.6 (0.82)
  N
  0 106
  1 34
  2 34
  3 1
     
  Significant markers N = 0
Clinical variable #6: 'PATHOLOGY.M.STAGE'

No gene related to 'PATHOLOGY.M.STAGE'.

Table S8.  Basic characteristics of clinical feature: 'PATHOLOGY.M.STAGE'

PATHOLOGY.M.STAGE Labels N
  M0 136
  M1 6
  MX 37
     
  Significant markers N = 0
Clinical variable #7: 'GENDER'

One gene related to 'GENDER'.

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

GENDER Labels N
  FEMALE 105
  MALE 76
     
  Significant markers N = 1
  Higher in MALE 1
  Higher in FEMALE 0
List of one gene differentially expressed by 'GENDER'

Table S10.  Get Full Table List of one gene differentially expressed by 'GENDER'. 0 significant gene(s) located in sex chromosomes is(are) filtered out.

W(pos if higher in 'MALE') wilcoxontestP Q AUC
NA|CLAUDIN-7-R-V 5477 1.93e-05 0.00309 0.6863
Clinical variable #8: 'KARNOFSKY.PERFORMANCE.SCORE'

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

Table S11.  Basic characteristics of clinical feature: 'KARNOFSKY.PERFORMANCE.SCORE'

KARNOFSKY.PERFORMANCE.SCORE Mean (SD) 60 (41)
  Significant markers N = 0
Clinical variable #9: 'HISTOLOGICAL.TYPE'

No gene related to 'HISTOLOGICAL.TYPE'.

Table S12.  Basic characteristics of clinical feature: 'HISTOLOGICAL.TYPE'

HISTOLOGICAL.TYPE Labels N
  LUNG ACINAR ADENOCARCINOMA 5
  LUNG ADENOCARCINOMA MIXED SUBTYPE 43
  LUNG ADENOCARCINOMA- NOT OTHERWISE SPECIFIED (NOS) 111
  LUNG BRONCHIOLOALVEOLAR CARCINOMA MUCINOUS 3
  LUNG BRONCHIOLOALVEOLAR CARCINOMA NONMUCINOUS 8
  LUNG MICROPAPILLARY ADENOCARCINOMA 2
  LUNG MUCINOUS ADENOCARCINOMA 1
  LUNG PAPILLARY ADENOCARCINOMA 5
  MUCINOUS (COLLOID) CARCINOMA 3
     
  Significant markers N = 0
Clinical variable #10: 'RADIATIONS.RADIATION.REGIMENINDICATION'

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

Table S13.  Basic characteristics of clinical feature: 'RADIATIONS.RADIATION.REGIMENINDICATION'

RADIATIONS.RADIATION.REGIMENINDICATION Labels N
  NO 12
  YES 169
     
  Significant markers N = 0
Clinical variable #11: 'NUMBERPACKYEARSSMOKED'

No gene related to 'NUMBERPACKYEARSSMOKED'.

Table S14.  Basic characteristics of clinical feature: 'NUMBERPACKYEARSSMOKED'

NUMBERPACKYEARSSMOKED Mean (SD) 41.82 (27)
  Significant markers N = 0
Clinical variable #12: 'COMPLETENESS.OF.RESECTION'

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

Table S15.  Basic characteristics of clinical feature: 'COMPLETENESS.OF.RESECTION'

COMPLETENESS.OF.RESECTION Labels N
  R0 119
  R1 8
  R2 1
  RX 5
     
  Significant markers N = 0
Clinical variable #13: 'RACE'

No gene related to 'RACE'.

Table S16.  Basic characteristics of clinical feature: 'RACE'

RACE Labels N
  ASIAN 2
  BLACK OR AFRICAN AMERICAN 6
  WHITE 141
     
  Significant markers N = 0
Methods & Data
Input

  • Expresson data file = LUAD-TP.rppa.txt

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

  • Number of patients = 181

  • Number of genes = 160

  • 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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