Correlation between mutation rate and clinical features
Overview
Introduction

This pipeline uses various statistical tests to identify selected clinical features related to mutation rate.

Summary

Testing the association between 2 variables and 15 clinical features across 136 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 2 clinical features related to at least one variables.

  • 1 variable correlated to 'NEOPLASM_DISEASESTAGE'.

    • MUTATIONRATE_SILENT

  • 1 variable correlated to 'PATHOLOGY_T_STAGE'.

    • MUTATIONRATE_NONSYNONYMOUS

  • No variables correlated to 'DAYS_TO_DEATH_OR_LAST_FUP', 'AGE', 'AGE_mutation.rate', 'PATHOLOGY_N_STAGE', 'PATHOLOGY_M_STAGE', 'GENDER', 'HISTOLOGICAL_TYPE', 'NUMBER_PACK_YEARS_SMOKED', 'YEAR_OF_TOBACCO_SMOKING_ONSET', 'COMPLETENESS_OF_RESECTION', 'NUMBER_OF_LYMPH_NODES', 'RACE', and '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 variables that are significantly associated with each clinical feature at P value < 0.05 and Q value < 0.3.

Clinical feature Statistical test Significant variables Associated with                 Associated with
DAYS_TO_DEATH_OR_LAST_FUP Cox regression test   N=0        
AGE Spearman correlation test   N=0        
AGE Linear Regression Analysis   N=0        
NEOPLASM_DISEASESTAGE Kruskal-Wallis test N=1        
PATHOLOGY_T_STAGE Spearman correlation test N=1 higher stage N=1 lower stage N=0
PATHOLOGY_N_STAGE Wilcoxon test   N=0        
PATHOLOGY_M_STAGE Wilcoxon test   N=0        
GENDER Wilcoxon test   N=0        
HISTOLOGICAL_TYPE Kruskal-Wallis test   N=0        
NUMBER_PACK_YEARS_SMOKED Spearman correlation test   N=0        
YEAR_OF_TOBACCO_SMOKING_ONSET Spearman correlation test   N=0        
COMPLETENESS_OF_RESECTION Kruskal-Wallis test   N=0        
NUMBER_OF_LYMPH_NODES Spearman correlation test   N=0        
RACE Kruskal-Wallis test   N=0        
ETHNICITY Wilcoxon test   N=0        
Clinical variable #1: 'DAYS_TO_DEATH_OR_LAST_FUP'

No variable 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) 0.1-75.1 (median=13.8)
  censored N = 64
  death N = 71
     
  Significant variables N = 0
Clinical variable #2: 'AGE'

No variable related to 'AGE'.

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

AGE Mean (SD) 64.88 (11)
  Significant variables N = 0
Clinical variable #3: 'AGE'

No variable related to 'AGE'.

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

AGE Mean (SD) 64.88 (11)
  Significant variables N = 0
Clinical variable #4: 'NEOPLASM_DISEASESTAGE'

One variable related to 'NEOPLASM_DISEASESTAGE'.

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

NEOPLASM_DISEASESTAGE Labels N
  STAGE IA 4
  STAGE IB 6
  STAGE IIA 20
  STAGE IIB 99
  STAGE III 4
  STAGE IV 3
     
  Significant variables N = 1
List of one variable associated with 'NEOPLASM_DISEASESTAGE'

Table S5.  Get Full Table List of one variable differentially expressed by 'NEOPLASM_DISEASESTAGE'

kruskal_wallis_P Q
MUTATIONRATE_SILENT 0.04229 0.0846
Clinical variable #5: 'PATHOLOGY_T_STAGE'

One variable related to 'PATHOLOGY_T_STAGE'.

Table S6.  Basic characteristics of clinical feature: 'PATHOLOGY_T_STAGE'

PATHOLOGY_T_STAGE Mean (SD) 2.85 (0.49)
  N
  T1 5
  T2 13
  T3 115
  T4 3
     
  Significant variables N = 1
  pos. correlated 1
  neg. correlated 0
List of one variable associated with 'PATHOLOGY_T_STAGE'

Table S7.  Get Full Table List of one variable significantly correlated to 'PATHOLOGY_T_STAGE' by Spearman correlation test

SpearmanCorr corrP Q
MUTATIONRATE_NONSYNONYMOUS 0.213 0.0128 0.0256
Clinical variable #6: 'PATHOLOGY_N_STAGE'

No variable related to 'PATHOLOGY_N_STAGE'.

Table S8.  Basic characteristics of clinical feature: 'PATHOLOGY_N_STAGE'

PATHOLOGY_N_STAGE Labels N
  N0 32
  N1 104
     
  Significant variables N = 0
Clinical variable #7: 'PATHOLOGY_M_STAGE'

No variable related to 'PATHOLOGY_M_STAGE'.

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

PATHOLOGY_M_STAGE Labels N
  class0 62
  class1 3
     
  Significant variables N = 0
Clinical variable #8: 'GENDER'

No variable related to 'GENDER'.

Table S10.  Basic characteristics of clinical feature: 'GENDER'

GENDER Labels N
  FEMALE 62
  MALE 74
     
  Significant variables N = 0
Clinical variable #9: 'HISTOLOGICAL_TYPE'

No variable related to 'HISTOLOGICAL_TYPE'.

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

HISTOLOGICAL_TYPE Labels N
  PANCREAS-ADENOCARCINOMA DUCTAL TYPE 122
  PANCREAS-ADENOCARCINOMA-OTHER SUBTYPE 11
  PANCREAS-COLLOID (MUCINOUS NON-CYSTIC) CARCINOMA 2
     
  Significant variables N = 0
Clinical variable #10: 'NUMBER_PACK_YEARS_SMOKED'

No variable related to 'NUMBER_PACK_YEARS_SMOKED'.

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

NUMBER_PACK_YEARS_SMOKED Mean (SD) 25.99 (18)
  Significant variables N = 0
Clinical variable #11: 'YEAR_OF_TOBACCO_SMOKING_ONSET'

No variable related to 'YEAR_OF_TOBACCO_SMOKING_ONSET'.

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

YEAR_OF_TOBACCO_SMOKING_ONSET Mean (SD) 1969.15 (13)
  Significant variables N = 0
Clinical variable #12: 'COMPLETENESS_OF_RESECTION'

No variable related to 'COMPLETENESS_OF_RESECTION'.

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

COMPLETENESS_OF_RESECTION Labels N
  R0 77
  R1 48
  R2 1
  RX 3
     
  Significant variables N = 0
Clinical variable #13: 'NUMBER_OF_LYMPH_NODES'

No variable related to 'NUMBER_OF_LYMPH_NODES'.

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

NUMBER_OF_LYMPH_NODES Mean (SD) 3.14 (3.4)
  Significant variables N = 0
Clinical variable #14: 'RACE'

No variable related to 'RACE'.

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

RACE Labels N
  ASIAN 2
  BLACK OR AFRICAN AMERICAN 5
  WHITE 125
     
  Significant variables N = 0
Clinical variable #15: 'ETHNICITY'

No variable related to 'ETHNICITY'.

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

ETHNICITY Labels N
  HISPANIC OR LATINO 3
  NOT HISPANIC OR LATINO 104
     
  Significant variables N = 0
Methods & Data
Input

  • Expresson data file = PAAD-TP.patients.counts_and_rates.txt

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

  • Number of patients = 136

  • Number of variables = 2

  • Number of clinical features = 15

Selected clinical features

  • For clinical features selected for this analysis and their value conozzle.versions, please find a documentation on selected CDEs .

  • 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, 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

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.

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)
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