Multivariate Cox Regression of PRMT1 expression Tumour Grade in Triple-Negative Breast Cancer Patients in TGCA Data

Get TGCA data from XenaBrowser

Bash scripts using system()

system(wget “https://tcga-xena-hub.s3.us-east-1.amazonaws.com/download/survival%2FBRCA_survival.txt”)

system(wget “https://tcga-xena-hub.s3.us-east-1.amazonaws.com/download/TCGA.BRCA.sampleMap%2FBRCA_clinicalMatrix”)

system(wget “https://tcga-xena-hub.s3.us-east-1.amazonaws.com/download/TCGA.BRCA.sampleMap%2FHiSeqV2.gz”)

system(gunzip “TCGA.BRCA.sampleMap_HiSeqV2.gz”)

setwd("/Users/ken/Downloads")
rna.seq <- as.matrix(read.table("TCGA.BRCA.sampleMap_HiSeqV2", sep="\t",header=TRUE,row.names = 1))
clin.data <- read.table("TCGA.BRCA.sampleMap_BRCA_clinicalMatrix", sep= "\t", header=T, row.names=1)
survival <- read.table("BRCA_survival.txt", sep="\t",header=TRUE, row.names = 1)

Loading the Library

library("survival")
library("survminer")

## Loading required package: ggplot2

## Loading required package: ggpubr

library("dplyr")

## 
## Attaching package: 'dplyr'

## The following objects are masked from 'package:stats':
## 
##     filter, lag

## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union

Fixing and alignlng data frames and matrices

rownames(clin.data)<-gsub(rownames(clin.data), pattern="-", replace=".")
rownames(survival)<-gsub(rownames(survival), pattern="-", replace=".")
clin.data <- clin.data[colnames(rna.seq),]

RNAseq and survival

OS.Time.rna <- survival[colnames(rna.seq),"OS.time"]
OS.Event.rna <- as.numeric(survival[colnames(rna.seq),"OS"])
OS.rna <- Surv(OS.Time.rna,OS.Event.rna)

Cox Regression - RNA expression data

Results.OS_rna.seq<- array(NA, c(nrow(rna.seq),4))
colnames(Results.OS_rna.seq)<-c("HR","LCI","UCI","PVAL")
rownames(Results.OS_rna.seq)<-rownames(rna.seq)
Results.OS_rna.seq <- as.data.frame(Results.OS_rna.seq)

for(i in 1:nrow(rna.seq)){
  coxphmodel <- coxph(OS.rna~ as.numeric(rna.seq[i,]))
  Results.OS_rna.seq$HR[i] <- summary(coxphmodel)$coef[1,2]
  Results.OS_rna.seq$LCI[i] <- summary(coxphmodel)$conf.int[1,3]
  Results.OS_rna.seq$UCI[i] <- summary(coxphmodel)$conf.int[1,4]
  Results.OS_rna.seq$PVAL[i] <- summary(coxphmodel)$coef[1,5]
}

## Warning in fitter(X, Y, istrat, offset, init, control, weights = weights, :
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## Warning in fitter(X, Y, istrat, offset, init, control, weights = weights, :
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## Warning in fitter(X, Y, istrat, offset, init, control, weights = weights, :
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## Warning in fitter(X, Y, istrat, offset, init, control, weights = weights, :
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## Warning in fitter(X, Y, istrat, offset, init, control, weights = weights, :
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## Warning in fitter(X, Y, istrat, offset, init, control, weights = weights, :
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## Warning in fitter(X, Y, istrat, offset, init, control, weights = weights, :
## Loglik converged before variable 1 ; coefficient may be infinite.

## Warning in fitter(X, Y, istrat, offset, init, control, weights = weights, :
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## Warning in fitter(X, Y, istrat, offset, init, control, weights = weights, :
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## Warning in fitter(X, Y, istrat, offset, init, control, weights = weights, :
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## Warning in fitter(X, Y, istrat, offset, init, control, weights = weights, :
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## Warning in fitter(X, Y, istrat, offset, init, control, weights = weights, :
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## Warning in fitter(X, Y, istrat, offset, init, control, weights = weights, :
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## Warning in fitter(X, Y, istrat, offset, init, control, weights = weights, :
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## Warning in fitter(X, Y, istrat, offset, init, control, weights = weights, :
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## Warning in fitter(X, Y, istrat, offset, init, control, weights = weights, :
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## Warning in fitter(X, Y, istrat, offset, init, control, weights = weights, :
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## Warning in fitter(X, Y, istrat, offset, init, control, weights = weights, :
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## Warning in fitter(X, Y, istrat, offset, init, control, weights = weights, :
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## Warning in fitter(X, Y, istrat, offset, init, control, weights = weights, :
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## Warning in fitter(X, Y, istrat, offset, init, control, weights = weights, :
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## Warning in fitter(X, Y, istrat, offset, init, control, weights = weights, :
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## Warning in fitter(X, Y, istrat, offset, init, control, weights = weights, :
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## Warning in fitter(X, Y, istrat, offset, init, control, weights = weights, :
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## Warning in fitter(X, Y, istrat, offset, init, control, weights = weights, :
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## Warning in fitter(X, Y, istrat, offset, init, control, weights = weights, :
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## Warning in fitter(X, Y, istrat, offset, init, control, weights = weights, :
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## Warning in fitter(X, Y, istrat, offset, init, control, weights = weights, :
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## Warning in fitter(X, Y, istrat, offset, init, control, weights = weights, :
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## Warning in fitter(X, Y, istrat, offset, init, control, weights = weights, :
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## Warning in fitter(X, Y, istrat, offset, init, control, weights = weights, :
## Loglik converged before variable 1 ; coefficient may be infinite.

## Warning in fitter(X, Y, istrat, offset, init, control, weights = weights, :
## Loglik converged before variable 1 ; coefficient may be infinite.

## Warning in fitter(X, Y, istrat, offset, init, control, weights = weights, :
## Loglik converged before variable 1 ; coefficient may be infinite.

## Warning in fitter(X, Y, istrat, offset, init, control, weights = weights, :
## Loglik converged before variable 1 ; coefficient may be infinite.

## Warning in fitter(X, Y, istrat, offset, init, control, weights = weights, :
## Loglik converged before variable 1 ; coefficient may be infinite.

## Warning in fitter(X, Y, istrat, offset, init, control, weights = weights, :
## Loglik converged before variable 1 ; coefficient may be infinite.

## Warning in fitter(X, Y, istrat, offset, init, control, weights = weights, :
## Loglik converged before variable 1 ; coefficient may be infinite.

## Warning in fitter(X, Y, istrat, offset, init, control, weights = weights, :
## Loglik converged before variable 1 ; coefficient may be infinite.

## Warning in fitter(X, Y, istrat, offset, init, control, weights = weights, :
## Loglik converged before variable 1 ; coefficient may be infinite.

## Warning in fitter(X, Y, istrat, offset, init, control, weights = weights, :
## Loglik converged before variable 1 ; coefficient may be infinite.

## Warning in fitter(X, Y, istrat, offset, init, control, weights = weights, :
## Loglik converged before variable 1 ; coefficient may be infinite.

## Warning in fitter(X, Y, istrat, offset, init, control, weights = weights, :
## Loglik converged before variable 1 ; coefficient may be infinite.

## Warning in fitter(X, Y, istrat, offset, init, control, weights = weights, :
## Loglik converged before variable 1 ; coefficient may be infinite.

## Warning in fitter(X, Y, istrat, offset, init, control, weights = weights, :
## Loglik converged before variable 1 ; coefficient may be infinite.

## Warning in fitter(X, Y, istrat, offset, init, control, weights = weights, :
## Loglik converged before variable 1 ; coefficient may be infinite.

## Warning in fitter(X, Y, istrat, offset, init, control, weights = weights, :
## Loglik converged before variable 1 ; coefficient may be infinite.

## Warning in fitter(X, Y, istrat, offset, init, control, weights = weights, :
## Loglik converged before variable 1 ; coefficient may be infinite.

## Warning in fitter(X, Y, istrat, offset, init, control, weights = weights, :
## Loglik converged before variable 1 ; coefficient may be infinite.

## Warning in fitter(X, Y, istrat, offset, init, control, weights = weights, :
## Loglik converged before variable 1 ; coefficient may be infinite.

## Warning in fitter(X, Y, istrat, offset, init, control, weights = weights, :
## Loglik converged before variable 1 ; coefficient may be infinite.

## Warning in fitter(X, Y, istrat, offset, init, control, weights = weights, :
## Loglik converged before variable 1 ; coefficient may be infinite.

## Warning in fitter(X, Y, istrat, offset, init, control, weights = weights, :
## Loglik converged before variable 1 ; coefficient may be infinite.

## Warning in fitter(X, Y, istrat, offset, init, control, weights = weights, :
## Loglik converged before variable 1 ; coefficient may be infinite.

## Warning in fitter(X, Y, istrat, offset, init, control, weights = weights, :
## Loglik converged before variable 1 ; coefficient may be infinite.

## Warning in fitter(X, Y, istrat, offset, init, control, weights = weights, :
## Loglik converged before variable 1 ; coefficient may be infinite.

## Warning in fitter(X, Y, istrat, offset, init, control, weights = weights, :
## Loglik converged before variable 1 ; coefficient may be infinite.

## Warning in fitter(X, Y, istrat, offset, init, control, weights = weights, :
## Loglik converged before variable 1 ; coefficient may be infinite.

## Warning in fitter(X, Y, istrat, offset, init, control, weights = weights, :
## Loglik converged before variable 1 ; coefficient may be infinite.

## Warning in fitter(X, Y, istrat, offset, init, control, weights = weights, :
## Loglik converged before variable 1 ; coefficient may be infinite.

Results.OS_rna.seq$FDR <- p.adjust(Results.OS_rna.seq$PVAL,method="fdr")
Results.OS_rna.seq<-Results.OS_rna.seq[order(Results.OS_rna.seq$FDR, decreasing=F),]
Results.OS_rna.seq["PRMT1",]

##              HR       LCI       UCI      PVAL       FDR
## PRMT1 0.7576524 0.5926882 0.9685315 0.0267481 0.1170569

Cox Regression - Stage (tumour grade)

# Stage
stage.III <- grep("III", clin.data$pathologic_stage)
stage.IV <- grep("IV", clin.data$pathologic_stage)
stage.high <- rep(0, nrow((clin.data)))
stage.high [c(stage.III,stage.IV)] <- 1

# Stage cox regression
coxph(OS.rna ~ stage.high)

## Call:
## coxph(formula = OS.rna ~ stage.high)
## 
##              coef exp(coef) se(coef)     z        p
## stage.high 0.7815    2.1847   0.1487 5.255 1.48e-07
## 
## Likelihood ratio test=25.21  on 1 df, p=5.147e-07
## n= 1214, number of events= 198 
##    (4 observations deleted due to missingness)

Results.OS_stage<-array(NA, c(nrow(rna.seq),4))
colnames(Results.OS_stage)<-c("HR","LCI","UCI","PVAL")
rownames(Results.OS_stage)<-rownames(rna.seq)
Results.OS_stage<-as.data.frame(Results.OS_stage)

for(i in 1:nrow(rna.seq)){
  coxphmodel_stage <- coxph(OS.rna ~ stage.high)
  Results.OS_stage$HR[i] <- summary(coxphmodel_stage)$coef[1,2]
  Results.OS_stage$LCI[i] <- summary(coxphmodel_stage)$conf.int[1,3]
  Results.OS_stage$UCI[i] <- summary(coxphmodel_stage)$conf.int[1,4]
  Results.OS_stage$PVAL[i] <- summary(coxphmodel_stage)$coef[1,5]
}
Results.OS_stage$FDR <- p.adjust(Results.OS_stage$PVAL, method =  "fdr")

summary(coxphmodel_stage)$coef[1,2]       # HR = 2.1847

## [1] 2.1847

summary(coxphmodel_stage)$conf.int[1,3]   # LCI = 1.632361

## [1] 1.632361

summary(coxphmodel_stage)$conf.int[1,4]   # HCI = 2.923933

## [1] 2.923933

summary(coxphmodel_stage)$coef[1,5]

## [1] 1.477636e-07

Cox Regression - TNBC (triple-negative breast cancer patients)

# Receptor status
TNBC.stat <- rep(0, nrow((clin.data)))
TNBC.stat[clin.data$breast_carcinoma_estrogen_receptor_status =="Negative" &
          clin.data$breast_carcinoma_progesterone_receptor_status =="Negative" &
          clin.data$lab_proc_her2_neu_immunohistochemistry_receptor_status == "Negative"] <- 1

# TNBC cox regression
coxph(OS.rna ~ TNBC.stat)

## Call:
## coxph(formula = OS.rna ~ TNBC.stat)
## 
##             coef exp(coef) se(coef)     z    p
## TNBC.stat 0.1956    1.2161   0.2228 0.878 0.38
## 
## Likelihood ratio test=0.73  on 1 df, p=0.3916
## n= 1214, number of events= 198 
##    (4 observations deleted due to missingness)

Results.OS_TNBC<-array(NA, c(nrow(rna.seq),4))
colnames(Results.OS_TNBC)<-c("HR","LCI","UCI","PVAL")
rownames(Results.OS_TNBC)<-rownames(rna.seq)
Results.OS_TNBC<-as.data.frame(Results.OS_TNBC)

for(i in 1:nrow(rna.seq)){
  coxphmodel_TNBC <- coxph(OS.rna ~ TNBC.stat)
  Results.OS_TNBC$HR[i] <- summary(coxphmodel_TNBC)$coef[1,2]
  Results.OS_TNBC$LCI[i] <- summary(coxphmodel_TNBC)$conf.int[1,3]
  Results.OS_TNBC$UCI[i] <- summary(coxphmodel_TNBC)$conf.int[1,4]
  Results.OS_TNBC$PVAL[i] <- summary(coxphmodel_TNBC)$coef[1,5]
}
Results.OS_TNBC$FDR <- p.adjust(Results.OS_TNBC$PVAL, method =  "fdr")

summary(coxphmodel_TNBC)$coef[1,2]       # HR = 1.216075

## [1] 1.216075

summary(coxphmodel_TNBC)$conf.int[1,3]   # LCI = 0.7858219

## [1] 0.7858219

summary(coxphmodel_TNBC)$conf.int[1,4]   # HCI = 1.881901

## [1] 1.881901

summary(coxphmodel_TNBC)$coef[1,5]

## [1] 0.3798901

Multivariate

High PRMT1 expression + TNBC + Stage

Results.OS_rna.seq_fctrs<-array(NA, c(nrow(rna.seq),4))
colnames(Results.OS_rna.seq_fctrs)<-c("HR","LCI","UCI","PVAL")
rownames(Results.OS_rna.seq_fctrs)<-rownames(rna.seq)
Results.OS_rna.seq_fctrs<-as.data.frame(Results.OS_rna.seq_fctrs)

for(i in 1:nrow(rna.seq)){
  coxphmodel3 <- coxph(OS.rna ~ as.numeric(rna.seq[i,]+TNBC.stat+stage.high))
  Results.OS_rna.seq_fctrs$HR[i] <- summary(coxphmodel3)$coef[1,2]
  Results.OS_rna.seq_fctrs$LCI[i] <- summary(coxphmodel3)$conf.int[1,3]
  Results.OS_rna.seq_fctrs$UCI[i] <- summary(coxphmodel3)$conf.int[1,4]
  Results.OS_rna.seq_fctrs$PVAL[i] <- summary(coxphmodel3)$coef[1,5]
}

## Warning in fitter(X, Y, istrat, offset, init, control, weights = weights, :
## Loglik converged before variable 1 ; coefficient may be infinite.

Results.OS_rna.seq_fctrs <- as.data.frame(Results.OS_rna.seq_fctrs)
Results.OS_rna.seq_fctrs$FDR <- p.adjust(Results.OS_rna.seq_fctrs$PVAL, method =  "fdr")
Results.OS_rna.seq_fctrs<-Results.OS_rna.seq_fctrs[order(Results.OS_rna.seq_fctrs$FDR, decreasing=F),]

# Summary PRMT1
summary(rna.seq["PRMT1",])

##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##   9.134  10.526  10.855  10.928  11.264  13.544

Results.OS_rna.seq["PRMT1",]        # Univariate cox regression

##              HR       LCI       UCI      PVAL       FDR
## PRMT1 0.7576524 0.5926882 0.9685315 0.0267481 0.1170569

Results.OS_stage["PRMT1",]          # Univariate cox regression - Stage 

##           HR      LCI      UCI         PVAL          FDR
## PRMT1 2.1847 1.632361 2.923933 1.477636e-07 1.477636e-07

Results.OS_TNBC["PRMT1",]           # Univariate cox regression - TNBC

##             HR       LCI      UCI      PVAL       FDR
## PRMT1 1.216075 0.7858219 1.881901 0.3798901 0.3798901

Results.OS_rna.seq_fctrs["PRMT1",]  # Multivariate cox regression

##            HR       LCI      UCI      PVAL       FDR
## PRMT1 1.13513 0.9558661 1.348014 0.1483816 0.1973359

PRMT1.high <- as.numeric(rna.seq["PRMT1",]>mean(rna.seq["PRMT1",]))

KM Plot

grid <- matrix(c(1,2,3), nrow = 1, ncol = 3, byrow = T)
layout(grid)
plot(survfit(OS.rna ~ PRMT1.high), col=c("#B10026", "#0D4A70"),
     lwd=2,mark.time=TRUE, xlab="OS Time (days)", ylab="Survival Probability")
legend("bottomleft",legend=c("High PRMT1 expression","Low PRMT1 expression"),
       col=c("#0D4A70","#B10026"),lwd=3)
text(2900,0.15,"HR=0.76 (95% CI, 0.59-0.97)")
text(350,0.20, "FDR")
text(1600,0.20, "> 0.05")
plot(survfit(OS.rna ~ stage.high), col=c("#B10026", "#0D4A70"),
     lwd=2,mark.time=TRUE, xlab="OS Time (days)", ylab="Survival Probability")
legend("bottomleft",legend=c("Stage III and IV","Stage I and II"),
       col=c("#0D4A70","#B10026"),lwd=3)
text(2900,0.15,"HR=2.19 (95% CI, 1.63-2.92)")
text(350,0.20, "FDR")
text(1700,0.20, "< 0.001")
plot(survfit(OS.rna ~ TNBC.stat), col=c("#B10026", "#0D4A70"),
     lwd=2,mark.time=TRUE, xlab="OS Time (days)", ylab="Survival Probability")
legend("bottomleft",legend=c("TNBC","Not TNBC"),
       col=c("#0D4A70","#B10026"),lwd=3)
text(2900,0.15,"HR=1.21 (95% CI, 0.78-1.88)")
text(350,0.20, "FDR")
text(1600,0.20, "> 0.05")

dev.off()

## null device 
##           1

ggsurvplot(survfit(Surv(OS.Time.rna, OS.Event.rna) ~ PRMT1.high, data = survival),
           conf.int = F, risk.table = "absolute", 
           risk.table.y.text.col = TRUE,
           xlab = "OS Time (days)", 
           legend = "bottom", 
           break.time.by = 1000)

## Warning: Vectorized input to `element_text()` is not officially supported.
## Results may be unexpected or may change in future versions of ggplot2.

dev.off()

## null device 
##           1