How can I create an automated cbind() to use with for loop?

This is the part that returns error

expression <- cbind(expression, rrM.ProfileData)

The following is my function

genes is a character vector containing names of the desired genes.

cancer is also a character vector string containing names of desired cancers.

csvname will be used as name of exported csv file containing desired expression profile.

makeHeatmapForAllCancers <- function(genes, cancers, csvname, method="mean", zscore.cutoff=2)
{
    print("Make sure the VPN is connected, otherwise the function wont be able to get the required data from http://www.cbioportal.org/")

    ## Type of computing function

    if (method=="mean"){
        cfunc <- function(x) mean(x, na.rm=TRUE)
    } else if (method=="median") {
        cfunc <- function(x) median(x, na.rm=TRUE)
    } else {
        print("method can not be left empety, it should be defined as mean or median")
    }

    ## Getting the required gene expresssion profile

    print("Downloading the required gene expresssion profile from http://www.cbioportal.org/")
    library("cgdsr")
    mycgds = CGDS("http://www.cbioportal.org/")
    colname <- vector("character", length(cancers))
    colname[1] <- "Gene.names"
    samplesize <- vector("numeric", length(cancers))
    cancernames <- vector("character", length(cancers))

    cancers <- (cancers[cancers!="Metastatic Prostate Cancer, SU2C/PCF Dream Team (Robinson et al., Cell 2015)"])
    Metastatic.Prostate.Cancer.mycancerstudy = getCancerStudies(mycgds)[
        which(getCancerStudies(mycgds)[,2]=="Metastatic Prostate Cancer, SU2C/PCF Dream Team (Robinson et al., Cell 2015)"),1]
    Metastatic.Prostate.Cancer.mycaselist = getCaseLists(mycgds,Metastatic.Prostate.Cancer.mycancerstudy)[6,1]
    Metastatic.Prostate.Cancer.mygeneticprofile = getGeneticProfiles(mycgds,Metastatic.Prostate.Cancer.mycancerstudy)[2,1]
    Metastatic.Prostate.Cancer.ProfileData <- t(getProfileData(mycgds,genes,Metastatic.Prostate.Cancer.mygeneticprofile,Metastatic.Prostate.Cancer.mycaselist))
    Expression <- vector("numeric", length=length(genes))
    for(i in 1:length(genes)){
        Expression[i] <- cfunc(as.vector(Metastatic.Prostate.Cancer.ProfileData[i,])[Metastatic.Prostate.Cancer.ProfileData[i,] > zscore.cutoff])
    }
    dim(Expression)  <- c(length(genes),1)

    ## expressionProfile <<- data.frame(expressionProfile, Metastatic.Prostate.Cancer=Expression)

    colname[1] <- "Metastatic.Prostate.Cancer"
    cancernames[1] <- "Metastatic.Prostate.Cancer"
    samplesize[1] <- ncol(Metastatic.Prostate.Cancer.ProfileData)

    ## TCGA

    for(k in 1:length(cancers)){
        mycancerstudy = getCancerStudies(mycgds)[which(getCancerStudies(mycgds)[,2]==as.character(cancers[k])),1]
        mycaselist = getCaseLists(mycgds,mycancerstudy)[which(getCaseLists(mycgds,mycancerstudy)[,2]=="Tumor Samples with mRNA data (RNA Seq V2)"),1]
        mygeneticprofile = getGeneticProfiles(mycgds,mycancerstudy)[which(getGeneticProfiles(mycgds,mycancerstudy)[,2]=="mRNA Expression z-Scores (RNA Seq V2 RSEM)"),1]
        ProfileData <- t(getProfileData(mycgds,genes,mygeneticprofile,mycaselist))
        samplesize[k+2] <- ncol(ProfileData)
        rrM.ProfileData <- vector("numeric", length=length(genes))
        for(j in 1:length(genes)){
            rrM.ProfileData[j] <- cfunc(as.vector(ProfileData[j,])[ProfileData[j,] > zscore.cutoff])
        }

        dim(rrM.ProfileData)  <- c(length(genes),1)
        expression <- cbind(expression, rrM.ProfileData)
        cname <- sapply(strsplit(as.character(cancers[k]), split=" (", fixed=TRUE), function(x) (x[1]))
        colname[k+2] <- as.character(cname)
        cancernames[k+2] <- as.character(cname)
    }

    ## Creating expressionSet class

    print("Creating expressionSet class for obtained data")
    library(Biobase)
    dimnames(expression) <- list(genes, colname)
    expressionpData <- data.frame(Sample.size=samplesize, stringsAsFactors = FALSE)
    colnames(expressionpData) <- colname
    expressionpData <- AnnotatedDataFrame(expressionpData)
    expression.Set <<- ExpressionSet(expression, expressionpData)

    ## Plotting Heatmap

    print("Prepairing Heatmap")
    library(gplots)
    library(RColorBrewer)
    library(rafalib)
    tissue= pData(expression.Set)$tissue
    hmcol <- rev(colorRampPalette(brewer.pal(9, "RdBu"))(100))
    print(heatmap.2(exprs(expression.Set), labCol=tissue, trace="none", symbreaks = T, col=hmcol, cexRow =0.7, cexCol= 0.8, margins= c(17,15)))

    ## Save the expression profile

    genes.list <- t(exprs(expression.Set))
    write.table(genes.list, file=csvname)
    cat("A .csv file entitled", csvname,
        "which contains expression profile for requested genes in all cancers was saved in",
        get.seq(), "directory", sep=" ")

    print("The function was programmed by Arman Shahrisa")
}