Why is my R session in PyCharm IDE slowing down despite sufficient available RAM?

I have the below code:

cur_data <- readRDS("./TCGA-LUAD.rds")

mRNA <- cur_data$mRNAUnstranded
clinical <- cur_data$clinical
mRNATPM <- cur_data$mRNATPM
miRNA <- cur_data$miRNA
cnv <- cur_data$cnv
methyl <- cur_data$meth450

rm(cur_data)
gc()

After running these lines, my R session gets very slow that even printing a string takes 10-15 seconds. I have checked the object sizes:

> object.size(cur_data)
3654078952 bytes
> object.size(cnv)
99061912 bytes
> object.size(methyl)
1826984576 bytes
> object.size(miRNA)
9215840 bytes
> object.size(mRNA)
166234336 bytes
> object.size(mRNATPM)
305757664 bytes

I have the below code:

cur_data <- readRDS("./TCGA-LUAD.rds")

mRNA <- cur_data$mRNAUnstranded
clinical <- cur_data$clinical
mRNATPM <- cur_data$mRNATPM
miRNA <- cur_data$miRNA
cnv <- cur_data$cnv
methyl <- cur_data$meth450

rm(cur_data)
gc()

After running these lines, my R session gets very slow that even printing a string takes 10-15 seconds. I have checked the object sizes:

> object.size(cur_data)
3654078952 bytes
> object.size(cnv)
99061912 bytes
> object.size(methyl)
1826984576 bytes
> object.size(miRNA)
9215840 bytes
> object.size(mRNA)
166234336 bytes
> object.size(mRNATPM)
305757664 bytes

On the machine that I am running my code, we have around 230GB memory available. Below I have included the memory info as well:

library(pryr)
library(ps)

# Check memory before loading data
cat("Memory before loading data: \n")
print(mem_used())
print(ps::ps_memory_info())

cur_data <- readRDS("./TCGA-LUAD.rds")

# Check memory after loading data
cat("Memory after loading data: \n")
print(mem_used())
print(ps::ps_memory_info())

The output is:

Memory before loading data:
70.4 MB

        rss         vms      shared        text         lib        data 
  151760896 19957977088    27262976    11669504           0 18425253888 
      dirty 
          0 


Memory after loading data:
3.58 GB
        rss         vms      shared        text         lib        data 
 3647713280 23454457856    27262976    11669504           0 21921734656 
      dirty 
          0 

Also running below command:

system("free -b", intern = TRUE)

returns:

[[1]]
[1] "               total        used        free      shared  buff/cache   available"

[[2]]
[1] "Mem:     270086418432 19110584320 212453797888     1396736 38522036224 248626864128"

[[3]]
[1] "Swap:    262143995904 22240501760 239903494144"

Even though I have enough RAM available, my question is why the R session gets slow? A note that I am using PyCharm (Jetbrains Client using SSH) IDE to run my codes. (Also each list item in the cur_data are a list themselves and if asking to work with one of them at the time, I need to load multiple of them at once to be able to do some processing.)

*Another quick point is that I have tried already to run the script through command line, and there is no issue with that.