How can I compute pairwise correlations between two matrices with the same/different dimensions?

Question

[huynguyen96.dnu]

I who am relatively new to R having two datasets 'df1' and 'df2', followings are reproducible datasets, respectively:

df1 = structure(list(CNAcor_DOWN = c(125L, 116L, 139L, 128L, 126L, 
132L), CNAcor_UP = c(83L, 92L, 69L, 80L, 82L, 76L)), row.names =
c("AAMDC",  "ABCC3", "ABRA", "ACACA", "ACE", "ACER3"), class =
"data.frame")

df2 = structure(list(CNAcor_DOWN = c(110L, 99L, 122L, 111L, 129L,
120L,  115L, 92L, 120L, 97L, 128L, 113L), CNAcor_UP = c(98L, 109L,
86L,  97L, 79L, 88L, 93L, 116L, 88L, 111L, 80L, 95L)), row.names =
c("AATK",  "ABCG5", "ABHD2", "ACACA", "ACADL", "ACTR8", "ADAM32",
"ADAM8",  "ADCYAP1", "ADPRH", "ADRA1B", "ADSSL1"), class =
"data.frame")

In which,they both are frequency of expression levels of genes whose levels are divided by either of levels: UP or DOWN across the patients in CNA data (df1) and those in MET data (df2).

Now, I'm wanting to compute the Pearson's pairwise correlations among the frequencies of CNVcor_UP, CNVcor_DOWN, METcor_UP, and METcor_DOWN genes, so that the wanted results look like:

Can anyone help me? Any help would be appreciated. Many Thanks in advance.