Remove certain elements of a list for multiple columns in a DataFrame

I have a table like that:

As you can see Columns 3-5 are made of lists entirely and what I want is to remove dash (-) along with "nan" elements from the lists in those columns.

So the output should look like this at the end:

The closest to this outcome I was able to get with the following function:

Table1["Column3"] = Table1["Column3"].apply(lambda x: [el for el in x if el != '-' if pd.isnull(el) == False])

But the problem with it is that I don't know how to apply it for all the columns that are made out of lists in the DataFrame. This is simplified example, in the original I have nearly 15 columns and was wondering if there is a way to achieve it, instead of writing a function like that separately for all 15 columns.

Another solution:

for c in df.columns:
    df[c] = df[c].apply(
        lambda x: [v for v in x if v != "-" and pd.notna(v)]
        if isinstance(x, list)
        else x
    )

print(df)

Prints:

   Column1 Column2 Column3          Column4     Column5
0      100    John     [1]  [brown, yellow]          []
1      200  Stefan     [2]         [yellow]  [accepted]