The right answer depends on the selectivity of the various columns. In particular, how many different values are there for table1.col1C? If there are a total of two values (such as 'M' and 'F' in the entire table, then you are better off not even including it in the combined index. If however, there are about a third as many distinct values in col1C as there are rows in table2, then it's possible that an index on just table1.col1C will give blindingly fast results.
If the optimizer can find three rows in table1 without doing any joins, and then do a lookup join three times to get matching rows in table2, that will be very, very fast.
Barring extensive knowledge of how the optimizer works, and extensive analysis of the data population, you are probably better off to try a couple of alternatives and run benchmarks.
Here's the good news: you can always change the index design later on.