The original paper (here: http://www.sciencemag.org/content/347/6217/78.abstract -- the abstract is enough to deduce the conclusion) is a simple statistical analysis of mutation probability in certain cell types. It's basically saying that many cancers are not necessarily influenced by external factors and can be predicted by nothing more than the number of cell divisions and the probability of DNA mutation compounded.
That, in itself, is a fascinating scientific result. Arguing against the statistics here is probably not a good idea, unless there was a serious error in the math or an order of magnitude error in the probability of mutation. Certainly there are other possibilities of error in the data or methodology.
But the article in opposition (OP) is doing something odd that doesn't appear to be a scientific argument: it's railing against the language and the implications of the very concept of statistical analysis applied to the problem. It's assuming that because we discovered that, perhaps, cancer has a certain probability of occurring independent of external factors, that it will somehow slow research or cause us to throw up our hands and give up on prevention strategies or research.
I don't think that's the case. Rather than understanding the absolutely fascinating statistical analysis here, the OP article comes across as reactionary and unscientific.
Assuming the data is sound, the statistical analysis is profound. Most often, statistics such as that are profoundly misunderstood as well: people have an incredible capacity for attribution bias and data disbelief. This simply underscores the need for a better education in basic statistics as well as science across the board.