Why did expression based subtypng of breast cancer gain much more acceptance than others
In two words: incidence and funding
I'm not an expert on this topic, but I assume it has something to do with the incidence of breast cancer itself:

Breast cancer is the most common cancer in American women, except for skin cancers. Currently, the average risk of a woman in the United States developing breast cancer sometime in her life is about 13%. This means there is a 1 in 8 chance she will develop breast cancer. This also means there is a 7 in 8 chance she will never have the disease.

This incidence most likely amplifies how big of a problem society/funders/governments consider breast cancer to be. For example, a study performed by Northwestern University’s Feinberg School of Medicine and Robert H. Lurie Comprehensive Cancer Center showed that breast cancer research is by and large one of the most well-funded areas of cancer research.

This higher amount of funding leads to more and better resources and research into every aspect of breast cancer, from identification to treatment. I would wager better funding has had the effect of increasing the level of research performed in the usage of sub-typing for identifying people at risk of getting breast cancer. Given positive results and lots of literature backing up such a method as useful, its levels of acceptance in clinical settings increased.