Cancer is the main health problem with high morbidity and mortality. The worldwide annual incidence and deaths from cancers are estimated in millions [1,2]. Hence, cancer therapy must be continuously promoted and developed. Cancer study, like in other diseases, highly depends on representative and reliable models. However, the tumor is not uniform, but rather a heterogenic and highly variable and complex than other diseases, rendering its study extremely difficult, expensive [3]. The most common treatment methods for cancers are based on surgery [4], chemotherapy [5], radiotherapy [6], and immunotherapy [7]. The response of cancers to these various treatment strategies differs according to tumor subtype, clinical stage, and associated risk factors and unfortunately fails to limit the progression of cancer in various cases. Even the same tumor of the same organ or tissue differs in response to therapy among patients and the recurrence and metastasis which are associated with high resistance to therapy are main issues [8]. Also, chemotherapy affects the quality of life because of its potential side effects and therefore disfavored by many patients. Therefore, suitable models to expect the treatment response with high precision are of extreme need toward more personalized treatment of patients.