Human Cancer Modeling: Recapitulating Tumor Heterogeneity Towards Personalized Medicine

Despite diagnostic, preventive and therapeutic advances, growing incidence of cancer and high rate of mortality among patients affected by specific cancer types indicate current clinical measures are not ideally useful in eradicating cancer. Chemoresistance and subsequent disease relapse are believed to be mainly driven by the cell-molecular heterogeneity of human tumors that necessitates personalized approaches to deal with uniquely complex genetic profile of each patient’s tumor. Such personalized medicinal therapies require dissection of cancer molecular profiles in order to profoundly understand mechanisms underlying drug resistance and disease recurrence. Technological advances in comparative genome sequencing have begun to result in identification of common somatic mutations in specific cancer subtypes that potentially constitute bases for prognostic and diagnostic biomarkers and present novel therapeutic targets. These targets have to be tested in reliable platforms so data of drug responses obtained can be correlated with those responses elicited in origin by the parental tumor itself. Here, I review different models of cancer in vitro and in vivo and outline the utility of these models in drug discovery and novel therapies of cancer with prospect for developing personalized anti-cancer strategies.

Keywords:

Xenograft , Human Tumor , Personalized Medicine , Drug Discovery.