Cancer heterogeneity: origins and implications for genetic association studies

Abstract

Genetic association studies have become standard approaches to characterize the genetic and epigenetic variability associated with cancer development, including predispositions and mutations. However, the bewildering genetic and phenotypic heterogeneity inherent in cancer both magnifies the conceptual and methodological problems associated with these approaches and renders the translation of available genetic information into a knowledge that is both biologically sound and clinically relevant difficult. Here, we elaborate on the underlying causes of this complexity, illustrate why it represents a challenge for genetic association studies, and briefly discuss how it can be reconciled with the ultimate goal of identifying targetable disease pathways and successfully treating individual patients.

Regularized Machine Learning in the Genetic Prediction of Complex Traits

“…Although modeling of gene expression variability poses some technical challenges, similar to those already encountered when modeling GWA datasets [52] , [53] , incorporating such continuous features into the disease prediction models should be relatively straightforward. Adding the nongenetic information will likely be instrumental when going toward less heritable diseases, such as some cancer subtypes, which traditionally have been challenging to predict using standard GWA approaches [29] , [32] , [33] , [54] – [56] . Finally, including family medical history and other clinical data from electronic health records should improve the personal risk assessment models, as well as provide guidance on lifestyle changes for those currently healthy individuals that have increased genetic risk for the disease susceptibility [57] , [58] .…”

Precision Medicine Concepts in T-Cell Lymphoma

“…Genetic approaches are state of the art for most diseases and have also been successful in some indications (e.g., targeting BCR-ABL with imatinib in chronic myeloid leukemia (CML)). TCLs, however, as most cancers, categorically differ from the rare monogenetic disease model and are driven by microevolutionary processes leading to broad genetic heterogeneity [10] and making a purely correlational logic extremely challenging [11].…”

Acquired and Intrinsic Resistance to Colorectal Cancer Treatment

“…In their review, Marusyk and colleagues remark that even though genetic heterogeneity is not likely to contribute considerably to phenotypic heterogeneity, it still supports tumor evolution during tumorigenesis and treatment resistance [110]. Phenotypic heterogeneity manifests as phenotypic diverse subpopulations of subpopulation of tumor cells, histologic alterations, different patterns of disease progression, prognosis, diagnosis, and also responses to therapy [111]. This necessitates further investigations on therapeutic resistance of CRC with respect to phenotypic heterogeneity.…”