With the development of high-throughput technologies and big data analysis methods it has become largely apparent that clinical diagnoses do not correspond to a single molecular signature. Even clinically homogeneous patient cohorts may be heterogeneous at the molecular level and comprise several subgroups defined by distinct pathomechanisms. Such subgroups of patients are called endotypes or disease subtypes and may demonstrate differential treatment response or adverse drug reactions and have distinct prognosis.
The most prominent example of heterogeneous disease is cancer. Each tumor is characterized by a unique set of molecular lesions promoting its malignant properties. Some of these molecular changes are recurrent and define cancer subtypes, demonstrating differential therapy response and disease prognosis. Therefore, a number of molecular classifications of tumors is used in clinical practice and many research initiatives are aimed at the discovery of novel molecular subtypes and biomarkers for patient stratification.

Although molecular heterogeneity is mostly discussed in the context of cancer, disease endotypes have been recently reported for many non-cancerous diseases. These include asthma and allergic diseases, rheumatoid arthritis, Alzheimer’s, essential hypertension and many other human disorders. Despite this, most studies aiming to elucidate disease mechanisms or identify novel biomarkers implicitly assume a shared mechanism and often neglect to consider potential disease heterogeneity. Analysis of datasets with unresolved heterogeneity can obscure identification of distinct disease mechanisms, especially those specific to less prevalent subtypes. It also complicates the identification of biomarkers, as some may work for only specific disease subtypes. Therefore, the development of novel methods for patient stratification and bioinformatics approaches aware of potential disease heterogeneity represents an important research direction.

The goal of this Research Topic is to promote the exploration of molecular heterogeneity in human diseases. Investigation of this phenomenon is extremely important for fundamental research and for the advancement of personalized and precision medicine. The Research Topic welcomes Original Research, Methods, Technology and Code, Review, Mini Review, Perspective, and Opinion manuscripts on:

• omics-based patient stratification and the discovery of disease endotypes;
• computational tools for for the detection of molecular subtypes;
• application of methods initially designed to explore cancer heterogeneity to other human diseases;
• the relationships between molecular and genetic heterogeneity;
and other studies exploring the heterogeneity of human diseases and tackling the problem of the identification of disease subtypes.

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Frontiers in Genetics

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