Discrete Ollivier-Ricci Flow Finds Distinct Subpopulations of Patients Treated with PD-1 Inhibition

Abstract

In recent years immune checkpoint inhibitors (ICIs), also called immune checkpoint blockers, have revolutionized the standard of care for patients with cancers of many types. Researchers across many disciplines have endeavored to find biomarkers of response to ICI therapy but so far little consensus has been reached. In this paper we attempt to cluster patients in an unsupervised manner using discrete Ollivier-Ricci Flow (ORF). Our method surfaces populations with distinct survival curves which in turn allows us to find many potential biomarkers, including gene expression modules. We believe the algorithm may be of independent interest for clustering other datasets in a diverse set of research areas.