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Endothelin receptor A (ETA), a class A G protein-coupled receptor (GPCR), is a promising tumor-associated antigen due to its close association with the progression and metastasis of many types of cancer, such as colorectal, breast, lung, ovarian, and prostate cancer. However, only small-molecule drugs have been developed as ETAantagonists with anticancer effects. In a previous study, we identified an antibody (AG8) with highly selective binding to human ETAthrough screening of a human naïve immune antibody library. Although both in vitro and in vivo experiments indicated that the identified AG8 had anticancer effects, there is a need for improvement in biochemical and physicochemical properties such as the ETAbinding affinity, thermostability, and productivity. In this study, we engineered the framework regions of AG8 and isolated an anti-ETAantibody (MJF1) exhibiting significantly improved thermostability and ETAbinding affinity. Subsequently, our previously isolated PFc29, an Fc variant with an enhanced pH-dependent human FcRn binding profile, was introduced to MJF1, and the resulting Fc-engineered anti-ETAantibody (MJF1-PFc29) inhibited the proliferation of tumor cells comparably to MJF1 and showed a 4.2-fold increased serum half-life in human FcRn transgenic mice. Moreover, MJF1-PFc29 elicited higher tumor growth inhibition in colorectal cancer xenograft mice compared to MJF1. Our results demonstrate that the engineered human anti-ETAantibody MJF1-PFc29 has great therapeutic potential and high antitumor potency against various types of cancers including colorectal cancer.

Recurrence is a hallmark of cancer-driving mutations. Recurrent mutations can arise at the same site or affect the same gene at different sites. Here we identified a set of mutations arising in individual samples and altering different cis-regulatory elements that converge on a common gene via chromatin interactions. The mutations and genes identified in this fashion showed strong relevance to cancer, in contrast to noncoding mutations with site-specific recurrence only. We developed a prediction method that identifies potentially recurrent mutations on the basis of the features shared by mutations whose recurrence is observed in a given cohort. Our method was capable of accurately predicting recurrent mutations at the level of target genes but not mutations recurring at the same site. We experimentally validated predicted mutations in distal regulatory regions of the TERT gene. In conclusion, we propose a novel approach to discovering potential cancer-driving mutations in noncoding regions.