Kevin M. Haigis

This paper designs an orthogonal self-labeling protein, LUCI-tag, using deep learning, which enables rapid and payload-agnostic labeling of proteins in live cells.

This study identifies a neuronal PCSK1-M-ENK pathway in the ENS that suppresses colorectal cancer growth through OGFr activation.

The paper shows that inhibiting the HMWR complex causes mitotic defects and enhances cancer cell vulnerability when combined with genotoxic agents.

This study identifies tissue-specific cancer genes using a statistical framework applied to a large dataset, revealing that tissue specificity is common in cancer genes.

This study shows that specific KRAS mutations, like A59E, cooperate with other genetic alterations in CRC and affect response to EGFR inhibitors.

The paper shows that low baseline c-Myc expression restricts oncogenic K-Ras activity in tissues, and this can be reversed by increasing c-Myc in the liver.

This study identifies rare germline structural variants as risk factors for pediatric solid tumors, particularly neuroblastoma, by analyzing genome sequencing data from affected children and controls.

This study uses deep mutational scanning to analyze KRAS variants, identifying gain- and loss-of-function mechanisms and their impact on oncogenic activity.

This study develops a genetic tool to reversibly inhibit miRNA-mediated gene repression in vivo and shows tissue-specific dependencies on miRNA function for homeostasis and regeneration.

This paper introduces a method to identify miRNA targets in vivo using Halo-Enhanced Ago2 Pulldown and demonstrates its application in mouse models.

This paper develops a semi-supervised learning framework to translate genomic responses from mouse models to human inflammatory disease contexts, finding it more accurate than direct generalization.