Cancers have dysfunctional redox regulation resulting in reactive oxygen species production, damaging both DNA and free dNTPs. The MTH1 protein sanitizes oxidized dNTP pools to prevent incorporation of damaged bases during DNA replication. Although MTH1 is non-essential in normal cells, we show that cancer cells require MTH1 activity to avoid incorporation of oxidized dNTPs, resulting in DNA damage and cell death. We validate MTH1 as an anticancer target in vivo and describe small molecules TH287 and TH588 as first-in-class nudix hydrolase family inhibitors that potently and selectively engage and inhibit the MTH1 protein in cells. Protein co-crystal structures demonstrate that the inhibitors bind in the active site of MTH1. The inhibitors cause incorporation of oxidized dNTPs in cancer cells, leading to DNA damage, cytotoxicity and therapeutic responses in patient-derived mouse xenografts. This study exemplifies the non-oncogene addiction concept for anticancer treatment and validates MTH1 as being cancer phenotypic lethal.

New fentanyl analogs have recently emerged as new psychoactive substances and have caused numerous fatalities worldwide. To determine if the new analogs follow the same metabolic pathways elucidated for fentanyl and known fentanyl analogs, we performed in vitro and in vivo metabolite identification studies for acetylfentanyl, acrylfentanyl, 4-fluoro-isobutyrylfentanyl, and furanylfentanyl. All compounds were incubated at 10 μM with pooled human hepatocytes for up to 5 h. For each compound, four or five authentic human urine samples from autopsy cases with and without enzymatic hydrolysis were analyzed. Data acquisition was performed in data-dependent acquisition mode during liquid chromatography high-resolution mass spectrometry analyses. Data was analyzed (1) manually based on predicted biotransformations and (2) with MetaSense software using data-driven search algorithms. Acetylfentanyl, acrylfentanyl, and 4-fluoro-isobutyrylfentanyl were predominantly metabolized by N-dealkylation, cleaving off the phenethyl moiety, monohydroxylation at the ethyl linker and piperidine ring, as well as hydroxylation/methoxylation at the phenyl ring. In contrast, furanylfentanyl's major metabolites were generated by amide hydrolysis and dihydrodiol formation, while the nor-metabolite was minor or not detected in case samples at all. In general, in vitro results matched the in vivo findings well, showing identical biotransformations in each system. Phase II conjugation was observed, particularly for acetylfentanyl. Based on our results, we suggest the following specific and abundant metabolites as analytical targets in urine: a hydroxymethoxy and monohydroxylated metabolite for acetylfentanyl, a monohydroxy and dihydroxy metabolite for acrylfentanyl, two monohydroxy metabolites and a hydroxymethoxy metabolite for 4-fluoro-isobutyrylfentanyl, and a dihydrodiol metabolite and the amide hydrolysis metabolite for furanylfentanyl.

DNA immunoprecipitation followed by sequencing (DIP-seq) is a common enrichment method for profiling DNA modifications in mammalian genomes. However, the results of independent DIP-seq studies often show considerable variation between profiles of the same genome and between profiles obtained by alternative methods. Here we show that these differences are primarily due to the intrinsic affinity of IgG for short unmodified DNA repeats. This pervasive experimental error accounts for 50-99% of regions identified as 'enriched' for DNA modifications in DIP-seq data. Correction of this error profoundly altered DNA-modification profiles for numerous cell types, including mouse embryonic stem cells, and subsequently revealed novel associations among DNA modifications, chromatin modifications and biological processes. We conclude that both matched input and IgG controls are essential in order for the results of DIP-based assays to be interpreted correctly, and that complementary, non-antibody-based techniques should be used to validate DIP-based findings to avoid further misinterpretation of genome-wide profiling data.