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Topoisomerase IV (Topo IV) is the main decatenation enzyme in Escherichia coli; it removes catenation links that are formed during DNA replication. Topo IV binding and cleavage sites were previously identified in the E. coli genome with ChIP-Seq and NorfIP. Here, we used a more sensitive, single-nucleotide resolution Topo-Seq procedure to identify Topo IV cleavage sites (TCSs) genome-wide. We detected thousands of TCSs scattered in the bacterial genome. The determined cleavage motif of Topo IV contained previously known cleavage determinants (−4G/+8C, −2A/+6 T, −1 T/+5A) and additional, not observed previously, positions −7C/+11G and −6C/+10G. TCSs were depleted in the Ter macrodomain except for two exceptionally strong non-canonical cleavage sites located in 33 and 38 bp from the XerC-box of the dif-site. Topo IV cleavage activity was increased in Left and Right macrodomains flanking the Ter macrodomain and was especially high in the 50–60 kb region containing the oriC origin of replication. Topo IV enrichment was also increased downstream of highly active transcription units, indicating that the enzyme is involved in relaxation of transcription-induced positive supercoiling.

Along with advances in precision oncology, checkpoint inhibitors and targeted therapies have substantially improved outcomes for cancer patients. However, many patients still demonstrate a limited response to these therapies due to many biological factors, including genetic heterogeneity, unique molecular profiles, and the complex features of the tumor microenvironment (TME). Therefore, the selection of personalized effective treatment requires a comprehensive source of therapy response biomarkers, enabling precision medicine strategies for therapy selection. Here, we present a first-in-class automated biomarker analysis database, Astraea, that comprehensively describes genomic, transcriptomic, and TME biomarkers across a wide array of cancers. Automated daily literature reviews of the therapeutic efficacy of biomarkers provided the foundation of Astraea. To date, the database contains a total of 4,116 published biomarkers associated with genomic events, the TME, and targeted proteomic, transcriptomic, and gene signatures. To ensure accuracy of the final inclusion of biomarkers in the database, a multi-step quality control process was implemented that includes an automatic validation step and manual review. After selection, each biomarker is organized into a unique profile in the database which includes assay specifics, the biomarker-associated cancer type, therapy, primary study design, and statistical analysis. Data available from The Cancer Genome Atlas (TCGA) was then used to aggregate interrelated biomarkers into 25 biologically meaningful clusters, with the most prominent clusters identified as components of the TME (i.e., cytotoxic T cells, B cells, fibroblasts) and proliferation rate signatures. The aggregation enabled an easier interpretation and understanding of potentially actionable molecular findings as well as insight into unique neoplastic drivers. To apply Astraea in a clinical setting, we then developed a platform to match therapies to patients based on 1) identified biomarkers prioritized according to level of evidence, including both number of associated publications, statistical strength of individual studies, and cohort size and 2) therapies scored according to supporting biomarkers and associated relevance (resistance/response). By providing comprehensive, up-to-date biomarker identification and matching through utilization of a large automated multi-platform database, this technique aids in the identification and application of biomarkers unique to each patient. Taken together, our results show that Astraea, accompanied by a multi-step personalized cancer therapy-matching platform, could improve precision medicine strategies and help optimize therapeutic decisions. Citation Format: Azamat Gafurov, Ivan Mamichev, Elena V. Vasileva, Georgy D. Sagaradze, Maria S. Shitova, Grigorii Nos, Nikita Kotlov, Jessica H. Brown, Alexander Bagaev, Nathan Fowler. Astraea: A first-in-class biomarker database integrating genomic, transcriptomic, and tumor microenvironment properties for precision oncology [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 205.