Predicting clinical response to anticancer drugs remains a major challenge in cancer treatment. Emerging reports indicate that the tumour microenvironment and heterogeneity can limit the predictive power of current biomarker-guided strategies for chemotherapy. Here we report the engineering of personalized tumour ecosystems that contextually conserve the tumour heterogeneity, and phenocopy the tumour microenvironment using tumour explants maintained in defined tumour grade-matched matrix support and autologous patient serum. The functional response of tumour ecosystems, engineered from 109 patients, to anticancer drugs, together with the corresponding clinical outcomes, is used to train a machine learning algorithm; the learned model is then applied to predict the clinical response in an independent validation group of 55 patients, where we achieve 100% sensitivity in predictions while keeping specificity in a desired high range. The tumour ecosystem and algorithm, together termed the CANScript technology, can emerge as a powerful platform for enabling personalized medicine.

Heparin has been used as a clinical anticoagulant for more than 50 years, making it one of the most effective pharmacological agents known. Much of heparin's activity can be traced to its ability to bind antithrombin III (AT-III). Low molecular weight heparin (LMWH), derived from heparin by its controlled breakdown, maintains much of the antithrombotic activity of heparin without many of the serious side effects. The clinical significance of LMWH has highlighted the need to understand and develop chemical or enzymatic means to generate it. The primary enzymatic tools used for the production of LMWH are the heparinases from Flavobacterium heparinum, specifically heparinases I and II. Using pentasaccharide and hexasaccharide model compounds, we show that heparinases I and II, but not heparinase III, cleave the AT-III binding site, leaving only a partially intact site. Furthermore, we show herein that glucosamine 3-O sulfation at the reducing end of a glycosidic linkage imparts resistance to heparinase I, II, and III cleavage. Finally, we examine the biological and pharmacological consequences of a heparin oligosaccharide that contains only a partial AT-III binding site. We show that such an oligosaccharide lacks some of the functional attributes of heparin-and heparan sulfate-like glycosaminoglycans containing an intact AT-III site.

Previous nuclear magnetic resonance (NMR) studies of unmodified and pseudouridine39-modified tRNA(Lys) anticodon stem loops (ASLs) show that significant structural rearrangements must occur to attain a canonical anticodon loop conformation. The Escherichia coli tRNA(Lys) modifications mnm(5)s(2)U34 and t(6)A37 have indeed been shown to remodel the anticodon loop, although significant dynamic flexibility remains within the weakly stacked U35 and U36 anticodon residues. The present study examines the individual effects of mnm(5)s(2)U34, s(2)U34, t(6)A37, and Mg(2+) on tRNA(Lys) ASLs to decipher how the E. coli modifications accomplish the noncanonical to canonical structural transition. We also investigated the effects of the corresponding human tRNA(Lys,3) versions of the E. coli modifications, using NMR to analyze tRNA ASLs containing the nucleosides mcm(5)U34, mcm(5)s(2)U34, and ms(2)t(6)A37. The human wobble modification has a less dramatic loop remodeling effect, presumably because of the absence of a positive charge on the mcm(5) side chain. Nonspecific magnesium effects appear to play an important role in promoting anticodon stacking. Paradoxically, both t(6)A37 and ms(2)t(6)A37 actually decrease anticodon stacking compared to A37 by promoting U36 bulging. Rather than stack with U36, the t(6)A37 nucleotide in the free tRNAs is prepositioned to form a cross-strand stack with the first codon nucleotide as seen in the recent crystal structures of tRNA(Lys) ASLs bound to the 30S ribosomal subunit. Wobble modifications, t(6)A37, and magnesium each make unique contributions toward promoting canonical tRNA structure in the fundamentally dynamic tRNA(Lys)(UUU) anticodon.