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In vivo inducible reverse genetics in patients' tumors to identify individual therapeutic targets
(2021)
High-throughput sequencing describes multiple alterations in individual tumors, but their functional relevance is often unclear. Clinic-close, individualized molecular model systems are required for functional validation and to identify therapeutic targets of high significance for each patient. Here, we establish a Cre-ERT2-loxP (causes recombination, estrogen receptor mutant T2, locus of X-over P1) based inducible RNAi- (ribonucleic acid interference) mediated gene silencing system in patient-derived xenograft (PDX) models of acute leukemias in vivo. Mimicking anti-cancer therapy in patients, gene inhibition is initiated in mice harboring orthotopic tumors. In fluorochrome guided, competitive in vivo trials, silencing of the apoptosis regulator MCL1 (myeloid cell leukemia sequence 1) correlates to pharmacological MCL1 inhibition in patients´ tumors, demonstrating the ability of the method to detect therapeutic vulnerabilities. The technique identifies a major tumor-maintaining potency of the MLL-AF4 (mixed lineage leukemia, ALL1-fused gene from chromosome 4) fusion, restricted to samples carrying the translocation. DUX4 (double homeobox 4) plays an essential role in patients’ leukemias carrying the recently described DUX4-IGH (immunoglobulin heavy chain) translocation, while the downstream mediator DDIT4L (DNA-damage-inducible transcript 4 like) is identified as therapeutic vulnerability. By individualizing functional genomics in established tumors in vivo, our technique decisively complements the value chain of precision oncology. Being broadly applicable to tumors of all kinds, it will considerably reinforce personalizing anti-cancer treatment in the future.
A plethora of modified nucleotides extends the chemical and conformational space for natural occurring RNAs. tRNAs constitute the class of RNAs with the highest modification rate. The extensive modification modulates their overall stability, the fidelity and efficiency of translation. However, the impact of nucleotide modifications on the local structural dynamics is not well characterized. Here we show that the incorporation of the modified nucleotides in tRNAfMet from Escherichia coli leads to an increase in the local conformational dynamics, ultimately resulting in the stabilization of the overall tertiary structure. Through analysis of the local dynamics by NMR spectroscopic methods we find that, although the overall thermal stability of the tRNA is higher for the modified molecule, the conformational fluctuations on the local level are increased in comparison to an unmodified tRNA. In consequence, the melting of individual base pairs in the unmodified tRNA is determined by high entropic penalties compared to the modified. Further, we find that the modifications lead to a stabilization of long-range interactions harmonizing the stability of the tRNA’s secondary and tertiary structure. Our results demonstrate that the increase in chemical space through introduction of modifications enables the population of otherwise inaccessible conformational substates.
Pseudomonas aeruginosa is a human pathogen that causes health-care associated blood stream infections (BSI). Although P. aeruginosa BSI are associated with high mortality rates, the clinical relevance of pathogen-derived prognostic biomarker to identify patients at risk for unfavorable outcome remains largely unexplored. We found novel pathogen-derived prognostic biomarker candidates by applying a multi-omics approach on a multicenter sepsis patient cohort. Multi-level Cox regression was used to investigate the relation between patient characteristics and pathogen features (2298 accessory genes, 1078 core protein levels, 107 parsimony-informative variations in reported virulence factors) with 30-day mortality. Our analysis revealed that presence of the helP gene encoding a putative DEAD-box helicase was independently associated with a fatal outcome (hazard ratio 2.01, p = 0.05). helP is located within a region related to the pathogenicity island PAPI-1 in close proximity to a pil gene cluster, which has been associated with horizontal gene transfer. Besides helP, elevated protein levels of the bacterial flagellum protein FliL (hazard ratio 3.44, p < 0.001) and of a bacterioferritin-like protein (hazard ratio 1.74, p = 0.003) increased the risk of death, while high protein levels of a putative aminotransferase were associated with an improved outcome (hazard ratio 0.12, p < 0.001). The prognostic potential of biomarker candidates and clinical factors was confirmed with different machine learning approaches using training and hold-out datasets. The helP genotype appeared the most attractive biomarker for clinical risk stratification due to its relevant predictive power and ease of detection.