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Daptomycin is a lipopeptide with bactericidal activity that acts on the cell membrane of enterococci and is often used off-label to treat patients infected with vancomycin-resistant enterococci. However, the emergence of resistance to daptomycin during therapy threatens its usefulness. We performed whole-genome sequencing and characterization of the cell envelope of a clinical pair of vancomycin-resistant Enterococcus faecalis isolates from the blood of a patient with fatal bacteremia; one isolate (S613) was from blood drawn before treatment and the other isolate (R712) was from blood drawn after treatment with daptomycin. The minimal inhibitory concentrations (MICs) of these two isolates were 1 and 12 μg per milliliter, respectively. Gene replacements were made to exchange the alleles found in isolate S613 with those in isolate R712. Isolate R712 had in-frame deletions in three genes. Two genes encoded putative enzymes involved in phospholipid metabolism, GdpD (which denotes glycerophosphoryl diester phosphodiesterase) and Cls (which denotes cardiolipin synthetase), and one gene encoded a putative membrane protein, LiaF (which denotes lipid II cycle-interfering antibiotics protein but whose exact function is not known). LiaF is predicted to be a member of a three-component regulatory system (LiaFSR) involved in the stress-sensing response of the cell envelope to antibiotics. Replacement of the liaF allele of isolate S613 with the liaF allele from isolate R712 quadrupled the MIC of daptomycin, whereas replacement of the gdpD allele had no effect on MIC. Replacement of both the liaF and gdpD alleles of isolate S613 with the liaF and gdpD alleles of isolate R712 raised the daptomycin MIC for isolate S613 to 12 μg per milliliter. As compared with isolate S613, isolate R712 — the daptomycin-resistant isolate — had changes in the structure of the cell envelope and alterations in membrane permeability and membrane potential. Mutations in genes encoding LiaF and a GdpD-family protein were necessary and sufficient for the development of resistance to daptomycin during the treatment of vancomycin-resistant enterococci.

Natural language-based generative artificial intelligence (AI) has become increasingly prevalent in scientific research. Intriguingly, capabilities of generative pre-trained transformer (GPT) language models beyond the scope of natural language tasks have recently been identified. Here we explored how GPT-4 might be able to perform rudimentary structural biology modeling. We prompted GPT-4 to model 3D structures for the 20 standard amino acids and an α-helical polypeptide chain, with the latter incorporating Wolfram mathematical computation. We also used GPT-4 to perform structural interaction analysis between the anti-viral nirmatrelvir and its target, the SARS-CoV-2 main protease. Geometric parameters of the generated structures typically approximated close to experimental references. However, modeling was sporadically error-prone and molecular complexity was not well tolerated. Interaction analysis further revealed the ability of GPT-4 to identify specific amino acid residues involved in ligand binding along with corresponding bond distances. Despite current limitations, we show the current capacity of natural language generative AI to perform basic structural biology modeling and interaction analysis with atomic-scale accuracy.

PurposeDownregulation of miRNA-22 in triple-negative breast cancer (TNBC) is associated with upregulation of eukaryotic elongation 2 factor kinase (eEF2K) protein, which regulates tumor growth, chemoresistance, and tumor immunosurveillance. Moreover, exogenous administration of miRNA-22, loaded in nanoparticles to prevent degradation and improve tumor delivery (termed miRNA-22 nanotherapy), to suppress eEF2K production has shown potential as an investigational therapeutic agent in vivo.MethodsTo evaluate the translational potential of miRNA-22 nanotherapy, we developed a multiscale mechanistic model, calibrated to published in vivo data and extrapolated to the human scale, to describe and quantify the pharmacokinetics and pharmacodynamics of miRNA-22 in virtual patient populations.ResultsOur analysis revealed the dose-response relationship, suggested optimal treatment frequency for miRNA-22 nanotherapy, and highlighted key determinants of therapy response, from which combination with immune checkpoint inhibitors was identified as a candidate strategy for improving treatment outcomes. More importantly, drug synergy was identified between miRNA-22 and standard-of-care drugs against TNBC, providing a basis for rational therapeutic combinations for improved responseConclusionsThe present study highlights the translational potential of miRNA-22 nanotherapy for TNBC in combination with standard-of-care drugs.

We have previously shown that the long non-coding (lnc)RNA ( ; formerly ) functions as a trans-dominant negative oncogene by targeting the previously unrecognized prostate cancer suppressor gene (a homolog of the gene), thereby forming a functional unit within a unique allelic locus in human cells. Here, we investigated the / regulatory axis from early (tumorigenic) to late (biochemical recurrence) genetic events during human prostate cancer progression. The reciprocal and gene expression relationship in paired prostate cancer and adjacent normal prostate was analyzed in two independent retrospective cohorts of clinically annotated cases post-radical prostatectomy: a single-institutional discovery cohort (n=107) and a multi-institutional validation cohort (n=497). We compared the tumor gene expression of and to their corresponding expression in the normal prostate. We also serially examined clinical/pathological variables including time to disease recurrence. We consistently observed increased expression of and decreased expression of in prostate cancer compared with the adjacent normal prostate across all tumor grades and stages. However, there was no association between the relative gene expression levels of or and time to disease recurrence, independent of tumor grades and stages. We concluded that upregulation of the lncRNA and targeted downregulation of the protein-coding gene in prostate cancer could be early (rather than late) molecular events in the progression of human prostate tumorigenesis but are not associated with biochemical recurrence. Further studies of PCA3/PRUNE2 dysregulation are warranted. We received support from the Human Tissue Repository and Tissue Analysis Shared Resource from the Department of Pathology of the University of New Mexico School of Medicine and a pilot award from the University of New Mexico Comprehensive Cancer Center. RP and WA were supported by awards from the Levy-Longenbaugh Donor-Advised Fund and the Prostate Cancer Foundation. EDN reports research fellowship support from the Brazilian National Council for Scientific and Technological Development (CNPq), Brazil, and the Associação Beneficente Alzira Denise Hertzog Silva (ABADHS), Brazil. This work has been funded in part by the NCI Cancer Center Support Grants (CCSG; P30) to the University of New Mexico Comprehensive Cancer Center (CA118100) and the Rutgers Cancer Institute of New Jersey (CA072720).

Lymphatic malformations (LMs) often pose treatment challenges due to a large size or a critical location that could lead to disfigurement, and there are no standardized treatment approaches for either refractory or unresectable cases. We examined the genomic landscape of a patient cohort of LMs ( = 30 cases) that underwent comprehensive genomic profiling using a large-panel next-generation sequencing assay. Immunohistochemical analyses were completed in parallel. These LMs had low mutational burden with hotspot mutations ( = 20) and ( = 5) mutations being most frequent, and mutually exclusive. All LM cases with Kaposi sarcoma-like (kaposiform) histology had mutations. One index patient presented with subacute abdominal pain and was diagnosed with a large retroperitoneal LM harboring a somatic gain-of-function mutation (H1047R). The patient achieved a rapid and durable radiologic complete response, as defined in RECIST1.1, to the PI3Kα inhibitor alpelisib within the context of a personalized -of-1 clinical trial (NCT03941782). In translational correlative studies, canonical PI3Kα pathway activation was confirmed by immunohistochemistry and human LM-derived lymphatic endothelial cells carrying an allele with an activating mutation at the same locus were sensitive to alpelisib treatment in vitro, which was demonstrated by a concentration-dependent drop in measurable impedance, an assessment of cell status. Our findings establish that LM patients with conventional or kaposiform histology have distinct, yet targetable, driver mutations. R.P. and W.A. are supported by awards from the Levy-Longenbaugh Fund. S.G. is supported by awards from the Hugs for Brady Foundation. This work has been funded in part by the NCI Cancer Center Support Grants (CCSG; P30) to the University of Arizona Cancer Center (CA023074), the University of New Mexico Comprehensive Cancer Center (CA118100), and the Rutgers Cancer Institute of New Jersey (CA072720). B.K.M. was supported by National Science Foundation via Graduate Research Fellowship DGE-1143953. NCT03941782.

Vectors mediating strong, durable, and tissue-specific transgene expression are mandatory for safe and effective gene therapy. In settings requiring systemic vector administration, the availability of suited vectors is extremely limited. Here, we present a strategy to select vectors with true specificity for a target tissue from random peptide libraries displayed on adeno-associated virus (AAV) by screening the library under circulation conditions in a murine model. Guiding the in vivo screening by next-generation sequencing, we were able to monitor the selection kinetics and to determine the right time point to discontinue the screening process. The establishment of different rating scores enabled us to identify the most specifically enriched AAV capsid candidates. As proof of concept, a capsid variant was selected that specifically and very efficiently delivers genes to the endothelium of the pulmonary vasculature after intravenous administration. This technical approach of selecting target-specific vectors in vivo is applicable to any given tissue of interest and therefore has broad implications in translational research and medicine.

The mechanism controlling long-chain fatty acid (LCFA) mobilization from adipose tissue is not well understood. Here, we investigated how the LCFA transporter CD36 regulates this process. By using tissue-specific KO mouse models, we showed that CD36 in adipocytes and endothelial cells mediated both LCFA deposition into and release from adipose tissue. We demonstrated the role of adipocytic and endothelial CD36 in promoting tumor growth and chemoresistance conferred by adipose tissue-derived LCFAs. We showed that dynamic cysteine S-acylation of CD36 in adipocytes, endothelial cells, and cancer cells mediated intercellular LCFA transport. We demonstrated that lipolysis induction in adipocytes triggered CD36 deacylation and deglycosylation, as well as its dissociation from interacting proteins, prohibitin-1 (PHB) and annexin 2 (ANX2). Our data indicate that lipolysis triggers caveolar endocytosis and translocation of CD36 from the cell membrane to lipid droplets. This study suggests a mechanism for both outside-in and inside-out cellular LCFA transport regulated by CD36 S-acylation and its interactions with PHB and ANX2.

Checkpoint inhibitor therapy of cancer has led to markedly improved survival of a subset of patients in multiple solid malignant tumor types, yet the factors driving these clinical responses or lack thereof are not known. We have developed a mechanistic mathematical model for better understanding these factors and their relations in order to predict treatment outcome and optimize personal treatment strategies. Here, we present a translational mathematical model dependent on three key parameters for describing efficacy of checkpoint inhibitors in human cancer: tumor growth rate ( ), tumor-immune infiltration ( ), and immunotherapy-mediated amplification of anti-tumor response ( ). The model was calibrated by fitting it to a compiled clinical tumor response dataset (n = 189 patients) obtained from published anti-PD-1 and anti-PD-L1 clinical trials, and then validated on an additional validation cohort (n = 64 patients) obtained from our in-house clinical trials. The derived parameters and were both significantly different between responding versus nonresponding patients. Of note, our model appropriately classified response in 81.4% of patients by using only tumor volume measurements and within 2 months of treatment initiation in a retrospective analysis. The model reliably predicted clinical response to the PD-1/PD-L1 class of checkpoint inhibitors across multiple solid malignant tumor types. Comparison of model parameters to immunohistochemical measurement of PD-L1 and CD8+ T cells confirmed robust relationships between model parameters and their underlying biology. These results have demonstrated reliable methods to inform model parameters directly from biopsy samples, which are conveniently obtainable as early as the start of treatment. Together, these suggest that the model parameters may serve as early and robust biomarkers of the efficacy of checkpoint inhibitor therapy on an individualized per-patient basis. We gratefully acknowledge support from the Andrew Sabin Family Fellowship, Center for Radiation Oncology Research, Sheikh Ahmed Center for Pancreatic Cancer Research, GE Healthcare, Philips Healthcare, and institutional funds from the University of Texas M.D. Anderson Cancer Center. We have also received Cancer Center Support Grants from the National Cancer Institute (P30CA016672 to the University of Texas M.D. Anderson Cancer Center and P30CA072720 the Rutgers Cancer Institute of New Jersey). This research has also been supported in part by grants from the National Science Foundation Grant DMS-1930583 (ZW, VC), the National Institutes of Health (NIH) 1R01CA253865 (ZW, VC), 1U01CA196403 (ZW, VC), 1U01CA213759 (ZW, VC), 1R01CA226537 (ZW, RP, WA, VC), 1R01CA222007 (ZW, VC), U54CA210181 (ZW, VC), and the University of Texas System STARS Award (VC). BC acknowledges support through the SER Cymru II Programme, funded by the European Commission through the Horizon 2020 Marie Skłodowska-Curie Actions (MSCA) COFUND scheme and the Welsh European Funding Office (WEFO) under the European Regional Development Fund (ERDF). EK has also received support from the Project Purple, NIH (U54CA210181, U01CA200468, and U01CA196403), and the Pancreatic Cancer Action Network (16-65-SING). MF was supported through NIH/NCI center grant U54CA210181, R01CA222959, DoD Breast Cancer Research Breakthrough Level IV Award W81XWH-17-1-0389, and the Ernest Cockrell Jr. Presidential Distinguished Chair at Houston Methodist Research Institute. RP and WA received serial research awards from AngelWorks, the Gillson-Longenbaugh Foundation, and the Marcus Foundation. This work was also supported in part by grants from the National Cancer Institute to SHC (R01CA109322, R01CA127483, R01CA208703, and U54CA210181 CITO pilot grant) and to PYP (R01CA140243, R01CA188610, and U54CA210181 CITO pilot grant). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Contemporary cancer treatment strategies are shifting toward targeted therapies to improve efficacy and minimize toxicity. Here, we report the design and preclinical evaluation of MBRC-101, a first-in-class antibody-drug conjugate (ADC) targeting EphA5, a receptor tyrosine kinase with an established role in embryonic development but not extensively studied in cancer. We show that EphA5 is expressed in multiple solid tumors, including cancers of the aerodigestive (non-small cell lung, head and neck, gastric, colon, and pancreatic) and genitourinary (bladder and ovary) tracts, as well as most breast cancer subsets (including triple-negative tumors), with limited expression in normal tissues. MBRC-101 is a humanized anti-EphA5 antibody conjugated to monomethyl auristatin E (MMAE) through a ThioBridge, thereby ensuring stable drug-to-antibody ratio and reducing off-target effects. MBRC-101 showed potent antitumor activity, achieving complete tumor regression in several patient-derived xenograft models. Preclinical Good Laboratory Practice-compliant toxicology studies in rats and nonhuman primates demonstrated that MBRC-101 is well tolerated, with observed toxicities limited to known MMAE off-target effects. These findings establish EphA5 as a therapeutic target in cancer and support the translational development of MBRC-101 as a promising ADC candidate for clinical evaluation, currently in a first-in-human multicenter investigational trial for patients with advanced solid tumors (ClinicalTrials.gov, NCT06014658).