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At least 1,027 records · Page 57

Transcription Factor 4 loss-of-function is associated with deficits in progenitor proliferation and cortical neuron content

Transcription Factor 4 ( TCF4) has been associated with autism, schizophrenia, and other neuropsychiatric disorders. However, how pathological TCF4 mutations affect the human neural tissue is poorly understood. Here, we derive neural progenitor cells, neurons, and brain organoids from skin fibroblasts obtained from children with Pitt-Hopkins Syndrome carrying clinically relevant mutations in TCF4 . We show that neural progenitors bearing these mutations have reduced proliferation and impaired capacity to differentiate into neurons. We identify a mechanism through which TCF4 loss-of-function leads to decreased Wnt signaling and then to diminished expression of SOX genes, culminating in reduced progenitor proliferation in vitro. Moreover, we show reduced cortical neuron content and impaired electrical activity in the patient-derived organoids, phenotypes that were rescued after correction of TCF4 expression or by pharmacological modulation of Wnt signaling. This work delineates pathological mechanisms in neural cells harboring TCF4 mutations and provides a potential target for therapeutic strategies for genetic disorders associated with this gene.

59 BASIC BIOLOGICAL SCIENCES↗

Computational identification of HCV neutralizing antibodies with a common HCDR3 disulfide bond motif in the antibody repertoires of infected individuals

Despite recent success in hepatitis C virus (HCV) treatment using antivirals, an HCV vaccine is still needed to prevent reinfections in treated patients, to avert the emergence of drug-resistant strains, and to provide protection for people with no access to the antiviral therapeutics. The early production of broadly neutralizing antibodies (bNAbs) associates with HCV clearance. Several potent bNAbs bind a conserved HCV glycoprotein E2 epitope using an unusual heavy chain complementarity determining region 3 (HCDR3) containing an intra-loop disulfide bond. Isolation of additional structurally-homologous bNAbs would facilitate the recognition of key determinants of such bNAbs and guide rational vaccine design. Here we report the identification of new antibodies containing an HCDR3 disulfide bond motif using computational screening with the Rosetta software. Using the newly-discovered and already-known members of this antibody family, we review the required HCDR3 amino acid composition and propose determinants for the bent versus straight HCDR3 loop conformation observed in these antibodies.

59 BASIC BIOLOGICAL SCIENCES↗

Identification of $\mathrm{IOMA}$-class neutralizing antibodies targeting the $\mathrm{CD4}$-binding site on the $\mathrm{HIV}$-1 envelope glycoprotein

A major goal of current HIV-1 vaccine design efforts is to induce broadly neutralizing antibodies (bNAbs). The VH1-2-derived bNAb IOMA directed to the CD4-binding site of the HIV-1 envelope glycoprotein is of interest because, unlike the better-known VH1-2-derived VRC01-class bNAbs, it does not require a rare short light chain complementarity-determining region 3 (CDRL3). Here, we describe three IOMA-class NAbs, ACS101-103, with up to 37% breadth, that share many characteristics with IOMA, including an average-length CDRL3. Cryo-electron microscopy revealed that ACS101 shares interactions with those observed with other VH1-2 and VH1-46-class bNAbs, but exhibits a unique binding mode to residues in loop D. Analysis of longitudinal sequences from the patient suggests that a transmitter/founder-virus lacking the N276 glycan might have initiated the development of these NAbs. Together these data strengthen the rationale for germline-targeting vaccination strategies to induce IOMA-class bNAbs and provide a wealth of sequence and structural information to support such strategies.

59 BASIC BIOLOGICAL SCIENCES↗

Inhibiting ACK1-mediated phosphorylation of C-terminal Src kinase counteracts prostate cancer immune checkpoint blockade resistance

Solid tumours are highly refractory to immune checkpoint blockade (ICB) therapies due to the functional impairment of effector T cells and their inefficient trafficking to tumours. T-cell activation is negatively regulated by C-terminal Src kinase (CSK); however, the exact mechanism remains unknown. Here we show that the conserved oncogenic tyrosine kinase Activated CDC42 kinase 1 (ACK1) is able to phosphorylate CSK at Tyrosine 18 (pY18), which enhances CSK function, constraining T-cell activation. Mice deficient in the Tnk2 gene encoding Ack1, are characterized by diminished CSK Y18-phosphorylation and spontaneous activation of CD 8+ and CD 4+ T cells, resulting in inhibited growth of transplanted ICB-resistant tumours. Furthermore, ICB treatment of castration-resistant prostate cancer (CRPC) patients results in re-activation of ACK1/pY18-CSK signalling, confirming the involvement of this pathway in ICB insensitivity. An ACK1 small-molecule inhibitor, (R)-9b, recapitulates inhibition of ICB-resistant tumours, which provides evidence for ACK1 enzymatic activity playing a pivotal role in generating ICB resistance. Overall, our study identifies an important mechanism of ICB resistance and holds potential for expanding the scope of ICB therapy to tumours that are currently unresponsive.

60 APPLIED LIFE SCIENCES↗

Structural interplay of anesthetics and paralytics on muscle nicotinic receptors

General anesthetics and neuromuscular blockers are used together during surgery to stabilize patients in an unconscious state. Anesthetics act mainly by potentiating inhibitory ion channels and inhibiting excitatory ion channels, with the net effect of dampening nervous system excitability. Neuromuscular blockers act by antagonizing nicotinic acetylcholine receptors at the motor endplate; these excitatory ligand-gated ion channels are also inhibited by general anesthetics. The mechanisms by which anesthetics and neuromuscular blockers inhibit nicotinic receptors are poorly understood but underlie safe and effective surgeries. Here we took a direct structural approach to define how a commonly used anesthetic and two neuromuscular blockers act on a muscle-type nicotinic receptor. We discover that the intravenous anesthetic etomidate binds at an intrasubunit site in the transmembrane domain and stabilizes a non-conducting, desensitized-like state of the channel. The depolarizing neuromuscular blocker succinylcholine also stabilizes a desensitized channel but does so through binding to the classical neurotransmitter site. Rocuronium binds in this same neurotransmitter site but locks the receptor in a resting, non-conducting state. Together, this study reveals a structural mechanism for how general anesthetics work on excitatory nicotinic receptors and further rationalizes clinical observations in how general anesthetics and neuromuscular blockers interact.

59 BASIC BIOLOGICAL SCIENCES↗

Molecular mechanism of phosphopeptide neoantigen immunogenicity

Abstract often leads to surface presentation of phosphopeptide neoantigens. However, their role in cancer immunogenicity remains unclear. Here we describe a mechanism by which an HLA-B*0702-specific acute myeloid leukemia phosphoneoantigen, pMLL 747–755 (EPR(pS)PSHSM), is recognized by a cognate T cell receptor named TCR27, a candidate for cancer immunotherapy. We show that the replacement of phosphoserine P 4 with serine or phosphomimetics does not affect pMHC conformation or peptide-MHC affinity but abrogates TCR27-dependent T cell activation and weakens binding between TCR27 and pMHC. Here we describe the crystal structures for TCR27 and cognate pMHC, map of the interface produced by nuclear magnetic resonance, and a ternary complex generated using information-driven protein docking. Our data show that non-covalent interactions between the epitope phosphate group and TCR27 are crucial for TCR specificity. This study supports development of new treatment options for cancer patients through target expansion and TCR optimization.

59 BASIC BIOLOGICAL SCIENCES↗

Selective CK1α degraders exert antiproliferative activity against a broad range of human cancer cell lines

Molecular-glue degraders are small molecules that induce a specific interaction between an E3 ligase and a target protein, resulting in the target proteolysis. The discovery of molecular glue degraders currently relies mostly on screening approaches. Here, we describe screening of a library of cereblon (CRBN) ligands against a panel of patient-derived cancer cell lines, leading to the discovery of SJ7095, a potent degrader of CK1α, IKZF1 and IKZF3 proteins. Through a structure-informed exploration of structure activity relationship (SAR) around this small molecule we develop SJ3149, a selective and potent degrader of CK1α protein in vitro and in vivo. The structure of SJ3149 co-crystalized in complex with CK1α + CRBN + DDB1 provides a rationale for the improved degradation properties of this compound. In a panel of 115 cancer cell lines SJ3149 displays a broad antiproliferative activity profile, which shows statistically significant correlation with MDM2 inhibitor Nutlin-3a. These findings suggest potential utility of selective CK1α degraders for treatment of hematological cancers and solid tumors.

59 BASIC BIOLOGICAL SCIENCES↗

Structural studies of the IFNλ4 receptor complex using cryoEM enabled by protein engineering

Abstract IFNλ4 has posed a conundrum in human immunology since its discovery in 2013, with its expression linked to complications with viral clearance. While genetic and cellular studies revealed the detrimental effects of IFNλ4 expression, extensive structural and functional characterization has been limited by the inability to express and purify the protein, complicating explanations of its paradoxical behavior. In this work, we report a method for robust production of IFNλ4. We then use yeast surface display to affinity-mature IL10Rβ and solve the 72 kilodalton structures of IFNλ4 (3.26 Å) and IFNλ3 (3.00 Å) in complex with their receptors IFNλR1 and IL10Rβ using cryogenic electron microscopy. Comparison of the structures highlights differences in receptor engagement and reveals a distinct 12-degree rotation in overall receptor geometry, providing a potential mechanistic explanation for differences in cell signaling, downstream gene induction, and antiviral activities. Further, we perform a structural analysis using molecular modeling and simulation to identify a unique region of IFNλ4 that, when replaced, enables secretion of the protein from cells. These findings provide a structural and functional understanding of the IFNλ4 protein and enable future comprehensive studies towards correcting IFNλ4 dysfunction in large populations of affected patients.

Science & Technology - Other Topics↗

Computational ranking identifies Plexin-B2 in circulating tumor cell clustering with monocytes in breast cancer metastasis

Abstract Multicellular circulating tumor cell (CTC) clusters can be up to 50 times more efficient than single CTCs in mediating viable metastasis. Here, combining computational ranking and functional determination, we identify the transmembrane protein Plexin-B2 (PLXNB2) as one of the top molecular targets associated with unfavorable distant metastasis-free survival, showing enriched expression in CTC clusters versus single CTCs from patients with advanced breast cancer (mostly female). Loss of PLXNB2 (Plxnb2) reduces the formation of homotypic tumor cell clusters and heterotypic tumor-myeloid cell clusters, reducing spontaneous metastases in female mice bearing human (mouse) breast cancer. Interactions of PLXNB2 with its ligands SEMA4C on tumor cells and SEMA4A on myeloid cells (monocytes) promote homotypic and heterotypic CTC cluster formation, respectively, thereby driving lung metastasis. Global proteomic analysis reveals downstream effectors of the PLXNB2 pathway associated with tumor cell clustering. Thus, PLXNB2 is a therapeutic target for preventing new metastasis in breast cancer.

Science & Technology - Other Topics↗

Multidimensional quantitative phenotypic and molecular analysis reveals neomorphic behaviors of p53 missense mutants

Abstract Mutations in the TP53 tumor suppressor gene occur in >80% of the triple-negative or basal-like breast cancer. To test whether neomorphic functions of specific TP53 missense mutations contribute to phenotypic heterogeneity, we characterized phenotypes of non-transformed MCF10A-derived cell lines expressing the ten most common missense mutant p53 proteins and observed a wide spectrum of phenotypic changes in cell survival, resistance to apoptosis and anoikis, cell migration, invasion and 3D mammosphere architecture. The p53 mutants R248W, R273C, R248Q, and Y220C are the most aggressive while G245S and Y234C are the least, which correlates with survival rates of basal-like breast cancer patients. Interestingly, a crucial amino acid difference at one position—R273C vs. R273H—has drastic changes on cellular phenotype. RNA-Seq and ChIP-Seq analyses show distinct DNA binding properties of different p53 mutants, yielding heterogeneous transcriptomics profiles, and MD simulation provided structural basis of differential DNA binding of different p53 mutants. Integrative statistical and machine-learning-based pathway analysis on gene expression profiles with phenotype vectors across the mutant cell lines identifies quantitative association of multiple pathways including the Hippo/YAP/TAZ pathway with phenotypic aggressiveness. Further, comparative analyses of large transcriptomics datasets on breast cancer cell lines and tumors suggest that dysregulation of the Hippo/YAP/TAZ pathway plays a key role in driving the cellular phenotypes towards basal-like in the presence of more aggressive p53 mutants. Overall, our study describes distinct gain-of-function impacts on protein functions, transcriptional profiles, and cellular behaviors of different p53 missense mutants, which contribute to clinical phenotypic heterogeneity of triple-negative breast tumors.

60 APPLIED LIFE SCIENCES↗

The impact of bilateral injuries on the pathophysiology and functional outcomes of volumetric muscle loss

Volumetric muscle loss (VML)—defined as the irrecoverable loss of skeletal muscle tissue with associated persistent functional deficits—is among the most common and highly debilitating combat-related extremity injuries. This is particularly true in cases of severe polytrauma wherein multiple extremities may be involved as a result of high energy wounding mechanisms. As such, significant investment and effort has been made toward developing a clinically viable intervention capable of restoring the form and function of the affected musculature. While these investigations conducted to date have varied with respect to the species, breed, and sex of the chosen pre-clinical in-vivo model system, the majority of these studies have been performed in unilateral injury models, an aspect which may not fully exemplify the clinical representation of the multiply injured patient. Furthermore, while various components of the basal pathophysiology of VML (e.g., fibrosis and inflammation) have been investigated, relatively little effort has focused on how the pathophysiology and efficacy of pro-regenerative technologies is altered when there are multiple VML injuries. Thus, the purpose of this study was two-fold: (1) to investigate if/how the pathophysiology of unilateral VML injuries differs from bilateral VML injuries and (2) to interrogate the effect of bilateral VML injuries on the efficacy of a well-characterized regenerative therapy, minced muscle autograft (MMG). In contrast to our hypothesis, we show that bilateral VML injuries exhibit a similar systemic inflammatory response and improved muscle functional recovery, compared to unilateral injured animals. Furthermore, MMG treatment was found to only be effective at promoting an increase in functional outcomes in unilateral VML injuries. The findings presented herein add to the growing knowledge base of the pathophysiology of VML, and, importantly, reiterate the importance of comprehensively characterizing preclinical models which are utilized for early-stage screening of putative therapies as they can directly influence the translational research pipeline.

60 APPLIED LIFE SCIENCES↗

A deep generative model for deciphering cellular dynamics and in silico drug discovery in complex diseases

Human diseases are characterized by intricate cellular dynamics. Single-cell transcriptomics provides critical insights, yet a persistent gap remains in computational tools for detailed disease progression analysis and targeted in silico drug interventions. Here we introduce UNAGI, a deep generative neural network tailored to analyse time-series single-cell transcriptomic data. This tool captures the complex cellular dynamics underlying disease progression, enhancing drug perturbation modelling and screening. When applied to a dataset from patients with idiopathic pulmonary fibrosis, UNAGI learns disease-informed cell embeddings that sharpen our understanding of disease progression, leading to the identification of potential therapeutic drug candidates. Validation using proteomics reveals the accuracy of UNAGI’s cellular dynamics analysis, and the use of the fibrotic cocktail-treated human precision-cut lung slices confirms UNAGI’s predictions that nifedipine, an antihypertensive drug, may have anti-fibrotic effects on human tissues. UNAGI’s versatility extends to other diseases, including COVID, demonstrating adaptability and confirming its broader applicability in decoding complex cellular dynamics beyond idiopathic pulmonary fibrosis, amplifying its use in the quest for therapeutic solutions across diverse pathological landscapes.

Neural Network↗

Artificial intelligence in cancer research, diagnosis and therapy

Artificial intelligence and machine learning techniques are breaking into biomedical research and health care, which importantly includes cancer research and oncology, where the potential applications are vast. These include detection and diagnosis of cancer, subtype classification, optimization of cancer treatment and identification of new therapeutic targets in drug discovery. While big data used to train machine learning models may already exist, leveraging this opportunity to realize the full promise of artificial intelligence in both the cancer research space and the clinical space will first require significant obstacles to be surmounted. In this Viewpoint article, we asked four experts for their opinions on how we can begin to implement artificial intelligence while ensuring standards are maintained so as transform cancer diagnosis and the prognosis and treatment of patients with cancer and to drive biological discovery.

60 APPLIED LIFE SCIENCES↗

The NIH Somatic Cell Genome Editing program

The move from reading to writing the human genome offers new opportunities to improve human health. The United States National Institutes of Health (NIH) Somatic Cell Genome Editing (SCGE) Consortium aims to accelerate the development of safer and more-effective methods to edit the genomes of disease-relevant somatic cells in patients, even in tissues that are difficult to reach. Here we discuss the consortium’s plans to develop and benchmark approaches to induce and measure genome modifications, and to define downstream functional consequences of genome editing within human cells. Central to this effort is a rigorous and innovative approach that requires validation of the technology through third-party testing in small and large animals. New genome editors, delivery technologies and methods for tracking edited cells in vivo, as well as newly developed animal models and human biological systems, will be assembled—along with validated datasets—into an SCGE Toolkit, which will be disseminated widely to the biomedical research community. We visualize this toolkit—and the knowledge generated by its applications—as a means to accelerate the clinical development of new therapies for a wide range of conditions.

59 BASIC BIOLOGICAL SCIENCES↗

Cross-HLA targeting of intracellular oncoproteins with peptide-centric CARs

The majority of oncogenic drivers are intracellular proteins, thus constraining their immunotherapeutic targeting to mutated peptides (neoantigens) presented by individual human leukocyte antigen (HLA) allotypes. However, most cancers have a modest mutational burden that is insufficient to generate responses using neoantigen-based therapies. Neuroblastoma is a paediatric cancer that harbours few mutations and is instead driven by epigenetically deregulated transcriptional networks. Here we show that the neuroblastoma immunopeptidome is enriched with peptides derived from proteins that are essential for tumourigenesis and focus on targeting the unmutated peptide QYNPIRTTF, discovered on HLA-A*24:02, which is derived from the neuroblastoma dependency gene and master transcriptional regulator PHOX2B. To target QYNPIRTTF, we developed peptide-centric chimeric antigen receptors (CARs) using a counter-panning strategy with predicted potentially cross-reactive peptides. We further hypothesized that peptide-centric CARs could recognize peptides on additional HLA allotypes when presented in a similar manner. Informed by computational modelling, we showed that PHOX2B peptide-centric CARs also recognize QYNPIRTTF presented by HLA-A*23:01 and the highly divergent HLA-B*14:02. Finally, we demonstrated potent and specific killing of neuroblastoma cells expressing these HLAs in vitro and complete tumour regression in mice. These data suggest that peptide-centric CARs have the potential to vastly expand the pool of immunotherapeutic targets to include non-immunogenic intracellular oncoproteins and widen the population of patients who would benefit from such therapy by breaking conventional HLA restriction.

59 BASIC BIOLOGICAL SCIENCES↗

Genome-scale metabolic reconstruction of 7,302 human microorganisms for personalized medicine

The human microbiome influences the efficacy and safety of a wide variety of commonly prescribed drugs. Designing precision medicine approaches that incorporate microbial metabolism would require strain- and molecule-resolved, scalable computational modeling. Here, we extend our previous resource of genome-scale metabolic reconstructions of human gut microorganisms with a greatly expanded version. AGORA2 (assembly of gut organisms through reconstruction and analysis, version 2) accounts for 7,302 strains, includes strain-resolved drug degradation and biotransformation capabilities for 98 drugs, and was extensively curated based on comparative genomics and literature searches. The microbial reconstructions performed very well against three independently assembled experimental datasets with an accuracy of 0.72 to 0.84, surpassing other reconstruction resources and predicted known microbial drug transformations with an accuracy of 0.81. We demonstrate that AGORA2 enables personalized, strain-resolved modeling by predicting the drug conversion potential of the gut microbiomes from 616 patients with colorectal cancer and controls, which greatly varied between individuals and correlated with age, sex, body mass index and disease stages. AGORA2 serves as a knowledge base for the human microbiome and paves the way to personalized, predictive analysis of host–microbiome metabolic interactions.

59 BASIC BIOLOGICAL SCIENCES↗

Comprehensive characterization of protein–protein interactions perturbed by disease mutations

Technological and computational advances in genomics and interactomics have made it possible to identify how disease mutations perturb protein–protein interaction (PPI) networks within human cells. Here, we show that disease-associated germline variants are significantly enriched in sequences encoding PPI interfaces compared to variants identified in healthy participants from the projects 1000 Genomes and ExAC. Somatic missense mutations are also significantly enriched in PPI interfaces compared to noninterfaces in 10,861 tumor exomes. We computationally identified 470 putative oncoPPIs in a pan-cancer analysis and demonstrate that oncoPPIs are highly correlated with patient survival and drug resistance/sensitivity. Further, we experimentally validate the network effects of 13 oncoPPIs using a systematic binary interaction assay, and also demonstrate the functional consequences of two of these on tumor cell growth. In summary, this human interactome network framework provides a powerful tool for prioritization of alleles with PPI-perturbing mutations to inform pathobiological mechanism- and genotype-based therapeutic discovery.

59 BASIC BIOLOGICAL SCIENCES↗

Genomic analyses implicate noncoding de novo variants in congenital heart disease

A genetic etiology is identified for one-third of patients with congenital heart disease (CHD), with 8% of cases attributable to coding de novo variants (DNVs). To assess the contribution of noncoding DNVs to CHD, we compared genome sequences from 749 CHD probands and their parents with those from 1,611 unaffected trios. Neural network prediction of noncoding DNV transcriptional impact identified a burden of DNVs in individuals with CHD (n = 2,238 DNVs) compared to controls (n = 4,177; P = 8.7 × 10 -4 ). Independent analyses of enhancers showed an excess of DNVs in associated genes (27 genes versus 3.7 expected, P = 1 × 10 -5 ). We observed significant overlap between these transcription-based approaches (odds ratio (OR) = 2.5, 95% confidence interval (CI) 1.1-5.0, P = 5.4 × 10 -3 ). CHD DNVs altered transcription levels in 5 of 31 enhancers assayed. Finally, we observed a DNV burden in RNA-binding-protein regulatory sites (OR = 1.13, 95% CI 1.1-1.2, P = 8.8 × 10 -5 ). Overall, our findings demonstrate an enrichment of potentially disruptive regulatory noncoding DNVs in a fraction of CHD at least as high as that observed for damaging coding DNVs.

60 APPLIED LIFE SCIENCES↗