Next generation immuno-oncology tumor profiling using a rapid, non-invasive, computational biophysics biomarker in early-stage breast cancer

BackgroundImmuno-oncology (IO) therapies targeting the PD-1/PD-L1 axis, such as immune checkpoint inhibitor (ICI) antibodies, have emerged as promising treatments for early-stage breast cancer (ESBC). Despite immunotherapy's clinical significance, the number of benefiting patients remains small, and the therapy can prompt severe immune-related events. Current pathologic and transcriptomic predictions of IO response are limited in terms of accuracy and rely on single-site biopsies, which cannot fully account for tumor heterogeneity. In addition, transcriptomic analyses are costly and time-consuming. We therefore constructed a computational biomarker coupling biophysical simulations and artificial intelligence-based tissue segmentation of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRIs), enabling IO response prediction across the entire tumor.MethodsBy analyzing both single-cell and whole-tissue RNA-seq data from non-IO-treated ESBC patients, we associated gene expression levels of the PD-1/PD-L1 axis with local tumor biology. PD-L1 expression was then linked to biophysical features derived from DCE-MRIs to generate spatially- and temporally-resolved atlases (virtual tumors) of tumor biology, as well as the TumorIO biomarker of IO response. We quantified TumorIO within patient virtual tumors (n = 63) using integrative modeling to train and develop a corresponding TumorIO Score.ResultsWe validated the TumorIO biomarker and TumorIO Score in a small, independent cohort of IO-treated patients (n = 17) and correctly predicted pathologic complete response (pCR) in 15/17 individuals (88.2% accuracy), comprising 10/12 in triple negative breast cancer (TNBC) and 5/5 in HR+/HER2- tumors. We applied the TumorIO Score in a virtual clinical trial (n = 292) simulating ICI administration in an IO-naïve cohort that underwent standard chemotherapy. Using this approach, we predicted pCR rates of 67.1% for TNBC and 17.9% for HR+/HER2- tumors with addition of IO therapy; comparing favorably to empiric pCR rates derived from published trials utilizing ICI in both cancer subtypes.ConclusionThe TumorIO biomarker and TumorIO Score represent a next generation approach using integrative biophysical analysis to assess cancer responsiveness to immunotherapy. This computational biomarker performs as well as PD-L1 transcript levels in identifying a patient's likelihood of pCR following anti-PD-1 IO therapy. The TumorIO biomarker allows for rapid IO profiling of tumors and may confer high clinical decision impact to further enable personalized oncologic care

Functional Amyloids Composed of Phenol Soluble Modulins Stabilize Staphylococcus aureus Biofilms

Staphylococcus aureus is an opportunistic pathogen that colonizes the skin and mucosal surfaces of mammals. Persistent staphylococcal infections often involve surface-associated communities called biofilms. Here we report the discovery of a novel extracellular fibril structure that promotes S. aureus biofilm integrity. Biochemical and genetic analysis has revealed that these fibers have amyloid-like properties and consist of small peptides called phenol soluble modulins (PSMs). Mutants unable to produce PSMs were susceptible to biofilm disassembly by matrix degrading enzymes and mechanical stress. Previous work has associated PSMs with biofilm disassembly, and we present data showing that soluble PSM peptides disperse biofilms while polymerized peptides do not. This work suggests the PSMs' aggregation into amyloid fibers modulates their biological activity and role in biofilms

Monobodies as enabling tools for structural and mechanistic biology

Monobodies, built with the scaffold of the fibronectin type III domain, are among the most well-established synthetic binding proteins. They promote crystallization of challenging molecular systems. They have strong tendency to bind to functional sites and thus serve as drug-like molecules that perturb the biological functions of their targets. Monobodies lack disulfide bonds and thus they are particularly suited as genetically encoded reagents to be used intracellularly. This article reviews recent monobody-enabled studies that reveal new structures, molecular mechanisms and potential therapeutic opportunities. A systematic analysis of the crystal structures of monobody-target complexes suggests important attributes that make monobodies effective crystallization chaperones

Minimalist design of water-soluble cross-β architecture

Demonstrated successes of protein design and engineering suggest significant potential to produce diverse protein architectures and assemblies beyond those found in nature. Here, we describe a new class of synthetic protein architecture through the successful design and atomic structures of water-soluble cross-β proteins. The cross-β motif is formed from the lamination of successive β-sheet layers, and it is abundantly observed in the core of insoluble amyloid fibrils associated with protein-misfolding diseases. Despite its prominence, cross-β has been designed only in the context of insoluble aggregates of peptides or proteins. Cross-β’s recalcitrance to protein engineering and conspicuous absence among the known atomic structures of natural proteins thus makes it a challenging target for design in a water-soluble form. Through comparative analysis of the cross-β structures of fibril-forming peptides, we identified rows of hydrophobic residues (“ladders”) running across β-strands of each β-sheet layer as a minimal component of the cross-β motif. Grafting a single ladder of hydrophobic residues designed from the Alzheimer’s amyloid-β peptide onto a large β-sheet protein formed a dimeric protein with a cross-β architecture that remained water-soluble, as revealed by solution analysis and x-ray crystal structures. These results demonstrate that the cross-β motif is a stable architecture in water-soluble polypeptides and can be readily designed. Our results provide a new route for accessing the cross-β structure and expanding the scope of protein design

Structures of single‐layer β‐sheet proteins evolved from β‐hairpin repeats

Free-standing single-layer β-sheets are extremely rare in naturally occurring proteins, even though β-sheet motifs are ubiquitous. Here we report the crystal structures of three homologous, single-layer, anti-parallel β-sheet proteins, comprised of three or four twisted β-hairpin repeats. The structures reveal that, in addition to the hydrogen bond network characteristic of β-sheets, additional hydrophobic interactions mediated by small clusters of residues adjacent to the turns likely play a significant role in the structural stability and compensate for the lack of a compact hydrophobic core. These structures enabled identification of a family of secreted proteins that are broadly distributed in bacteria from the human gut microbiome and are putatively involved in the metabolism of complex carbohydrates. A conserved surface patch, rich in solvent-exposed tyrosine residues, was identified on the concave surface of the β-sheet. These new modular single-layer β-sheet proteins may serve as a new model system for studying folding and design of β-rich proteins

Diagnostic accuracy of coronary CT angiography using 3rd-generation dual-source CT and automated tube voltage selection: clinical application in a non-obese and obese patient population

Purpose: To investigate diagnostic accuracy of 3rd-generation dual-source CT (DSCT) coronary angiography in obese and non-obese patients. Methods: We retrospectively analyzed 76 patients who underwent coronary CT angiography (CCTA) and invasive coronary angiography. Prospectively ECG-triggered acquisition was performed with automated tube voltage selection (ATVS). Patients were dichotomized based on body mass index in groups A (<30 kg/m2, n = 37) and B (≥30 kg/m2, n = 39) and based on tube voltage in groups C (<120 kV, n = 46) and D (120 kV, n = 30). Coronary arteries were assessed for significant stenoses (≥50 % luminal narrowing) and diagnostic accuracy was calculated. Results: Per-patient overall sensitivity, specificity, positive predictive value, negative predictive value (NPV) and accuracy were 96.9 %, 95.5 %, 93.9 %, 97.7 % and 96.1 %, respectively. Sensitivity and NPV were lower in groups B and D compared to groups A and C, but no statistically significant differences were observed (group A vs. B: sensitivity, 100.0 % vs. 93.3 %, p = 0.9493; NPV, 100 % vs. 95.5 %, p = 0.9812; group C vs. D: sensitivity, 100.0 % vs. 92.3 %, p = 0.8462; NPV, 100.0 % vs. 94.1 %, p = 0.8285). Conclusion: CCTA using 3rd-generation DSCT and (ATVS) provides high diagnostic accuracy in both non-obese and obese patients. Key Points: • Coronary CTA provides high diagnostic accuracy in non-obese and obese patients. • Diagnostic accuracy between obese and non-obese patients showed no significant difference. • <120 kV studies were performed in 44 % of obese patients. • Current radiation dose-saving approaches can be applied independent of body habitus

A designer ligand specific for Kv1.3 channels from a scorpion neurotoxin-based library.

Venomous animals immobilize prey using protein toxins that act on ion channels and other targets of biological importance. Broad use of toxins for biomedical research, diagnosis, and therapy has been limited by inadequate target discrimination, for example, among ion channel subtypes. Here, a synthetic toxin is produced by a new strategy to be specific for human Kv1.3 channels, critical regulators of immune T cells. A phage display library of 11,200 de novo proteins is designed using the alpha-KTx scaffold of 31 scorpion toxin sequences known or predicted to bind to potassium channels. Mokatoxin-1 (moka1) is isolated by affinity selection on purified target. Moka1 blocks Kv1.3 at nanomolar levels that do not inhibit Kv1.1, Kv1.2, or KCa1.1. As a result, moka1 suppresses CD3/28-induced cytokine secretion by T cells without cross-reactive gastrointestinal hyperactivity. The 3D structure of moka1 rationalizes its specificity and validates the engineering approach, revealing a unique interaction surface supported on an alpha-KTx scaffold. This scaffold-based/target-biased strategy overcomes many obstacles to production of selective toxins

Magnesium transporter 1 (MAGT1) deficiency causes selective defects in N-linked glycosylation and expression of immune-response genes

Magnesium transporter 1 (MAGT1) critically mediates magnesium homeostasis in eukaryotes and is highly-conserved across different evolutionary branches. In humans, loss– of–function mutations in the MAGT1 gene cause X-linked magnesium deficiency with Epstein-Barr virus (EBV) infection and neoplasia (XMEN), a disease that has a broad range of clinical and immunological consequences. We have previously shown that EBV susceptibility in XMEN is associated with defective expression of the antiviral natural-killer group 2 member D (NKG2D) protein and abnormal Mg transport. New evidence suggests that MAGT1 is the human homolog of the yeast OST3/ OST6 proteins that form an integral part of the N-linked glycosylation complex, although the exact contributions of these perturbations in the glycosylation pathway to disease pathogenesis are still unknown. Using MS-based glycoproteomics, along with CRISPR/Cas9-KO cell lines, natural killer cell-killing assays, and RNA-Seq experiments, we now demonstrate that humans lacking functional MAGT1 have a selective deficiency in both immune and nonimmune glycoproteins, and we identified several critical glycosylation defects in important immune-response proteins and in the expression of genes involved in immunity, particularly CD28. We show that MAGT1 function is partly interchangeable with that of the paralog protein tumor-suppressor candidate 3 (TUSC3) but that each protein has a different tissue distribution in humans. We observed that MAGT1-dependent glycosylation is sensitive to Mg levels and that reduced Mg impairs immune-cell function via the loss of specific glycoproteins. Our findings reveal that defects in protein glycosylation and gene expression underlie immune defects in an inherited disease due to MAGT1 deficiency

Data_Sheet_3_Next generation immuno-oncology tumor profiling using a rapid, non-invasive, computational biophysics biomarker in early-stage breast cancer.PDF

BackgroundImmuno-oncology (IO) therapies targeting the PD-1/PD-L1 axis, such as immune checkpoint inhibitor (ICI) antibodies, have emerged as promising treatments for early-stage breast cancer (ESBC). Despite immunotherapy's clinical significance, the number of benefiting patients remains small, and the therapy can prompt severe immune-related events. Current pathologic and transcriptomic predictions of IO response are limited in terms of accuracy and rely on single-site biopsies, which cannot fully account for tumor heterogeneity. In addition, transcriptomic analyses are costly and time-consuming. We therefore constructed a computational biomarker coupling biophysical simulations and artificial intelligence-based tissue segmentation of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRIs), enabling IO response prediction across the entire tumor.MethodsBy analyzing both single-cell and whole-tissue RNA-seq data from non-IO-treated ESBC patients, we associated gene expression levels of the PD-1/PD-L1 axis with local tumor biology. PD-L1 expression was then linked to biophysical features derived from DCE-MRIs to generate spatially- and temporally-resolved atlases (virtual tumors) of tumor biology, as well as the TumorIO biomarker of IO response. We quantified TumorIO within patient virtual tumors (n = 63) using integrative modeling to train and develop a corresponding TumorIO Score.ResultsWe validated the TumorIO biomarker and TumorIO Score in a small, independent cohort of IO-treated patients (n = 17) and correctly predicted pathologic complete response (pCR) in 15/17 individuals (88.2% accuracy), comprising 10/12 in triple negative breast cancer (TNBC) and 5/5 in HR+/HER2- tumors. We applied the TumorIO Score in a virtual clinical trial (n = 292) simulating ICI administration in an IO-naïve cohort that underwent standard chemotherapy. Using this approach, we predicted pCR rates of 67.1% for TNBC and 17.9% for HR+/HER2- tumors with addition of IO therapy; comparing favorably to empiric pCR rates derived from published trials utilizing ICI in both cancer subtypes.ConclusionThe TumorIO biomarker and TumorIO Score represent a next generation approach using integrative biophysical analysis to assess cancer responsiveness to immunotherapy. This computational biomarker performs as well as PD-L1 transcript levels in identifying a patient's likelihood of pCR following anti-PD-1 IO therapy. The TumorIO biomarker allows for rapid IO profiling of tumors and may confer high clinical decision impact to further enable personalized oncologic care.</p