The use of fluoroproline in MUC1 antigen enables efficient detection of antibodies in patients with prostate cancer

A structure-based design of a new generation of tumor-associated glycopeptides with improved affinity against two anti-MUC1 antibodies is described. These unique antigens feature a fluorinated proline residue, such as a (4S)-4-fluoro-l-proline or 4,4-difluoro-l-proline, at the most immunogenic domain. Binding assays using biolayer interferometry reveal 3-fold to 10-fold affinity improvement with respect to the natural (glyco)peptides. According to X-ray crystallography and MD simulations, the fluorinated residues stabilize the antigen-antibody complex by enhancing key CH/π interactions. Interestingly, a notable improvement in detection of cancer-associated anti-MUC1 antibodies from serum of patients with prostate cancer is achieved with the non-natural antigens, which proves that these derivatives can be considered better diagnostic tools than the natural antigen for prostate cancer.We thank the Ministerio de Economía y Competitividad (projects CTQ2015-67727-R, UNLR13-4E-1931, CTQ2013-44367-C2-2-P, CTQ2015-64597-C2-1P, and BFU2016-75633-P). I.A.B. thanks the Asociación Española Contra el Cancer en La Rioja for a grant. I.S.A. and G.J.L.B. thank FCT Portugal (Ph.D. studentship and FCT Investigator, respectively) and EPSRC. G.J.L.B. holds a Royal Society URF and an ERC StG (TagIt). F.C. and G.J.L.B thank the EU (Marie-Sklodowska Curie ITN, Protein Conjugates). R.H-G. thanks Agencia Aragonesa para la Investigación y Desarrollo (ARAID) and the Diputación General de Aragón (DGA, B89) for financial support. The research leading to these results has also received funding from the FP7 (2007-2013) under BioStruct-X (grant agreement no. 283570 and BIOSTRUCTX_5186). We thank synchrotron radiation source DIAMOND (Oxford) and beamline I04 (number of experiment mx10121-19). The Hokkaido University group acknowledges JSPS KAKENHI grant no. 25220206 and JSPS Wakate B KAKENHI grant no. 24710242. We also thank CESGA (Santiago de Compostela) for computer support.Peer reviewedPeer Reviewe

Structure-Guided Approach for the Development of MUC1-Glycopeptide-Based Cancer Vaccines with Predictable Responses

Mucin-1 (MUC1) glycopeptides are exceptional candidates for potential cancer vaccines. However, their autoantigenic nature often results in a weak immune response. To overcome this drawback, we carefully engineered synthetic antigens with precise chemical modifications. To be effective and stimulate an anti-MUC1 response, artificial antigens must mimic the conformational dynamics of natural antigens in solution and have an equivalent or higher binding affinity to anti-MUC1 antibodies than their natural counterparts. As a proof of concept, we have developed a glycopeptide that contains noncanonical amino acid (2S,3R)-3-hydroxynorvaline. The unnatural antigen fulfills these two properties and effectively mimics the threonine-derived antigen. On the one hand, conformational analysis in water shows that this surrogate explores a landscape similar to that of the natural variant. On the other hand, the presence of an additional methylene group in the side chain of this analog compared to the threonine residue enhances a CH/π interaction in the antigen/antibody complex. Despite an enthalpy–entropy balance, this synthetic glycopeptide has a binding affinity slightly higher than that of its natural counterpart. When conjugated with gold nanoparticles, the vaccine candidate stimulates the formation of specific anti-MUC1 IgG antibodies in mice and shows efficacy comparable to that of the natural derivative. The antibodies also exhibit cross-reactivity to selectively target, for example, human breast cancer cells. This investigation relied on numerous analytical (e.g., NMR spectroscopy and X-ray crystallography) and biophysical techniques and molecular dynamics simulations to characterize the antigen–antibody interactions. This workflow streamlines the synthetic process, saves time, and reduces the need for extensive, animal-intensive immunization procedures. These advances underscore the promise of structure-based rational design in the advance of cancer vaccine development

Probing altered receptor specificities of antigenically drifting human H3N2 viruses by chemoenzymatic synthesis, NMR, and modeling

Prototypic receptors for human influenza viruses are N-glycans carrying α2,6-linked sialosides. Due to immune pressure, A/H3N2 influenza viruses have emerged with altered receptor specificities that bind α2,6-linked sialosides presented on extended N-acetyl-lactosamine (LacNAc) chains. Here, binding modes of such drifted hemagglutinin’s (HAs) are examined by chemoenzymatic synthesis of N-glycans having 13C-labeled monosaccharides at strategic positions. The labeled glycans are employed in 2D STD-1H by 13C-HSQC NMR experiments to pinpoint which monosaccharides of the extended LacNAc chain engage with evolutionarily distinct HAs. The NMR data in combination with computation and mutagenesis demonstrate that mutations distal to the receptor binding domain of recent HAs create an extended binding site that accommodates with the extended LacNAc chain. A fluorine containing sialoside is used as NMR probe to derive relative binding affinities and confirms the contribution of the extended LacNAc chain for binding

Structure-Guided Approach for the Development of MUC1-Glycopeptide-Based Cancer Vaccines with Predictable Responses

Mucin-1(MUC1)glycopeptidesareexceptionalcandidatesforpotentialcancervaccines.However,theirautoantigenicnatureoftenresultsinaweakimmuneresponse.Toovercomethisdrawback,wecarefullyengineeredsyntheticantigenswithprecisechemicalmodifications.Tobeeffectiveandstimulateananti-MUC1response,artificialantigensmustmimictheconforma-tionaldynamicsofnaturalantigensinsolutionandhaveanequivalentorhigherbindingaffinitytoanti-MUC1antibodiesthantheirnaturalcounterparts.Asa proofofconcept,wehavedevelopeda glycopeptidethatcontainsnoncanonicalaminoacid(2S,3R)-3-hydroxynorvaline.Theunnaturalantigenfulfillsthesetwopropertiesandeffectivelymimicsthethreonine-derivedantigen.Ontheonehand,conformationalanalysisinwatershowsthatthissurrogateexploresalandscapesimilartothatofthenaturalvariant.Ontheotherhand,thepresenceofanadditionalmethylenegroupinthesidechainofthisanalogcomparedtothethreonineresidueenhancesa CH/interactionintheantigen/antibodycomplex.Despiteanenthalpyentropybalance,thissyntheticglycopeptidehasabindingaffinityslightlyhigherthanthatofitsnaturalcounterpart.Whenconjugatedwithgoldnanoparticles,thevaccinecandidatestimulatestheformationofspecificanti-MUC1IgGantibodiesinmiceandshowsefficacycomparabletothatofthenaturalderivative.Theantibodiesalsoexhibitcross-reactivitytoselectivelytarget,forexample,humanbreastcancercells.Thisinvestigationreliedonnumerousanalytical(e.g.,NMRspectroscopyandX-raycrystallography)andbiophysicaltechniquesandmoleculardynamicssimulationstocharacterizetheantigenantibodyinteractions.Thisworkflowstreamlinesthesyntheticprocess,savestime,andreducestheneedforextensive,animal-intensiveimmunizationprocedures.Theseadvancesunderscorethepromiseofstructure-basedrationaldesignintheadvanceofcance

Solving patients with rare diseases through programmatic reanalysis of genome-phenome data.

Funder: EC | EC Seventh Framework Programm | FP7 Health (FP7-HEALTH - Specific Programme "Cooperation": Health); doi: https://doi.org/10.13039/100011272; Grant(s): 305444, 305444Funder: Ministerio de Economía y Competitividad (Ministry of Economy and Competitiveness); doi: https://doi.org/10.13039/501100003329Funder: Generalitat de Catalunya (Government of Catalonia); doi: https://doi.org/10.13039/501100002809Funder: EC | European Regional Development Fund (Europski Fond za Regionalni Razvoj); doi: https://doi.org/10.13039/501100008530Funder: Instituto Nacional de Bioinformática ELIXIR Implementation Studies Centro de Excelencia Severo OchoaFunder: EC | EC Seventh Framework Programm | FP7 Health (FP7-HEALTH - Specific Programme "Cooperation": Health)Reanalysis of inconclusive exome/genome sequencing data increases the diagnosis yield of patients with rare diseases. However, the cost and efforts required for reanalysis prevent its routine implementation in research and clinical environments. The Solve-RD project aims to reveal the molecular causes underlying undiagnosed rare diseases. One of the goals is to implement innovative approaches to reanalyse the exomes and genomes from thousands of well-studied undiagnosed cases. The raw genomic data is submitted to Solve-RD through the RD-Connect Genome-Phenome Analysis Platform (GPAP) together with standardised phenotypic and pedigree data. We have developed a programmatic workflow to reanalyse genome-phenome data. It uses the RD-Connect GPAP's Application Programming Interface (API) and relies on the big-data technologies upon which the system is built. We have applied the workflow to prioritise rare known pathogenic variants from 4411 undiagnosed cases. The queries returned an average of 1.45 variants per case, which first were evaluated in bulk by a panel of disease experts and afterwards specifically by the submitter of each case. A total of 120 index cases (21.2% of prioritised cases, 2.7% of all exome/genome-negative samples) have already been solved, with others being under investigation. The implementation of solutions as the one described here provide the technical framework to enable periodic case-level data re-evaluation in clinical settings, as recommended by the American College of Medical Genetics

Solve-RD: systematic pan-European data sharing and collaborative analysis to solve rare diseases.

For the first time in Europe hundreds of rare disease (RD) experts team up to actively share and jointly analyse existing patient's data. Solve-RD is a Horizon 2020-supported EU flagship project bringing together >300 clinicians, scientists, and patient representatives of 51 sites from 15 countries. Solve-RD is built upon a core group of four European Reference Networks (ERNs; ERN-ITHACA, ERN-RND, ERN-Euro NMD, ERN-GENTURIS) which annually see more than 270,000 RD patients with respective pathologies. The main ambition is to solve unsolved rare diseases for which a molecular cause is not yet known. This is achieved through an innovative clinical research environment that introduces novel ways to organise expertise and data. Two major approaches are being pursued (i) massive data re-analysis of >19,000 unsolved rare disease patients and (ii) novel combined -omics approaches. The minimum requirement to be eligible for the analysis activities is an inconclusive exome that can be shared with controlled access. The first preliminary data re-analysis has already diagnosed 255 cases form 8393 exomes/genome datasets. This unprecedented degree of collaboration focused on sharing of data and expertise shall identify many new disease genes and enable diagnosis of many so far undiagnosed patients from all over Europe

Twist exome capture allows for lower average sequence coverage in clinical exome sequencing

Background Exome and genome sequencing are the predominant techniques in the diagnosis and research of genetic disorders. Sufficient, uniform and reproducible/consistent sequence coverage is a main determinant for the sensitivity to detect single-nucleotide (SNVs) and copy number variants (CNVs). Here we compared the ability to obtain comprehensive exome coverage for recent exome capture kits and genome sequencing techniques. Results We compared three different widely used enrichment kits (Agilent SureSelect Human All Exon V5, Agilent SureSelect Human All Exon V7 and Twist Bioscience) as well as short-read and long-read WGS. We show that the Twist exome capture significantly improves complete coverage and coverage uniformity across coding regions compared to other exome capture kits. Twist performance is comparable to that of both short- and long-read whole genome sequencing. Additionally, we show that even at a reduced average coverage of 70× there is only minimal loss in sensitivity for SNV and CNV detection. Conclusion We conclude that exome sequencing with Twist represents a significant improvement and could be performed at lower sequence coverage compared to other exome capture techniques

A Solve-RD ClinVar-based reanalysis of 1522 index cases from ERN-ITHACA reveals common pitfalls and misinterpretations in exome sequencing

Purpose Within the Solve-RD project (https://solve-rd.eu/), the European Reference Network for Intellectual disability, TeleHealth, Autism and Congenital Anomalies aimed to investigate whether a reanalysis of exomes from unsolved cases based on ClinVar annotations could establish additional diagnoses. We present the results of the “ClinVar low-hanging fruit” reanalysis, reasons for the failure of previous analyses, and lessons learned. Methods Data from the first 3576 exomes (1522 probands and 2054 relatives) collected from European Reference Network for Intellectual disability, TeleHealth, Autism and Congenital Anomalies was reanalyzed by the Solve-RD consortium by evaluating for the presence of single-nucleotide variant, and small insertions and deletions already reported as (likely) pathogenic in ClinVar. Variants were filtered according to frequency, genotype, and mode of inheritance and reinterpreted. Results We identified causal variants in 59 cases (3.9%), 50 of them also raised by other approaches and 9 leading to new diagnoses, highlighting interpretation challenges: variants in genes not known to be involved in human disease at the time of the first analysis, misleading genotypes, or variants undetected by local pipelines (variants in off-target regions, low quality filters, low allelic balance, or high frequency). Conclusion The “ClinVar low-hanging fruit” analysis represents an effective, fast, and easy approach to recover causal variants from exome sequencing data, herewith contributing to the reduction of the diagnostic deadlock