Biology subjects

Daugherty, P. S.

Publications and source records attributed to Daugherty, P. S..

3 recordsLinked to original sources

bioRxiv2020

Autoantibody landscape of advanced prostate cancer

Although the importance of T-cell immune responses is well appreciated in cancer, autoantibody responses are less well-characterized. Nevertheless, autoantibody responses are of great interest, as they may be concordant with T-cell responses to cancer antigens or predictive of response to cancer immunotherapies. We performed serum epitope repertoire analysis (SERA) on a total of 1,229 serum samples obtained from a cohort of 72 men with metastatic castration-resistant prostate cancer (mCRPC) and 1,157 healthy control patients to characterize the autoantibody landscape of mCRPC. Using whole-genome sequencing results from paired solid-tumor metastasis biopsies and germline specimens, we identified tumor-specific epitopes in 29 mutant and 11 non-mutant proteins. Autoantibody enrichments for the top candidate autoantigen (NY-ESO-1) were validated using ELISA performed on the prostate cancer cohort and an independent cohort of 106 patients with melanoma. Our study recovers antigens of known importance and identifies novel tumor-specific epitopes of translational interest in advanced prostate cancer. Statement of significanceAutoantibodies have been shown to inform treatment response and candidate drug targets in various cancers. We present the first large-scale profiling of autoantibodies in advanced prostate cancer, utilizing a new next-generation sequencing-based approach to antibody profiling to reveal novel cancer-specific antigens and epitopes. Disclosure of Potential Conflicts of InterestJJA reports receiving consulting income from Janssen Biotech and Merck and honoraria from Astellas for speakers fees. MR reports receiving commercial research support from Novartis, Johnson & Johnson, Merck, Astellas, and Medivation, and is a consultant/advisory board member for Constellation Pharmaceuticals, Amgen, Ambrx, Johnson & Johnson, and Bayer. A.R. has received honoraria from consulting with Amgen, Bristol-Myers Squibb, Chugai, Dynavax, Genentech, Merck, Nektar, Novartis, Roche and Sanofi, is or has been a member of the scientific advisory board and holds stock in Advaxis, Arcus Biosciences, Bioncotech Therapeutics, Compugen, CytomX, Five Prime, RAPT, ImaginAb, Isoplexis, Kite-Gilead, Lutris Pharma, Merus, PACT Pharma, Rgenix and Tango Therapeutics. FYF serves on the advisory board for Dendreon, EMD Serono, Janssen Oncology, Ferring, Sanofi, Blue Earth Diagnostics, Celgene, consults for Bayer, Medivation/Astellas, Genetech, and Nutcracker Therapeutics, has honoraria from Clovis Oncology, and is a founder and has an ownership stake in PFS Genomics. SGZ and FYF have patent applications with Decipher Biosciences. SGZ and FYF have a patent application licensed to PFS Genomics. SGZ and FYF have patent applications with Celgene. WAH, RW, KK, PSD, and JCS have ownership of stocks or shares at Serimmune, paid employment at Serimmune, board membership at Serimmune, and patent applications on behalf of Serimmune.

cancer biology↗

bioRxiv2020

Protein-based Immunome Wide Association Studies (PIWAS) for the discovery of significant disease-associated antigens

Identification of the antigens associated with antibodies is vital to understanding immune responses in the context of infection, autoimmunity, and cancer. Discovering antigens at a proteome scale could enable broader identification of antigens that are responsible for generating an immune response or driving a disease state. Although targeted tests for known antigens can be straightforward, discovering antigens at a proteome scale using protein and peptide arrays is time consuming and expensive. We leverage Serum Epitope Repertoire Analysis (SERA), an assay based on a random bacterial display peptide library coupled with NGS, to power the development of Protein-based Immunome Wide Association Study (PIWAS). PIWAS uses proteome-based signals to discover candidate antibody-antigen epitopes that are significantly elevated in a subset of cases compared to controls. After demonstrating statistical power relative to the magnitude and prevalence of effect in synthetic data, we apply PIWAS to systemic lupus erythematosus (SLE, n=31) and observe known autoantigens, Smith and Ribosomal P, within the 22 highest scoring candidate protein antigens across the entire human proteome. We validate the magnitude and location of the SLE specific signal against the Smith family of proteins using a cohort of patients who are positive by predicate anti-Sm tests. Collectively, these results suggest that PIWAS provides a powerful new tool to discover disease-associated serological antigens within any known proteome. Author SummaryInfection, autoimmunity, and cancer frequently induce an antibody response in patients with disease. Identifying the protein antigens that are involved in the antibody response can aid in the development of diagnostics, biomarkers, and therapeutics. To enable high-throughput antigen discovery, we present PIWAS, which leverages the SERA technology to identify antigens at a proteome- and cohort-scale. We demonstrate the ability of PIWAS to identify known autoantigens in SLE. PIWAS represents a major step forward in the ability to discover protein antigens at a proteome scale.

immunology↗

bioRxiv2019

A general approach for identifying protein epitopes targeted by antibody repertoires using whole proteomes

Antibodies are essential to functional immunity, yet the epitopes targeted by antibody repertoires remain largely uncharacterized. To aid in characterization, we developed a generalizable strategy to identify antibody-binding epitopes within individual proteins and entire proteomes. Specifically, we selected antibody-binding peptides for 273 distinct sera out of a random library and identified the peptides using next-generation sequencing. To identify antibody-binding epitopes and the antigens from which these epitopes were derived, we tiled the sequences of candidate antigens into short overlapping subsequences of length k (k-mers). We used the enrichment over background of these k-mers in the antibody-binding peptide dataset to identify antibody-binding epitopes. As a positive control, we used this approach, termed K-mer Tiling of Protein Epitopes (K-TOPE), to identify epitopes targeted by monoclonal and polyclonal antibodies of well-characterized specificity, accurately recovering their known epitopes. K-TOPE characterized a commonly targeted antigen from Rhinovirus A, identifying three epitopes recognized by antibodies present in 83% of sera (n = 250). An analysis of 2,908 proteins from 400 viral taxa that infect humans revealed seven enterovirus epitopes and five Epstein-Barr virus epitopes recognized by >30% of specimens. Analysis of Staphylococcus and Streptococcus proteomes similarly revealed six epitopes recognized by >40% of specimens. These common viral and bacterial epitopes exhibited excellent agreement with previously mapped epitopes. Additionally, we identified 30 HSV2-specific epitopes that were 100% specific against HSV1 in novel and previously reported antigens. The K-TOPE approach thus provides a powerful new tool to elucidate the organisms, antigens, and epitopes targeted by human antibody repertoires.

bioinformatics↗