IMPORTANCE: The Drug-Gene Interaction Database (DGIdb) has a long history of driving hypothesis generation for biomedical research through the careful curation of drug-gene interaction data from primary and secondary sources with supporting literature. Recent advances in large-language model (LLM) and artificial intelligence (AI) technologies have enabled new paradigms for knowledge extraction and biocuration. The accelerating growth of biomedical literature presents a significant challenge for maintaining up-to-date interaction data. With more than 38 million citations indexed in PubMed alone, new strategies must evolve to identify and incorporate new interaction data into DGIdb. OBJECTIVE: Identify new cost-effective AI curation strategies for incorporating new drug-gene interactions into DGIdb. METHODS: We present a methodology that leverages deterministic natural language processing techniques, existing harmonization frameworks, and AI-assisted curation to systematically narrow the literature space and identify new drug-gene interactions from published studies for inclusion in DGIdb. RESULTS: We demonstrate the use of lemmatization to prioritize a set of 100 abstracts containing high amounts of interaction words for downstream AI curation. From our set of abstracts, we were then able to identify 137 drug-gene interactions via an AI curation task, with 121 (88.3%) of these interactions being completely novel to DGIdb. A human expert evaluator reviewed this interaction set and was able to validate 134 of 137 (97.8%) interactions as being valid based on the text provided. CONCLUSION: Taken together, our results highlight a promising, cost-effective method of ingesting new interactions into DGIdb. ### Competing Interest Statement The authors have declared no competing interest. National Human Genome Research Institute, https://ror.org/00baak391, R00HG010157

Background Identifying genetic mechanisms of inborn errors of immunity (IEI) is important for diagnosis and treatment of patients, yet most patients with suspected IEI have negative genetic testing results. Genetic mosaicism is an emerging mechanism of IEI, but it is challenging to identify. Objective We used a discovery-based approach to identify mosaic variants in genes relevant to immune dysregulation in patient and healthy cohorts. Methods We developed custom panels for high-depth sequencing of genes known or hypothesized to cause dominant immune dysregulation. Samples from 452 patients with immune dysregulation (affected) and 154 currently healthy were sequenced using 71- or 101-gene targeted panels. Results We identified mosaic variants in 9.5% of undiagnosed patients and 7.8% of healthy individuals. Using a strategy to predict pathogenicity of variants in IEI, 33% of variants identified in patients were predicted to be likely pathogenic or pathogenic, while no mosaic variants in healthy individuals were predicted to be pathogenic. Genes with mosaicism in >1 affected undiagnosed patients included FAS, STAT3, CARD11, CARD14, NRAS, TNFAIP3, NLRP3, and IKZF2. Four patients had variants in FAS with allele fractions <5% in blood but highly enriched in double-negative T cells, diagnostic for somatic FAS autoimmune lymphoproliferative syndrome. Conclusion These findings establish the utility of a high-depth sequencing panel to identify mosaic variants and demonstrate that mosaicism in immune-relevant genes is present in healthy individuals.

In this commentary, we describe how the Clinical Genome Resource’s (ClinGen’s) application programming interface-based microservices accelerate growth and dissemination of knowledge about human genetic variation. By exposing findable, accessible, interoperable, reusable, and AI-ready variant data, ClinGen lays a foundation for next-generation software applications, AI systems, and variant classification workflows.

Personalized neoantigen (neoAg) vaccines have shown clinical promise in solid tumors 1-8 , yet their efficacy and mechanism of action in hematopoietic malignancies remain poorly defined 9-11 . Herein, we establish an immunocompetent syngeneic A20 B-cell lymphoma platform to test the efficacy of neoAg vaccines used either as mono- or combinatorial therapies with other immunotherapies 12-17 . Whereas subcutaneous A20 tumors were refractory to single-agent αPD-1 or αCTLA4 therapy, they were eradicated in a T cell-dependent manner in 90% of syngeneic hosts treated with dual immune checkpoint therapy (dual ICT, i.e., αPD-1 + αCTLA4). By mapping antigen specificity of dual-ICT-elicited T cells, we identified and validated dominant endogenous A20 MHC-I and MHC-II neoantigens and designed therapeutic synthetic long peptide (SLP) vaccines containing these neoepitopes. This vaccine (A20 neoVAX) promoted robust neoAg-specific CD4□ and CD8□ T cell responses in naïve syngeneic BALB/c mice and induced tumor rejection in ∼70% of subcutaneous tumor-bearing mice. In addition, nearly all mice rejected their subcutaneous A20 tumors when A20 neoVAX was combined with αPD-1. To render the results of this study more physiologic, we developed a systemic A20 lymphoma model and found that dual ICT failed to control tumor progression and A20 neoVAX delayed tumor progression and prolonged animal survival but did not induce tumor rejection. In contrast, A20 neoVAX plus dual ICT achieved durable systemic tumor elimination. Mechanistically, the combination of A20 neoVAX plus dual ICT amplified priming of A20 neoAg-specific T cells, prevented T cell dysfunction, sustained the cytotoxic capacity of tumor-specific CD8 + T cells, and induced Th1-skewing of CD4 + T cells in tumor and peripheral compartments. To increase the clinical relevance of these findings and to minimize potential adverse events in tumor-bearing, therapeutically treated individuals, we substituted CD8-targeted cytokine muteins (CD8-IL2 or CD8-IL21) for αCTLA4. These agents represent genetically modified forms of IL-2 or IL-21 that selectively stimulate CD8 + T cells but have significantly reduced capacity to activate chronic inflammation and immunosuppressive functions of other immune cells. Whereas mice bearing systemic A20 lymphoma treated with either nothing, A20 neoVAX, or A20 neoVAX + CD8-IL2 failed to control tumor outgrowth, 66.7% of tumor-bearing mice treated with A20 neoVAX + CD8-IL2 + αPD-1 rejected their tumors. In similar experiments in which CD8-IL21 was substituted for CD8-IL2, tumor clearance was also observed in two-thirds of A20-bearing mice but now rejection occurred in the absence of αPD1. Together, these data define a framework for optimal personalized neoAg vaccination in B-lymphoma and demonstrate that neoAg vaccines can safely synergize with CD8 + T cell-selective immunotherapies to prevent T-cell dysfunction and generate durable systemic anti-tumor immunity.

Pancreatic ductal adenocarcinoma (PDAC) is unresponsive to standard immunotherapies despite harboring cancer neoantigens capable of eliciting T cell responses. We completed two phase 1 clinical trials (NCT03956056 and NCT03122106) evaluating safety and immunogenicity of synthetic long peptide (SLP) and DNA personalized cancer vaccines (PCVs). PCVs were administered after resection and adjuvant chemotherapy. Tumor/normal whole-exome sequencing, RNA sequencing, and pVACtools were used to identify and prioritize candidate PCV neoantigens. PCVs were well tolerated without any grade ≥3 adverse events. Neoantigen-specific responses were demonstrated by interferon-γ enzyme-linked immunospot and intracellular cytokine staining. Expanded T cell receptor clonotypes were sequenced and transduced into autologous peripheral blood mononuclear cells to confirm neoantigen specificity. When compared with a contemporaneous institutional propensity-matched cohort, PCV patients demonstrated a trend toward prolonged median overall survival (4.4 versus 3.5 years, log-rank P = 0.23). Overall, PDAC PCVs are safe and feasible and elicit polyclonal T cell responses, linking prioritized cancer neoantigens to functional antitumor immunity.

Abstract Neoantigens are tumor-specific molecules arising from somatic alterations in cancer cells and have garnered significant interest due to their immunogenic potential. Consequently, numerous computational pipelines have been developed to identify these targets. However, systematic comparisons between neopeptide generation tools are lacking, and there is no consensus on how to handle different mutation types.To address this gap, we compared the neopeptide sequences generated by four widely used tools: the Mutated Peptide Generator (MPG) from the Cancer Epitope Database and Analysis Resource (CEDAR), the Personalized Variant Antigens by Cancer Sequencing (pVACseq), the Mutated Peptide eXtractor and Informer (MuPeXI), and the Neoantigen Prediction Pipeline (NeoPredPipe). We applied these tools to somatic mutations from the Catalogue of Somatic Mutations in Cancer (COSMIC) v102 and validated the results with experimentally validated neoantigens curated in the CEDAR database.In total, 25% of the COSMIC mutations were considered by at least one method to generate neopeptides. The methods showed considerable variability, as only 22% of the neopeptides were generated by all tools. Overall, 29% of the discrepancies in neopeptide generation were attributed to different criteria used to select mutations or transcripts for downstream analysis. The remaining discrepancies were caused by differences in the algorithms used to handle and modify reference sequences into mutated neopeptides. Experimentally validated neoepitopes from CEDAR comprised only 0.005% of the total generated neopeptides. While most neoepitopes were accurately generated by the four methods, 10% were not consistently identified across the tools.These findings underscore the need for methodological standardization to ensure reliable and reproducible neoantigen discovery. To our knowledge, this is the first comprehensive evaluation of neoantigen pipelines focused specifically on neopeptide sequence generation. Citation Format: Ibel Carri, Angela Frentzen Worley, Ashmitaa Logandha Ramamoorthy Premlal, Gauri Renjith, Malachi Griffith, Jason Greenbaum, Alessandro Sette, Bjoern Peters, Zeynep Kosaloglu-Yalcin. A comparative study of neoantigen discovery pipelines uncovers discrepancies in the generation of mutated neopeptide sequences [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(8_Suppl):Abstract nr LB161.

AbstractPurpose: Standard care for high-grade gliomas (HGG) involves maximal surgical resection followed by radiation and temozolomide. Postoperative adjuvant therapy frequently causes lymphopenia, which is associated with poor prognosis. Interleukin 7 (IL7) is essential for lymphocyte development, homeostasis, and survival. NT-I7 (efineptakin alfa), a long-acting recombinant IL7, reverses lymphopenia and improves survival in murine glioma models. However, the safety, maximum tolerated dose (MTD), and impact of NT-I7 on immune cells in patients with HGG remain unknown. Patients and Methods: We conducted a phase I trial (NCT03687957) examining the MTD and effect of NT-I7 on lymphocytes in patients with newly diagnosed HGG. The primary endpoint was dose-limiting toxicity; secondary endpoints included absolute lymphocyte count (ALC) changes over time, overall response, progression-free survival, and overall survival. Exploratory endpoints included immune profiling at different time points using single-cell RNA sequencing (scRNA-seq) in a subset of patients. Results: NT-I7 was well tolerated with a MTD of 720 µg/kg. Moreover, NT-I7 significantly increased ALCs for more than 12 weeks in duration. Early elevations in CD4+, CD8+ T cells and NK cells further coincided with increased TNF and CXCL9 cytokine levels. Comprehensive immune profiling of peripheral blood T cells revealed selective clonotype expansion within CD8+, but not CD4+, T cells following NT-I7 administration. Finally, a subset of our patients with MGMT promoter–unmethylated glioblastoma, which are typically associated with a poorer prognosis, demonstrated promising clinical responses. Conclusions: NT-I7 has the potential to maintain and increase lymphocyte counts in patients with HGG and warrants further investigation, particularly in combination with immune-based therapies.

SUMMARY:The druggable genome encompasses the genes that are known or predicted to interact with drugs. The Drug-Gene Interaction Database (DGIdb) provides an integrated resource for discovering and contextualizing these interactions, supporting a broad range of research and clinical applications. DGIdb is currently accessed through structured web interfaces and API calls, requiring users to translate natural-language questions into database-specific query patterns. To allow for the use of DGIdb through natural language, we developed the DGIdb Model Context Protocol (MCP) server, which allows large language models (LLMs) access to up-to-date information through the DGIdb API. We demonstrate that the MCP server improves an LLM's ability to answer questions requiring accurate, up-to-date biomedical knowledge drawn from structured external resources. AVAILABILITY AND IMPLEMENTATION:The DGIdb MCP server is detailed at https://github.com/dgidb/dgidb-mcp-server and includes instructions for accessing the server through the Claude desktop app.

Background Mucosal melanomas (MM) arise from mucosal melanocytes at various anatomical sites. These tumors are rare, highly aggressive, and often associated with poor outcomes. Current treatments, including immune checkpoint inhibitors, show limited efficacy in advanced disease. Compared with cutaneous melanomas, there is a lack of data on the immunogenicity and interferon (IFN)-γ sensitivity of MM. In this study, we examined these features in sino-nasal melanomas (SN-MM) cell lines and clinical samples using microscopy and functional genomics.Methods The immune contexture of SN-MM was analyzed by immunohistochemistry on 48 tumor biopsies. RNA sequencing and mass spectrometry-based proteomic approaches were used to study the IFN-γ receptor (IFNGR) pathways in five patient-derived SN-MM cell lines. Moreover, their IFN-γ sensitivity, in terms of cell viability, IFNGR/JAK/STAT signaling pathway and IFN-γ inducible proteins, was evaluated by flow cytometry and immunoblots. Neoantigen prediction was performed through integrated whole exome sequencing and RNA-sequencing analysis using pVAC-Seq. Immune effector functions were evaluated in co-culture in vitro assays.Results SN-MM tumors are mainly immune “desert” with few tumor-infiltrating lymphocytes and contain immunosuppressive macrophages, features linked to poor prognosis; moreover, tumor cells are largely CD274/programmed death-ligand 1 negative. SN-MM cell lines express transcripts for melanocytic and cancer testis antigens; moreover, sequencing analysis identified a repertoire of high-confidence neoantigens, including candidates derived from recurrently mutated oncogenic drivers. Functional assays revealed that SN-MM cells are susceptible to NK cell-mediated killing. In terms of IFN-γ sensitivity, SN-MM cells show normal surface expression of IFNGR and maintain the integrity of the IFNGR/JAK/STAT signaling pathway. Transcriptomic and proteomic analyses demonstrate that SN-MM cell lines, as a group, respond to IFN-γ by upregulating genes involved in immune recognition and antigen presentation. In 60% of SN-MM lines, IFN-γ also induces cytotoxic and anti-proliferative effects, the release of CXCL10 and upregulation of CD274/PD-L1. The remaining SN-MM cell lines, characterized by poor differentiation, show refractoriness to these effects.Conclusions SN-MM displays an immune-desert phenotype yet retains intrinsic immunogenicity. Most tumors preserve functional IFN-γ signaling, while poorly differentiated cells show resistance to IFN-γ-mediated effects. These findings underscore heterogeneity in immune responsiveness and support functional immune profiling to refine immunotherapy strategies in MM.

Mantle cell lymphoma (MCL) is a B-cell non-Hodgkin lymphoma characterized by heterogeneous clinical courses despite a common pathobiological initiating event. In this work we explore the genomic variants that characterize MCL and integrate transcriptomic data to comprehensively describe MCL biology. We performed whole exome sequencing (WES) on 28 tumor-normal pairs (lymph node and skin, respectively), as well as whole genome sequencing (WGS) and RNA sequencing on subsets of samples. We used established DNA and RNA analysis pipelines to detect single-nucleotide variants (SNV) and indels, structural variants, copy-number alterations, and RNA fusions. The canonical t(11;14)(q13;q32) CCND1::IGH translocation was detected in 8 of 10 WGS samples. Structural variant analysis additionally identified recurrent rearrangements involving KMT2A and PAFAH1B2. SNV and indel analyses revealed frequent mutations in ATM, TP53, CCND1, IGH, and NOTCH1. ATM exhibited diverse variant classes, including missense mutations, frameshift mutations, deletions, and duplications, while all detected NOTCH1 mutations were predicted loss-of-function frameshift variants. Copy-number analysis identified recurrent losses affecting DNA damage response genes, including TP53 and ATM, and recurrent gains involving transcriptional regulators and oncogenic signaling genes. Integrated pathway analysis demonstrated enrichment of transcriptional misregulation, DNA repair, PI3K/AKT signaling, and interleukin signaling pathways. We also identified recurrent alterations in candidate genes, including ASXL1, suggesting additional mechanisms of epigenetic dysregulation in MCL. Together, these findings provide a comprehensive description of somatic alterations in MCL and demonstrate that diverse genomic lesions converge on common pathways involved in genomic instability, transcriptional regulation, and tumor survival.

Abstract Chimeric Antigen Receptor Dendritic Cells (CAR-DCs) represent a new class of immunotherapy designed to overcome the key limitations of CAR-T and immune checkpoint blockade (ICB) in solid tumors. By engineering conventional dendritic cells (cDCs) with a tumor-targeting CAR delivered via non-integrating mRNA, we have harnessed the intrinsic ability of DCs to cross-prime a broad repertoire of antitumor CD8+ T cells. This approach merges the precision of CAR technology with the natural antigen-presenting potency of DCs, enabling broad immune activation by inducing polyclonal CD8+ T-cell responses that extend beyond CAR-restricted epitopes. To enable clinical advancement, we have developed a scalable human manufacturing process that reliably produces >300 million CAR-DCs, overcoming a longstanding barrier to the translational deployment of DC-based therapies. Immunotherapies such as CAR-T and ICB have transformed hematologic cancer treatment but remain ineffective in many solid tumors due to finite target antigens and dependance on pre-existing tumor-reactive T cells. To overcome these challenges, we engineered type I conventional DCs with a CAR recognizing B7-H3, a clinically relevant solid and liquid tumor antigen. In vitro, B7-H3 CAR-DCs displayed enhanced uptake of diverse tumor antigens, maturation, and superior cross-presentation of tumor derived antigens to CD8+ T cells, driving potent cytotoxic T-cell activation. In vivo, using a C57BL/6 syngeneic 1956 sarcoma model comprised of 75% B7-H3+ and 25% B7-H3- tumor cells, untreated mice exhibited progressive disease. In contrast, both intratumoral and intravenous administration of B7-H3 CAR-DCs induced complete to almost complete tumor regression and confer durable protection upon rechallenge, demonstrating the establishment of robust, target-independent immunity. Analysis of tumor-draining lymph nodes (tdLNs) revealed that B7-H3 CAR-DCs delivered substantially greater amounts of tumor antigen to tdLNs. Correspondingly, transcriptional profiling of tdLN CD8+ T cells revealed signatures of enhanced activation, increased proliferative potential, and a shift toward memory formation which are hallmarks of efficient cross-priming. Mass spectrometry of MHC-I-cross presented peptides and tetramer analyses demonstrated CAR-DCs generated a broad expansion of endogenous tumor neoantigen-specific CD8+ T cells, confirming strong and effective diversification of the antitumor T-cell response. Together, these results position mRNA-engineered CAR-DCs as a first-in-class, translationally ready cell therapy platform that integrates antigen specificity, broadening of the antitumor T-cell response, durable memory formation, and GMP-compatible large-scale manufacturing thereby supporting rapid advancement toward IND-enabling studies and clinical evaluation in solid tumors. Citation Format: Shelby L. Namen, Gaurav Pandey, Teri Naismith, Colin Willoughby, Lizzie Longtine, Usman Panni, Cheryl F. Lichti, Kartik Singhal, Malachi Griffith, Carl DeSelm. A novel, first in class chimeric antigen receptor dendritic cell platform driving broad and durable antitumor immunity in solid tumors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 4008.

Advancements in immunogenomics and immuno-oncology have enabled the development of personalized cancer vaccines (PCVs) that target cancer cell-specific somatic variants. A subset of these variants produce neoantigens that, when presented on tumor cells by MHC molecules, have the potential to elicit a robust and specific immune response. To date, there are over one hundred interventional studies listed on clinicaltrials.gov that explore the use of PCVs. We have supported a number of these trials through the creation of bioinformatic pipelines, tools, and procedures for the identification of patient-specific neoantigen candidates. While many of these steps have been automated, the final selection of neoantigen candidates often relies on expert manual review, creating a bottleneck that limits scalability and full automation of PCV workflows. Addressing this challenge, we introduce NEAT (Neoantigen Evaluation & Automated Triage), a machine learning-based approach that enables automated neoantigen candidate prioritization and supports the transition toward more scalable and reproducible PCV design. We implemented a prediction model trained and tested on existing vaccine design results from 33 patients and 1,943 peptides, across 3 clinical trials, including 439 peptides prioritized for PCV inclusion. This model uses features such as tumor variant allele frequency, RNA expression, driver gene status, binding/presentation scores, and transcript support level to automatically predict whether a peptide will be accepted, rejected, or require further human review before inclusion in a vaccine. The model achieved a sensitivity of 0.847 and specificity of 0.924, with an area under the curve of 0.955. The model predictions have been incorporated in pVACtools v7.0.0. By integrating this model into the vaccine development pipeline, we foresee a significant reduction in the time required to transition from patient sample collection to vaccine manufacturing, thereby enhancing the efficiency and scalability of PCV production.

Feline oral squamous cell carcinoma (FOSCC) and human head and neck squamous cell carcinoma (HNSCC) are the 4th most common malignant neoplasms in cats and humans. Most cats are not treated due to the poor prognosis and die of their disease within a few months of diagnosis. In humans, despite surgery, radiation therapy, and chemotherapy, 1/3 of patients develop loco-regional recurrence within 5 years. FOSCC has commonly been proposed as a model for HNSCC since FOSCC is a spontaneous model and exhibits similar biologic behaviour, treatment course, and outcome to the human disease. The objective of this study was to identify genetic similarities and differences with HNSCC, therapeutic targets, and possible causes of FOSCC through whole exome sequencing. Thirty-six matched normal FOSCC tumours and three matched normal chronic gingivostomatitis lesions were sequenced with a previously validated custom Roche Nimblegen exome reagent, based on the Felis_catus_9.0 genome assembly, covering 35.7 Mb. The exome libraries were pooled and sequenced on the Illumina Novaseq6000 as 2 × 150 bp reads. The data was analysed with the McDonnell Genome Institute's (MGI) cancer informatics pipelines, namely the Genome Modelling System (GMS), which was adapted to the feline genome. TP53 harboured consequential variants in 71% of the FOSCC tumours and was the most commonly mutated gene. Consequential variants in TTN were seen in 18% tumours and consequential variants in FSIP2, LRP1B, RYR2 were seen 9% of tumours. Genes with highly recurrent copy number variants (CNVs) included CKDN2A, PTEN, and MYC. TMB was very low, 0-1.6 (mean 0.66). Six cats had a history of chronic gingivostomatitis for years before the diagnosis of FOSCC. Despite the low TMB, the genomic landscape of FOSCC parallels HPV-negative HNSCC. Aside from TP53, recurrent small-scale mutations in FOSCC were uncommon, but recurrent CNVs were common. FOSCC is a genetically and clinically heterogenous cancer. A multifactorial cause is suspected. Chronic gingivostomatitis, immunosuppression, and/or viral infection may be associated with FOSCC in young cats.

With the rise of checkpoint blockade therapies and neoantigen-based vaccines reaching later-stage trials, there is a growing need for computational tools to identify and prioritize neoantigens. pVACtools, initially introduced in 20161, is an open-source informatic suite designed to support basic and translational neoantigen research. pVACtools assists prediction, prioritization, and visualization of neoantigens, as well as design of neoantigen-based therapies. We describe several major advances to pVACtools since the last update: (1) expanded neoantigen quality and safety assessment features, including support for peptide presentation scoring, immunogenicity prediction, anchor residue analysis, reference proteome similarity, percentile score calculation; (2) addition of pVACsplice, a new tool for predicting neoantigens from tumor-specific cis-splicing mutations; (3) addition of pVACbind, a flexible tool that supports noncanonical neoantigen sources; (4) improvement in neoantigen selection strategies; (5) a substantially improved pVACvector algorithm that achieves higher DNA/mRNA vector vaccine design success rates with shorter runtimes; (6) new utilities to support synthetic long peptide vaccine design; (7) extended prediction support for many non-human species; and (8) addition of pVACcompare, a tool to support comparison between two pVACseq results. Together, these updates reinforce pVACtools as the field's most comprehensive toolkit for neoantigen research, from basic discovery to the design and execution of personalized cancer vaccine clinical trials.

Congenital heart disease (CHD) affects ~1% of live births, yet the genetic basis of many cases remains unresolved. Uniparental disomy (UPD), the inheritance of both homologous chromosomes from one parent, is often overlooked. We developed TrioMix-UPD, an integrated short- and long-read sequencing framework for UPD detection and classification. Applying it to 3,740 CHD trios, we identified 12 UPD events, representing a 6.57-fold enrichment relative to the general population. Both advanced maternal age and enrichment of rare inherited variants in synaptonemal complex genes implicated meiotic chromosome segregation defects in UPD risk. Within UPD regions, we identified pathogenic homozygous variants in PIEZO1 and GLYR1 and nominate MESD as a novel CHD candidate gene. Functional studies in zebrafish and human cells recapitulated patient-specific cardiac phenotypes. Differential methylation analyses implicated imprinting dysregulation, including at the Prader-Willi critical region. Collectively, these findings establish UPD as an underrecognized contributor to CHD.

The occurrence of both non-Hodgkin lymphoma (NHL) and classic Hodgkin lymphoma (cHL) in an individual patient (hereafter referred to as composite lymphoma) is a relatively rare and poorly characterized phenomenon. We hypothesized that analysis of the shared and divergent mutations harbored by composite lymphomas might shed light on genetic drivers of composite lymphomagenesis. We performed exome sequencing of two cases of composite NHL and cHL, and validated somatic variants using the AmpliSeq platform. Additionally, we utilized B-cell receptor sequencing of the immunoglobulin heavy chain (IGH) gene region as a tool to provide an orthogonal comparison of the composite lymphomas. Interestingly, both cases contained stop gain mutations in TNFRSF14 that were shared between the cHL and NHL samples. Other genes with shared somatic variants of potential biologic significance included TP53, SRSF6, PLCG2, BCL10, and PCLO. Furthermore, sequencing of the B-cell receptor immunoglobulin heavy chain (IGH) gene region revealed clones with common V(D)J gene usage in the NHL and cHL cases. Our data suggest a common precursor in these two cases of composite lymphoma. The shared somatic variants we identified may represent early events in lymphomagenesis and potential therapeutic targets.

Glioblastoma is a fatal disease with a median prognosis of 12-18 months. Recent studies have shown encouraging results using neoantigen-based vaccines to stimulate glioblastoma-directed immune responses, but overall immunogenicity has been low. Here, we report the results of an open-label, single-arm, phase 1 clinical trial (GT-20) to evaluate the safety and feasibility (primary endpoints) as well as immunogenicity and preliminary clinical activity (secondary endpoints) of GNOS-PV01 monotherapy, a DNA-based personalized therapeutic cancer vaccine administered following surgical resection and radiation for patients with MGMT unmethylated glioblastoma. The GT-20 study vaccinated nine patients, using up to 40 neoantigens per patient (range, 17-40) without causing any serious adverse events, unexpected toxicities or dose-limiting toxicities. The vaccine induced activation and expansion of circulating peripheral T cells in all evaluated patients, except one who was being treated with dexamethasone. The secondary endpoint was to evaluate 6 month progression-free survival and 12 month overall survival; each observed in 66.7% of patients. Median progression-free survival was 8.5 months, median overall survival was 16.3 months and survival at 24 months was 33%, including one long-term survivor still alive 4 years from the time of initial surgery. This study met the pre-specified endpoints and supports the use of GNOS-PV01 as a potentially impactful component of glioblastoma immunotherapy. ClinicalTrials.gov: NCT04015700 .

PURPOSE:The Clinical Genome Resource (ClinGen) Von Hippel-Lindau (VHL) Variant Curation Expert Panel (VCEP) has created variant classification specifications tailored to the VHL gene, including phenotype-driven and evidence-based criteria, utilizing somatic and germline mutational hotspots, along with functional and in silico data. METHODS:Using the American College of Medical Genetics and Genomics guidance and the ClinGen Sequence Variant Interpretation recommendations, the VCEP made substantial modifications to 8 evidence codes (PVS1, PS3, PS4, PM1, BS2, BS3, BS4, and BP5), whereas 14 had minor changes, and 6 were not used (PM3, PP2, BP1, PP4, PP5/BP6). The VHL VCEP applied 2 literature sets of over >428 articles in Clinical Interpretations of Variants in Cancer and >8700 structured annotations using Hypothesis. RESULTS:From 31 pilot variants, 15 remained pathogenic/likely pathogenic, and 9 resolved to benign through the stand-alone benign evidence code, whereas 7 variants with initial uncertain classifications lacking additional evidence, remained uncertain. CONCLUSION:The versioned VHL VCEP Specifications are publicly available in the ClinGen Criteria Specifications Registry and will enhance the transparency and consistency of variant classifications for this highly sequenced hereditary cancer gene.