E Protein-Driven iNKT Subset Modulation Shapes Early Immune Responses during Influenza a Virus Infection

American Journal of Respiratory Cell and Molecular Biology · 2026-03-21

Invariant natural killer T (iNKT) cells play a critical role in the early phases of the response to Influenza A virus (IAV) infection by influencing inflammation and immune regulation, but the impact of the different iNKT functional subsets (iNKT1, iNKT2, and iNKT17) in these responses is unclear. We used genetically altered mouse strains with normal numbers of iNKT cells, but different iNKT subset representation (NKTWT and NKTET2) to analyze the impact of different iNKT functional subsets on IAV infection outcomes. We show that IAV-infected NKTET2 mice have reduced weight loss, diminished myeloid recruitment and activation, and a 40% reduction in lung-infected areas compared with controls. This was accompanied by lower expression of inflammatory mediators (Ifna, Isg15, Ifit1) and chemoattractants Ccl2 and Cxcl2, along with elevated levels of type III interferon (Ifnl3). scRNAseq analysis of iNKTs suggests that these changes are driven by quantitative differences in iNKT responses, which are predominantly type I in NKTWT mice but type 17 in NKTET2 mice. These differences correlate with higher levels of Il22b and Il1b in NKTET2 mice lungs. Altogether our results indicate that changes in iNKT subset representation impact the outcome of IAV infections by changing the character of the early immune response.

Abstract 3598: Investigating divergent ER+and ER-breast cancer subtype risks by using oppositely associated genetic variants

Cancer Research · 2026-04-03

Abstract Breast cancer is the second most common cause of cancer-related deaths among women in the United States, with its incidence increasing each year. Estrogen receptor-negative (ER-) breast cancers are particularly aggressive and less responsive to conventional treatments compared to estrogen receptor-positive (ER+) types, though they exhibit higher immunogenicity and better responses to immunotherapies. This study focuses on identifying single nucleotide polymorphisms (SNPs) that are oppositely associated between ER+ and ER- breast cancers, meaning that the presence of a SNP increases the risk of one subtype while decreasing the risk of the other subtype. We identified 481 SNPs from the Breast Cancer Association Consortium (BCAC) that were oppositely associated between subtypes (p < 0.1) and cross-validated these associations using data from breast cancer patients in The Cancer Genome Atlas (TCGA), imputed using the TOPMED imputation server. Our findings revealed 45 SNPs associated with increased ER+ risk but decreased ER- risk and 2 SNPs associated with increased ER- risk but decreased ER+ risk that were concordant between the BCAC and TCGA datasets. Of the concordant SNPs that increased ER+ risk, the majority mapped to a region of chromosome 11 near the known tumor suppressor gene ATM; however, one SNP on chromosome 10 (10:21471086:C/T) has been previously shown to increase circulating IGF-1 and decrease colorectal cancer risk to a greater extent in women than men. Further analysis using the CIBERSORTx tool showed that this SNP was associated with increased infiltration of perivascular-like immature cells in the tumor microenvironment. Of the SNPs that increased ER- risk, one localized to a poorly described antisense non-coding transcript of the DLX2 gene which has been implicated in breast cancer, while the other localized to an intron of the PTPRN2 gene that is implicated in type 1 diabetes mellitus and many cancers. While this study is limited by its focus on European women and the small sample size of ER- cases, the results offer preliminary insight into inherited variants that may differentially influence ER+ and ER- disease, supporting future work aimed at clarifying the pathways that contribute to subtype-specific risk, immune infiltration, and treatment response. Citation Format: Phillip Schofield, Meghana Pagadala, Timothy Sears, Hannah K. Carter. Investigating divergent ER+and ER-breast cancer subtype risks by using oppositely associated genetic variants [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 3598.

NeoPrecis: Enhancing Immunotherapy Response Prediction through Integration of Qualified Immunogenicity and Clonality-Aware Neoantigen Landscapes

bioRxiv (Cold Spring Harbor Laboratory) · 2025-07-27 · 1 citations

Despite the transformative impact of cancer immunotherapy, the need for improved patient stratification remains critical due to suboptimal response rates. While neoantigens are central to anti-tumor immunity, current metrics like tumor mutation burden are limited by their neglect of immunogenicity and tumor heterogeneity. We present NeoPrecis, a computational framework designed to refine neoantigen characterization across MHC-I and MHC-II pathways and integrate tumor clonality to improve immunotherapy response prediction. NeoPrecis features an interpretable T-cell recognition model that reveals the critical influence of MHC molecules on TCR recognition beyond mere antigen presentation. Benefit HLA alleles identified through model-driven contribution analysis exhibit significant predictive power for patient outcomes in immune checkpoint inhibitor treatment (melanoma: p-value = 0.04; NSCLC: p-value = 0.01). Applying NeoPrecis to immunotherapy-treated tumors, we show the clonality-aware neoantigen landscape improves response prediction in melanoma and heterogeneous NSCLC, achieving 11% and 20% improvement of AUROC compared to TMB respectively. Heterogeneous NSCLCs, more common among never smokers, retain more subclonal neoantigens due to lower immunoediting pressure, where NeoPrecis better captures the varying prevalence of neoantigens. We propose NeoPrecis as a more comprehensive evaluative framework for neoantigen assessment by incorporating both immunogenicity and tumor clonality, offering insights into the link between collective quality of neoantigen landscapes and immunotherapy response.

Aberrant Splicing Burden Predicts Immune Infiltration and Prognosis in Head and Neck Squamous Cell Carcinomas

Head & Neck · 2025-08-04

BACKGROUND: The role of alternative splicing events (ASEs) in immune evasion and prognosis in head and neck squamous cell carcinoma (HNSC) is not well characterized. METHODS: Using The Cancer Genome Atlas data, we identified ASEs (using our novel algorithm OutSplice) and characterized associations between splice burden, immune infiltration (quantified by xCell) and prognosis with multivariable logistic regression and survival models. RESULTS: HSNC tumors with low splice burden and high immune infiltration had significantly better prognosis than tumors with high splice burden and low immune infiltration when controlling for age, pathologic stage, HPV status, and tumor mutational burden (hazard ratio = 0.61). High splice burden predicted decreased immune infiltration in HNSC, which was validated in five other cancer types and supported by murine models of oral squamous cell carcinoma. CONCLUSIONS: High splicing burden, as defined by OutSplice, is a novel biomarker to predict poor both immune infiltration and prognosis in HNSC.

Association of HOXB13 G84E With Prostate Cancer Among 592,158 Men

Journal of the National Comprehensive Cancer Network · 2025-09-15

BACKGROUND: The HOXB13 c.G251G>A:p.G84E (rs138213197) variant is associated with an increased risk of prostate cancer (PrCa); however, its link to aggressive PrCa remains controversial. Limited data from large, population-based cohorts are available to inform genetic counseling and clarify the PrCa risk associated with this variant. PATIENTS AND METHODS: We identified individuals heterozygous for HOXB13 p.G84E or homozygous wild-type among 592,158 male participants in single nucleotide polymorphism genotyping data from the Veterans Health Administration (VA) Million Veteran Program (MVP). Individuals with PrCa were identified, and Cox proportional hazards models were used to estimate age-specific risk of developing PrCa. In a subset of patients who underwent their first prostate biopsy within the VA health system, a multivariable logistic regression model-adjusting for known PrCa risk factors-was used to assess PrCa risk. RESULTS: Of the MVP participants, 1,660 (0.3%) were heterozygous for HOXB13 p.G84E. Heterozygosity was significantly associated with risk of any PrCa (hazard ratio [HR], 3.17 [95% CI, 2.90-3.46]; P<2.0E-16), metastatic PrCa (HR, 2.99 [95% CI, 2.32-3.84]; P<2.0E-16), and PrCa-specific mortality (HR, 2.63 [95% CI, 1.66-4.19]; P=4.4E-05). In the subset of MVP participants who underwent prostate biopsy within the VA health system (n=36,321), a multivariable logistic regression model controlling for known PrCa risk factors showed that HOXB13 p.G84E heterozygotes had a higher risk of PrCa diagnosis (odds ratio, 2.60 [95% CI, 1.94-3.52]; P<.001). HOXB13 p.G84E heterozygotes were diagnosed with PrCa at a slightly younger age but had similar Gleason score distributions and comparable rates of de novo, any, and castration-resistant metastatic disease. CONCLUSIONS: In the largest cohort of men with the HOXB13 p.G84E variant studied to date, we demonstrate a moderately increased lifetime risk of PrCa. However, the PrCa that develops is not more aggressive, although it may occur at younger ages. Further research is warranted to determine whether early PrCa screening in HOXB13 p.G84E heterozygotes improves outcomes.

A meta-analysis of experimentally validated neo-epitopes: patterns, biases, and opportunities

Cancer Immunology Immunotherapy · 2025-11-06 · 1 citations

Cancer cells harbor somatic mutations that generate novel amino acid sequences that are absent in the self-proteome. These mutation-derived cancer-specific peptides are defined as "neo-peptides". Neo-peptides eliciting immune responses, i.e. immunogenic neo-peptides, are defined as "neo-epitopes". Given their relevance to cancer immunotherapy, we conducted a meta-analysis to examine how experimental evidence informs our understanding of neo-epitopes. Our study is the largest reported to date. Using the cancer epitope database and analysis resource (CEDAR), we analyzed over 16,000 neo-peptides tested in more than 20,000 T cell assays across 180 studies. We found that validated neo-epitope frequencies varied across cancer types, with the highest rates in skin and lung and the lowest in colorectal cancer. Neo-epitopes were enriched in driver genes such as TP53 and KRAS. However, testing frequency correlated with mutation prevalence, revealing bias toward recurrent mutations. Despite the high sequence similarity among RAS family members, validated neo-epitope overlap was minimal, challenging pan-RAS strategies. Shared neo-epitopes across cancer types are rare, with only 16 validated in more than one cancer type. While most assays involved HLA class I, class II alleles presented a higher proportion of validated neo-epitopes. Specific alleles, including HLA-B*40:01 and HLA-DRB1*11:01, were enriched for neo-epitopes, whereas others, like HLA-A*02:01, were enriched for non-immunogenic neo-peptides. Finally, amino acid substitutions that altered hydrophobicity or charge were more common in neo-epitopes. Together, these findings define key features of neo-epitopes, expose methodological and biological biases in the literature, and highlight opportunities to improve the selection and prioritization of neo-epitopes for cancer immunotherapy.

GAME: Genomic API for Model Evaluation

bioRxiv (Cold Spring Harbor Laboratory) · 2025-07-08

The rapid expansion of genomics datasets and the application of machine learning has produced sequence-to-activity genomics models with ever-expanding capabilities. However, benchmarking these models on practical applications has been challenging because individual projects evaluate their models in ad hoc ways, and there is substantial heterogeneity of both model architectures and benchmarking tasks. To address this challenge, we have created GAME, a system for large-scale, community-led standardized model benchmarking on user-defined evaluation tasks. We borrow concepts from the Application Programming Interface (API) paradigm to allow for seamless communication between pre-trained models and benchmarking tasks, ensuring consistent evaluation protocols. Because all models and benchmarks are inherently compatible in this framework, the continual addition of new models and new benchmarks is easy. We also developed a Matcher module powered by a large language model (LLM) to automate ambiguous task alignment between benchmarks and models. Containerization of these modules enhances reproducibility and facilitates the deployment of models and benchmarks across computing platforms. By focusing on predicting underlying biochemical phenomena (e.g. gene expression, open chromatin, DNA binding), we ensure that tasks remain technology-independent. We provide examples of benchmarks and models implementing this framework, and anticipate that the community will contribute their own, leading to an ever-expanding and evolving set of models and evaluation tasks. This resource will accelerate genomics research by illuminating the best models for a given task, motivating novel functional genomic benchmarks, and providing a more nuanced understanding of model abilities.

Cutting edge: Extrinsic and intrinsic sex effects differentially regulate pulmonary ILC2 numbers, phenotype, and function

The Journal of Immunology · 2025-06-09 · 1 citations

Pulmonary type 2 innate lymphocytes (ILC2s) show sex dimorphism in numbers, phenotype, and function. We used a novel strategy of competitive, mixed male-female donor bone marrow chimeras to determine if sex differences in murine ILC2s result from extrinsic factors in the recipient environment or from durable intrinsic variables in donor cells. We show that the recipient sex environment regulated ILC2 numbers and IL33R/ST2 and KLRG1 surface levels, independent of donor sex. In contrast, ILC2 production of interleukin (IL)-5 depended on donor cell sex and the type of inflammatory stimulus. After allergen exposure, or upon treatment of naïve lung cells with PMA/ionomycin, a higher frequency of female donor-derived ILC2s produced IL-5. In contrast, influenza virus infection induced a greater proportion of male donor-derived ILC2s to produce IL-5. Thus, while a current sex environment governed pulmonary ILC2 numbers and canonical markers, ILC2 functional responses were shaped by durable factors stemming from intrinsic biological sex.

Session Introduction: Biological molecular function: methods and benchmarks for finding function in biological dark matter

2025-12-01

The accurate determination of biological molecular function remains one of the most significant challenges in computational biology, with vast areas of biological "dark matter" persisting in microbiomes, viruses, and unexplored sequence space. To meet this challenge, we developed at PSB session to address the limitations of traditional sequence similarity-based functional annotation methods and explores how recent advances in AI/ML and high-throughput data generation are transforming the field. We highlight four innovative contributions presented in this session: a geometric framework using signed distance functions for modeling protein surfaces; a reinforcement learning-based approach for steering protein generative models to design functional sequences; an ensemble framework combining sequence, structural, and network features for subcellular localization prediction; and a scalable factorization method integrating gene-gene interaction data for analyzing high-dimensional genetic perturbation profiles. Together, these methodologies showcase the potential for computational and AI-driven tools to address the complex and multiscale nature of molecular function prediction, paving the way for new discoveries in understanding and engineering biological systems.

Aryl hydrocarbon receptor and hypoxia mediating inflammatory DCs in pulmonary fibrosis 3980

The Journal of Immunology · 2025-11-01

Abstract Description Idiopathic pulmonary fibrosis is a progressive, fibrotic disease with a prognosis of only 3-5 years of survival after diagnosis. The immune system and inflammation play a role in the development of fibrosis, but the sterile nature of IPF suggests dysregulated innate immunity. Our data demonstrate that type 1 dendritic cells (cDC1s) play an exacerbating role in our bleomycin-driven pulmonary fibrosis model. Complementary data shows that cDC1s express high levels of the transcription factor Aryl Hydrocarbon Receptor (AHR), which can act through both anti-inflammatory canonical pathways and pro-inflammatory noncanonical pathways. Our data suggest that during fibrogenesis, AHR is augmenting inflammation and contributing to worsening fibrosis, however the stimulus shunting AHR toward this non-canonical proinflammatory pathway is unclear. Canonical AHR activity and hypoxia-inducible pathways share a common mediator, suggesting a possible mechanism through which hypoxia and AHR may antagonize each other and influence inflammatory cDC1 functions. Using in vitro induced CD103+ DCs in a 1% O2 hypoxia chamber versus our standard normoxic incubator, we analyzed impact on DC signaling. Early studies suggest that hypoxia is decimating canonical AHR stimulation, however it is also eliminating inflammatory responses to TLR9 agonists. Thus, severe hypoxia does not appear to be recapitulating our in vivo findings. Studies to test other oxygen levels and other mechanisms are ongoing. Funding Sources This work has been supported by NIH T32GM007863-41 (HC), T32AI007413-28 (HC), R35HL144481-03 (BM), and by the Pulmoary Fibrosis Foundation Scholars Award (SG). Topic Categories Innate Immune Responses and Host Defense: Cellular Mechanisms (INC)