Biology subjects

Haley, B.

Publications and source records attributed to Haley, B..

13 recordsLinked to original sources

bioRxiv2025

Cryptic leukemia antigens share homology with microbial epitopes and stimulate T-cell responses in healthy donors

Leukemia cells express cryptic tumor-specific antigens (TSAs) derived from aberrantly transcribed non-exomic genome sequences. These antigens are generally absent from healthy tissues yet shared across patients, making them attractive immunotherapy targets by minimizing on-target/off-tumor toxicity while offering broad applicability. However, their immunogenic potential and the nature of the T-cell repertoire they stimulate remain unknown. Cryptic antigen-specific CD8+ T cells could be expanded from healthy donor T-cell repertoires for six out of nine candidate acute leukemia cryptic TSA. T-cell receptor (TCR) and epitope sequence analysis revealed oligoclonal or near-monoclonal responses, involving shared and donor-restricted clonotypes recognizing cryptic TSAs which shared sequence homology with microbial epitopes. Orthotopic TCR replacement with cryptic TSA-specific TCR chains using a one-step CRISPR-Cas9 approach further validated the antigenic specificity and therapeutic potential of two TCRs respectively targeting cryptic TSAs from acute myeloid and lymphoid leukemia. To our knowledge, this is the first report describing functional TCRs directed against cryptic leukemia TSAs and highlights their potential as a new class of antigens for T-cell-based immunotherapies. Key pointsO_LIA high proportion of cryptic leukemia TSAs shares homology with microbial epitopes and can stimulate expansion of low-frequency T cell repertoire in healthy individuals. C_LIO_LIEx vivo expansion of cryptic TSA-specific T cells enables TCR identification that can be used to devise new T cell immunotherapies. C_LI Visual Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=122 SRC="FIGDIR/small/691479v1_ufig1.gif" ALT="Figure 1"> View larger version (30K): org.highwire.dtl.DTLVardef@1bd720dorg.highwire.dtl.DTLVardef@8ac6d6org.highwire.dtl.DTLVardef@104289aorg.highwire.dtl.DTLVardef@5a65e_HPS_FORMAT_FIGEXP M_FIG C_FIG ConclusionCryptic leukemia antigens elicit antigenic and specific T-cell responses and represents novel targets for TCR or BiTE immunotherapy.

immunology↗

bioRxiv2025

Cross-competition shapes CD8+ T cell hierarchies and differentiation after RNA vaccination

Short SummaryImmunodominance is a universal feature of adaptive immunity that constrains T cell expansion, clonal diversity and breadth resulting in a narrowly focused T cell response. While observed across diverse priming settings and vaccine platforms, the influence of immunodominance on T cell phenotype remains unclear. Using an mRNA lipoplex vaccine encoding multiple antigens to study how immunodominance influences CD8+ T cell fate, we found that dominant CD8+ T cell responses alter the magnitude and phenotype of subdominant responses through peptide-MHC-I stability-mediated T cell cross-competition. Dominant CD8+ T cell responses preferentially acquired markers associated with terminal differentiation and cytotoxic function, while sub-dominant responses adopted memory-precursor and stem-like features. Removal of dominant responses allowed increased expansion of sub-dominant T cell responses and adoption of terminally differentiated effector phenotypes. These findings reveal that immunodominance dynamically shapes the magnitude, breadth and differentiation of CD8+ T cell responses and highlights opportunities to fine-tune T cell responses for therapeutic vaccination.

immunology↗

bioRxiv2025

A novel, high-density CRISPR activation platform for mapping cancer dependencies and resistance pathways ex vivo and in vivo

CRISPR activation (CRISPRa) enables precise, locus-specific upregulation of gene expression, offering potential for both ex vivo and in vivo applications. However, the lack of scalable, high-coverage tools has limited its use in comprehensive genetic screens, particularly in murine models. Here, we introduce Partita, a next-generation, whole-genome CRISPRa sgRNA platform designed for unparalleled efficiency and depth in gene activation studies. Partita employs a high-density targeting strategy, deploying 10 sgRNAs per transcription start site, structured into five gene family-specific sub-libraries to maximize transcriptional induction. To demonstrate its capabilities, we performed a series of large-scale screens: an in vitro enrichment/depletion screen in iBMDMs, whole-genome CRISPRa screens in a double-hit lymphoma model to uncover genes driving resistance to pro-apoptotic drugs (venetoclax, nutlin-3a, etoposide), and an in vivo whole-genome screen identifying accelerators of Myc-driven lymphomagenesis. Each experiment revealed both expected and novel regulators of cellular phenotypes, with a high validation rate in secondary assays. By enabling robust, high-throughput gain-of-function screening, Partita unlocks new avenues for functional genomics and expands the toolkit for discovering key drivers of biological processes across diverse research fields.

cancer biology↗

bioRxiv2025

Fluctuation structure predicts genome-wide perturbation outcomes

Pooled single-cell perturbation screens represent powerful experimental platforms for functional genomics, yet interpreting these rich datasets for meaningful biological conclusions remains challenging. Most current methods fall at one of two extremes: either opaque deep learning models that obscure biological meaning, or simplified frameworks that treat genes as isolated units. As such, these approaches overlook a crucial insight: gene co-fluctuations in unperturbed cellular states can be harnessed to model perturbation responses. Here we present CIPHER (Covariance Inference for Perturbation and High-dimensional Expression Response), a conceptual framework leveraging ideas from linear response in statistical physics to model transcriptome-wide perturbation outcomes using gene co-fluctuations in unperturbed cells. We validated our approach on synthetic regulatory networks before applying it to 29 large-scale single-cell genetic perturbation datasets covering 19,003 perturbations and over 6.26M cells. Our work robustly recapitulated genome-wide responses to single and double perturbations by exploiting baseline gene covariance structure. Importantly, eliminating gene-gene covariances, while retaining gene-intrinsic variances, i.e. mean-field conditions, dramatically reduced model performance by several folds across multiple metrics, demonstrating the rich information stored within baseline fluctuation structures. Benchmarked against recent deep learning and linear baselines, CIPHER matched or exceeded the best-performing approaches with fitting a single parameter. Moreover, gene-gene correlations transferred successfully across independent studies of the same cell type, revealing stereotypic fluctuation structures. We further extended CIPHER to the inverse problem of identifying true driver perturbations, where it achieved high performance across both genetic and chemical perturbation screens through uncertainty-aware Bayesian inference. We further used CIPHER to nominate drivers of therapy resistance in melanoma and pancreatic cancer, validating its top predictions experimentally. Finally, most genome-wide responses propagated through the covariance matrix along approximately 1-3 independent and global gene modules, consistent with a low-rank structure of the underlying gene regulatory network, which we show can enable the framework's success. We have also created a package called cipher-perturb, available on PyPI, to apply the framework to any dataset, accompanied by a detailed website (https://goyallab.github.io/CIPHERWebsite/). Our study underscores the importance of theoretically-grounded models in capturing complex biological responses, highlighting fundamental design principles encoded in cellular fluctuation patterns.

systems biology↗

bioRxiv2024

Chemically-inducible CRISPR/Cas9 circuits for ultra-high dynamic range gene perturbation

CRISPR/Cas9 technologies provide unique capabilities for modeling disease and understanding gene-to-phenotype connections. In cultured cells, chemical-mediated control of Cas9 activity can limit off-target effects and enable mechanistic study of essential genes. However, widely-used Tet-On systems often show "leaky" Cas9 expression, leading to unintended edits, as well as weak activity upon induction. Leakiness can be distinctly problematic in the context of Cas9 nuclease activity, which may result in cumulative DNA damage and degradation of the target cell genome over time. To overcome these deficiencies, we established transgenic platforms that minimize Cas9 functionality in the off-state along with maximized and uncompromised on-state gene editing efficiency. By combining conditional destabilization and inhibition of Cas9, we developed an all-in-one (one or multiple guide RNAs and Cas9) ultra-tight, Tet-inducible system with exceptional dynamic range (on vs. off-state) across various cell lines and targets. As an alternative to Tet-mediated induction, we created a branaplam-regulated splice switch module for low-baseline and robust Cas9 activity control. Lastly, for circumstances where DNA damage needs to be avoided, we constructed a dual-control, Tet-inducible CRISPRi module for tight and potent transcriptional silencing. This upgraded suite of inducible CRISPR systems has broad applications for numerous cell types and experimental conditions.

molecular biology↗

bioRxiv2024

A CRISPR/Cas9 screen reveals proteins at the endosome-Golgi interface that modulate cellular ASO activity

Anti-sense oligonucleotides (ASOs) are modified synthetic single-stranded molecules with enhanced stability, activity, and bioavailability. They associate with RNA through sequence complementarity and can reduce or alter mRNA expression upon binding of splice site positions. To target RNA in the nucleus or cytoplasm, ASOs must cross membranes, a poorly understood process. We have performed an unbiased CRISPR/Cas9 knockout screen with a genetic splice reporter to identify genes that can increase or decrease ASOs activity, resulting in the most comprehensive catalog of ASOs-activity modifier genes. Distinct targets were uncovered, including AP1M1 and TBC1D23, linking ASOs activity to transport of cargo between the Golgi and endosomes. AP1M1 absence strongly increased ASO activity by delaying endosome-to-lysosome transport in vitro and in vivo. Prolonged ASOs residence time in the endosomal system may increase the likelihood of ASOs escape from this organelle before they reach lysosomes. This insight into AP1M1 role in ASOs trafficking suggests a way for enhancing the therapeutic efficacy of ASOs by manipulating the endolysosomal pathways.

cell biology↗

bioRxiv2024

Advancing the genetic engineering toolbox by combining AsCas12a knock-in mice with ultra-compact screening

Cas12a is a gene-editing tool that simplifies multiplexed gene targeting through its RNase activity, enabling maturation of individual crRNAs from a pre-crRNA-encoding RNA. Here, we present a mouse model that constitutively expresses enhanced Acidaminococcus sp. Cas12a (enAsCas12a) linked to an mCherry fluorescent reporter. We demonstrate efficient single and multiplexed gene-editing in cells from enAsCas12aKI mice. To test in vivo activity, we transduced haematopoietic stem cells from E-MycT/+;enAsCas12aKI/+animals with Trp53-targeting pre-crRNAs followed by transplantation into irradiated recipient animals. Tumour development was accelerated and TRP53 protein lost. We generated compact, genome-wide Cas12a knockout libraries targeting each gene with four guide RNAs encoded on two (Menuetto) or one (Scherzo) vector. Introducing these libraries into E-MycT/+;enAsCas12aKI/+lymphoma cells followed by treatment with an MCL-1 inhibitor (S63845) or TRP53-inducer (nutlin-3a) identified known and novel drug resistance genes. Finally, we demonstrate simultaneous gene knockouts (Trp53 or combined Bax/Bak) and activation (Cd19) in primary T cells and mouse dermal fibroblasts from crosses of our enAsCas12a and CRISPR activation models (dCas9a-SAM). Our enAsCas12a mouse model and accompanying libraries enhance genome engineering capabilities and complements current CRISPR technologies.

molecular biology↗

bioRxiv2023

Accelerated drug resistant variant discovery with an enhanced, scalable mutagenic base editor platform

Personalized cancer therapeutics bring directed treatment options to patients based on the genetic signatures of their tumors. Unfortunately, tumor genomes are remarkably adaptable, and acquired resistance to these drugs through genetic means is an all-too-frequent occurrence. Identifying mutations that promote resistance within drug-treated patient populations can be cost, resource, and time intensive. Accordingly, base editing, enabled by Cas9-deaminase domain fusions, has emerged as a promising approach for rapid, large-scale resistance variant screening in situ. We adapted and optimized a conditional activation-induced cytidine deaminase (AID)-dCas9 system, which demonstrated greater heterogeneity of edits with an expanded footprint compared to the most commonly utilized cytosine base editor, BE4. When combined with a custom sgRNA library, we were able to identify both individual and complex, compound variants in EGFR and BRAF that confer resistance to established EGFR inhibitors. This system and the developed analytical pipeline provide a simple, highly-scalable platform for cis or trans drug-modifying variant discovery and for uncovering unique insights into protein structure-function relationships.

molecular biology↗

bioRxiv2022

HLApollo: A superior transformer model for pan-allelic peptide-MHC-I presentation prediction, with diverse negative coverage, deconvolution and protein language features.

Antigen presentation on MHC class I (MHC-I) is key to the adaptive immune response to cancerous cells. Computational prediction of peptide presentation by MHC-I has enabled individualized cancer immunotherapies. Here, we introduce HLApollo, a transformer-based approach with end-to-end modeling of MHC-I sequence, deconvolution, and flanking sequences. To achieve this, we develop a novel training strategy, negative set switching, which greatly reduces overfitting to falsely presumed negatives that are necessarily found in presentation datasets. HLApollo shows a meaningful improvement compared to recent MHC-I models on peptide presentation (20.19% average precision (AP)) and immunogenicity (4.1% AP). As expected, adding gene expression boosts the performance of HLApollo. More interestingly, we show that introduction of features from a protein language model, ESM 1b, remarkably recoups much of the benefits of gene expression in absence of true expression measurements. Finally, we demonstrate excellent pan-allelic generalization, and introduce a framework for estimating the expected accuracy of HLApollo for untrained alleles. This guides the use of HLApollo in a clinical setting, where rare alleles may be observed in some subjects, particularly for underrepresented minorities.

immunology↗

bioRxiv2022

Discovery of prevalent, clinically actionable tumor neoepitopes via integrated biochemical and cell-based platforms

Strategies for maximizing the potency and specificity of cancer immunotherapies have sparked efforts to identify recurrent epitopes presented in the context of defined tumor-associated neoantigens. Discovering these "neoepitopes" can be difficult owing to the limited number of peptides that arise from a single point mutation, a low number of copies presented on the cell surface, and variable binding specificity of the human leukocyte antigen (HLA) class I complex. Due to these limitations, many discovery efforts focus on identifying neoepitopes from a small number of cancer neoantigens in the context of few HLA alleles. Here we describe a systematic workflow to characterize binding and presentation of neoepitopes derived from 47 shared cancer neoantigens in the context of 15 HLA alleles. Through the development of a high-throughput neoepitope-HLA binding assay, we surveyed 24,149 candidate neoepitope-HLA combinations resulting in 587 stable complexes. These data were supplemented by computational prediction that identified an additional 257 neoepitope-HLA pairs, resulting in a total of 844 unique combinations. We used these results to build sensitive targeted mass spectrometry assays to validate neoepitope presentation on a panel of HLA-I monoallelic cell lines engineered to express neoantigens of interest as a single polypeptide. Altogether, our analyses detected 84 unique neoepitope-HLA pairs derived from 37 shared cancer neoantigens and presented across 12 HLA alleles. We subsequently identified multiple TCRs which specifically recognized two of these neoantigen-HLA combinations. Finally, these novel TCRs were utilized to elicit a T cell response suggesting that these neoepitopes are likely to be immunogenic. Together these data represent a validated, extensive resource of therapeutically relevant neoepitopes and the HLA context in which they can be targeted.

cancer biology↗

bioRxiv2022

A versatile, high-efficiency platform for CRISPR-based gene activation

CRISPR-mediated transcriptional activation (CRISPRa) is a powerful technology for inducing gene expression from endogenous loci with exciting applications in high throughput gain-of-function genomic screens and the engineering of cell-based models. However, current strategies for generating potent, stable, CRISPRa-competent cell-lines present limitations for the broad utility of this approach. Here, we provide a high-efficiency, self-selecting CRISPRa enrichment strategy, which combined with piggyBac transposon technology enables rapid production of CRISPRa-ready cell populations compatible with a variety of downstream assays. We complement this with a new, optimized guide RNA scaffold that significantly enhances CRISPRa functionality. Finally, we describe a novel, synthetic guide RNA tool set that enables transient, population-wide gene activation when used with the self-selecting CRISPRa system. Taken together, this versatile platform greatly enhances the potential for CRISPRa across a wide variety of cellular contexts.

bioengineering↗

bioRxiv2020

G9a methyltransferase governs cell identity in the lung and is required for KRAS G12D tumor development and propagation

Lung development, integrity and repair rely on precise Wnt signaling, which is corrupted in diverse diseases, including cancer. Here, we discover that G9a methyltransferase regulates Wnt signaling in the lung by controlling the transcriptional activity of chromatin-bound {beta}-catenin, through a non-histone substrate. Inhibition of G9a induces transcriptional, morphologic, and molecular changes consistent with alveolar type 2 (AT2) lineage commitment. Mechanistically, G9a activity functions to support regenerative properties of KrasG12D tumors and normal AT2 cells - the predominant cell of origin of this cancer. Consequently, G9a inhibition prevents KrasG12D lung adenocarcinoma tumor formation and propagation,and disrupts normal AT2 cell trans-differentiation. Consistent with these findings, low G9a expression in human lung adenocarcinoma correlates with enhanced AT2 gene expression and improved prognosis. These data reveal G9a as a critical regulator of Wnt signaling, implicating G9a as a potential target in lung cancer and other AT2-mediated lung pathologies.

cancer biology↗

bioRxiv2018

Disruption of IRE1α through its Kinase Domain Attenuates Multiple Myeloma

Multiple myeloma (MM) arises from malignant immunoglobulin-secreting plasma cells and remains an incurable, often lethal disease despite recent therapeutic advances. The unfolded-protein response sensor IRE1 supports protein secretion by deploying a kinase-endoribonuclease module to activate the transcription factor XBP1s. MM cells may coopt the IRE1-XBP1s pathway; however, the validity of IRE1 as a potential MM therapeutic target is controversial. Here we show that genetic disruption of IRE1 or XBP1s, or pharmacologic IRE1 kinase inhibition, attenuated subcutaneous or orthometastatic growth of MM tumors in mice, and augmented efficacy of two well-established frontline antimyeloma agents, bortezomib or lenalidomide. Mechanistically, IRE1 perturbation inhibited expression of key components of the ER-associated degradation machinery, as well as cytokines and chemokines known to promote MM growth. Selective IRE1 kinase inhibition reduced viability of CD138+ plasma cells while sparing CD138- cells from bone marrow of newly diagnosed MM patients or patients whose disease relapsed after 1 - 4 lines of treatment in both US- and EU-based cohorts. IRE1 inhibition preserved survival and glucose-induced insulin secretion by pancreatic microislets. Together, these results establish a strong therapeutic rationale for targeting IRE1 with kinase-based small-molecule inhibitors in MM.\n\nSignificance statementMultiple myeloma (MM) is a lethal malignancy of plasma cells. MM cells have an expanded endoplasmic reticulum (ER) that is constantly under stress due to immunoglobulin hyperproduction. The ER-resident sensor IRE1 mitigates ER stress by expanding the ERs protein-folding capacity while supporting proteasomal degradation of misfolded ER proteins. IRE1 elaborates these functions by deploying its cytoplasmic kinase-RNase module to activate the transcription factor XBP1s. The validity of IRE1 as a potential therapeutic target in MM has been questioned. Using genetic and pharmacologic disruption in vitro and in vivo, we demonstrate that the IRE1-XBP1s pathway plays a critical role in MM growth. We further show that IRE1s kinase domain is an effective and safe potential small-molecule target for MM therapy.

cancer biology↗