Biology subjects

Ban, Y.

Publications and source records attributed to Ban, Y..

13 recordsLinked to original sources

bioRxiv2026

MicroRNA-29a enhances and preserves stem-like CD8 T cell differentiation by regulating master epigenetic circuits of exhaustion.

CD8 T cells mediate protective immune responses. However, persisting antigens such as chronic viruses or tumors redirect CD8 T cell differentiation to a sub-optimal, epigenetically defined state called exhaustion. Exhausted T cells (TEX) lose their ability to persist long-term and to initiate functional memory responses. Checkpoint inhibitor blockade temporarily restores effector functions, but immune reinvigoration is not long-lasting, due to the epigenetic stability of TEX. Therefore, epigenetic reprogramming of TEX leading to durable T cell responses is essential to improve disease control. Here, we demonstrate that a single microRNA (miR), miR-29a, epigenetically re-directs TEX differentiation and preserves TEX into a stem-like state, leading to long-term persisting progenitor TEX. MiR-29a rewires epigenetic maintenance programs, including downregulation of key exhaustion-associated regulators (Dnmt1, Dnmt3a, and Dnmt3b), alongside increased expression of progenitor- and stemness-associated genes such as Tcf7 and Il7r. These reprogrammed CD8 T cells are more sensitive to PD-L1 checkpoint blockade. Ectopic expression of miR-29a combined with aPD-L1 treatments enhances effector responses, while preserving T cell stemness. Together, our findings suggest that miR-29a can be leveraged to overcome current barriers to immune checkpoint blockade. HighlightsO_LIMiR-29a rewires key exhaustion-associated epigenetic maintenance programs, while enhancing stemness-associated transcriptional circuits. C_LIO_LIMiR-29a drives extensive remodeling of accessible chromatin in TEX. C_LIO_LIMiR-29a preserves newly generated progenitor TEX in a durable, epigenetically defined stem-like state with increased effector function. C_LIO_LIMiR-29a synergizes with aPD-L1; while miR-29a preserves progenitor TEX state, addition of aPD-L1 enhances the cytotoxic potential of these progenitor TEX cells. C_LI

immunology↗

bioRxiv2025

Targeting CREB remodels the immune microenvironment to enhance immunotherapy responses in pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) remains a challenging disease in need of improved treatments. Cyclic adenosine monophosphate response element binding protein 1 (CREB) is an emerging therapeutic target whose oncogenic effects in PDAC have been largely attributed to a key molecular interplay between oncogenic KrasG12D/+ (Kras*) and chronic inflammation driving irreversible acinar to ductal reprogramming. Here, we demonstrate that CREB activation fosters tumor associated macrophage (TAM) mediated immunosuppression and promotes PDAC growth in an aggressive LSL-KrasG12D/+;Trp53R172H/+;Pdx1Cre/+(KPC) genetically engineered mouse model. Selective deletion of CREB (Crebfl/fl) in KPC(KPCC-/-) mice attenuates primary disease burden. Unbiased transcriptomic analysis and validation using diverse molecular, genetic and pharmacological approaches in vitro and in vivo identify CREB-mediated transcriptional regulation of leukemia inhibitory factor (Lif) as one of the potential mediators of tumor cell-macrophage crosstalk promoting a pro-tumor polarization of TAMs, thereby attenuating the infiltration of effector T cells. Mechanistically, cancer cell derived LIF facilitates an immunosuppressive, pro-tumorigenic state. Importantly, pharmacological targeting of the CREB-LIF signaling axis between cancer cells and macrophages, using a CREB-specific inhibitor (CREBi), significantly suppresses tumor growth and sensitizes PDAC to immunotherapy, highlighting the therapeutic potential of this treatment combination to improve outcomes in this aggressive disease.

cancer biology↗

bioRxiv2025

A multi-scale segmentation-free self-supervised AI model to characterize the heterogeneity of the brain tumor microenvironment

Brain tumors affect about 1 million people in the U.S., with aggressive types like glioblastoma having very low survival rates due to complex tumor biology and the protective blood-brain barrier. Current treatments are limited in effectiveness, and our understanding of brain tumor biology remains incomplete. High dimensional multiplexed imaging has enabled us to better understand the tumor microenvironment (TME); however, analyses typically rely on cell segmentation, which is error-prone, may discard useful context outside the cell boundary, and neglects complex tissue-wide features. To address this limitation, we developed a segmentation-free, self-supervised representation learning framework that enables us to train directly on multiplexed images using masked image modeling. We used this approach to analyze 389 imaging mass cytometry images from 185 brain tumor patients. To study tissue-wide features, we first trained our model on 64x64 micron tiles capturing neighborhoods of 10-20 cells, which we termed local tumor microenvironments (LTMEs). To further characterize these LTMEs, we trained our model on 16x16 micron tiles centered on individual cells in our dataset, so that each tile captures a single cell and its surrounding area, which we termed single-cell microenvironments (SCMEs). This multi-scale, self-supervised approach enables a detailed analysis of the heterogeneity within the brain TME, examining single cells in their spatial context. In addition to validating known findings, we identified a novel LTME in GBM patients, composed primarily of tumor cells and a few B and T cells, which strongly correlated with increased survival. By analyzing these B cells with our SCME model, we found they were distinct from other GBM B cells, and higher concentrations of these B cells were linked to improved survival. In conclusion, our study introduces a multi-scale, segmentation-free, self-supervised machine learning model that provides unprecedented insights into brain TMEs, enabling discovery of previously unrecognized cell interactions and spatial features that are predictive of patient survival.

cancer biology↗

bioRxiv2024

Characterization of tumor heterogeneity through segmentation-free representation learning

The interaction between tumors and their microenvironment is complex and heterogeneous. Recent developments in high-dimensional multiplexed imaging have revealed the spatial organization of tumor tissues at the molecular level. However, the discovery and thorough characterization of the tumor microenvironment (TME) remains challenging due to the scale and complexity of the images. Here, we propose a self-supervised representation learning framework, CANVAS, that enables discovery of novel types of TMEs. CANVAS is a vision transformer that directly takes high-dimensional multiplexed images and is trained using self-supervised masked image modeling. In contrast to traditional spatial analysis approaches which rely on cell segmentations, CANVAS is segmentation-free, utilizes pixel-level information, and retains local morphology and biomarker distribution information. This approach allows the model to distinguish subtle morphological differences, leading to precise separation and characterization of distinct TME signatures. We applied CANVAS to a lung tumor dataset and identified and validated a monocytic signature that is associated with poor prognosis.

cancer biology↗

bioRxiv2024

An Orthogonal T7 Replisome for Continuous Hypermutation and Accelerated Evolution in E. coli

Systems that perform continuous hypermutation of designated genes without compromising the integrity of the host genome can dramatically accelerate the evolution of new or enhanced protein functions. We describe an orthogonal DNA replication system in E. coli based on the controlled expression of the replisome of bacteriophage T7. The system replicates circular plasmids that enable high transformation efficiencies and seamless integration into standard molecular biology workflows. Engineering of T7 DNA polymerase yielded variant proteins with mutation rates of 1.7 x 10-5 substitutions per base in vivo - 100,000-fold above the genomic mutation rate. Continuous evolution using the mutagenic T7 replisome was demonstrated by expanding the substrate scope of TEM-1 {beta}-lactamase and increase activity 1,000-fold against clinically relevant monobactam and cephalosporin antibiotics in less than one week.

synthetic biology↗

bioRxiv2024

CREB activation drives acinar to ductal reprogramming and promote pancreatic cancer progression in animal models of alcoholic chronic pancreatitis

BACKGROUND & AIMSChronic alcoholism often leads to pancreatitis, which exacerbates pancreatic damage through acinar cell injury, fibrotic inflammation and activates AKT/mTOR/cyclic adenosine monophosphate response element binding protein 1 (CREB) signaling axis. However, the molecular interplay between oncogenic KrasG12D/+(Kras*) and CREB in promoting pancreatic cancer progression under chronic inflammation remains poorly understood. METHODSExperimental alcoholic chronic pancreatitis (ACP) induction was established in multiple mouse models, with euthanasia during the recovery stage to evaluate tumor latency. CREB was selectively deleted (Crebfl/fl) in Ptf1aCreERTM/+;LSL-KrasG12D/+(KC) genetic mouse models (KCC-/-). Pancreata from Ptf1aCreERTM/+, KC, and KCC-/- mice were analyzed using histological profiling, western blotting, phosphokinase array, and quantitative PCR. Single-cell RNA sequencing was performed in ACP-induced KC mice. Lineage tracing analysis in YFP reporter mice and acinar cell explant cultures analysis were also conducted. RESULTSACP induction in KC mice significantly impaired pancreas repair mechanism. Acinar cell-derived ductal lesions demonstrated sustained CREB hyperactivation in acinar-to-ductal metaplasia (ADM)/pancreatic intraepithelial neoplasia (PanIN) lesions associated with pancreatitis and pancreatic cancer. Persistent CREB activity reprogrammed acinar cells, and increased profibrotic inflammation. Notably, acinar specific Creb deletion in ACP induced models suppressed high grade PanIN development, restrained tumor progression, and improved acinar cell function. CONCLUSIONSOur findings demonstrate that CREB and Kras* promote irreversible ADM, accelerating pancreatic cancer progression with ACP. Targeting CREB may present a promising strategy to mitigate inflammation-driven pancreatic tumorigenesis.

cancer biology↗

bioRxiv2023

Targeting Ribosome Biogenesis as a Novel Therapeutic Approach to Overcome EMT-related Chemoresistance in Breast Cancer.

Epithelial-to-mesenchymal transition (EMT) contributes significantly to chemotherapy resistance and remains a critical challenge in treating advanced breast cancer. The complexity of EMT, involving redundant pro-EMT signaling pathways and its paradox reversal process, mesenchymal-to-epithelial transition (MET), has hindered the development of effective treatments. In this study, we utilized a Tri-PyMT EMT lineage-tracing model and single-cell RNA sequencing (scRNA-seq) to comprehensively analyze the EMT status of tumor cells. Our findings revealed elevated ribosome biogenesis (RiBi) during the transitioning phases of both EMT and MET processes. RiBi and its subsequent nascent protein synthesis mediated by ERK and mTOR signalings are essential for EMT/MET completion. Importantly, inhibiting excessive RiBi genetically or pharmacologically impaired the EMT/MET capability of tumor cells. Combining RiBi inhibition with chemotherapy drugs synergistically reduced metastatic outgrowth of epithelial and mesenchymal tumor cells under chemotherapies. Our study suggests that targeting the RiBi pathway presents a promising strategy for treating patients with advanced breast cancer. SignificanceThis study uncovers the crucial involvement of ribosome biogenesis (RiBi) in the regulation of epithelial and mesenchymal state oscillations in breast cancer cells, which plays a major role in the development of chemoresistant metastasis. By proposing a novel therapeutic strategy targeting the RiBi pathway, the study offers significant potential to enhance treatment efficacy and outcomes for patients with advanced breast cancer. This approach could help overcome the limitations of current chemotherapy options and address the complex challenges posed by EMT-mediated chemoresistance.

cancer biology↗

bioRxiv2022

Distinct Mechanisms of Innate and Adaptive Immune Regulation Underlie Poor Oncologic Outcomes Associated with KRAS-TP53 Co-Alteration in Pancreatic Cancer

Co-occurrent KRAS and TP53 mutations define a majority of patients with pancreatic ductal adenocarcinoma (PDAC) and define its pro-metastatic proclivity. Here, we demonstrate that KRAS-TP53 co-alteration is associated with worse survival compared with either KRAS-alone or TP53-alone altered PDAC in 245 patients with metastatic disease treated at a tertiary referral cancer center, and validate this observation in two independent molecularly annotated datasets. Compared with non-TP53 mutated KRAS-altered tumors, KRAS-TP53 co-alteration engenders disproportionately innate immune-enriched and CD8+ T-cell-excluded immune signatures. Leveraging in silico, in vitro, and in vivo models of human and murine PDAC, we discover a novel intersection between KRAS-TP53 co-altered transcriptomes, TP63-defined squamous trans-differentiation, and myeloid-cell migration into the tumor microenvironment. Comparison of single-cell transcriptomes between KRAS-TP53 co-altered and KRAS-altered/TP53WT tumors revealed cancer cell-autonomous transcriptional programs that orchestrate innate immune trafficking and function. Moreover, we uncover granulocyte-derived inflammasome activation and TNF signaling as putative paracrine mediators of innate immunoregulatory transcriptional programs in KRAS-TP53 co-altered PDAC. Immune subtyping of KRAS-TP53 co-altered PDAC reveals conflation of intratumor heterogeneity with progenitor-like stemness properties. Coalescing these distinct molecular characteristics into a KRAS-TP53 co-altered "immunoregulatory program" predicts chemoresistance in metastatic PDAC patients enrolled in the COMPASS trial, as well as worse overall survival.

cancer biology↗

bioRxiv2021

Spike-frequency dependent coregulation of multiple ionic conductances in fast-spiking cells forces a metabolic tradeoff

High-frequency action potentials (APs) allow rapid information acquisition and processing in neural systems, but create biophysical and metabolic challenges for excitable cells. The electric fish Eigenmannia virescens images its world and communicates with high-frequency (200-600 Hz) electric organ discharges (EODs) produced by synchronized APs generated at the same frequency in the electric organ cells (electrocytes). We cloned three previously unidentified Na+-activated K+ channel isoforms from electroctyes (eSlack1, eSlack2, and eSlick1). In electrocytes, mRNA transcript levels of the rapidly-activating eSlick, but not the slower eSlack1 or eSlack2, correlated with EOD frequency across individuals. In addition, transcript levels of an inward-rectifier K+ channel, a voltage-gated Na+ channel, and Na+,K+-ATPases also correlated with EOD frequency while a second Na+ channel isoform did not. Computational simulations showed that maintaining electrocyte AP waveform integrity as firing rates increase requires scaling conductances in accordance with these mRNA expression correlations, causing AP metabolic costs to increase exponentially.

neuroscience↗

bioRxiv2021

Derived loss of signal complexity and plasticity in a genus of weakly electric fish

Signal plasticity can maximize the usefulness of costly animal signals such as the electric organ discharges (EODs) of weakly electric fishes. Some species of the order Gymnotiformes rapidly alter their EOD amplitude and duration in response to circadian cues and social stimuli. How this plasticity is maintained across related species with different degrees of signal complexity is poorly understood. In one genus of weakly electric gymnotiform fish (Brachyhypopomus) only one species, B. bennetti, produces a monophasic signal while all other species emit complex biphasic or multiphasic EOD waveforms produced by two overlapping but asynchronous action potentials in each electric organ cell (electrocyte). One consequence of this signal complexity is the suppression of low-frequency signal content that is detectable by electroreceptive predators. In complex EODs, reduction of the EOD amplitude and duration during daytime inactivity can decrease both predation risk and the metabolic cost of EOD generation. We compared EOD plasticity and its underlying physiology in Brachyhypopomus focusing on B. bennetti. We found that B. bennetti exhibits minimal EOD plasticity, but that its electrocytes retained vestigial mechanisms of biphasic signaling and vestigial mechanisms for modulating the EOD amplitude. These results suggest that this species represents a transitional phenotypic state within a clade where signal complexity and plasticity were initially gained and then lost. We discuss potential the roles of signal mimicry, species recognition, and sexual selection in maintaining the monophasic EOD phenotype in the face of detection by electroreceptive predators.

physiology↗

bioRxiv2021

LBH is a cancer stem cell- and metastasis-driving oncogene essential for WNT stem cell function in breast cancer

Cancer stem cells (CSCs) initiate tumors, resist treatment, and seed lethal metastases; yet CSC-specific treatments are lacking. Aggressive, treatment-resistant triple-negative breast cancers (TNBC) exhibit WNT pathway activation and are CSC enriched. Here, we show that Limb-Bud- and-Heart (LBH), a WNT/{beta}-catenin target required for normal mammary stem cell self-renewal, marks poor prognosis, stem-like TNBC, and is a key controller of breast cancer stemness. LBH is specifically expressed in tumor-initiating CD44+CD24-/low breast CSCs. LBH overexpression confers stem-like, metastatic traits on both TNBC and luminal origin, non-TNBC breast cancer cells by activating stem cell transcriptional programs. Importantly, silencing LBH potently suppresses tumor initiation and metastasis in vivo, and sensitizes TNBC cells to chemotherapy. LBH knockout in the MMTV-Wnt1 breast cancer mouse model, furthermore, revealed LBH is required for WNT-driven breast CSC expansion. Our findings identify LBH as an essential CSC driver downstream of WNT, and a new molecular target for anti-cancer stem cell therapy.

cancer biology↗

bioRxiv2019

pathwayPCA: an R package for integrative pathway analysis with modern PCA methodology and gene selection

With the advance in high-throughput technology for molecular assays, multi-omics datasets have become increasingly available. However, most currently available pathway analysis software provide little or no functionalities for analyzing multiple types of -omics data simultaneously. In addition, most tools do not provide sample-specific estimates of pathway activities, which are important for precision medicine. To address these challenges, we present pathwayPCA, a unique R package for integrative pathway analysis that utilizes modern statistical methodology including supervised PCA and adaptive elastic-net PCA for principal component analysis. pathwayPCA can analyze continuous, binary, and survival outcomes in studies with multiple covariate and/or interaction effects. We provide three case studies to illustrate pathway analysis with gene selection, integrative analysis of multi-omics datasets to identify driver genes, estimating and visualizing sample-specific pathway activities in ovarian cancer, and identifying sex-specific pathway effects in kidney cancer. pathwayPCA is an open source R package, freely available to the research community. We expect pathwayPCA to be a useful tool for empowering the wide scientific community on the analyses and interpretation of the wealth of multiomics data recently made available by TCGA, CPTAC and other large consortiums.

bioinformatics↗

bioRxiv2016

GSKB: A gene set database for pathway analysis in mouse

Interpretation of high-throughput genomics data based on biological pathways constitutes a constant challenge, partly because of the lack of supporting pathway database. In this study, we created a functional genomics knowledgebase in mouse, which includes 33,261 pathways and gene sets compiled from 40 sources such as Gene Ontology, KEGG, GeneSetDB, PANTHER, microRNA and transcription factor target genes, etc. In addition, we also manually collected and curated 8,747 lists of differentially expressed genes from 2,526 published gene expression studies to enable the detection of similarity to previously reported gene expression signatures. These two types of data constitute a Gene Set Knowledgebase (GSKB), which can be readily used by various pathway analysis software such as gene set enrichment analysis (GSEA). Using our knowledgebase, we were able to detect the correct microRNA (miR-29) pathway that was suppressed using antisense oligonucleotides and confirmed its role in inhibiting fibrogenesis, which might involve upregulation of transcription factor SMAD3. The knowledgebase can be queried as a source of published gene lists for further meta-analysis. Through meta-analysis of 56 published gene lists related to retina cells, we revealed two fundamentally different types of gene expression changes. One is related to stress and inflammatory response blamed for causing blindness in many diseases; the other associated with visual perception by normal retina cells. GSKB is available online at http://ge-lab.org/gs/, and also as a Bioconductor package (gskb, https://bioconductor.org/packages/gskb/). This database enables in-depth interpretation of mouse genomics data both in terms of known pathways and the context of thousands of published expression signatures.

bioinformatics↗