Biology subjects

Fu, Y.-H.

Publications and source records attributed to Fu, Y.-H..

7 recordsLinked to original sources

bioRxiv2026

Radioligand therapy in combination with CAR T cells overcomes the heterogeneous immunosuppressive prostate tumor microenvironment

177Lu-PSMA-617 (PluvictoTM, Lu-177 RLT) is an FDA-approved targeted radioligand therapy (RLT) for metastatic castration-resistant prostate cancer (mCRPC), but its durability of response to this singular approach poses a challenge to the field. Chimeric antigen receptor (CAR) T cell therapy has revolutionized clinical practice for hematological malignancies, but its clinical development for solid tumors, including mCRPC, has been encumbered by antigen heterogeneity and the immunosuppressive tumor microenvironment (TME). Here, we evaluate the therapeutic combination of Lu-177 RLT and PSCA-CAR T cells to overcome these barriers. In human xenograft and mouse syngeneic prostate cancer models with homogeneous or heterogeneous antigen expression, the sequential administration of Lu-177 RLT, cyclophosphamide (Cy), and PSCA-CAR T cells improves tumor control and prolongs survival compared to monotherapies. Mechanistically, Lu-177 RLT alone or with Cy remodels the TME by promoting pro-inflammatory myeloid responses and activating endogenous T cells, while enhancing CAR T cell activation and effector function. We additionally evaluated 225Ac-PSMA-617 RLT as an emerging approach in combination with CAR T cells and observed anti-tumor responses, supporting its potential as an alternative RLT partner. These findings support RLT as an immune priming strategy to enhance CAR T cell therapy and provide a rationale for clinical translation of this combination in mCRPC. One Sentence SummaryCombining 177Lu-PSMA-617 radioligand therapy with PSCA-CAR T cells improves tumor control and survival in prostate cancer models by overcoming the antigen heterogeneity and reshaping the immunosuppressive tumor microenvironment.

cancer biology↗

bioRxiv2026

Multiomic State-Transitions Reveal Post-Treatment Transcriptome Desynchronization in Acute Myeloid Leukemia

Temporal dynamics of the peripheral blood transcriptome are crucial for understanding leukemia evolution and response to therapy because they can reveal how gene expression programs drive abnormal cell states, disease heterogeneity, and treatment resistance. Using a mathematical model of state-transitions, we studied the temporal dynamics of peripheral blood messenger RNA (mRNA) and microRNA (miRNA) transcriptomes in a mouse model of acute myeloid leukemia (AML). In our state-transition model, mRNA and miRNA transcriptomes are represented as a particle undergoing Brownian motion in a two-dimensional multiomic potential landscape. Following chemotherapy, we observed a temporal desynchronization between mRNA and miRNA transcriptomic responses corresponding to an asymmetric shift in the landscape. Specifically, mRNA trajectories responded almost immediately post-treatment, whereas miRNA responses were delayed by approximately two weeks. Clustering analysis identified that the temporal delay is driven by a prominent cluster of miRNAs from the imprinted Dlk1-Dio3 region. Although previously implicated in acute promyelocytic leukemia, lymphomas, and metabolic dysregulation, this provides the first evidence linking the Dlk1-Dio3 locus to AML chemotherapy response and treatment-induced transcriptomic desynchronization. This framework offers an innovative dynamics-based strategy to identify biological drivers of therapeutic response and novel therapeutic targets across hematological malignancies. Key PointsO_LITreatment can induce desynchronization between messenger RNA and microRNA transcriptome dynamics in a murine model of AML C_LIO_LIMicroRNAs from the imprinted Dlk1-Dio3 locus are identified as key contributors to desynchronization and may serve as therapeutic targets C_LI

cancer biology↗

bioRxiv2026

Oncolytic Adenovirus Armed with cGAS Activates STING Pathway and Enhances Antitumor Immunity in Lung Cancer with Superior Combined Efficacy of PD-L1 Therapy

The extensive expression of STING in patients with non - small cell lung cancer (NSCLC) is closely associated with overall survival and other factors. Activation of the STING pathway can suppress NSCLC. However, the clinical translation of STING agonists remains hindered by challenges such as off-target effects, metabolic instability, and suboptimal pharmacokinetics. In this study, we engineered two oncolytic adenoviruses (OAds), OAd-HcGAS and OAd-McGAS, expressing human or murine cGAS, respectively, using an Ad5/3 chimeric adenovirus platform under regulation by the hTERT promoter to evaluatewhether OVs carrying the cGAS gene are capable of specifically activating the STING pathway within tumors and enhancing the anti - tumor efficacy of OVs both in vitro and in vivo.In vitro, OAd-HcGAS exhibited robust replication and potent cytolytic activity in tumor cells. It activated the STING-TBK1-IRF3 signaling axis, triggering a strong type I interferon (IFN-I) and pro-inflammatory cytokine response without compromising viral replication. In a murine Lewis lung carcinoma allograft model, intratumoral (i.t.) administration of OAd-McGAS led to substantial cGAS expression and consequential activation of the STING pathway. Moreover, the combination with anti-PD-L1 therapy resulted in tumor regression in over half of the cases. Notably, this armed oncolytic virus strategy enhanced the activation and infiltration of multiple immune cell populations. Collectively, these findings establish cGAS-expressing oncolytic adenoviruses as a novel and effective therapeutic strategy for lung cancer treatment. Graphical AbstractViral replication & Transgene expression & Cancer treatment

immunology↗

bioRxiv2025

Overcoming treatment resistance mediated by the bone marrow vascular niche in acute myeloid leukemia

Acute myeloid leukemia (AML) is a hematologic malignancy originating in the bone marrow, frequently progressing to extramedullary sites. Despite advances in molecularly targeted therapies and hematopoietic stem cell transplantation, clinical outcomes remain suboptimal. Tyrosine kinase inhibitors (TKIs) confer benefit in a subset of AML patients harboring FLT3-ITD mutations, yet relapse and resistance are common. These failures are driven by both intrinsic properties of leukemic stem cells (LSCs)--a quiescent, self-renewing population--and extrinsic cues from the tumor microenvironment. We previously demonstrated that arteriolar endothelial cells (ECs) produce miR-126, which is transferred to LSCs, promoting quiescence, treatment resistance, and niche retention. During disease progression, TNF- secreted by expanding blasts suppresses EC miR-126 production, enabling LSCs and their progeny to proliferate. Following TKI administration, blast reduction lowers TNF- levels, restoring EC miR-126 production and enabling LSCs to re-enter quiescence--thereby escaping therapy and facilitating relapse. To investigate this dynamic, we developed an agent-based computational model of the AML bone marrow microenvironment, parameterized with in vitro and in vivo data. The model captures vascular niche remodeling and the feedback between leukemic populations and endothelial signaling. Simulations reveal that LSC protection mediated by miR-126 can be overcome by combining TKIs with miRisten, a miR-126 inhibitor. When administered on a defined schedule, this combination disrupts the protective niche and enhances LSC eradication. These findings underscore the therapeutic potential of targeting microenvironmental feedback to overcome resistance and prevent AML relapse.

cancer biology↗

bioRxiv2025

Longitudinal single cell RNA-sequencing reveals evolution of micro- and macro-states in chronic myeloid leukemia

Single cell RNA sequencing (scRNA-seq) has revolutionized our understanding of cancer, yet identifying meaningful disease states from single cell data remains challenging. Here, we systematically explore the chronic myeloid leukemia (CML) specific information content encoded in single cell versus bulk transcriptomics to resolve this paradox and clarify how discrete disease-defining states emerge from inherently noisy single cell data. We demonstrate that, while CML single cell transcriptomes exist along continuous transcriptional microstates, clinically relevant leukemia phenotypes clearly manifest only at the pseudobulk (macrostate) level. By leveraging state-transition theory, we reveal how robust disease phenotype state-transitions are governed by cell type specific contributions. Our results establish a theoretical framework explaining why discrete disease phenotypes remain hidden at the single cell scale but emerge clearly at the aggregated macrostate level, enabling previously inaccessible biological insights into leukemia evolution. By resolving how single-cell variation aggregates into macroscopic disease states, our framework provides new insight into CML progression and offers a broadly applicable strategy for exploring disease dynamics across cancers and other complex conditions.

systems biology↗

bioRxiv2024

Nutrient Abundance Signals the Changing of the Seasons by Phosphorylating PER2

The circadian clock synchronizes metabolic and behavioral cycles with the rotation of the Earth by integrating environmental cues, such as light. Nutrient content also regulates the clock, though how and why this environmental signal affects the clock remains incompletely understood. Here, we elucidate a role for nutrient in regulating circadian alignment to seasonal photoperiods. High fat diet (HFD) promoted entrainment to a summer light cycle and inhibited entrainment to a winter light cycle by phosphorylating PER2 on serine 662. PER2-S662 phospho-mimetic mutant mice were incapable of entraining to a winter photoperiod, while PER2-S662 phospho-null mutant mice were incapable of entraining to a summer photoperiod, even in the presence of HFD. Multi-omic experimentation in conjunction with isocaloric hydrogenated-fat feeding, revealed a role for polyunsaturated fatty acids in nutrient-dependent seasonal entrainment. Altogether, we identify the mechanism whereby nutrient content shifts circadian rhythms to anticipate seasonal photoperiods in which that nutrient state predominates. HIGHLIGHTSO_LIHigh fat diet promotes entrainment to summer but inhibits entrainment to winter. C_LIO_LICalorie restriction promotes entrainment to winter but inhibits entrainment to summer. C_LIO_LIPER2-S662 phosphorylation is required for nutritional regulation of seasonal circadian entrainment. C_LIO_LIDietary polyunsaturated fatty acids regulate seasonal circadian entrainment. C_LI

neuroscience↗

bioRxiv2023

State-transition Modeling of Blood Transcriptome Predicts Disease Evolution and Treatment Response in Chronic Myeloid Leukemia (CML)

Chronic myeloid leukemia (CML) is initiated and maintained by BCR::ABL which is clinically targeted using tyrosine kinase inhibitors (TKIs). TKIs can induce long-term remission but are also not curative. Thus, CML is an ideal system to test our hypothesis that transcriptome-based state-transition models accurately predict cancer evolution and treatment response. We collected time-sequential blood samples from tetracycline-off (Tet-Off) BCR::ABL-inducible transgenic mice and wild-type controls. From the transcriptome, we constructed a CML statespace and a three-well leukemogenic potential landscape. The potentials stable critical points defined observable disease states. Early states were characterized by anti-CML genes opposing leukemia; late states were characterized by pro-CML genes. Genes with expression patterns shaped similarly to the potential landscape were identified as drivers of disease transition. Re-introduction of tetracycline to silence the BCR::ABL gene returned diseased mice transcriptomes to a near healthy state, without reaching it, suggesting parts of the transition are irreversible. TKI only reverted the transcriptome to an intermediate disease state, without approaching a state of health; disease relapse occurred soon after treatment. Using only the earliest time-point as initial conditions, our state-transition models accurately predicted both disease progression and treatment response, supporting this as a potentially valuable approach to time clinical intervention even before phenotypic changes become detectable.

cancer biology↗