Browsing by Author "Gan, Dailin"

Now showing 1 - 4 of 4
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    Ketogenic diet alters the epigenetic and immune landscape of prostate cancer to overcome resistance to immune checkpoint blockade therapy
    (American Association for Cancer Research, 2024) Murphy, Sean; Rahmy, Sharif; Gan, Dailin; Liu, Guoqiang; Zhu, Yini; Manyak, Maxim; Duong, Loan; He, Jianping; Schofield, James H.; Schafer, Zachary T.; Li, Jun; Lu, Xuemin; Lu, Xin; Medicine, School of Medicine
    Resistance to immune checkpoint blockade (ICB) therapy represents a formidable clinical challenge limiting the efficacy of immunotherapy. In particular, prostate cancer poses a challenge for ICB therapy due to its immunosuppressive features. A ketogenic diet (KD) has been reported to enhance response to ICB therapy in some other cancer models. However, adverse effects associated with continuous KD were also observed, demanding better mechanistic understanding and optimized regimens for using KD as an immunotherapy sensitizer. In this study, we established a series of ICB-resistant prostate cancer cell lines and developed a highly effective strategy of combining anti-PD1 and anti-CTLA4 antibodies with histone deacetylase inhibitor (HDACi) vorinostat, a cyclic KD (CKD), or dietary supplementation of the ketone body β-hydroxybutyrate (BHB), which is an endogenous HDACi. CKD and BHB supplementation each delayed prostate cancer tumor growth as monotherapy, and both BHB and adaptive immunity were required for the antitumor activity of CKD. Single-cell transcriptomic and proteomic profiling revealed that HDACi and ketogenesis enhanced ICB efficacy through both cancer cell-intrinsic mechanisms, including upregulation of MHC class I molecules, and -extrinsic mechanisms, such as CD8+ T-cell chemoattraction, M1/M2 macrophage rebalancing, monocyte differentiation toward antigen-presenting cells, and diminished neutrophil infiltration. Overall, these findings illuminate a potential clinical path of using HDACi and optimized KD regimens to enhance ICB therapy for prostate cancer. Significance: Optimized cyclic ketogenic diet and 1,3-butanediol supplementation regimens enhance the efficacy of immune checkpoint blockade in prostate cancer through epigenetic and immune modulations, providing dietary interventions to sensitize tumors to immunotherapy.
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    Neutrophils Resist Ferroptosis and Promote Breast Cancer Metastasis through Aconitate Decarboxylase 1
    (Elsevier, 2023) Zhao, Yun; Liu, Zhongshun; Liu, Guoqiang; Zhang, Yuting; Liu, Sheng; Gan, Dailin; Chang, Wennan; Peng, Xiaoxia; Sung, Eun Suh; Gilbert, Keegan; Zhu, Yini; Wang, Xuechun; Zeng, Ziyu; Baldwin, Hope; Ren, Guanzhu; Weaver, Jessica; Huron, Anna; Mayberry, Toni; Wang, Qingfei; Wang, Yujue; Diaz-Rubio, Maria Elena; Su, Xiaoyang; Stack, M. Sharon; Zhang, Siyuan; Lu, Xuemin; Sheldon, Ryan D.; Li, Jun; Zhang, Chi; Wan, Jun; Lu, Xin; Medical and Molecular Genetics, School of Medicine
    Metastasis causes breast cancer-related mortality. Tumor-infiltrating neutrophils (TINs) inflict immunosuppression and promote metastasis. Therapeutic debilitation of TINs may enhance immunotherapy, yet it remains a challenge to identify therapeutic targets highly expressed and functionally essential in TINs but under-expressed in extra-tumoral neutrophils. Here, using single-cell RNA sequencing to compare TINs and circulating neutrophils in murine mammary tumor models, we identified aconitate decarboxylase 1 (Acod1) as the most upregulated metabolic enzyme in mouse TINs and validated high Acod1 expression in human TINs. Activated through the GM-CSF-JAK/STAT5-C/EBPβ pathway, Acod1 produces itaconate, which mediates Nrf2-dependent defense against ferroptosis and upholds the persistence of TINs. Acod1 ablation abates TIN infiltration, constrains metastasis (but not primary tumors), bolsters antitumor T cell immunity, and boosts the efficacy of immune checkpoint blockade. Our findings reveal how TINs escape from ferroptosis through the Acod1-dependent immunometabolism switch and establish Acod1 as a target to offset immunosuppression and improve immunotherapy against metastasis.
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    Protein Signature Differentiating Neutrophils and Myeloid-Derived Suppressor Cells Determined Using a Human Isogenic Cell Line Model and Protein Profiling
    (MDPI, 2024-05-07) Zhang, Yuting; Hu, Jin; Zhang, Xiashiyao; Liang, Minzhi; Wang, Xuechun; Gan, Dailin; Li, Jun; Lu, Xuemin; Wan, Jun; Feng, Shan; Lu, Xin; Medical and Molecular Genetics, School of Medicine
    Myeloid-derived suppressor cells (MDSCs) play an essential role in suppressing the antitumor activity of T lymphocytes in solid tumors, thus representing an attractive therapeutic target to enhance the efficacy of immunotherapy. However, the differences in protein expression between MDSCs and their physiological counterparts, particularly polymorphonuclear neutrophils (PMNs), remain inadequately characterized, making the specific identification and targeting of MDSCs difficult. PMNs and PMN-MDSCs share markers such as CD11b+CD14−CD15+/CD66b+, and some MDSC-enriched markers are emerging, such as LOX-1 and CD84. More proteomics studies are needed to identify the signature and markers for MDSCs. Recently, we reported the induced differentiation of isogenic PMNs or MDSCs (referred to as iPMNs and iMDSCs, respectively) from the human promyelocytic cell line HL60. Here, we profiled the global proteomics and membrane proteomics of these cells with quantitative mass spectrometry, which identified a 41-protein signature (“cluster 6”) that was upregulated in iMDSCs compared with HL60 and iPMN. We further integrated our cell line-based proteomics data with a published proteomics dataset of normal human primary monocytes and monocyte-derived MDSCs induced by cancer-associated fibroblasts. The analysis identified a 38-protein signature that exhibits an upregulated expression pattern in MDSCs compared with normal monocytes or PMNs. These signatures may provide a hypothesis-generating platform to identify protein biomarkers that phenotypically distinguish MDSCs from their healthy counterparts, as well as potential therapeutic targets that impair MDSCs without harming normal myeloid cells.
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    SCIPAC: quantitative estimation of cell-phenotype associations
    (Springer Nature, 2024-05-13) Gan, Dailin; Zhu, Yini; Lu, Xin; Li, Jun; Medicine, School of Medicine
    Numerous algorithms have been proposed to identify cell types in single-cell RNA sequencing data, yet a fundamental problem remains: determining associations between cells and phenotypes such as cancer. We develop SCIPAC, the first algorithm that quantitatively estimates the association between each cell in single-cell data and a phenotype. SCIPAC also provides a p-value for each association and applies to data with virtually any type of phenotype. We demonstrate SCIPAC's accuracy in simulated data. On four real cancerous or noncancerous datasets, insights from SCIPAC help interpret the data and generate new hypotheses. SCIPAC requires minimum tuning and is computationally very fast.