Browsing by Author "Yu, Hao"

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    Author Correction: Mutant p53 drives clonal hematopoiesis through modulating epigenetic pathway
    (Nature Publishing Group, 2020-07-28) Chen, Sisi; Wang, Qiang; Yu, Hao; Capitano, Maegan L.; Vemula, Sasidhar; Nabinger, Sarah C.; Gao, Rui; Yao, Chonghua; Kobayashi, Michihiro; Geng, Zhuangzhuang; Fahey, Aidan; Henley, Danielle; Liu, Stephen Z.; Barajas, Sergio; Cai, Wenjie; Wolf, Eric R.; Ramdas, Baskar; Cai, Zhigang; Gao, Hongyu; Luo, Na; Sun, Yang; Wong, Terrence N.; Link, Daniel C.; Liu, Yunlong; Boswell, H. Scott; Mayo, Lindsey D.; Huang, Gang; Kapur, Reuben; Yoder, Mervin C.; Broxmeyer, Hal E.; Gao, Zhonghua; Liu, Yan; Biochemistry and Molecular Biology, School of Medicine
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    Bmi1 promotes erythroid development through regulating ribosome biogenesis
    (Wiley, 2015-03) Gao, Rui; Chen, Sisi; Kobayashi, Michihiro; Yu, Hao; Zhang, Yingchi; Wan, Yang; Young, Sara K.; Soltis, Anthony; Yu, Ming; Vemula, Sasidhar; Fraenkel, Ernest; Cantor, Alan; Antipin, Yevgeniy; Xu, Yang; Yoder, Mervin C.; Wek, Ronald C.; Ellis, Steven R.; Kapur, Reuben; Zhu, Xiaofan; Liu, Yan; Department of Pediatrics, Indiana University School of Medicine
    While Polycomb group protein Bmi1 is important for stem cell maintenance, its role in lineage commitment is largely unknown. We have identified Bmi1 as a novel regulator of erythroid development. Bmi1 is highly expressed in mouse erythroid progenitor cells and its deficiency impairs erythroid differentiation. BMI1 is also important for human erythroid development. Furthermore, we discovered that loss of Bmi1 in erythroid progenitor cells results in decreased transcription of multiple ribosomal protein genes and impaired ribosome biogenesis. Bmi1 deficiency stabilizes p53 protein, leading to upregulation of p21 expression and subsequent G0/G1 cell cycle arrest. Genetic inhibition of p53 activity rescues the erythroid defects seen in the Bmi1 null mice, demonstrating that a p53-dependent mechanism underlies the pathophysiology of the anemia. Mechanistically, Bmi1 is associated with multiple ribosomal protein genes and may positively regulate their expression in erythroid progenitor cells. Thus, Bmi1 promotes erythroid development, at least in part through regulating ribosome biogenesis. Ribosomopathies are human disorders of ribosome dysfunction, including Diamond-Blackfan anemia (DBA) and 5q- syndrome, in which genetic abnormalities cause impaired ribosome biogenesis, resulting in specific clinical phenotypes. We observed that BMI1 expression in human hematopoietic stem and progenitor cells from patients with DBA is correlated with the expression of some ribosomal protein genes, suggesting that BMI1 deficiency may play a pathological role in DBA and other ribosomopathies.
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    Bmi1 Regulates Wnt Signaling in Hematopoietic Stem and Progenitor Cells
    (Springer, 2021) Yu, Hao; Gao, Rui; Chen, Sisi; Liu, Xicheng; Wang, Qiang; Cai, Wenjie; Vemula, Sasidhar; Fahey, Aidan C.; Henley, Danielle; Kobayashi, Michihiro; Liu, Stephen Z.; Qian, Zhijian; Kapur, Reuben; Broxmeyer, Hal E.; Gao, Zhonghua; Xi, Rongwen; Liu, Yan; Pediatrics, School of Medicine
    Polycomb group protein Bmi1 is essential for hematopoietic stem cell (HSC) self-renewal and terminal differentiation. However, its target genes in hematopoietic stem and progenitor cells are largely unknown. We performed gene expression profiling assays and found that genes of the Wnt signaling pathway are significantly elevated in Bmi1 null hematopoietic stem and progenitor cells (HSPCs). Bmi1 is associated with several genes of the Wnt signaling pathway in hematopoietic cells. Further, we found that Bmi1 represses Wnt gene expression in HSPCs. Importantly, loss of β-catenin, which reduces Wnt activation, partially rescues the HSC self-renewal and differentiation defects seen in the Bmi1 null mice. Thus, we have identified Bmi1 as a novel regulator of Wnt signaling pathway in HSPCs. Given that Wnt signaling pathway plays an important role in hematopoiesis, our studies suggest that modulating Wnt signaling may hold potential for enhancing HSC self-renewal, thereby improving the outcomes of HSC transplantation.
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    Machine Learning to Build and Validate a Model for Radiation Pneumonitis Prediction in Patients with Non–Small Cell Lung Cancer
    (AACR, 2019-07) Yu, Hao; Wu, Huanmei; Wang, Weili; Jolly, Shruti; Jin, Jianyue; Hu, Chen; Kong, Feng-Ming (Spring); BioHealth Informatics, School of Informatics and Computing
    Purpose: Radiation pneumonitis is an important adverse event in patients with non–small cell lung cancer (NSCLC) receiving thoracic radiotherapy. However, the risk of radiation pneumonitis grade ≥ 2 (RP2) has not been well predicted. This study hypothesized that inflammatory cytokines or the dynamic changes during radiotherapy can improve predictive accuracy for RP2. Experimental Design: Levels of 30 inflammatory cytokines and clinical information in patients with stages I–III NSCLC treated with radiotherapy were from our prospective studies. Statistical analysis was used to select predictive cytokine candidates and clinical covariates for adjustment. Machine learning algorithm was used to develop the generalized linear model for predicting risk RP2. Results: A total of 131 patients were eligible and 17 (13.0%) developed RP2. IL8 and CCL2 had significantly (Bonferroni) lower expression levels in patients with RP2 than without RP2. But none of the changes in cytokine levels during radiotherapy was significantly associated with RP2. The final predictive GLM model for RP2 was established, including IL8 and CCL2 at baseline level and two clinical variables. Nomogram was constructed based on the GLM model. The model's predicting ability was validated in the completely independent test set (AUC = 0.863, accuracy = 80.0%, sensitivity = 100%, specificity = 76.5%). Conclusions: By machine learning, this study has developed and validated a comprehensive model integrating inflammatory cytokines with clinical variables to predict RP2 before radiotherapy that provides an opportunity to guide clinicians.
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    Mutant p53 drives clonal hematopoiesis through modulating epigenetic pathway
    (Nature Research, 2019-12-11) Chen, Sisi; Wang, Qiang; Yu, Hao; Capitano, Maegan L.; Vemula, Sasidhar; Nabinger, Sarah C.; Gao, Rui; Yao, Chonghua; Kobayashi, Michihiro; Geng, Zhuangzhuang; Fahey, Aidan; Henley, Danielle; Liu, Stephen Z.; Barajas, Sergio; Sergio, Wenjie; Wolf, Eric R.; Ramdas, Baskar; Cai, Zhigang; Gao, Hongyu; Luo, Na; Sun, Yang; Wong, Terrence N.; Link, Daniel C.; Liu, Yunlong; Boswell, H. Scott; Mayo, Lindsey D.; Huang, Gang; Kapur, Reuben; Yoder, Mervin C.; Broxmeyer, Hal E.; Gao, Zhonghua; Liu, Yan; Biochemistry and Molecular Biology, School of Medicine
    Clonal hematopoiesis of indeterminate potential (CHIP) increases with age and is associated with increased risks of hematological malignancies. While TP53 mutations have been identified in CHIP, the molecular mechanisms by which mutant p53 promotes hematopoietic stem and progenitor cell (HSPC) expansion are largely unknown. Here we discover that mutant p53 confers a competitive advantage to HSPCs following transplantation and promotes HSPC expansion after radiation-induced stress. Mechanistically, mutant p53 interacts with EZH2 and enhances its association with the chromatin, thereby increasing the levels of H3K27me3 in genes regulating HSPC self-renewal and differentiation. Furthermore, genetic and pharmacological inhibition of EZH2 decreases the repopulating potential of p53 mutant HSPCs. Thus, we uncover an epigenetic mechanism by which mutant p53 drives clonal hematopoiesis. Our work will likely establish epigenetic regulator EZH2 as a novel therapeutic target for preventing CHIP progression and treating hematological malignancies with TP53 mutations.
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    Pharmacological inhibition of AKT activity in human CD34+ cells enhances their ability to engraft immunodeficient mice
    (Elsevier, 2017-01) Chen, Sisi; Gao, Rui; Kobayashi, Michihiro; Yu, Hao; Yao, Chonghua; Kapur, Reuben; Yoder, Mervin C.; Liu, Yan; Biochemistry and Molecular Biology, School of Medicine
    Although practiced clinically for more than 40 years, the use of hematopoietic stem cell (HSC) transplantation remains limited by the inability to expand functional HSCs ex vivo. To determine the role of phosphoinositide 3-kinase (PI3K)/AKT signaling in human hematopoietic stem and progenitor cell (HSPC) maintenance, we examined the effect of genetic and pharmacological inhibition of AKT on human umbilical cord blood (UCB) CD34+ cells. We found that knock-down of AKT1 in human UCB CD34+ cells using short interfering RNAs targeting AKT1 enhances their quiescence and colony formation potential in vitro. We treated human UCB CD34+ cells with an AKT-specific inhibitor (AKTi) and performed both in vitro and in vivo stem and progenitor cell assays. We found that ex vivo treatment of human HSPCs maintains CD34 expression and enhances colony formation in serial replating assays. Moreover, pharmacological inhibition of AKT enhances the short-term repopulating potential of human UCB CD34+ cells in immunodeficient mice. Mechanistically, genetic and pharmacological inhibition of AKT activity promotes human HSPC quiescence. These preclinical results suggest a positive role for AKTi during ex vivo culture of human UCB HSPCs.
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    PRL2/PTP4A2 phosphatase is important for hematopoietic stem cell self-renewal
    (Wiley, 2014-07) Kobayashi, Michihiro; Bai, Yunpeng; Dong, Yuanshu; Yu, Hao; Chen, Sisi; Gao, Rui; Zhang, Lujuan; Yoder, Mervin C.; Kapur, Reuben; Zhang, Zhong-Yin; Liu, Yan; Department of Pediatrics, Indiana University School of Medicine
    Hematopoietic stem cell (HSC) self-renewal is tightly controlled by cytokines and other signals in the microenvironment. While stem cell factor (SCF) is an early acting cytokine that activates the receptor tyrosine kinase KIT and promotes HSC maintenance, how SCF/KIT signaling is regulated in HSCs is poorly understood. The protein tyrosine phosphatase 4A (PTP4A) family (aka PRL [phosphatase of regenerating liver] phosphatases), consisting of PTP4A1/PRL1, PTP4A2/PRL2, and PTP4A3/PRL3, represents an intriguing group of phosphatases implicated in cell proliferation and tumorigenesis. However, the role of PTP4A in hematopoiesis remains elusive. To define the role of PTP4A in hematopoiesis, we analyzed HSC behavior in Ptp4a2 (Prl2) deficient mice. We found that Ptp4a2 deficiency impairs HSC self-renewal as revealed by serial bone marrow transplantation assays. Moreover, we observed that Ptp4a2 null hematopoietic stem and progenitor cells (HSPCs) are more quiescent and show reduced activation of the AKT and ERK signaling. Importantly, we discovered that the ability of PTP4A2 to enhance HSPC proliferation and activation of AKT and ERK signaling depends on its phosphatase activity. Furthermore, we found that PTP4A2 is important for SCF-mediated HSPC proliferation and loss of Ptp4a2 decreased the ability of oncogenic KIT/D814V mutant in promoting hematopoietic progenitor cell proliferation. Thus, PTP4A2 plays critical roles in regulating HSC self-renewal and mediating SCF/KIT signaling.
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    Significance of radiation esophagitis: Conditional survival assessment in patients with non-small cell lung cancer
    (Elsevier, 2021) Yu, Hao; Lam, Ka-On; Green, Michael D.; Wu, Huanmei; Yang, Li; Wang, Weili; Jin, Jianyue; Hu, Chen; Wang, Yang; Jolly, Shruti; Kong, Feng-Ming (Spring); Biomedical Engineering and Informatics, Luddy School of Informatics, Computing, and Engineering
    Purpose: This study aimed to examine the effect of radiation esophagitis (RE) and the dynamics of RE on subsequent survival in non-small cell lung cancer (NSCLC) patients who underwent radiotherapy. Experimental Design: Patients with NSCLC treated with fractionated thoracic radiotherapy enrolled in prospective trials were eligible. RE was graded prospectively according to Common Terminology Criteria for Adverse Events (CTCAE) v3.0 per protocol requirement weekly during-RT and 1 month after RT. This study applied conditional survival assessment which has advantage over traditional survival analysis as it assesses the survival from the event instead of from the baseline. P-value less than 0.05 was considered to be significant. The primary endpoint is overall survival. Results: A total of 177 patients were eligible, with a median follow-up of 5 years. The presence of RE, the maximum RE grade, the evolution of RE and the onset timing of RE events were all correlated with subsequent survival. At all conditional time points, patients first presented with RE grade1 (initial RE1) had significant inferior subsequent survival (multivariable HRs median: 1.63, all P-values<0.05); meanwhile those with RE progressed had significant inferior subsequent survival than those never develop RE (multivariable HRs median: 2.08, all P-values<0.05). Multivariable Cox proportional-hazards analysis showed significantly higher C-indexes for models with inclusion of RE events than those without (all P-values<0.05). Conclusion: This study comprehensively evaluated the impact of RE with conditional survival assessment and demonstrated that RE is associated with inferior survival in NSCLC patients treated with RT.
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    Spatial Expansion and Soil Organic Carbon Storage Changes of Croplands in the Sanjiang Plain, China
    (MDPI, 2017-04) Man, Weidong; Yu, Hao; Li, Lin; Liu, Mingyue; Mao, Dehua; Ren, Chunying; Wang, Zongming; Jia, Mingming; Miao, Zhenghong; Lu, Chunyan; Li, Huiying; Earth Sciences, School of Science
    Soil is the largest pool of terrestrial organic carbon in the biosphere and interacts strongly with the atmosphere, climate and land cover. Remote sensing (RS) and geographic information systems (GIS) were used to study the spatio-temporal dynamics of croplands and soil organic carbon density (SOCD) in the Sanjiang Plain, to estimate soil organic carbon (SOC) storage. Results show that croplands increased with 10,600.68 km2 from 1992 to 2012 in the Sanjiang Plain. Area of 13,959.43 km2 of dry farmlands were converted into paddy fields. Cropland SOC storage is estimated to be 1.29 ± 0.27 Pg C (1 Pg = 103 Tg = 1015 g) in 2012. Although the mean value of SOCD for croplands decreased from 1992 to 2012, the SOC storage of croplands in the top 1 m in the Sanjiang Plain increased by 70 Tg C (1220 to 1290). This is attributed to the area increases of cropland. The SOCD of paddy fields was higher and decreased more slowly than that of dry farmlands from 1992 to 2012. Conversion between dry farmlands and paddy fields and the agricultural reclamation from natural land-use types significantly affect the spatio-temporal patterns of cropland SOCD in the Sanjiang Plain. Regions with higher and lower SOCD values move northeast and westward, respectively, which is almost consistent with the movement direction of centroids for paddy fields and dry farmlands in the study area. Therefore, these results were verified. SOC storages in dry farmlands decreased by 17.5 Tg·year−1 from 1992 to 2012, whilst paddy fields increased by 21.0 Tg·C·year−1.
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    Weighted-Support Vector Machine Learning Classifier of Circulating Cytokine Biomarkers to Predict Radiation-Induced Lung Fibrosis in Non-Small-Cell Lung Cancer Patients
    (Frontiers Media, 2021-02-01) Yu, Hao; Lam, Ka-On; Wu, Huanmei; Green, Michael; Wang, Weili; Jin, Jian-Yue; Hu, Chen; Jolly, Shruti; Wang, Yang; Kong, Feng-Ming Spring; BioHealth Informatics, School of Informatics and Computing
    Background: Radiation-induced lung fibrosis (RILF) is an important late toxicity in patients with non-small-cell lung cancer (NSCLC) after radiotherapy (RT). Clinically significant RILF can impact quality of life and/or cause non-cancer related death. This study aimed to determine whether pre-treatment plasma cytokine levels have a significant effect on the risk of RILF and investigate the abilities of machine learning algorithms for risk prediction. Methods: This is a secondary analysis of prospective studies from two academic cancer centers. The primary endpoint was grade≥2 (RILF2), classified according to a system consistent with the consensus recommendation of an expert panel of the AAPM task for normal tissue toxicity. Eligible patients must have at least 6 months' follow-up after radiotherapy commencement. Baseline levels of 30 cytokines, dosimetric, and clinical characteristics were analyzed. Support vector machine (SVM) algorithm was applied for model development. Data from one center was used for model training and development; and data of another center was applied as an independent external validation. Results: There were 57 and 37 eligible patients in training and validation datasets, with 14 and 16.2% RILF2, respectively. Of the 30 plasma cytokines evaluated, SVM identified baseline circulating CCL4 as the most significant cytokine associated with RILF2 risk in both datasets (P = 0.003 and 0.07, for training and test sets, respectively). An SVM classifier predictive of RILF2 was generated in Cohort 1 with CCL4, mean lung dose (MLD) and chemotherapy as key model features. This classifier was validated in Cohort 2 with accuracy of 0.757 and area under the curve (AUC) of 0.855. Conclusions: Using machine learning, this study constructed and validated a weighted-SVM classifier incorporating circulating CCL4 levels with significant dosimetric and clinical parameters which predicts RILF2 risk with a reasonable accuracy. Further study with larger sample size is needed to validate the role of CCL4, and this SVM classifier in RILF2.