Browsing by Author "Dong, Tianhan"

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    Combinatorial analyses reveal cellular composition changes have different impacts on transcriptomic changes of cell type specific genes in Alzheimer’s Disease
    (Springer Nature, 2021-01-11) Johnson, Travis S.; Xiang, Shunian; Dong, Tianhan; Huang, Zhi; Cheng, Michael; Wang, Tianfu; Yang, Kai; Ni, Dong; Huang, Kun; Zhang, Jie; Biostatistics, School of Public Health
    Alzheimer’s disease (AD) brains are characterized by progressive neuron loss and gliosis. Previous studies of gene expression using bulk tissue samples often fail to consider changes in cell-type composition when comparing AD versus control, which can lead to differences in expression levels that are not due to transcriptional regulation. We mined five large transcriptomic AD datasets for conserved gene co-expression module, then analyzed differential expression and differential co-expression within the modules between AD samples and controls. We performed cell-type deconvolution analysis to determine whether the observed differential expression was due to changes in cell-type proportions in the samples or to transcriptional regulation. Our findings were validated using four additional datasets. We discovered that the increased expression of microglia modules in the AD samples can be explained by increased microglia proportions in the AD samples. In contrast, decreased expression and perturbed co-expression within neuron modules in the AD samples was likely due in part to altered regulation of neuronal pathways. Several transcription factors that are differentially expressed in AD might account for such altered gene regulation. Similarly, changes in gene expression and co-expression within astrocyte modules could be attributed to combined effects of astrogliosis and astrocyte gene activation. Gene expression in the astrocyte modules was also strongly correlated with clinicopathological biomarkers. Through this work, we demonstrated that combinatorial analysis can delineate the origins of transcriptomic changes in bulk tissue data and shed light on key genes and pathways involved in AD.
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    Corrigendum: eIF3a Regulation of NHEJ Repair Protein Synthesis and Cellular Response to Ionizing Radiation
    (Frontiers Media, 2021-01-07) Tumia, Rima; Wang, Chao J.; Dong, Tianhan; Ma, Shijie; Beebe, Jenny; Chen, Juan; Dong, Zizheng; Liu, Jing-Yuan; Zhang, Jian-Ting; Pharmacology and Toxicology, School of Medicine
    [This corrects the article DOI: 10.3389/fcell.2020.00753.].
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    eIF3a Regulation of NHEJ Repair Protein Synthesis and Cellular Response to Ionizing Radiation
    (Frontiers, 2020-08-19) Tumia, Rima; Wang, Chao J.; Dong, Tianhan; Ma, Shijie; Beebe, Jenny; Chen, Juan; Dong, Zizheng; Liu, Jing-Yuan; Zhang, Jian-Ting; Pharmacology and Toxicology, School of Medicine
    Translation initiation in protein synthesis regulated by eukaryotic initiation factors (eIFs) is a crucial step in controlling gene expression. eIF3a has been shown to regulate protein synthesis and cellular response to treatments by anticancer agents including cisplatin by regulating nucleotide excision repair. In this study, we tested the hypothesis that eIF3a regulates the synthesis of proteins important for the repair of double-strand DNA breaks induced by ionizing radiation (IR). We found that eIF3a upregulation sensitized cellular response to IR while its downregulation caused resistance to IR. eIF3a increases IR-induced DNA damages and decreases non-homologous end joining (NHEJ) activity by suppressing the synthesis of NHEJ repair proteins. Furthermore, analysis of existing patient database shows that eIF3a expression associates with better overall survival of breast, gastric, lung, and ovarian cancer patients. These findings together suggest that eIF3a plays an important role in cellular response to DNA-damaging treatments by regulating the synthesis of DNA repair proteins and, thus, eIIF3a likely contributes to the outcome of cancer patients treated with DNA-damaging strategies including IR.
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    Highly robust model of transcription regulator activity predicts breast cancer overall survival
    (BMC, 2020) Dong, Chuanpeng; Liu, Jiannan; Chen, Steven X.; Dong, Tianhan; Jiang, Guanglong; Wang, Yue; Wu, Huanmei; Reiter, Jill L.; Liu, Yunlong; Medical and Molecular Genetics, School of Medicine
    Background: While several multigene signatures are available for predicting breast cancer prognosis, particularly in early stage disease, effective molecular indicators are needed, especially for triple-negative carcinomas, to improve treatments and predict diagnostic outcomes. The objective of this study was to identify transcriptional regulatory networks to better understand mechanisms giving rise to breast cancer development and to incorporate this information into a model for predicting clinical outcomes. Methods: Gene expression profiles from 1097 breast cancer patients were retrieved from The Cancer Genome Atlas (TCGA). Breast cancer-specific transcription regulatory information was identified by considering the binding site information from ENCODE and the top co-expressed targets in TCGA using a nonlinear approach. We then used this information to predict breast cancer patient survival outcome. Result: We built a multiple regulator-based prediction model for breast cancer. This model was validated in more than 5000 breast cancer patients from the Gene Expression Omnibus (GEO) databases. We demonstrated our regulator model was significantly associated with clinical stage and that cell cycle and DNA replication related pathways were significantly enriched in high regulator risk patients. Conclusion: Our findings demonstrate that transcriptional regulator activities can predict patient survival. This finding provides additional biological insights into the mechanisms of breast cancer progression.
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    MAL2 drives immune evasion in breast cancer by suppressing tumor antigen presentation
    (The American Society for Clinical Investigation, 2021-01-07) Fang, Yuanzhang; Wang, Lifei; Wan, Changlin; Sun, Yifan; Van der Jeught, Kevin; Zhou, Zhuolong; Dong, Tianhan; So, Ka Man; Yu, Tao; Li, Yujing; Eyvani, Haniyeh; Colter, Austyn B.; Dong, Edward; Cao, Sha; Wang, Jin; Schneider, Bryan P.; Sandusky, George E.; Liu, Yunlong; Zhang, Chi; Lu, Xiongbin; Zhang, Xinna; Medical and Molecular Genetics, School of Medicine
    Immune evasion is a pivotal event in tumor progression. To eliminate human cancer cells, current immune checkpoint therapy is set to boost CD8+ T cell-mediated cytotoxicity. However, this action is eventually dependent on the efficient recognition of tumor-specific antigens via T cell receptors. One primary mechanism by which tumor cells evade immune surveillance is to downregulate their antigen presentation. Little progress has been made toward harnessing potential therapeutic targets for enhancing antigen presentation on the tumor cell. Here, we identified MAL2 as a key player that determines the turnover of the antigen-loaded MHC-I complex and reduces the antigen presentation on tumor cells. MAL2 promotes the endocytosis of tumor antigens via direct interaction with the MHC-I complex and endosome-associated RAB proteins. In preclinical models, depletion of MAL2 in breast tumor cells profoundly enhanced the cytotoxicity of tumor-infiltrating CD8+ T cells and suppressed breast tumor growth, suggesting that MAL2 is a potential therapeutic target for breast cancer immunotherapy.