IU Indianapolis ScholarWorks :: Browsing by Author "Dong, Chuanpeng"

Browsing by Author "Dong, Chuanpeng"

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CGPE: A user-friendly gene and pathway explore webserver for public cancer transcriptional data
Liu, Jiannan; Dong, Chuanpeng; Liu, Yunlong; Wu, Huanmei
High throughput technology has been widely used by researchers to understand diseases at the molecular level. Database and servers for downloading and analyzing these publicly data is available as well. But there is still lacking tools for facilitating researchers to study the function of genes in pathways views by integrated public omics data.
CGPE: an integrated online server for Cancer Gene and Pathway Exploration
(Oxford University Press, 2021) Liu, Jiannan; Dong, Chuanpeng; Liu, Yunlong; Wu, Huanmei; BioHealth Informatics, School of Informatics and Computing
Summary: Cancer Gene and Pathway Explorer (CGPE) is developed to guide biological and clinical researchers, especially those with limited informatics and programming skills, performing preliminary cancer-related biomedical research using transcriptional data and publications. CGPE enables three user-friendly online analytical and visualization modules without requiring any local deployment. The GenePub HotIndex applies natural language processing, statistics and association discovery to provide analytical results on gene-specific PubMed publications, including gene-specific research trends, cancer types correlations, top-related genes and the WordCloud of publication profiles. The OnlineGSEA enables Gene Set Enrichment Analysis (GSEA) and results visualizations through an easy-to-follow interface for public or in-house transcriptional datasets, integrating the GSEA algorithm and preprocessed public TCGA and GEO datasets. The preprocessed datasets ensure gene sets analysis with appropriate pathway alternation and gene signatures. The CellLine Search presents evidence-based guidance for cell line selections with combined information on cell line dependency, gene expressions and pathway activity maps, which are valuable knowledge to have before conducting gene-related experiments. In a nutshell, the CGPE webserver provides a user-friendly, visual, intuitive and informative bioinformatics tool that allows biomedical researchers to perform efficient analyses and preliminary studies on in-house and publicly available bioinformatics data.
Diagnostic Evidence GAuge of Single cells (DEGAS): a flexible deep transfer learning framework for prioritizing cells in relation to disease
(BMC, 2022-02-01) Johnson, Travis S.; Yu, Christina Y.; Huang, Zhi; Xu, Siwen; Wang, Tongxin; Dong, Chuanpeng; Shao, Wei; Zaid, Mohammad Abu; Huang, Xiaoqing; Wang, Yijie; Bartlett, Christopher; Zhang, Yan; Walker, Brian A.; Liu, Yunlong; Huang, Kun; Zhang, Jie; Medicine, School of Medicine
We propose DEGAS (Diagnostic Evidence GAuge of Single cells), a novel deep transfer learning framework, to transfer disease information from patients to cells. We call such transferrable information "impressions," which allow individual cells to be associated with disease attributes like diagnosis, prognosis, and response to therapy. Using simulated data and ten diverse single-cell and patient bulk tissue transcriptomic datasets from glioblastoma multiforme (GBM), Alzheimer's disease (AD), and multiple myeloma (MM), we demonstrate the feasibility, flexibility, and broad applications of the DEGAS framework. DEGAS analysis on myeloma single-cell transcriptomics identified PHF19high myeloma cells associated with progression.
Generation of the tumor-suppressive secretome from tumor cells
(Ivyspring International, 2021-07-25) Liu, Shengzhi; Sun, Xun; Li, Kexin; Zha, Rongrong; Feng, Yan; Sano, Tomohiko; Dong, Chuanpeng; Liu, Yunlong; Aryal, Uma K.; Sudo, Akihiro; Li, Bai-Yan; Yokota, Hiroki; Biomedical Engineering, School of Engineering and Technology
Rationale: The progression of cancer cells depends on the soil and building an inhibitory soil might be a therapeutic option. We previously created tumor-suppressive secretomes by activating Wnt signaling in MSCs. Here, we examined whether the anti-tumor secretomes can be produced from tumor cells. Methods: Wnt signaling was activated in tumor cells by overexpressing β-catenin or administering BML284, a Wnt activator. Their conditioned medium (CM) was applied to cancer cells or tissues, and the effects of CM were evaluated. Tumor growth in the mammary fat pad and tibia in C57BL/6 female mice was also evaluated through μCT imaging and histology. Whole-genome proteomics analysis was conducted to determine and characterize novel tumor-suppressing proteins, which were enriched in CM. Results: The overexpression of β-catenin or the administration of BML284 generated tumor-suppressive secretomes from breast, prostate and pancreatic cancer cells. In the mouse model, β-catenin-overexpressing CM reduced tumor growth and tumor-driven bone destruction. This inhibition was also observed with BML284-treated CM. Besides p53 and Trail, proteomics analysis revealed that CM was enriched with enolase 1 (Eno1) and ubiquitin C (Ubc) that presented notable tumor-suppressing actions. Importantly, Eno1 immunoprecipitated CD44, a cell-surface adhesion receptor, and its silencing suppressed Eno1-driven tumor inhibition. A pan-cancer survival analysis revealed that the downregulation of MMP9, Runx2 and Snail by CM had a significant impact on survival outcomes (p < 0.00001). CM presented a selective inhibition of tumor cells compared to non-tumor cells, and it downregulated PD-L1, an immune escape modulator. Conclusions: The tumor-suppressive secretome can be generated from tumor cells, in which β-catenin presented two opposing roles, as an intracellular tumor promoter in tumor cells and a generator of extracellular tumor suppressor in CM. Eno1 was enriched in CM and its interaction with CD44 was involved in Eno1's anti-tumor action. Besides presenting a potential option for treating primary cancers and metastases, the result indicates that aggressive tumors may inhibit the growth of less aggressive tumors via tumor-suppressive secretomes.
Genetic Regulation of Human isomiR Biogenesis
(MDPI, 2023-09-04) Jiang, Guanglong; Reiter, Jill L.; Dong, Chuanpeng; Wang, Yue; Fang, Fang; Jiang, Zhaoyang; Liu, Yunlong; BioHealth Informatics, School of Informatics and Computing
MicroRNAs play a critical role in regulating gene expression post-transcriptionally. Variations in mature microRNA sequences, known as isomiRs, arise from imprecise cleavage and nucleotide substitution or addition. These isomiRs can target different mRNAs or compete with their canonical counterparts, thereby expanding the scope of miRNA post-transcriptional regulation. Our study investigated the relationship between cis-acting single-nucleotide polymorphisms (SNPs) in precursor miRNA regions and isomiR composition, represented by the ratio of a specific 5'-isomiR subtype to all isomiRs identified for a particular mature miRNA. Significant associations between 95 SNP-isomiR pairs were identified. Of note, rs6505162 was significantly associated with both the 5'-extension of hsa-miR-423-3p and the 5'-trimming of hsa-miR-423-5p. Comparison of breast cancer and normal samples revealed that the expression of both isomiRs was significantly higher in tumors than in normal tissues. This study sheds light on the genetic regulation of isomiR maturation and advances our understanding of post-transcriptional regulation by microRNAs.
Genetic Variants of Phospholipase C-γ2 Alter the Phenotype and Function of Microglia and Confer Differential Risk for Alzheimer’s Disease
(Elsevier, 2023) Tsai, Andy P.; Dong, Chuanpeng; Lin, Peter Bor-Chian; Oblak, Adrian L.; Di Prisco, Gonzalo Viana; Wang, Nian; Hajicek, Nicole; Carr, Adam J.; Lendy, Emma K.; Hahn, Oliver; Atkins, Micaiah; Foltz, Aulden G.; Patel, Jheel; Xu, Guixiang; Moutinho, Miguel; Sondek, John; Zhang, Qisheng; Mesecar, Andrew D.; Liu, Yunlong; Atwood, Brady K.; Wyss-Coray, Tony; Nho, Kwangsik; Bissel, Stephanie J.; Lamb, Bruce T.; Landreth, Gary E.; Medical and Molecular Genetics, School of Medicine
Genetic association studies have demonstrated the critical involvement of the microglial immune response in Alzheimer's disease (AD) pathogenesis. Phospholipase C-gamma-2 (PLCG2) is selectively expressed by microglia and functions in many immune receptor signaling pathways. In AD, PLCG2 is induced uniquely in plaque-associated microglia. A genetic variant of PLCG2, PLCG2P522R, is a mild hypermorph that attenuates AD risk. Here, we identified a loss-of-function PLCG2 variant, PLCG2M28L, that confers an increased AD risk. PLCG2P522R attenuated disease in an amyloidogenic murine AD model, whereas PLCG2M28L exacerbated the plaque burden associated with altered phagocytosis and Aβ clearance. The variants bidirectionally modulated disease pathology by inducing distinct transcriptional programs that identified microglial subpopulations associated with protective or detrimental phenotypes. These findings identify PLCG2M28L as a potential AD risk variant and demonstrate that PLCG2 variants can differentially orchestrate microglial responses in AD pathogenesis that can be therapeutically targeted.
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.
Impact of Proinflammatory Cytokines on Alternative Splicing Patterns in Human Islets
(American Diabetes Association, 2021) Wu, Wenting; Syed, Farooq; Simpson, Edward; Lee, Chih-Chun; Liu, Jing; Chang, Garrick; Dong, Chuanpeng; Seitz, Clayton; Eizirik, Decio L.; Mirmira, Raghavendra G.; Liu, Yunlong; Evans-Molina, Carmella; Medical and Molecular Genetics, School of Medicine
Alternative splicing (AS) within the β-cell has been proposed as one potential pathway that may exacerbate autoimmunity and unveil novel immunogenic epitopes in type 1 diabetes (T1D). We used a computational strategy to prioritize pathogenic splicing events in human islets treated with interleukin-1β plus interferon-γ as an ex vivo model of T1D and coupled this analysis with a k-mer–based approach to predict RNA-binding proteins involved in AS. In total, 969 AS events were identified in cytokine-treated islets, with a majority (44.8%) involving a skipped exon. ExonImpact identified 129 events predicted to affect protein structure. AS occurred with high frequency in MHC class II–related mRNAs, and targeted quantitative PCR validated reduced inclusion of exon 5 in the MHC class II gene HLA-DMB. Single-molecule RNA fluorescence in situ hybridization confirmed increased HLA-DMB splicing in β-cells from human donors with established T1D and autoantibody positivity. Serine/arginine-rich splicing factor 2 was implicated in 37.2% of potentially pathogenic events, including exon 5 exclusion in HLA-DMB. Together, these data suggest that dynamic control of AS plays a role in the β-cell response to inflammatory signals during T1D evolution.
INPP5D expression is associated with risk for Alzheimer’s disease and induced by plaque-associated microglia
(Elsevier, 2021-06) Tsai, Andy P.; Bor-Chian, Lin Peter; Dong, Chuanpeng; Moutinho, Miguel; Casali, Brad T.; Liu, Yunlong; Lamb, Bruce T.; Landreth, Gary E.; Oblak, Adrian L.; Nho, Kwangsik; Medical and Molecular Genetics, School of Medicine
Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by cognitive decline, robust microgliosis, neuroinflammation, and neuronal loss. Genome-wide association studies recently highlighted a prominent role for microglia in late-onset AD (LOAD). Specifically, inositol polyphosphate-5-phosphatase (INPP5D), also known as SHIP1, is selectively expressed in brain microglia and has been reported to be associated with LOAD. Although INPP5D is likely a crucial player in AD pathophysiology, its role in disease onset and progression remains unclear. We performed differential gene expression analysis to investigate INPP5D expression in AD and its association with plaque density and microglial markers using transcriptomic (RNA-Seq) data from the Accelerating Medicines Partnership for Alzheimer's Disease (AMP-AD) cohort. We also performed quantitative real-time PCR, immunoblotting, and immunofluorescence assays to assess INPP5D expression in the 5xFAD amyloid mouse model. Differential gene expression analysis found that INPP5D expression was upregulated in LOAD and positively correlated with amyloid plaque density. In addition, in 5xFAD mice, Inpp5d expression increased as the disease progressed, and selectively in plaque-associated microglia. Increased Inpp5d expression levels in 5xFAD mice were abolished entirely by depleting microglia with the colony-stimulating factor receptor-1 antagonist PLX5622. Our findings show that INPP5D expression increases as AD progresses, predominantly in plaque-associated microglia. Importantly, we provide the first evidence that increased INPP5D expression might be a risk factor in AD, highlighting INPP5D as a potential therapeutic target. Moreover, we have shown that the 5xFAD mouse model is appropriate for studying INPP5D in AD.
Intron Retention Induced Neoantigen as Biomarkers in Diseases
(2022-08) Dong, Chuanpeng; Yan, Jingwen; Liu, Yunlong; Huang, Kun; Wan, Jun; Liu, Xiaowen
Alternative splicing is a regulatory mechanism that generates multiple mRNA transcripts from a single gene, allowing significant expansion in proteome diversity. Disruption of splicing mechanisms has a large impact on the transcriptome and is a significant driver of complex diseases by producing condition-specific transcripts. Recent studies have reported that mis-spliced RNA transcripts can be another major source of neoantigens directly associated with immune responses. Particularly, aberrant peptides derived from unspliced introns can be presented by the major histocompatibility complex (MHC) class I molecules on the cell surface and elicit immunogenicity. In this dissertation, we first developed an integrated computational pipeline for identifying IR-induced neoantigens (IR-neoAg) from RNA sequencing (RNA-Seq) data. Our workflow also included a random forest classifier for prioritizing the neoepitopes with the highest likelihood to induce a T cell response. Second, we analyzed IR neoantigen using RNA-Seq data for multiple myeloma patients from the MMRF study. Our results suggested that the IR-neoAg load could serve as a prognosis biomarker, and immunosuppression in the myeloma microenvironment might offset the increasing neoantigen load effect. Thirdly, we demonstrated that high IR-neoAg predicts better overall survival in TCGA pancreatic cancer patients. Moreover, our results indicated the IR-neoAg load might be useful in identifying pancreatic cancer patients who might benefit from immune checkpoint blockade (ICB) therapy. Finally, we explored the association of IR-induced neo-peptides with neurodegeneration disease pathology and susceptibility. In conclusion, we presented a state-of-art computational solution for identifying IR-neoAgs, which might aid neoantigen-based vaccine development and the prediction of patient immunotherapy responses. Our studies provide remarkable insights into the roles of alternative splicing in complex diseases by directly mediating immune responses.

Browsing by Author "Dong, Chuanpeng"

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