Browsing by Author "Xu, Ying"

Now showing 1 - 6 of 6
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    Acid–base Homeostasis and Implications to the Phenotypic Behaviors of Cancer
    (Elsevier, 2023) Zhou, Yi; Chang, Wennan; Lu, Xiaoyu; Wang, Jin; Zhang, Chi; Xu, Ying; Medical and Molecular Genetics, School of Medicine
    Acid-base homeostasis is a fundamental property of living cells, and its persistent disruption in human cells can lead to a wide range of diseases. In this study, we conducted a computational modeling analysis of transcriptomic data of 4750 human tissue samples of 9 cancer types in The Cancer Genome Atlas (TCGA) database. Built on our previous study, we quantitatively estimated the average production rate of OH- by cytosolic Fenton reactions, which continuously disrupt the intracellular pH (pHi) homeostasis. Our predictions indicate that all or at least a subset of 43 reprogrammed metabolisms (RMs) are induced to produce net protons (H+) at comparable rates of Fenton reactions to keep the pHi stable. We then discovered that a number of well-known phenotypes of cancers, including increased growth rate, metastasis rate, and local immune cell composition, can be naturally explained in terms of the Fenton reaction level and the induced RMs. This study strongly suggests the possibility to have a unified framework for studies of cancer-inducing stressors, adaptive metabolic reprogramming, and cancerous behaviors. In addition, strong evidence is provided to demonstrate that a popular view that Na+/H+ exchangers along with lactic acid exporters and carbonic anhydrases are responsible for the intracellular alkalization and extracellular acidification in cancer may not be justified.
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    Co-expression based cancer staging and application
    (Nature Publishing group, 2020-06-30) Yu, Xiangchun; Cao, Sha; Zhou, Yi; Yu, Zhezhou; Xu, Ying; Biochemistry and Molecular Biology, School of Medicine
    A novel method is developed for predicting the stage of a cancer tissue based on the consistency level between the co-expression patterns in the given sample and samples in a specific stage. The basis for the prediction method is that cancer samples of the same stage share common functionalities as reflected by the co-expression patterns, which are distinct from samples in the other stages. Test results reveal that our prediction results are as good or potentially better than manually annotated stages by cancer pathologists. This new co-expression-based capability enables us to study how functionalities of cancer samples change as they evolve from early to the advanced stage. New and exciting results are discovered through such functional analyses, which offer new insights about what functions tend to be lost at what stage compared to the control tissues and similarly what new functions emerge as a cancer advances. To the best of our knowledge, this new capability represents the first computational method for accurately staging a cancer sample.
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    Competition between DNA Methylation, Nucleotide Synthesis, and Antioxidation in Cancer versus Normal Tissues
    (AACR, 2017-08) Cao, Sha; Zhu, Xiwen; Zhang, Chi; Qian, Hong; Schuttler, Heinz-Bernd; Gong, Jianping; Xu, Ying; Medical and Molecular Genetics, School of Medicine
    Global DNA hypomethylation occurs in many cancer types, but there is no explanation for its differential occurrence or possible impact on cancer cell physiology. Here we address these issues with a computational study of genome-scale DNA methylation in 16 cancer types. Specifically, we identified (i) a possible determinant for global DNA methylation in cancer cells and (ii) a relationship between levels of DNA methylation, nucleotide synthesis, and intracellular oxidative stress in cells. We developed a system of kinetic equations to capture the metabolic relations among DNA methylation, nucleotide synthesis, and antioxidative stress response, including their competitions for methyl and sulfur groups, based on known information about one-carbon metabolism and trans-sulfuration pathways. We observed a kinetic-based regulatory mechanism that controls reaction rates of the three competing processes when their shared resources are limited, particularly when the nucleotide synthesis rates or oxidative states are high. The combination of this regulatory mechanism and the need for rapid nucleotide synthesis, as well as high production of glutathione dictated by cancer-driving forces, led to the nearly universal observations of reduced global DNA methylation in cancer. Our model provides a natural explanation for differential global DNA methylation levels across cancer types and supports the observation that more malignant cancers tend to exhibit reduced DNA methylation levels. Insights obtained from this work provide useful information about the complexities of cancer due to interplays among competing, dynamic biological processes.
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    Elucidating the Functional Roles of Long Non-Coding RNAs in Alzheimer’s Disease
    (MDPI, 2024-08-25) Huang, Zhenyu; Chen, Qiufen; Mu, Xuechen; An, Zheng; Xu, Ying; Medicine, School of Medicine
    Alzheimer's disease (AD) is a multifaceted neurodegenerative disorder characterized by cognitive decline and neuronal loss, representing a most challenging health issue. We present a computational analysis of transcriptomic data of AD tissues vs. healthy controls, focused on the elucidation of functional roles played by long non-coding RNAs (lncRNAs) throughout the AD progression. We first assembled our own lncRNA transcripts from the raw RNA-Seq data generated from 527 samples of the dorsolateral prefrontal cortex, resulting in the identification of 31,574 novel lncRNA genes. Based on co-expression analyses between mRNAs and lncRNAs, a co-expression network was constructed. Maximal subnetworks with dense connections were identified as functional clusters. Pathway enrichment analyses were conducted over mRNAs and lncRNAs in each cluster, which served as the basis for the inference of functional roles played by lncRNAs involved in each of the key steps in an AD development model that we have previously built based on transcriptomic data of protein-encoding genes. Detailed information is presented about the functional roles of lncRNAs in activities related to stress response, reprogrammed metabolism, cell polarity, and development. Our analyses also revealed that lncRNAs have the discerning power to distinguish between AD samples of each stage and healthy controls. This study represents the first of its kind.
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    IsoTree: A New Framework for De novo Transcriptome Assembly from RNA-seq Reads
    (IEEE, 2018-02) Zhao, Jin; Feng, Haodi; Zhu, Daming; Zhang, Chi; Xu, Ying; Medical and Molecular Genetics, School of Medicine
    High-throughput sequencing of mRNA has made the deep and efficient probing of transcriptome more affordable. However, the vast amounts of short RNA-seq reads make de novo transcriptome assembly an algorithmic challenge. In this work, we present IsoTree, a novel framework for transcripts reconstruction in the absence of reference genomes. Unlike most of de novo assembly methods that build de Bruijn graph or splicing graph by connecting $k-mers$ which are sets of overlapping substrings generated from reads, IsoTree constructs splicing graph by connecting reads directly. For each splicing graph, IsoTree applies an iterative scheme of mixed integer linear program to build a prefix tree, called isoform tree. Each path from the root node of the isoform tree to a leaf node represents a plausible transcript candidate which will be pruned based on the information of paired-end reads. Experiments showed that in most cases IsoTree performs better than other leading transcriptome assembly programs. IsoTree is available at https://github.com/Jane110111107/IsoTree.
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    Warburg Effects in Cancer and Normal Proliferating Cells: Two Tales of the Same Name
    (Elsevier, 2019) Sun, Huiyan; Chen, Liang; Cao, Sha; Liang, Yanchun; Xu, Ying; Biostatistics, School of Public Health
    It has been observed that both cancer tissue cells and normal proliferating cells (NPCs) have the Warburg effect. Our goal here is to demonstrate that they do this for different reasons. To accomplish this, we have analyzed the transcriptomic data of over 7000 cancer and control tissues of 14 cancer types in TCGA and data of five NPC types in GEO. Our analyses reveal that NPCs accumulate large quantities of ATPs produced by the respiration process before starting the Warburg effect, to raise the intracellular pH from ∼6.8 to ∼7.2 and to prepare for cell division energetically. Once cell cycle starts, the cells start to rely on glycolysis for ATP generation followed by ATP hydrolysis and lactic acid release, to maintain the elevated intracellular pH as needed by cell division since together the three processes are pH neutral. The cells go back to the normal respiration-based ATP production once the cell division phase ends. In comparison, cancer cells have reached their intracellular pH at ∼7.4 from top down as multiple acid-loading transporters are up-regulated and most acid-extruding ones except for lactic acid exporters are repressed. Cancer cells use continuous glycolysis for ATP production as way to acidify the intracellular space since the lactic acid secretion is decoupled from glycolysis-based ATP generation and is pH balanced by increased expressions of acid-loading transporters. Co-expression analyses suggest that lactic acid secretion is regulated by external, non-pH related signals. Overall, our data strongly suggest that the two cell types have the Warburg effect for very different reasons.