Autotaxin (ATX) is a secreted glycoprotein and functions as a key enzyme to produce extracellular lysophosphatidic acid (LPA). LPA interacts with at least six G protein-coupled receptors, LPAR1-6, on the cell membrane to activate various signal transduction pathways through distinct G proteins, such as Gi/0, G12/13, Gq/11, and Gs. The ATX-LPA axis plays an important role in physiological and pathological processes, including embryogenesis, obesity, and inflammation. ATX is one of the top 40 most unregulated genes in metastatic cancer, and the ATX-LPA axis is involved in the development of different types of cancers, such as colorectal cancer, ovarian cancer, breast cancer, and glioblastoma. ATX expression is under multifaceted controls at the transcription, post-transcription, and secretion levels. ATX and LPA in the tumor microenvironment not only promote cell proliferation, migration, and survival, but also increase the expression of inflammation-related circuits, which results in poor outcomes for patients with cancer. Currently, ATX is regarded as a potential cancer therapeutic target, and an increasing number of ATX inhibitors have been developed. In this review, we focus on the mechanism of ATX expression regulation and the functions of ATX in cancer development.

Autotaxin (ATX), the key enzyme that generates lysophosphatidic acid (LPA) from lysophosphatidylcholine (LPC), is involved in tumorigenesis through the ATX-LPA axis and is regarded as a valuable target in tumor therapy. Hypoxia is a major feature of solid tumors and contributes to tumor development with striking alterations in the gene expression profile. Here, we show that hypoxia induces ATX expression in a hypoxia-inducible factor (HIF) 2α-dependent fashion in human colon cancer SW480 cells. HIF-2α is directly bound to specific hypoxia response elements (HREs) in the ATX promoter. Under hypoxic conditions, knockout or inhibition of ATX suppressed the migration of SW480 cells, which could be rescued by the addition of LPA, suggesting that the induction of ATX during hypoxia promotes cancer cell migration through the ATX-LPA axis. Further studies showed that ATX expression was induced by HIF-2α through recruiting p300/CBP, which led to crotonylation but not acetylation of histone H3 in the ATX promoter region during hypoxia. Moreover, elevation of cellular histone crotonylation levels could induce ATX expression under normoxic conditions. In conclusion, our findings reveal that ATX is induced in SW480 cells during hypoxia by histone crotonylation in a HIF-2α-dependent manner, while as a novel mechanism of ATX expression regulation, the upregulation of ATX expression by histone crotonylation is not confined to hypoxia.

OBJECTIVE: Identification of interstitial lung disease (ILD) may be difficult in certain cases using pulmonary function tests (PFTs) or subjective radiological analysis. We evaluated the efficacy of quantitative computed tomography (CT) with 3-dimensional (3D) reconstruction for distinguishing ILD patients from healthy controls. MATERIALS AND METHODS: We retrospectively collected chest CT images of 102 ILD patients and 102 healthy matched controls, and measured the following parameters: lung parenchymal volume, emphysema indices low attenuation area LAA910 volume, LAA950 volume, LAA910%, and LAA950%, and mean lung density (MLD) for whole lung, left lung, right lung, and each lobe, respectively. The Mann-Whitney U test was used to compare quantitative CT parameters between groups. Receiver operating characteristic (ROC) curves, Bayesian stepwise discriminant analysis, and deep neural network analysis were used to test the discriminative performance of quantitative CT parameters. Binary logistic regression was performed to identify ILD markers. RESULTS: Total lung volume was lower in ILD patients than controls, while emphysema and MLD values were higher ( P < 0.001) except LAA910 volume in right middle lobe. LAA910 volume, LAA950 volume, LAA910%, LAA950%, and MLD accurately distinguished ILD patients from healthy controls (AUC >0.5, P < 0.05), and high MLD was a significant marker for ILD (OR = 1.047, P < 0.05). CONCLUSIONS: This quantitative CT analysis can effectively identify ILD patients, providing an alternative to subjective image analysis and PFTs.