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Zhang X, Liu S, Yang L, Cheng C, Wang H, Hu D, Zhang X, Zhang M, Liu Y, Tian X, Zhang H, Xu KF. Omics research in lymphangioleiomyomatosis: status and challenges. Expert Rev Respir Med 2024; 18:805-814. [PMID: 39257348 DOI: 10.1080/17476348.2024.2403498] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2024] [Revised: 09/05/2024] [Accepted: 09/09/2024] [Indexed: 09/12/2024]
Abstract
INTRODUCTION Lymphangioleiomyomatosis (LAM) is a rare and progressive disorder that usually arises in the lung and almost exclusively affects women of childbearing age. In recent years, a number of molecules have been shown to be differentially expressed between patients with LAM and healthy control individuals, and some of these molecules, in addition to vascular endothelial growth factor D (VEGF-D), have the potential to be novel biomarkers. AREAS COVERED This review summarizes the recent advances in omics research, including genomics, transcriptomics, proteomics, and metabolomics, in LAM biomarker discovery. It also retrieves the literature on LAM biomarkers studied by omics techniques in the last 10 years using PubMed and other retrieval tools. EXPERT OPINION Further research on expanded sample sizes can be conducted to construct specific models to study the role of these molecules in the pathogenesis of LAM and clarify the underlying mechanisms involved. In the future, in terms of technology, the combination of various omics methods is expected to result in novel biomarker discovery.
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Affiliation(s)
- Xinhe Zhang
- Department of Pulmonary and Critical Care Medicine, State Key Laboratory of Complex, Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
- Eight-year Medical Doctor Program, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Song Liu
- Center for bioinformatics, National Infrastructures for Translational Medicine, Institute of Clinical Medicine & Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Luning Yang
- Department of Pulmonary and Critical Care Medicine, State Key Laboratory of Complex, Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Chongsheng Cheng
- Department of Pulmonary and Critical Care Medicine, State Key Laboratory of Complex, Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Hanghang Wang
- Department of Pulmonary and Critical Care Medicine, State Key Laboratory of Complex, Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Danjing Hu
- Department of Pulmonary and Critical Care Medicine, State Key Laboratory of Complex, Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Xiaoxin Zhang
- Department of Pulmonary and Critical Care Medicine, State Key Laboratory of Complex, Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Miaoyan Zhang
- Department of Pulmonary and Critical Care Medicine, State Key Laboratory of Complex, Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Yaping Liu
- Department of Genetics, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Xinlun Tian
- Department of Pulmonary and Critical Care Medicine, State Key Laboratory of Complex, Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Hongbing Zhang
- Department of Physiology, State Key Laboratory of Common Mechanism Research for Major Diseases, Institute of Basic Medical Sciences and School of Basic Medicine, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Kai-Feng Xu
- Department of Pulmonary and Critical Care Medicine, State Key Laboratory of Complex, Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
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Li X, Lv X, Li H, Zhang G, Long Y, Li K, Fan Y, Jin D, Zhou F, Liu H. Undifferentially Expressed CXXC5 as a Transcriptionally Regulatory Biomarker of Breast Cancer. Adv Biol (Weinh) 2023; 7:e2300189. [PMID: 37423953 DOI: 10.1002/adbi.202300189] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Revised: 06/17/2023] [Indexed: 07/11/2023]
Abstract
This work hypothesizes that some genes undergo radically changed transcription regulations (TRs) in breast cancer (BC), but don't show differential expressions for unknown reasons. The TR of a gene is quantitatively formulated by a regression model between the expression of this gene and multiple transcription factors (TFs). The difference between the predicted and real expression levels of a gene in a query sample is defined as the mqTrans value of this gene, which quantitatively reflects its regulatory changes. This work systematically screens the undifferentially expressed genes with differentially expressed mqTrans values in 1036 samples across five datasets and three ethnic groups. This study calls the 25 genes satisfying the above hypothesis in at least four datasets as dark biomarkers, and the strong dark biomarker gene CXXC5 (CXXC Finger Protein 5) is even supported by all the five independent BC datasets. Although CXXC5 does not show differential expressions in BC, its transcription regulations show quantitative associations with BCs in diversified cohorts. The overlapping long noncoding RNAs (lncRNAs) may have contributed their transcripts to the expression miscalculations of dark biomarkers. The mqTrans analysis serves as a complementary view of the transcriptome-based detections of biomarkers that are ignored by many existing studies.
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Affiliation(s)
- Xue Li
- School of Public Health, the Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guiyang, 550025, China
- School of Biology and Engineering, Guizhou Medical University, Guiyang, 550025, China
- Engineering Research Center of Medical Biotechnology, Guizhou Medical University, Guiyang, Guizhou, 550025, China
| | - Xiaoying Lv
- School of Biology and Engineering, Guizhou Medical University, Guiyang, 550025, China
- Engineering Research Center of Medical Biotechnology, Guizhou Medical University, Guiyang, Guizhou, 550025, China
| | - Haijun Li
- School of Biology and Engineering, Guizhou Medical University, Guiyang, 550025, China
- Engineering Research Center of Medical Biotechnology, Guizhou Medical University, Guiyang, Guizhou, 550025, China
| | - Gongyou Zhang
- School of Biology and Engineering, Guizhou Medical University, Guiyang, 550025, China
- Engineering Research Center of Medical Biotechnology, Guizhou Medical University, Guiyang, Guizhou, 550025, China
| | - Yaohang Long
- School of Biology and Engineering, Guizhou Medical University, Guiyang, 550025, China
- Engineering Research Center of Medical Biotechnology, Guizhou Medical University, Guiyang, Guizhou, 550025, China
| | - Kewei Li
- Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun, 130012, China
- College of Computer Science and Technology, Jilin University, Changchun, 130012, China
| | - Yusi Fan
- College of Software, Jilin University, Changchun, 130012, China
| | - Dawei Jin
- Research Institute of Guizhou Huada Life Big Data, Guiyang, Guizhou, 550025, China
| | - Fengfeng Zhou
- Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun, 130012, China
- College of Computer Science and Technology, Jilin University, Changchun, 130012, China
| | - Hongmei Liu
- School of Biology and Engineering, Guizhou Medical University, Guiyang, 550025, China
- Engineering Research Center of Medical Biotechnology, Guizhou Medical University, Guiyang, Guizhou, 550025, China
- Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun, 130012, China
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Kundu N, Holz MK. Lymphangioleiomyomatosis: a metastatic lung disease. Am J Physiol Cell Physiol 2023; 324:C320-C326. [PMID: 36571446 PMCID: PMC9886342 DOI: 10.1152/ajpcell.00202.2022] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Revised: 12/01/2022] [Accepted: 12/13/2022] [Indexed: 12/27/2022]
Abstract
Lymphangioleiomyomatosis (LAM) is a rare disease affecting women, caused by somatic mutations in the TSC1 or TSC2 genes, and driven by estrogen. Similar to many cancers, it is metastatic, primarily to the lung. Despite its monogenetic nature, like many cancers, LAM is a heterogeneous disease. The cellular constituents of LAM are very diverse, including mesenchymal, epithelial, endothelial, and immune cells. LAM is characterized by dysregulation of many cell signaling pathways, distinct populations of LAM cells, and a rich microenvironment, in which the immune system appears to play an important role. This review delineates the heterogeneity of LAM and focuses on the metastatic features of LAM, the deregulated signaling mechanisms and the tumor microenvironment. Understanding the tumor-host interaction in LAM may provide insights into the development of new therapeutic strategies, which could be combinatorial or superlative to Sirolimus, the current U.S. Food and Drug Administration-approved treatment.
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Affiliation(s)
- Nandini Kundu
- Department of Cell Biology and Anatomy, Graduate School of Biomedical Sciences, New York Medical College, Valhalla, New York
| | - Marina K Holz
- Department of Cell Biology and Anatomy, Graduate School of Biomedical Sciences, New York Medical College, Valhalla, New York
- Department of Biochemistry and Molecular Biology, Graduate School of Biomedical Sciences, New York Medical College, Valhalla, New York
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Farré X, Espín R, Baiges A, Blommaert E, Kim W, Giannikou K, Herranz C, Román A, Sáez B, Casanova Á, Ancochea J, Valenzuela C, Ussetti P, Laporta R, Rodríguez-Portal JA, van Moorsel CH, van der Vis JJ, Quanjel MJ, Tena-Garitaonaindia M, Sánchez de Medina F, Mateo F, Molina-Molina M, Won S, Kwiatkowski DJ, de Cid R, Pujana MA. Evidence for shared genetic risk factors between lymphangioleiomyomatosis and pulmonary function. ERJ Open Res 2021; 8:00375-2021. [PMID: 35083324 PMCID: PMC8784893 DOI: 10.1183/23120541.00375-2021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Accepted: 09/17/2021] [Indexed: 11/05/2022] Open
Abstract
IntroductionLymphangioleiomyomatosis (LAM) is a rare low-grade metastasising disease characterised by cystic lung destruction. The genetic basis of LAM remains incompletely determined, and the disease cell-of-origin is uncertain. We analysed the possibility of a shared genetic basis between LAM and cancer, and LAM and pulmonary function.MethodsThe results of genome-wide association studies of LAM, 17 cancer types and spirometry measures (forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC), FEV1/FVC ratio and peak expiratory flow (PEF)) were analysed for genetic correlations, shared genetic variants and causality. Genomic and transcriptomic data were examined, and immunodetection assays were performed to evaluate pleiotropic genes.ResultsThere were no significant overall genetic correlations between LAM and cancer, but LAM correlated negatively with FVC and PEF, and a trend in the same direction was observed for FEV1. 22 shared genetic variants were uncovered between LAM and pulmonary function, while seven shared variants were identified between LAM and cancer. The LAM-pulmonary function shared genetics identified four pleiotropic genes previously recognised in LAM single-cell transcriptomes: ADAM12, BNC2, NR2F2 and SP5. We had previously associated NR2F2 variants with LAM, and we identified its functional partner NR3C1 as another pleotropic factor. NR3C1 expression was confirmed in LAM lung lesions. Another candidate pleiotropic factor, CNTN2, was found more abundant in plasma of LAM patients than that of healthy women.ConclusionsThis study suggests the existence of a common genetic aetiology between LAM and pulmonary function.
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