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      EMS1/DLL4-Notch Signaling Axis Augments Cell Cycle-Mediated Tumorigenesis and Progress in Human Adrenocortical Carcinoma

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          Abstract

          Adrenocortical carcinoma (ACC) is a rare malignant neoplasm that is prone to local invasion and metastasis. Meanwhile, overexpressed endothelial cell-specific molecule 1 ( ESM1) is closely related to tumorigenesis of multitudinous tumors. However, the prognosis value and biological function of ESM1 in ACC remains undefined. In the current essay, the assessment in human ACC samples and multiple public cancer databases suggested that ESM1 was significantly overexpressed in ACC patients. The abnormal expression of ESM1 was evidently correlated with dismal overall survival (OS) in ACC patients. Then, the gene-set enrichment analysis (GSEA) was applied to unravel that ESM1 was mostly involved in cell cycle and Notch4 signaling pathway. Furthermore, in vitro experiment, RNA interference of ESM1 was carried out to state that ESM1 augments CDK1 and p21-mediated G2/M-phase transition of mitosis, cell proliferation via DLL4-Notch signaling pathway in human ACC cell line, SW13 cells. Additionally, two possible or available therapeutic strategies, including immunotherapy and chemotherapy, have been further explored. Immune infiltration analysis highlighted that no significant difference was found in ACC patients between EMS1 high and EMS1 low group for immune checkpoint-related genes. In addition, the overexpression of ESM1 might trigger the accumulation of tumor mutation burden (TMB) during the cell cycle of DNA replication in ACC. The gene-drug interaction network then indicated that ESM1 inhibitors, such as cisplatin, might serve as potential drugs for the therapy of ACC. Collectively, the results asserted that ESM1 and related regulators might act as underlying prognostic biomarkers or novel therapeutic targets for ACC.

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          Most cited references48

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          Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles

          Although genomewide RNA expression analysis has become a routine tool in biomedical research, extracting biological insight from such information remains a major challenge. Here, we describe a powerful analytical method called Gene Set Enrichment Analysis (GSEA) for interpreting gene expression data. The method derives its power by focusing on gene sets, that is, groups of genes that share common biological function, chromosomal location, or regulation. We demonstrate how GSEA yields insights into several cancer-related data sets, including leukemia and lung cancer. Notably, where single-gene analysis finds little similarity between two independent studies of patient survival in lung cancer, GSEA reveals many biological pathways in common. The GSEA method is embodied in a freely available software package, together with an initial database of 1,325 biologically defined gene sets.
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            Hallmarks of Cancer: The Next Generation

            The hallmarks of cancer comprise six biological capabilities acquired during the multistep development of human tumors. The hallmarks constitute an organizing principle for rationalizing the complexities of neoplastic disease. They include sustaining proliferative signaling, evading growth suppressors, resisting cell death, enabling replicative immortality, inducing angiogenesis, and activating invasion and metastasis. Underlying these hallmarks are genome instability, which generates the genetic diversity that expedites their acquisition, and inflammation, which fosters multiple hallmark functions. Conceptual progress in the last decade has added two emerging hallmarks of potential generality to this list-reprogramming of energy metabolism and evading immune destruction. In addition to cancer cells, tumors exhibit another dimension of complexity: they contain a repertoire of recruited, ostensibly normal cells that contribute to the acquisition of hallmark traits by creating the "tumor microenvironment." Recognition of the widespread applicability of these concepts will increasingly affect the development of new means to treat human cancer. Copyright © 2011 Elsevier Inc. All rights reserved.
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              GEPIA: a web server for cancer and normal gene expression profiling and interactive analyses

              Abstract Tremendous amount of RNA sequencing data have been produced by large consortium projects such as TCGA and GTEx, creating new opportunities for data mining and deeper understanding of gene functions. While certain existing web servers are valuable and widely used, many expression analysis functions needed by experimental biologists are still not adequately addressed by these tools. We introduce GEPIA (Gene Expression Profiling Interactive Analysis), a web-based tool to deliver fast and customizable functionalities based on TCGA and GTEx data. GEPIA provides key interactive and customizable functions including differential expression analysis, profiling plotting, correlation analysis, patient survival analysis, similar gene detection and dimensionality reduction analysis. The comprehensive expression analyses with simple clicking through GEPIA greatly facilitate data mining in wide research areas, scientific discussion and the therapeutic discovery process. GEPIA fills in the gap between cancer genomics big data and the delivery of integrated information to end users, thus helping unleash the value of the current data resources. GEPIA is available at http://gepia.cancer-pku.cn/.
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                Author and article information

                Contributors
                Journal
                Front Oncol
                Front Oncol
                Front. Oncol.
                Frontiers in Oncology
                Frontiers Media S.A.
                2234-943X
                10 November 2021
                2021
                : 11
                : 771579
                Affiliations
                [1] 1 Department of Pathology, Taihe Hospital, Hubei University of Medicine , Shiyan, China
                [2] 2 Department of Immunology, Nankai University School of Medicine , Tianjin, China
                [3] 3 Department of Pediatric, Taihe Hospital, Hubei University of Medicine , Shiyan, China
                Author notes

                Edited by: Sridhar Muthusami, Karpagam Academy of Higher Education, India

                Reviewed by: Gardenia Militao, Federal University of Pernambuco, Brazil; Sara Sergio, University of Salento, Italy

                *Correspondence: Xiao-Min Su, xiaominsu@ 123456nankai.edu.cn ; Xian-Bin Tang, taihepathology@ 123456outlook.com

                †These authors share first authorship

                This article was submitted to Molecular and Cellular Oncology, a section of the journal Frontiers in Oncology

                Article
                10.3389/fonc.2021.771579
                8631517
                34858850
                3051b669-9be1-4e86-85f8-11ebd0a89a3e
                Copyright © 2021 Huang, Wang, Zhu, Tang, Tang and Su

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 06 September 2021
                : 22 October 2021
                Page count
                Figures: 9, Tables: 1, Equations: 0, References: 48, Pages: 14, Words: 6448
                Funding
                Funded by: National Natural Science Foundation of China , doi 10.13039/501100001809;
                Award ID: 81600436
                Categories
                Oncology
                Original Research

                Oncology & Radiotherapy
                adrenocortical carcinoma,acc,esm1,dll4,notch signaling pathway
                Oncology & Radiotherapy
                adrenocortical carcinoma, acc, esm1, dll4, notch signaling pathway

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