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      Systematic analysis of fatty acid desaturases in breast invasive carcinoma: The prognosis, gene mutation, and tumor immune microenvironment

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          Abstract

          Breast invasive carcinoma (BRCA) is one of the most common cancers in women, with its malignant progression significantly influenced by intracellular fatty acid (FA) desaturation. Stearoyl-coenzyme A desaturase (SCD) and fatty acid desaturase 2 (FADS2) are two key rate-limiting enzymes that catalyze the FA desaturation process and cooperate to accelerate lipid metabolic activities. In this study, we investigated the potential functions of SCD and FADS2 in BRCA using bioinformatic analysis and experimental validation. The gene expression profiling interactive analysis database showed that the expression of SCD or FADS2 genes was positively linked to worse overall survival and disease-free survival in the Cancer Genome Atlas database-BRCA. The University of Alabama at Birmingham cancer data analysis portal database indicates that the expression and methylation levels of SCD or FADS2 are associated with various clinicopathological factors in patients with BRCA. Moreover, the tumor immune estimation resource and TISCH databases showed a significant positive correlation between the expression of SCD and the abundance of CD8+ T cells and macrophage cell infiltration, while the expression of FADS2 was positively correlated with the abundance of B cells. Meanwhile, SCD or FADS2 had a higher expression in monocytes/macrophages analyzed the BRCA_GSE143423 and BRCA_GSE114727_inDrop datasets. Mechanistically, the Search Tool for the Retrieval of Distant Genes and CancerSEA databases showed that SCD and FADS2 were upregulated in several cell biology signaling pathways, particularly in inflammation, apoptosis, and DNA repair. Finally, SCD or FADS2 knockdown inhibited the proliferation of MCF-7 and MDA-MB-231 cells. In summary, SCD and FADS2 play significant roles in BRCA development, suggesting that they may serve as potential therapeutic targets for BRCA treatment.

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          Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries

          This article provides an update on the global cancer burden using the GLOBOCAN 2020 estimates of cancer incidence and mortality produced by the International Agency for Research on Cancer. Worldwide, an estimated 19.3 million new cancer cases (18.1 million excluding nonmelanoma skin cancer) and almost 10.0 million cancer deaths (9.9 million excluding nonmelanoma skin cancer) occurred in 2020. Female breast cancer has surpassed lung cancer as the most commonly diagnosed cancer, with an estimated 2.3 million new cases (11.7%), followed by lung (11.4%), colorectal (10.0 %), prostate (7.3%), and stomach (5.6%) cancers. Lung cancer remained the leading cause of cancer death, with an estimated 1.8 million deaths (18%), followed by colorectal (9.4%), liver (8.3%), stomach (7.7%), and female breast (6.9%) cancers. Overall incidence was from 2-fold to 3-fold higher in transitioned versus transitioning countries for both sexes, whereas mortality varied <2-fold for men and little for women. Death rates for female breast and cervical cancers, however, were considerably higher in transitioning versus transitioned countries (15.0 vs 12.8 per 100,000 and 12.4 vs 5.2 per 100,000, respectively). The global cancer burden is expected to be 28.4 million cases in 2040, a 47% rise from 2020, with a larger increase in transitioning (64% to 95%) versus transitioned (32% to 56%) countries due to demographic changes, although this may be further exacerbated by increasing risk factors associated with globalization and a growing economy. Efforts to build a sustainable infrastructure for the dissemination of cancer prevention measures and provision of cancer care in transitioning countries is critical for global cancer control.
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            Global Cancer Statistics 2018: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries

            This article provides a status report on the global burden of cancer worldwide using the GLOBOCAN 2018 estimates of cancer incidence and mortality produced by the International Agency for Research on Cancer, with a focus on geographic variability across 20 world regions. There will be an estimated 18.1 million new cancer cases (17.0 million excluding nonmelanoma skin cancer) and 9.6 million cancer deaths (9.5 million excluding nonmelanoma skin cancer) in 2018. In both sexes combined, lung cancer is the most commonly diagnosed cancer (11.6% of the total cases) and the leading cause of cancer death (18.4% of the total cancer deaths), closely followed by female breast cancer (11.6%), prostate cancer (7.1%), and colorectal cancer (6.1%) for incidence and colorectal cancer (9.2%), stomach cancer (8.2%), and liver cancer (8.2%) for mortality. Lung cancer is the most frequent cancer and the leading cause of cancer death among males, followed by prostate and colorectal cancer (for incidence) and liver and stomach cancer (for mortality). Among females, breast cancer is the most commonly diagnosed cancer and the leading cause of cancer death, followed by colorectal and lung cancer (for incidence), and vice versa (for mortality); cervical cancer ranks fourth for both incidence and mortality. The most frequently diagnosed cancer and the leading cause of cancer death, however, substantially vary across countries and within each country depending on the degree of economic development and associated social and life style factors. It is noteworthy that high-quality cancer registry data, the basis for planning and implementing evidence-based cancer control programs, are not available in most low- and middle-income countries. The Global Initiative for Cancer Registry Development is an international partnership that supports better estimation, as well as the collection and use of local data, to prioritize and evaluate national cancer control efforts. CA: A Cancer Journal for Clinicians 2018;0:1-31. © 2018 American Cancer Society.
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              STRING v11: protein–protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets

              Abstract Proteins and their functional interactions form the backbone of the cellular machinery. Their connectivity network needs to be considered for the full understanding of biological phenomena, but the available information on protein–protein associations is incomplete and exhibits varying levels of annotation granularity and reliability. The STRING database aims to collect, score and integrate all publicly available sources of protein–protein interaction information, and to complement these with computational predictions. Its goal is to achieve a comprehensive and objective global network, including direct (physical) as well as indirect (functional) interactions. The latest version of STRING (11.0) more than doubles the number of organisms it covers, to 5090. The most important new feature is an option to upload entire, genome-wide datasets as input, allowing users to visualize subsets as interaction networks and to perform gene-set enrichment analysis on the entire input. For the enrichment analysis, STRING implements well-known classification systems such as Gene Ontology and KEGG, but also offers additional, new classification systems based on high-throughput text-mining as well as on a hierarchical clustering of the association network itself. The STRING resource is available online at https://string-db.org/.
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                Author and article information

                Contributors
                Journal
                Medicine (Baltimore)
                Medicine (Baltimore)
                MD
                Medicine
                Lippincott Williams & Wilkins (Hagerstown, MD )
                0025-7974
                1536-5964
                21 June 2024
                21 June 2024
                : 103
                : 25
                : e38597
                Affiliations
                [a ]Department of Basic Medical Science, Wuxi School of Medicine, Jiangnan University, Wuxi, China
                [b ]Macao Centre for Research and Development in Chinese Medicine, State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Macao SAR, China
                [c ]Jiangnan University Medical Center, Wuxi, China.
                Author notes
                [* ]Correspondence: Guosheng Wu, Department of Basic Medical Science, Wuxi School of Medicine, Jiangnan University, Wuxi 214122, China (e-mail: 8878700009@ 123456jiangnan.edu.cn ).
                Author information
                https://orcid.org/0000-0002-4272-8441
                Article
                MD-D-24-04623 00030
                10.1097/MD.0000000000038597
                11191958
                38905386
                400699c3-204d-4ae6-9c73-fe95f688bfb5
                Copyright © 2024 the Author(s). Published by Wolters Kluwer Health, Inc.

                This is an open access article distributed under the Creative Commons Attribution License 4.0 (CCBY), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 29 April 2024
                : 23 May 2024
                : 24 May 2024
                Categories
                5750
                Research Article
                Observational Study
                Custom metadata
                TRUE
                T

                brca,scd,fads2,gene mutation,prognosis,tumor immune microenvironment

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