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      Identification of iron metabolism-related predictive markers of endometriosis and endometriosis-relevant ovarian cancer

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          Abstract

          Endometriosis is associated with ovarian cancers, mainly endometrioid and clear-cell carcinomas. Iron metabolism has been shown to play a role in endometriosis. Therefore, it is vital to explore the relationship between iron metabolism and ovarian cancer and to identify novel markers for diagnostics and therapeutics. The endometriosis dataset GSE51981 and the ovarian cancer dataset GSE26712 were obtained from the gene expression omnibus database, and differentially expressed genes were identified. Iron metabolism genes were obtained from molecular signatures database, and hub genes from the 3 datasets were obtained. Seven hub genes were identified by bioinformatic analysis, and 3 hub genes ( NCOA4, ETFDH, and TYW1) were further selected by logistic regression, which were verified in an independent endometriosis dataset (GSE25628) and ovarian cancer dataset (GSE14407), showing good predictive diagnostic value (area under the receiver operating characteristic curve of 0.88 and 0.9, respectively). Gene Ontology, gene set enrichment analysis, and immune infiltration analysis further confirmed the related functions, pathways, and immune relationship between iron metabolism and ovarian cancer. This study highlights the potential of targeting iron metabolism in the prevention of potential ovarian cancer and in the further exploration of endometriosis and endometriosis-relevant ovarian cancer therapeutics.

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          Cancer statistics, 2020

          Rebecca Siegel, Kimberly D Miller, Ahmedin Jemal (2020)
          Each year, the American Cancer Society estimates the numbers of new cancer cases and deaths that will occur in the United States and compiles the most recent data on population-based cancer occurrence. Incidence data (through 2016) were collected by the Surveillance, Epidemiology, and End Results Program; the National Program of Cancer Registries; and the North American Association of Central Cancer Registries. Mortality data (through 2017) were collected by the National Center for Health Statistics. In 2020, 1,806,590 new cancer cases and 606,520 cancer deaths are projected to occur in the United States. The cancer death rate rose until 1991, then fell continuously through 2017, resulting in an overall decline of 29% that translates into an estimated 2.9 million fewer cancer deaths than would have occurred if peak rates had persisted. This progress is driven by long-term declines in death rates for the 4 leading cancers (lung, colorectal, breast, prostate); however, over the past decade (2008-2017), reductions slowed for female breast and colorectal cancers, and halted for prostate cancer. In contrast, declines accelerated for lung cancer, from 3% annually during 2008 through 2013 to 5% during 2013 through 2017 in men and from 2% to almost 4% in women, spurring the largest ever single-year drop in overall cancer mortality of 2.2% from 2016 to 2017. Yet lung cancer still caused more deaths in 2017 than breast, prostate, colorectal, and brain cancers combined. Recent mortality declines were also dramatic for melanoma of the skin in the wake of US Food and Drug Administration approval of new therapies for metastatic disease, escalating to 7% annually during 2013 through 2017 from 1% during 2006 through 2010 in men and women aged 50 to 64 years and from 2% to 3% in those aged 20 to 49 years; annual declines of 5% to 6% in individuals aged 65 years and older are particularly striking because rates in this age group were increasing prior to 2013. It is also notable that long-term rapid increases in liver cancer mortality have attenuated in women and stabilized in men. In summary, slowing momentum for some cancers amenable to early detection is juxtaposed with notable gains for other common cancers.
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            Endometriosis

            Dan L Longo, Krina Zondervan, Christian Becker … (2020)
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              CAF secreted miR-522 suppresses ferroptosis and promotes acquired chemo-resistance in gastric cancer

              Haiyang Zhang, Ting Deng, Rui Liu … (2020)
              Background Ferroptosis is a novel mode of non-apoptotic cell death induced by build-up of toxic lipid peroxides (lipid-ROS) in an iron dependent manner. Cancer-associated fibroblasts (CAFs) support tumor progression and drug resistance by secreting various bioactive substances, including exosomes. Yet, the role of CAFs in regulating lipid metabolism as well as ferroptosis of cancer cells is still unexplored and remains enigmatic. Methods Ferroptosis-related genes in gastric cancer (GC) were screened by using mass spectrum; exosomes were isolated by ultra-centrifugation and CAF secreted miRNAs were determined by RT-qPCR. Erastin was used to induce ferroptosis, and ferroptosis levels were evaluated by measuring lipid-ROS, cell viability and mitochondrial membrane potential. Results Here, we provide clinical evidence to show that arachidonate lipoxygenase 15 (ALOX15) is closely related with lipid-ROS production in gastric cancer, and that exosome-miR-522 serves as a potential inhibitor of ALOX15. By using primary stromal cells and cancer cells, we prove that exosome-miR-522 is mainly derived from CAFs in tumor microenvironment. Moreover, heterogeneous nuclear ribonucleoprotein A1 (hnRNPA1) was found to mediate miR-522 packing into exosomes, and ubiquitin-specific protease 7 (USP7) stabilizes hnRNPA1 through de-ubiquitination. Importantly, cisplatin and paclitaxel promote miR-522 secretion from CAFs by activating USP7/hnRNPA1 axis, leading to ALOX15 suppression and decreased lipid-ROS accumulation in cancer cells, and ultimately result in decreased chemo-sensitivity. Conclusions The present study demonstrates that CAFs secrete exosomal miR-522 to inhibit ferroptosis in cancer cells by targeting ALOX15 and blocking lipid-ROS accumulation. The intercellular pathway, comprising USP7, hnRNPA1, exo-miR-522 and ALOX15, reveals new mechanism of acquired chemo-resistance in GC. Graphical abstract
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                Author and article information

                Contributors
                Xu Wang
                Lixiang Zhou
                Zhaomei Dong
                Journal
                Journal ID (nlm-ta): Medicine (Baltimore)
                Journal ID (publisher-id): MD
                Title: Medicine
                Publisher: Lippincott Williams & Wilkins (Hagerstown, MD )
                ISSN (Print): 0025-7974
                ISSN (Electronic): 1536-5964
                Publication date Collection: 14 April 2023
                Publication date (Electronic): 14 April 2023
                Volume: 102
                Issue: 15
                Electronic Location Identifier: e33478
                Affiliations
                [a ] School of Clinical Medicine, Dali University, Dali, Yunnan Province, China
                [b ] Department of Reproductive Medicine, The First Affiliated Hospital of Dali University, Dali, Yunnan Province, China
                [c ] Center of Genetic Testing, The First Affiliated Hospital of Dali University, Dali, Yunnan Province, China.
                Author notes
                * Correspondence: Guangming Wang, School of Clinical Medicine, Dali University, Dali 671000, Yunnan Province, China (e-mail: wgm1991@ 123456dali.edu.cn ).
                Author information
                https://orcid.org/0000-0002-0220-1493
                Article
                Accession ID: 00029
                DOI: 10.1097/MD.0000000000033478
                PMC ID: 10101319
                PubMed ID: 37058039
                SO-VID: da2af605-1a7f-4995-87e1-b3d41b209d27
                Copyright © Copyright © 2023 the Author(s). Published by Wolters Kluwer Health, Inc.
                License:

                This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial License 4.0 (CCBY-NC), where it is permissible to download, share, remix, transform, and buildup the work provided it is properly cited. The work cannot be used commercially without permission from the journal.

                History
                Date received : 04 January 2023
                Date received : 16 March 2023
                Date accepted : 17 March 2023
                Categories
                Subject: 5600
                Subject: Research Article
                Subject: Diagnostic Accuracy Study
                Custom metadata
                OPEN-ACCESS TRUE
                SDC T

                Keywords: endometriosis,endometriosis and ovarian cancer drugs,hub genes,immune infiltration,iron metabolism,ovarian cancer
                Data availability:
                Keywords: endometriosis, endometriosis and ovarian cancer drugs, hub genes, immune infiltration, iron metabolism, ovarian cancer

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