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      FDX1 can Impact the Prognosis and Mediate the Metabolism of Lung Adenocarcinoma

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          Abstract

          Background: Lung cancer has emerged as one of the most common cancers in recent years. The mitochondrial electron transport chain (ETC) is closely connected with metabolic pathways and inflammatory response. However, the influence of ETC-associated genes on the tumor immune response and the pathogenesis of lung cancer is not clear and needs further exploration.

          Methods: The RNA-sequencing transcriptome and clinical characteristic data of LUAD were downloaded from the Cancer Genome Atlas (TCGA) database. The LASSO algorithm was used to build the risk signature, and the prediction model was evaluated by the survival analysis and receiver operating characteristic curve. We explored the function of FDX1 through flow cytometry, molecular biological methods, and liquid chromatography–tandem mass spectrometry/mass spectrometry (LC–MS/MS).

          Results: 12 genes ( FDX1, FDX2, LOXL2, ASPH, GLRX2, ALDH2, CYCS, AKR1A1, MAOB, RDH16, CYBB, and CYB5A) were selected to build the risk signature, and the risk score was calculated with the coefficients from the LASSO algorithm. The 1-year, 3-year, and 5-year area under the curve (AUC) of ROC curves of the dataset were 0.7, 0.674, and 0.692, respectively. Univariate Cox analysis and multivariate Cox regression analysis indicated that the risk signature is an independent risk factor for LUAD patients. Among these genes, we focused on the FDX1 gene, and we found that knockdown of FDX1 neither inhibited tumor cell growth nor did it induce apoptosis or abnormal cell cycle distribution. But FDX1 could promote the ATP production. Furthermore, our study showed that FDX1 was closely related to the glucose metabolism, fatty acid oxidation, and amino acid metabolism.

          Conclusion: Collectively, this study provides new clues about carcinogenesis induced by ETC-associated genes in LUAD and paves the way for finding potential targets of LUAD.

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          Most cited references42

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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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            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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              Non–Small Cell Lung Cancer: Epidemiology, Screening, Diagnosis, and Treatment

              Lung cancer remains the leading cause of cancer deaths in the United States. In the past decade, significant advances have been made in the science of non-small cell lung cancer (NSCLC). Screening has been introduced with the goal of early detection. The National Lung Screening Trial found a lung cancer mortality benefit of 20% and a 6.7% decrease in all-cause mortality with the use of low-dose chest computed tomography in high-risk individuals. The treatment of lung cancer has also evolved with the introduction of several lines of tyrosine kinase inhibitors in patients with EGFR, ALK, ROS1, and NTRK mutations. Similarly, immune checkpoint inhibitors (ICIs) have dramatically changed the landscape of NSCLC treatment. Furthermore, the results of new trials continue to help us understand the role of these novel agents and which patients are more likely to benefit; ICIs are now part of the first-line NSCLC treatment armamentarium as monotherapy, combined with chemotherapy, or after definite chemoradiotherapy in patients with stage III unresectable NSCLC. Expression of programmed cell death protein-ligand 1 in malignant cells has been studied as a potential biomarker for response to ICIs. However, important drawbacks exist that limit its discriminatory potential. Identification of accurate predictive biomarkers beyond programmed cell death protein-ligand 1 expression remains essential to select the most appropriate candidates for ICI therapy. Many questions remain unanswered regarding the proper sequence and combinations of these new agents; however, the field is moving rapidly, and the overall direction is optimistic.
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                Author and article information

                Contributors
                Journal
                Front Pharmacol
                Front Pharmacol
                Front. Pharmacol.
                Frontiers in Pharmacology
                Frontiers Media S.A.
                1663-9812
                08 October 2021
                2021
                : 12
                : 749134
                Affiliations
                [ 1 ]Department of the First Clinical Medicine, Chongqing Medical University, Chongqing, China
                [ 2 ]Department of Medical Oncology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China
                [ 3 ]Binzhou Polytechnic, Binzhou, China
                [ 4 ]State Key Lab of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
                [ 5 ]Department of Clinical Laboratory, Beijing Friendship Hospital, Capital Medical University, Beijing, China
                [ 6 ]Department of Cell Biology and Genetics, Medicine and Cancer Research Center, Chongqing Medical University, Chongqing, China
                Author notes

                Edited by: Lesheng Teng, Jilin University, China

                Reviewed by: Yifan Ma, The Ohio State University, United States

                Shiyan Dong, Jilin University, China

                *Correspondence: Qing Zhu, qzhu0608@ 123456126.com ; Xiaobing Wang, wangxb@ 123456cicams.ac.cn ; Changzhu Duan, duanchzhu@ 123456cqmu.edu.cn
                [ † ]

                These authors have contributed equally to this work

                This article was submitted to Inflammation Pharmacology, a section of the journal Frontiers in Pharmacology

                Article
                749134
                10.3389/fphar.2021.749134
                8531531
                34690780
                b90a72be-c278-4a65-9dd4-93a69f2e3214
                Copyright © 2021 Zhang, Ma, Guo, Du, Zhu, Wang and Duan.

                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
                : 29 July 2021
                : 08 September 2021
                Categories
                Pharmacology
                Original Research

                Pharmacology & Pharmaceutical medicine
                lung cancer,inflammatory response,mitochondria electron transport chain,risk signature,metabolism

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