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      Hsa_circ_0009910 knockdown in HeLa cells increases miR‑198 expression levels and decreases c‑Met expression levels and cell viability

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          Abstract

          Cervical cancer (CC) is considered a public health problem. Circular RNAs (circRNAs) serve important roles in different types of cancer, including CC. However, the mechanisms used by circRNAs to facilitate CC progression are currently unclear. The present study analyzed the effects of hsa_circ_0009910 knockdown on microRNA (miRNA/miR)-198 and mesenchymal-epithelial transition factor (c-Met) expression levels and its impact on apoptosis and the viability of HeLa cells. Differentially expressed circRNAs in CC were identified using analysis of circRNA microarray data. Bioinformatics analysis was performed to predict circRNA-microRNA (miRNA) and miRNA-mRNA interactions. The knockdown of hsa_circ_0009910 in HeLa cells was performed using small interfering RNA and the expression levels of hsa_circ_0009910, miR-198 and c-Met were assessed using reverse transcription-quantitative PCR. The viability and apoptosis of HeLa cells were evaluated using MTT, neutral red uptake and ApoLive-Glo™ multiplex assays. Hsa_circ_0009910 was significantly upregulated in HeLa cells and the knockdown of hsa_circ_0009910 increased miRNA-198 expression levels, reduced c-Met expression levels and decreased cellular viability, but not apoptosis, in HeLa cells. Overall, these results indicated that hsa_circ_0009910 could act as a molecular sponge of miRNA-198 and contribute to the upregulation of c-Met expression levels. The hsa_circ_0009910/miRNA-198/c-Met interaction network affects the viability, but not apoptosis, of HeLa cells. Based on this mechanism, the present study suggests that hsa_circ_0009910 may be a promising biomarker for CC.

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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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            Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method.

            The two most commonly used methods to analyze data from real-time, quantitative PCR experiments are absolute quantification and relative quantification. Absolute quantification determines the input copy number, usually by relating the PCR signal to a standard curve. Relative quantification relates the PCR signal of the target transcript in a treatment group to that of another sample such as an untreated control. The 2(-Delta Delta C(T)) method is a convenient way to analyze the relative changes in gene expression from real-time quantitative PCR experiments. The purpose of this report is to present the derivation, assumptions, and applications of the 2(-Delta Delta C(T)) method. In addition, we present the derivation and applications of two variations of the 2(-Delta Delta C(T)) method that may be useful in the analysis of real-time, quantitative PCR data. Copyright 2001 Elsevier Science (USA).
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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

                Journal
                Oncol Lett
                Oncol Lett
                OL
                Oncology Letters
                D.A. Spandidos
                1792-1074
                1792-1082
                February 2025
                26 November 2024
                26 November 2024
                : 29
                : 2
                : 74
                Affiliations
                [1 ]Laboratory of Cancer Epigenetics, School of Chemical and Biological Sciences, Autonomous University of Guerrero, Chilpancingo, Guerrero 39070, Mexico
                [2 ]Laboratory of Neurotoxicology, Department of Toxicology, Center for Research and Advanced Studies of the National Polytechnic Institute, Mexico City 07300, Mexico
                [3 ]Laboratory of Cytopathology and Histochemistry, School of Chemical and Biological Sciences, Autonomous University of Guerrero, Chilpancingo, Guerrero 39070, Mexico
                [4 ]Clinical Research Laboratory, School of Chemical and Biological Sciences, Autonomous University of Guerrero, Chilpancingo, Guerrero 39070, Mexico
                Author notes
                Correspondence to: Dr Daniel Hernández-Sotelo, Laboratory of Cancer Epigenetics, School of Chemical and Biological Sciences, Autonomous University of Guerrero, Lázaro Cárdenas Avenue S/N, Colonia La Haciendita, Chilpancingo, Guerrero 39070, Mexico, E-mail: danhs1mx@ 123456yahoo.com
                Article
                OL-29-2-14820
                10.3892/ol.2024.14820
                11622005
                39650233
                46dfca0e-c8e3-4296-9de8-730e07e0a9d8
                Copyright: © 2024 Tolentino-Molina et al.

                This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

                History
                : 04 January 2024
                : 09 September 2024
                Funding
                Funded by: National Council of Humanities, Sciences, and Technologies
                Award ID: 242812
                The present study was supported by the National Council of Humanities, Sciences, and Technologies (grant no. 242812).
                Categories
                Articles

                Oncology & Radiotherapy
                cervical cancer,hsa_circ_0009910,mir-198,c-met,viability,hela
                Oncology & Radiotherapy
                cervical cancer, hsa_circ_0009910, mir-198, c-met, viability, hela

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