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      A novel combination therapy with Cabozantinib and Honokiol effectively inhibits c-Met-Nrf2-induced renal tumor growth through increased oxidative stress

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          Abstract

          Receptor tyrosine kinase (RTK), c-Met, is overexpressed and hyper active in renal cell carcinoma (RCC). Most of the therapeutic agents mediate cancer cell death through increased oxidative stress. Induction of c-Met in renal cancer cells promotes the activation of redox-sensitive transcription factor Nrf2 and cytoprotective heme oxygenase-1 (HO-1), which can mediate therapeutic resistance against oxidative stress. c-Met/RTK inhibitor, Cabozantinib, has been approved for the treatment of advanced RCC. However, acquired drug resistance is a major hurdle in the clinical use of cabozantinib. Honokiol, a naturally occurring phenolic compound, has a great potential to downregulate c-Met-induced pathways. In this study, we found that a novel combination treatment with cabozantinib + Honokiol inhibits the growth of renal cancer cells in a synergistic manner through increased production of reactive oxygen species (ROS); and it significantly facilitates apoptosis-and autophagy-mediated cancer cell death. Activation of c-Met can induce Rubicon (a negative regulator of autophagy) and p62 (an autophagy adaptor protein), which can stabilize Nrf2. By utilizing OncoDB online database, we found a positive correlation among c-Met, Rubicon, p62 and Nrf2 in renal cancer. Interestingly, the combination treatment significantly downregulated Rubicon, p62 and Nrf2 in RCC cells. In a tumor xenograft model, this combination treatment markedly inhibited renal tumor growth in vivo; and it is associated with decreased expression of Rubicon, p62, HO-1 and vessel density in the tumor tissues. Together, cabozantinib + Honokiol combination can significantly inhibit c-Met-induced and Nrf2-mediated anti-oxidant pathway in renal cancer cells to promote increased oxidative stress and tumor cell death.

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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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            Cancer statistics, 2023

            Each year, the American Cancer Society estimates the numbers of new cancer cases and deaths in the United States and compiles the most recent data on population-based cancer occurrence and outcomes using incidence data collected by central cancer registries and mortality data collected by the National Center for Health Statistics. In 2023, 1,958,310 new cancer cases and 609,820 cancer deaths are projected to occur in the United States. Cancer incidence increased for prostate cancer by 3% annually from 2014 through 2019 after two decades of decline, translating to an additional 99,000 new cases; otherwise, however, incidence trends were more favorable in men compared to women. For example, lung cancer in women decreased at one half the pace of men (1.1% vs. 2.6% annually) from 2015 through 2019, and breast and uterine corpus cancers continued to increase, as did liver cancer and melanoma, both of which stabilized in men aged 50 years and older and declined in younger men. However, a 65% drop in cervical cancer incidence during 2012 through 2019 among women in their early 20s, the first cohort to receive the human papillomavirus vaccine, foreshadows steep reductions in the burden of human papillomavirus-associated cancers, the majority of which occur in women. Despite the pandemic, and in contrast with other leading causes of death, the cancer death rate continued to decline from 2019 to 2020 (by 1.5%), contributing to a 33% overall reduction since 1991 and an estimated 3.8 million deaths averted. This progress increasingly reflects advances in treatment, which are particularly evident in the rapid declines in mortality (approximately 2% annually during 2016 through 2020) for leukemia, melanoma, and kidney cancer, despite stable/increasing incidence, and accelerated declines for lung cancer. In summary, although cancer mortality rates continue to decline, future progress may be attenuated by rising incidence for breast, prostate, and uterine corpus cancers, which also happen to have the largest racial disparities in mortality.
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              UALCAN: A Portal for Facilitating Tumor Subgroup Gene Expression and Survival Analyses1

              Genomics data from The Cancer Genome Atlas (TCGA) project has led to the comprehensive molecular characterization of multiple cancer types. The large sample numbers in TCGA offer an excellent opportunity to address questions associated with tumo heterogeneity. Exploration of the data by cancer researchers and clinicians is imperative to unearth novel therapeutic/diagnostic biomarkers. Various computational tools have been developed to aid researchers in carrying out specific TCGA data analyses; however there is need for resources to facilitate the study of gene expression variations and survival associations across tumors. Here, we report UALCAN, an easy to use, interactive web-portal to perform to in-depth analyses of TCGA gene expression data. UALCAN uses TCGA level 3 RNA-seq and clinical data from 31 cancer types. The portal's user-friendly features allow to perform: 1) analyze relative expression of a query gene(s) across tumor and normal samples, as well as in various tumor sub-groups based on individual cancer stages, tumor grade, race, body weight or other clinicopathologic features, 2) estimate the effect of gene expression level and clinicopathologic features on patient survival; and 3) identify the top over- and under-expressed (up and down-regulated) genes in individual cancer types. This resource serves as a platform for in silico validation of target genes and for identifying tumor sub-group specific candidate biomarkers. Thus, UALCAN web-portal could be extremely helpful in accelerating cancer research. UALCAN is publicly available at http://ualcan.path.uab.edu.
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                Author and article information

                Contributors
                Journal
                Redox Biol
                Redox Biol
                Redox Biology
                Elsevier
                2213-2317
                21 October 2023
                December 2023
                21 October 2023
                : 68
                : 102945
                Affiliations
                [a ]Division of Nephrology, Boston Children's Hospital, Boston, MA, USA
                [b ]Harvard Medical School, Boston, MA, USA
                [c ]Division of Genetics, Brigham and Women's Hospital, MA, USA
                [d ]Department of Ophthalmology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
                Author notes
                []Corresponding author. Division of Nephrology, Boston Children's Hospital, 300 Longwood Ave, Boston, MA 02115, USA. soumitro.pal@ 123456childrens.harvard.edu
                [1]

                AS and SP are co-senior authors.

                Article
                S2213-2317(23)00346-4 102945
                10.1016/j.redox.2023.102945
                10628632
                ec2c6c38-3f37-4d24-b4e2-8ac9c44c4b6f
                © 2023 The Authors. Published by Elsevier B.V.

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                : 11 October 2023
                : 17 October 2023
                : 19 October 2023
                Categories
                Research Paper

                renal cancer,c-met,nrf2,honokiol,oxidative stress
                renal cancer, c-met, nrf2, honokiol, oxidative stress

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