For Publishers
DiscoveryMetadataPeer reviewHostingPublishing
For Researchers
JoinPublishReviewCollect
Register
Blog
About
Search
Advanced search
My ScienceOpen
Search
For Publishers
For Researchers
Blog
About
21
views
38
references
 Top references
cited by
0
    
0 reviews
 Review
0
comments
 Comment
0
recommends
+1 Recommend
0 collections
    0
    shares
      778
      similar
       All similar
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      hMSH2 coordinated with the expression of E2F1 promotes platinum response in epithelial ovarian cancer

      research-article

      Read this article at

      ScienceOpenPublisherPMC
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Objective

          To explore underlying mechanisms that regulate hMSH2 expression and drug susceptibility in epithelial ovarian cancer (EOC).

          Methods

          Using data from the Cancer Genome Atlas (TCGA) we used bioinformatical analysis to predict transcription factors (TFs) that potentially regulate hMSH2. RT-qPCR, Western blot, and luciferase assays were undertaken using ovarian cancer cell lines to verify the identified TF. Expressions of the TF were modulated using overexpression or knockdown, and the corresponding cellular responses to cisplatin were examined.

          Results

          The TF, E2F1, was found to regulate the hMSH2 gene. The expression level of E2F1 correlated with cisplatin susceptibility in vitro. Kaplan-Meier analysis of 77 patients with EOC showed that low E2F1 expression was associated with worse survival.

          Conclusions

          To our knowledge, this is the first report of E2F1 regulated MSH2 expression playing a role in drug resistance of platinum-based treatments for patients with EOC. Further work is need to confirm our results.

          Related collections

          Most cited references38

          • Record: found
          • Abstract: found
          • Article: not found

          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.
          Article 0 comments Cited 9584 times – based on 0 reviews     Review now
          Article has an altmetric score of 3320
            Bookmark
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            GEPIA2: an enhanced web server for large-scale expression profiling and interactive analysis

            Zefang Tang, Boxi Kang, Chenwei Li … (2019)
            Abstract Introduced in 2017, the GEPIA (Gene Expression Profiling Interactive Analysis) web server has been a valuable and highly cited resource for gene expression analysis based on tumor and normal samples from the TCGA and the GTEx databases. Here, we present GEPIA2, an updated and enhanced version to provide insights with higher resolution and more functionalities. Featuring 198 619 isoforms and 84 cancer subtypes, GEPIA2 has extended gene expression quantification from the gene level to the transcript level, and supports analysis of a specific cancer subtype, and comparison between subtypes. In addition, GEPIA2 has adopted new analysis techniques of gene signature quantification inspired by single-cell sequencing studies, and provides customized analysis where users can upload their own RNA-seq data and compare them with TCGA and GTEx samples. We also offer an API for batch process and easy retrieval of the analysis results. The updated web server is publicly accessible at http://gepia2.cancer-pku.cn/.
            Article 0 comments Cited 1995 times – based on 0 reviews     Review now
            Article has an altmetric score of 11
              Bookmark
              • Record: found
              • Abstract: not found
              • Article: not found

              Visualizing and interpreting cancer genomics data via the Xena platform

              Mary J. Goldman, Brian Craft, Mim Hastie … (2020)
              Article 0 comments Cited 1737 times – based on 0 reviews     Review now
              Article has an altmetric score of 72
                Bookmark
                All references

                Author and article information

                Journal
                Journal ID (nlm-ta): J Int Med Res
                Journal ID (iso-abbrev): J Int Med Res
                Journal ID (publisher-id): IMR
                Journal ID (hwp): spimr
                Title: The Journal of International Medical Research
                Publisher: SAGE Publications (Sage UK: London, England )
                ISSN (Print): 0300-0605
                ISSN (Electronic): 1473-2300
                Publication date Collection: March 2023
                Publication date (Electronic): 30 March 2023
                Volume: 51
                Issue: 3
                Electronic Location Identifier: 03000605231163780
                Affiliations
                [1 ]Department of Oncology, Affiliated Xingtai People Hospital of Hebei Medical University, Xingtai, China
                [2 ]Department of Gynaecology, Affiliated Xingtai People Hospital of Hebei Medical, University, Xingtai, China
                Author notes
                [*]Tian Hua, Department of Gynaecology, Affiliated Xingtai People Hospital of Hebei Medical University, Hongxing road 16, Xingtai, 054001, China. Email: huatian1982@ 123456163.com
                Author information
                https://orcid.org/0000-0002-5138-8688
                Article
                Publisher ID: 10.1177_03000605231163780
                DOI: 10.1177/03000605231163780
                PMC ID: 10068988
                PubMed ID: 36994850
                SO-VID: 1c5e380d-0e77-44de-94f0-62f74e006120
                Copyright © © The Author(s) 2023
                License:

                Creative Commons Non Commercial CC BY-NC: This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License ( https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages ( https://us.sagepub.com/en-us/nam/open-access-at-sage).

                History
                Date received : 5 September 2022
                Date accepted : 24 February 2023
                Categories
                Subject: Pre-Clinical Research Report
                Custom metadata
                typesetter ts2

                Keywords: hmsh2,e2f1,mismatch repair,transcription factors,platinum resistance
                Data availability:
                Keywords: hmsh2, e2f1, mismatch repair, transcription factors, platinum resistance

                Comments

                Comment on this article

                scite_
                0
                0
                0
                0
                Smart Citations
                0
                0
                0
                0
                Citing PublicationsSupportingMentioningContrasting
                View Citations

                See how this article has been cited at scite.ai

                scite shows how a scientific paper has been cited by providing the context of the citation, a classification describing whether it supports, mentions, or contrasts the cited claim, and a label indicating in which section the citation was made.

                Similar content778

                See all similar

                Most referenced authors640

                See all reference authors