For Publishers
DiscoveryMetadataPeer reviewHostingPublishing
For Researchers
JoinPublishReviewCollect
Register
Blog
About
Search
Advanced search
My ScienceOpen
Search
For Publishers
For Researchers
Blog
About
10
views
50
references
 Top references
cited by
0
    
0 reviews
 Review
0
comments
 Comment
0
recommends
+1 Recommend
0 collections
    0
    shares
      441
      similar
       All similar
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Comprehensive analysis of PHGDH for predicting prognosis and immunotherapy response in patients with endometrial carcinoma

      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

          Background

          PHGDH (Phosphoglycerate Dehydrogenase) is the first branch enzyme in the serine biosynthetic pathway and plays a vital role in several cancers. However, little is known about the clinical significance of PHGDH in endometrial cancer.

          Methods

          Clinicopathological data of endometrial cancer were downloaded from the Cancer Genome Atlas database (TCGA). First, the expression of PHGDH in pan-cancer was investigated, as well as the expression and prognostic value of PHGDH in endometrial cancer. The effect of PHGDH expression on the prognosis of endometrial cancer was analyzed by Kaplan-Meier plotter and Cox regression. The relationship between PHGDH expression and clinical characteristics of endometrial cancer was investigated by logistic regression. Receiver operating characteristic (ROC) curves and nomograms were developed. Possible cellular mechanisms were explored using the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, the Gene Ontology (GO), and gene set enrichment analysis (GSEA). Finally, TIMER and CIBERSORT were used to analyze the relationship between PHGDH expression and immune infiltration. CellMiner™ was used to analyze the drug sensitivity of PHGDH.

          Results

          The results showed that PHGDH expression was significantly higher in endometrial cancer tissues than in normal tissues at mRNA and protein levels. Kaplan-Meier survival curves showed that patients in the high expression group had shorter overall survival (OS) and disease free survival (DFS) than patients in the low PHGDH expression group. Multifactorial COX regression analysis further supported that high PHGDH expression was an independent risk factor associated with prognosis in patients with endometrial cancer. The results showed estrogen response, mTOR, K-RAS, and epithelial mesenchymal transition (EMT) were differentially elevated in the high-expression group of the PHGDH group. CIBERSORT analysis showed that PHGDH expression is related to the infiltration of multiple immune cells. When PHGDH is highly expressed, the number of CD8 +T cells decreases.

          Conclusion

          PHGDH plays a vital role in the development of endometrial cancer, which is related to tumor immune infiltration, and can be used as an independent diagnostic and prognostic marker for endometrial cancer.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s12920-023-01463-5.

          Related collections

          Most cited references50

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

          Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries

          Hyuna Sung, Jacques Ferlay, Rebecca Siegel … (2021)
          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.
          Article 0 comments Cited 29027 times – based on 0 reviews     Review now
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Gene Ontology: tool for the unification of biology

            Michael Ashburner, Catherine A. Ball, Judith Blake … (2002)
            Genomic sequencing has made it clear that a large fraction of the genes specifying the core biological functions are shared by all eukaryotes. Knowledge of the biological role of such shared proteins in one organism can often be transferred to other organisms. The goal of the Gene Ontology Consortium is to produce a dynamic, controlled vocabulary that can be applied to all eukaryotes even as knowledge of gene and protein roles in cells is accumulating and changing. To this end, three independent ontologies accessible on the World-Wide Web (http://www.geneontology.org) are being constructed: biological process, molecular function and cellular component.
            Article 0 comments Cited 15273 times – based on 0 reviews     Review now
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles

              A. Subramanian, P. Tamayo, V. K. Mootha … (2005)
              Although genomewide RNA expression analysis has become a routine tool in biomedical research, extracting biological insight from such information remains a major challenge. Here, we describe a powerful analytical method called Gene Set Enrichment Analysis (GSEA) for interpreting gene expression data. The method derives its power by focusing on gene sets, that is, groups of genes that share common biological function, chromosomal location, or regulation. We demonstrate how GSEA yields insights into several cancer-related data sets, including leukemia and lung cancer. Notably, where single-gene analysis finds little similarity between two independent studies of patient survival in lung cancer, GSEA reveals many biological pathways in common. The GSEA method is embodied in a freely available software package, together with an initial database of 1,325 biologically defined gene sets.
              Article 0 comments Cited 12572 times – based on 0 reviews     Review now
                Bookmark
                All references

                Author and article information

                Contributors
                Weimin Kong: kwm1967@ccmu.edu.cn
                Journal
                Journal ID (nlm-ta): BMC Med Genomics
                Journal ID (iso-abbrev): BMC Med Genomics
                Title: BMC Medical Genomics
                Publisher: BioMed Central (London )
                ISSN (Electronic): 1755-8794
                Publication date (Electronic): 20 February 2023
                Publication date PMC-release: 20 February 2023
                Publication date Collection: 2023
                Volume: 16
                Electronic Location Identifier: 29
                Affiliations
                GRID grid.24696.3f, ISNI 0000 0004 0369 153X, Department of Gynecological Oncology, Beijing Obstetrics and Gynecology Hospital, Beijing Maternal and Child Health Care Hospital, , Capital Medical University, ; 100006 Beijing, China
                Article
                Publisher ID: 1463
                DOI: 10.1186/s12920-023-01463-5
                PMC ID: 9942409
                SO-VID: a0684d07-8990-4b8f-ad45-027173a8d73a
                Copyright © © The Author(s) 2023
                License:

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                Date received : 27 October 2022
                Date accepted : 16 February 2023
                Categories
                Subject: Research
                Custom metadata
                issue-copyright-statement © The Author(s) 2023

                ScienceOpen disciplines: Genetics
                Keywords: phgdh,endometrial carcinoma,tcga,bioinformatics,immune infiltrates
                Data availability:
                ScienceOpen disciplines: Genetics
                Keywords: phgdh, endometrial carcinoma, tcga, bioinformatics, immune infiltrates

                Comments

                Comment on this article