ReviewFrontiers in immunology2019
A Call for Epidemiological Research on Myeloid-Derived Suppressor Cells in Ovarian Cancer: A Review of the Existing Immunological Evidence and Suggestions for Moving Forward.
Review in Frontiers in immunology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
9 citing papers in PubMed, 11 citations in OpenAlex.
- Roles and mechanisms of CircRNAs in ovarian cancer.Frontiers in cell and developmental biology · 2022Review
- Non-viral vector mediated CKb11 with folic acid modification regulates macrophage polarization and DC maturation to elicit immune response against cancer.Bioactive materials · 2021Article
- Review
- Importance of myeloid derived suppressor cells in cancer from a biomarker perspective.Cellular immunology · 2021Review
- Circulating CD14American journal of reproductive immunology (New York, N.Y. : 1989) · 2021Article
- The blood transcriptome prior to ovarian cancer diagnosis: A case-control study in the NOWAC postgenome cohort.PloS one · 2021Article
- Accumulation of blood-circulating PD-L1-expressing M-MDSCs and monocytes/macrophages in pretreatment ovarian cancer patients is associated with soluble PD-L1.Journal of translational medicine · 2020Article
- Immunology and ovarian cancers.Journal of the Chinese Medical Association : JCMA · 2020Review
- The Ovarian Cancer Tumor Immune Microenvironment (TIME) as Target for Therapy: A Focus on Innate Immunity Cells as Therapeutic Effectors.International journal of molecular sciences · 2020Review
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
Recently, there have been encouraging findings suggesting that myeloid-derived suppressor cells (MDSCs) may be a good target for studying immune suppression in ovarian cancer. MDSCs are an abundance of immature myeloid cells that have demonstrated the ability to decrease tumor-infiltrating immune cells, increase the accrual of tumor-associated macrophages and regulatory T cells, as well as secrete various pro-inflammatory mediators and growth stimulating cytokines. Most studies on this topic utilized murine models, but there are limited reports in human subjects which have important limitations. With the majority of ovarian cancer patients presenting with distant metastases and a corresponding 5-year relative survival rate of < 30%, continued efforts are obligatory toward identifying potential prognostic factors. Given the difficulty of studying exposures in this patient population, as well as the existing immunologic characteristics of this cancer, there is growing interest in further identifying genetic and immunologic associations with patient survival. Furthermore, prognostic factors that may necessitate therapeutic intervention may significantly alter disease outlook. In this review paper, we address the current literature on MDSCs and their immunosuppressive behavior in ovarian cancer patients. While the previous studies on these cells in ovarian cancer have demonstrated some potential prognostic significance, there are many limitations to such studies including small sample sizes, inconsistent staging and histology, as well as inconsistent surface markers for the identification of MDSCs. Additionally, such studies include minimal patient characteristics involved with the clinical course of ovarian cancer. Here, we have proposed improving on studies analyzing MDSCs as a potential prognostic factor in ovarian cancer patients, as well as further identifying the potential of this novel prognostic factor in future care, through the use of a comprehensive epidemiologic model.
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