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Immune Cell Infiltration as Signatures for the Diagnosis and Prognosis of Malignant Gynecological Tumors

Background Malignant gynecological tumors are the main cause of cancer-related deaths in women worldwide and include uterine carcinosarcomas, endometrial cancer, cervical cancer, ovarian cancer, and breast cancer. This study aims to determine the association between immune cell infiltration and mali...

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Autores principales: Liu, Qi-Fang, Feng, Zi-Yi, Jiang, Li-Li, Xu, Tong-Tong, Li, Si-Man, Liu, Kui-Ran
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8247483/
https://www.ncbi.nlm.nih.gov/pubmed/34222265
http://dx.doi.org/10.3389/fcell.2021.702451
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author Liu, Qi-Fang
Feng, Zi-Yi
Jiang, Li-Li
Xu, Tong-Tong
Li, Si-Man
Liu, Kui-Ran
author_facet Liu, Qi-Fang
Feng, Zi-Yi
Jiang, Li-Li
Xu, Tong-Tong
Li, Si-Man
Liu, Kui-Ran
author_sort Liu, Qi-Fang
collection PubMed
description Background Malignant gynecological tumors are the main cause of cancer-related deaths in women worldwide and include uterine carcinosarcomas, endometrial cancer, cervical cancer, ovarian cancer, and breast cancer. This study aims to determine the association between immune cell infiltration and malignant gynecological tumors and construct signatures for diagnosis and prognosis. Methods We acquired malignant gynecological tumor RNA-seq transcriptome data from the TCGA database. Next, the “CIBERSORT” algorithm calculated the infiltration of 22 immune cells in malignant gynecological tumors. To construct diagnosis and prognosis signatures, step-wise regression and LASSO analyses were applied, and nomogram and immune subtypes were further identified. Results Notably, Immune cell infiltration plays a significant role in tumorigenesis and development. There are obvious differences in the distribution of immune cells in normal, and tumor tissues. Resting NK cells, M0 Macrophages, and M1 Macrophages participated in the construction of the diagnostic model, with an AUC value of 0.898. LASSO analyses identified a risk signature including T cells CD8, activated NK cells, Monocytes, M2 Macrophages, resting Mast cells, and Neutrophils, proving the prognostic value for the risk signature. We identified two subtypes according to consensus clustering, where immune subtype 3 presented the highest risk. Conclusion We identified diagnostic and prognostic signatures based on immune cell infiltration. Thus, this study provided a strong basis for the early diagnosis and effective treatment of malignant gynecological tumors.
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spelling pubmed-82474832021-07-02 Immune Cell Infiltration as Signatures for the Diagnosis and Prognosis of Malignant Gynecological Tumors Liu, Qi-Fang Feng, Zi-Yi Jiang, Li-Li Xu, Tong-Tong Li, Si-Man Liu, Kui-Ran Front Cell Dev Biol Cell and Developmental Biology Background Malignant gynecological tumors are the main cause of cancer-related deaths in women worldwide and include uterine carcinosarcomas, endometrial cancer, cervical cancer, ovarian cancer, and breast cancer. This study aims to determine the association between immune cell infiltration and malignant gynecological tumors and construct signatures for diagnosis and prognosis. Methods We acquired malignant gynecological tumor RNA-seq transcriptome data from the TCGA database. Next, the “CIBERSORT” algorithm calculated the infiltration of 22 immune cells in malignant gynecological tumors. To construct diagnosis and prognosis signatures, step-wise regression and LASSO analyses were applied, and nomogram and immune subtypes were further identified. Results Notably, Immune cell infiltration plays a significant role in tumorigenesis and development. There are obvious differences in the distribution of immune cells in normal, and tumor tissues. Resting NK cells, M0 Macrophages, and M1 Macrophages participated in the construction of the diagnostic model, with an AUC value of 0.898. LASSO analyses identified a risk signature including T cells CD8, activated NK cells, Monocytes, M2 Macrophages, resting Mast cells, and Neutrophils, proving the prognostic value for the risk signature. We identified two subtypes according to consensus clustering, where immune subtype 3 presented the highest risk. Conclusion We identified diagnostic and prognostic signatures based on immune cell infiltration. Thus, this study provided a strong basis for the early diagnosis and effective treatment of malignant gynecological tumors. Frontiers Media S.A. 2021-06-17 /pmc/articles/PMC8247483/ /pubmed/34222265 http://dx.doi.org/10.3389/fcell.2021.702451 Text en Copyright © 2021 Liu, Feng, Jiang, Xu, Li and Liu. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Cell and Developmental Biology
Liu, Qi-Fang
Feng, Zi-Yi
Jiang, Li-Li
Xu, Tong-Tong
Li, Si-Man
Liu, Kui-Ran
Immune Cell Infiltration as Signatures for the Diagnosis and Prognosis of Malignant Gynecological Tumors
title Immune Cell Infiltration as Signatures for the Diagnosis and Prognosis of Malignant Gynecological Tumors
title_full Immune Cell Infiltration as Signatures for the Diagnosis and Prognosis of Malignant Gynecological Tumors
title_fullStr Immune Cell Infiltration as Signatures for the Diagnosis and Prognosis of Malignant Gynecological Tumors
title_full_unstemmed Immune Cell Infiltration as Signatures for the Diagnosis and Prognosis of Malignant Gynecological Tumors
title_short Immune Cell Infiltration as Signatures for the Diagnosis and Prognosis of Malignant Gynecological Tumors
title_sort immune cell infiltration as signatures for the diagnosis and prognosis of malignant gynecological tumors
topic Cell and Developmental Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8247483/
https://www.ncbi.nlm.nih.gov/pubmed/34222265
http://dx.doi.org/10.3389/fcell.2021.702451
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