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Identification of a Novel Tumor Microenvironment Prognostic Signature for Advanced-Stage Serous Ovarian Cancer
SIMPLE SUMMARY: The expression of tumor microenvironment-related genes is known to be correlated with ovarian cancer patients’ prognosis. Immunotherapeutic targets are in part located in this complex cluster of cells and soluble factors. In our study, we constructed a prognostic 11-gene signature fo...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8268985/ https://www.ncbi.nlm.nih.gov/pubmed/34283076 http://dx.doi.org/10.3390/cancers13133343 |
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author | Zheng, Mingjun Long, Junyu Chelariu-Raicu, Anca Mullikin, Heather Vilsmaier, Theresa Vattai, Aurelia Heidegger, Helene Hildegard Batz, Falk Keckstein, Simon Jeschke, Udo Trillsch, Fabian Mahner, Sven Kaltofen, Till |
author_facet | Zheng, Mingjun Long, Junyu Chelariu-Raicu, Anca Mullikin, Heather Vilsmaier, Theresa Vattai, Aurelia Heidegger, Helene Hildegard Batz, Falk Keckstein, Simon Jeschke, Udo Trillsch, Fabian Mahner, Sven Kaltofen, Till |
author_sort | Zheng, Mingjun |
collection | PubMed |
description | SIMPLE SUMMARY: The expression of tumor microenvironment-related genes is known to be correlated with ovarian cancer patients’ prognosis. Immunotherapeutic targets are in part located in this complex cluster of cells and soluble factors. In our study, we constructed a prognostic 11-gene signature for advanced serous ovarian cancer from tumor microenvironment-related genes through lasso regression. The established risk score can quantify the prognosis of ovarian cancer patients more accurately and is able to predict the putative biological response of cancer samples to a programmed death ligand 1 blocking immunotherapy. This might empower the role of immunotherapy in ovarian cancer through its usage in future study protocols. ABSTRACT: (1) Background: The tumor microenvironment is involved in the growth and proliferation of malignant tumors and in the process of resistance towards systemic and targeted therapies. A correlation between the gene expression profile of the tumor microenvironment and the prognosis of ovarian cancer patients is already known. (2) Methods: Based on data from The Cancer Genome Atlas (379 RNA sequencing samples), we constructed a prognostic 11-gene signature (SNRPA1, CCL19, CXCL11, CDC5L, APCDD1, LPAR2, PI3, PLEKHF1, CCDC80, CPXM1 and CTAG2) for Fédération Internationale de Gynécologie et d’Obstétrique stage III and IV serous ovarian cancer through lasso regression. (3) Results: The established risk score was able to predict the 1-, 3- and 5-year prognoses more accurately than previously known models. (4) Conclusions: We were able to confirm the predictive power of this model when we applied it to cervical and urothelial cancer, supporting its pan-cancer usability. We found that immune checkpoint genes correlate negatively with a higher risk score. Based on this information, we used our risk score to predict the biological response of cancer samples to an anti-programmed death ligand 1 immunotherapy, which could be useful for future clinical studies on immunotherapy in ovarian cancer. |
format | Online Article Text |
id | pubmed-8268985 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-82689852021-07-10 Identification of a Novel Tumor Microenvironment Prognostic Signature for Advanced-Stage Serous Ovarian Cancer Zheng, Mingjun Long, Junyu Chelariu-Raicu, Anca Mullikin, Heather Vilsmaier, Theresa Vattai, Aurelia Heidegger, Helene Hildegard Batz, Falk Keckstein, Simon Jeschke, Udo Trillsch, Fabian Mahner, Sven Kaltofen, Till Cancers (Basel) Article SIMPLE SUMMARY: The expression of tumor microenvironment-related genes is known to be correlated with ovarian cancer patients’ prognosis. Immunotherapeutic targets are in part located in this complex cluster of cells and soluble factors. In our study, we constructed a prognostic 11-gene signature for advanced serous ovarian cancer from tumor microenvironment-related genes through lasso regression. The established risk score can quantify the prognosis of ovarian cancer patients more accurately and is able to predict the putative biological response of cancer samples to a programmed death ligand 1 blocking immunotherapy. This might empower the role of immunotherapy in ovarian cancer through its usage in future study protocols. ABSTRACT: (1) Background: The tumor microenvironment is involved in the growth and proliferation of malignant tumors and in the process of resistance towards systemic and targeted therapies. A correlation between the gene expression profile of the tumor microenvironment and the prognosis of ovarian cancer patients is already known. (2) Methods: Based on data from The Cancer Genome Atlas (379 RNA sequencing samples), we constructed a prognostic 11-gene signature (SNRPA1, CCL19, CXCL11, CDC5L, APCDD1, LPAR2, PI3, PLEKHF1, CCDC80, CPXM1 and CTAG2) for Fédération Internationale de Gynécologie et d’Obstétrique stage III and IV serous ovarian cancer through lasso regression. (3) Results: The established risk score was able to predict the 1-, 3- and 5-year prognoses more accurately than previously known models. (4) Conclusions: We were able to confirm the predictive power of this model when we applied it to cervical and urothelial cancer, supporting its pan-cancer usability. We found that immune checkpoint genes correlate negatively with a higher risk score. Based on this information, we used our risk score to predict the biological response of cancer samples to an anti-programmed death ligand 1 immunotherapy, which could be useful for future clinical studies on immunotherapy in ovarian cancer. MDPI 2021-07-03 /pmc/articles/PMC8268985/ /pubmed/34283076 http://dx.doi.org/10.3390/cancers13133343 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Zheng, Mingjun Long, Junyu Chelariu-Raicu, Anca Mullikin, Heather Vilsmaier, Theresa Vattai, Aurelia Heidegger, Helene Hildegard Batz, Falk Keckstein, Simon Jeschke, Udo Trillsch, Fabian Mahner, Sven Kaltofen, Till Identification of a Novel Tumor Microenvironment Prognostic Signature for Advanced-Stage Serous Ovarian Cancer |
title | Identification of a Novel Tumor Microenvironment Prognostic Signature for Advanced-Stage Serous Ovarian Cancer |
title_full | Identification of a Novel Tumor Microenvironment Prognostic Signature for Advanced-Stage Serous Ovarian Cancer |
title_fullStr | Identification of a Novel Tumor Microenvironment Prognostic Signature for Advanced-Stage Serous Ovarian Cancer |
title_full_unstemmed | Identification of a Novel Tumor Microenvironment Prognostic Signature for Advanced-Stage Serous Ovarian Cancer |
title_short | Identification of a Novel Tumor Microenvironment Prognostic Signature for Advanced-Stage Serous Ovarian Cancer |
title_sort | identification of a novel tumor microenvironment prognostic signature for advanced-stage serous ovarian cancer |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8268985/ https://www.ncbi.nlm.nih.gov/pubmed/34283076 http://dx.doi.org/10.3390/cancers13133343 |
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