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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...

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Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
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.
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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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