Cargando…
Development and Validation of the Promising PPAR Signaling Pathway-Based Prognostic Prediction Model in Uterine Cervical Cancer
A ligand-activated transcription factor, peroxisome proliferator-activated receptor (PPAR) regulates fatty acid uptake and transport. In several studies, upregulation of PPAR expression/activity by cancer cells has been associated with cancer progression. Worldwide, cancer of the cervix ranks fourth...
Autores principales: | , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10247326/ https://www.ncbi.nlm.nih.gov/pubmed/37292383 http://dx.doi.org/10.1155/2023/4962460 |
_version_ | 1785055175650574336 |
---|---|
author | Zhang, Yan Li, Xing Zhang, Jun Mao, Lin Wen, Zou Cao, Mingliang Mu, Xuefeng |
author_facet | Zhang, Yan Li, Xing Zhang, Jun Mao, Lin Wen, Zou Cao, Mingliang Mu, Xuefeng |
author_sort | Zhang, Yan |
collection | PubMed |
description | A ligand-activated transcription factor, peroxisome proliferator-activated receptor (PPAR) regulates fatty acid uptake and transport. In several studies, upregulation of PPAR expression/activity by cancer cells has been associated with cancer progression. Worldwide, cancer of the cervix ranks fourth among women's cancers. Angiogenesis inhibitors have improved treatment for recurrent and advanced cervical cancer since their introduction 5 years ago. In spite of that, the median overall survival rate for advanced cervical cancer is 16.8 months, indicating that treatment effectiveness is still lacking. Thus, it is imperative that new therapeutic methods be developed. In this work, we first downloaded the PPAR signaling pathway-related genes from the previous study. In addition, the single-sample gene set enrichment analysis (ssGSEA) algorithm was applied to calculate the PPAR score of patients with cervical cancer. Furthermore, cervical cancer patients with different PPAR scores show different sensitivity to immune checkpoint therapy. In order to screen the genes to serve as the best biomarker for cervical cancer patients, we then construct the PPAR-based prognostic prediction model. The results revealed that PCK1, MT1A, AL096855.1, AC096711.2, FAR2P2, and AC099568.2 not only play a key role in the PPAR signaling pathway but also show good predictive value in cervical cancer patients. The gene set variation analysis (GSVA) enrichment analysis also proved that the PPAR signaling pathway is one of the most enriched pathways in the prognostic prediction model. Finally, further analysis revealed that AC099568.2 may be the most promising biomarker for the diagnosis, treatment, and prognosis in cervical cancer patients. Both the survival analysis and Receiver Operating Characteristic curve demonstrated that AC099568.2 plays a key role in cervical cancer patients. However, to our knowledge, this is the first time a study focused on the role of AC099568.2 in cervical cancer patients. Our work successfully revealed a new biomarker for cervical cancer patients, which also provides a new direction for future research. |
format | Online Article Text |
id | pubmed-10247326 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-102473262023-06-08 Development and Validation of the Promising PPAR Signaling Pathway-Based Prognostic Prediction Model in Uterine Cervical Cancer Zhang, Yan Li, Xing Zhang, Jun Mao, Lin Wen, Zou Cao, Mingliang Mu, Xuefeng PPAR Res Research Article A ligand-activated transcription factor, peroxisome proliferator-activated receptor (PPAR) regulates fatty acid uptake and transport. In several studies, upregulation of PPAR expression/activity by cancer cells has been associated with cancer progression. Worldwide, cancer of the cervix ranks fourth among women's cancers. Angiogenesis inhibitors have improved treatment for recurrent and advanced cervical cancer since their introduction 5 years ago. In spite of that, the median overall survival rate for advanced cervical cancer is 16.8 months, indicating that treatment effectiveness is still lacking. Thus, it is imperative that new therapeutic methods be developed. In this work, we first downloaded the PPAR signaling pathway-related genes from the previous study. In addition, the single-sample gene set enrichment analysis (ssGSEA) algorithm was applied to calculate the PPAR score of patients with cervical cancer. Furthermore, cervical cancer patients with different PPAR scores show different sensitivity to immune checkpoint therapy. In order to screen the genes to serve as the best biomarker for cervical cancer patients, we then construct the PPAR-based prognostic prediction model. The results revealed that PCK1, MT1A, AL096855.1, AC096711.2, FAR2P2, and AC099568.2 not only play a key role in the PPAR signaling pathway but also show good predictive value in cervical cancer patients. The gene set variation analysis (GSVA) enrichment analysis also proved that the PPAR signaling pathway is one of the most enriched pathways in the prognostic prediction model. Finally, further analysis revealed that AC099568.2 may be the most promising biomarker for the diagnosis, treatment, and prognosis in cervical cancer patients. Both the survival analysis and Receiver Operating Characteristic curve demonstrated that AC099568.2 plays a key role in cervical cancer patients. However, to our knowledge, this is the first time a study focused on the role of AC099568.2 in cervical cancer patients. Our work successfully revealed a new biomarker for cervical cancer patients, which also provides a new direction for future research. Hindawi 2023-05-31 /pmc/articles/PMC10247326/ /pubmed/37292383 http://dx.doi.org/10.1155/2023/4962460 Text en Copyright © 2023 Yan Zhang et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Zhang, Yan Li, Xing Zhang, Jun Mao, Lin Wen, Zou Cao, Mingliang Mu, Xuefeng Development and Validation of the Promising PPAR Signaling Pathway-Based Prognostic Prediction Model in Uterine Cervical Cancer |
title | Development and Validation of the Promising PPAR Signaling Pathway-Based Prognostic Prediction Model in Uterine Cervical Cancer |
title_full | Development and Validation of the Promising PPAR Signaling Pathway-Based Prognostic Prediction Model in Uterine Cervical Cancer |
title_fullStr | Development and Validation of the Promising PPAR Signaling Pathway-Based Prognostic Prediction Model in Uterine Cervical Cancer |
title_full_unstemmed | Development and Validation of the Promising PPAR Signaling Pathway-Based Prognostic Prediction Model in Uterine Cervical Cancer |
title_short | Development and Validation of the Promising PPAR Signaling Pathway-Based Prognostic Prediction Model in Uterine Cervical Cancer |
title_sort | development and validation of the promising ppar signaling pathway-based prognostic prediction model in uterine cervical cancer |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10247326/ https://www.ncbi.nlm.nih.gov/pubmed/37292383 http://dx.doi.org/10.1155/2023/4962460 |
work_keys_str_mv | AT zhangyan developmentandvalidationofthepromisingpparsignalingpathwaybasedprognosticpredictionmodelinuterinecervicalcancer AT lixing developmentandvalidationofthepromisingpparsignalingpathwaybasedprognosticpredictionmodelinuterinecervicalcancer AT zhangjun developmentandvalidationofthepromisingpparsignalingpathwaybasedprognosticpredictionmodelinuterinecervicalcancer AT maolin developmentandvalidationofthepromisingpparsignalingpathwaybasedprognosticpredictionmodelinuterinecervicalcancer AT wenzou developmentandvalidationofthepromisingpparsignalingpathwaybasedprognosticpredictionmodelinuterinecervicalcancer AT caomingliang developmentandvalidationofthepromisingpparsignalingpathwaybasedprognosticpredictionmodelinuterinecervicalcancer AT muxuefeng developmentandvalidationofthepromisingpparsignalingpathwaybasedprognosticpredictionmodelinuterinecervicalcancer |