Cargando…

Six-mRNA risk score system and nomogram constructed for patients with ovarian cancer

Platinum is a commonly used drug for the treatment of ovarian cancer (OC). The aim of the current study was to design and construct a risk score system for predicting the prognosis of patients with OC receiving platinum chemotherapy. The mRNA sequencing data and copy number variation (CNV) informati...

Descripción completa

Detalles Bibliográficos
Autores principales: Wang, Qianqian, Lu, Zhuwu, Ma, Jinqi, Zhang, Qingsong, Wang, Ni, Qian, Li, Zhang, Jun, Chen, Chen, Lu, Bei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: D.A. Spandidos 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6607424/
https://www.ncbi.nlm.nih.gov/pubmed/31423184
http://dx.doi.org/10.3892/ol.2019.10404
_version_ 1783432094788091904
author Wang, Qianqian
Lu, Zhuwu
Ma, Jinqi
Zhang, Qingsong
Wang, Ni
Qian, Li
Zhang, Jun
Chen, Chen
Lu, Bei
author_facet Wang, Qianqian
Lu, Zhuwu
Ma, Jinqi
Zhang, Qingsong
Wang, Ni
Qian, Li
Zhang, Jun
Chen, Chen
Lu, Bei
author_sort Wang, Qianqian
collection PubMed
description Platinum is a commonly used drug for the treatment of ovarian cancer (OC). The aim of the current study was to design and construct a risk score system for predicting the prognosis of patients with OC receiving platinum chemotherapy. The mRNA sequencing data and copy number variation (CNV) information (training set) of patients with OC were downloaded from The Cancer Genome Atlas database. A validation set, GSE63885, was obtained from Gene Expression Omnibus database. The differentially expressed genes (DEGs) and CNV genes (DECNs) between platinum-resistant and platinum-sensitive groups were identified using the limma package. The intersection between DEGs and DECNs were selected. Cox regression analysis was used to identify the genes and clinical factors associated with prognosis. Risk score system assessment and nomogram analysis were performed using the survival and rms packages in R. Gene Set Enrichment Analysis was used to identify the enriched pathways in high and low risk score groups. From 1,144 DEGs and 1,864 DECNs, 48 genes that occurred in the two datasets were selected. A total of six independent prognostic genes (T-box transcription factor T, synemin, tektin 5, growth differentiation factor 3, solute carrier family 22 member 3 and calcium voltage-gated channel subunit α1 C) and platinum response status were revealed to be associated with prognosis. Based on the six independent prognostic genes, a risk score system was constructed and assessed. Nomogram analysis revealed that the patients with the sensitive status and low risk scores had an improved prognosis. Furthermore, the current study revealed that the 574 DEGs identified were involved in eight pathways, including chemokine signaling pathway, toll-like receptor signaling pathway, cytokine-cytokine receptor interaction, RIG I like receptor signaling pathway, natural killer cell mediated cytotoxicity, apoptosis, T cell receptor signaling pathway and Fc ε receptor 1 signaling pathway. The six-mRNA risk score system designed in the present study may be used as prognosis predictor in patients with OC, whereas the nomogram may be valuable for identifying patients with OC who may benefit from platinum chemotherapy.
format Online
Article
Text
id pubmed-6607424
institution National Center for Biotechnology Information
language English
publishDate 2019
publisher D.A. Spandidos
record_format MEDLINE/PubMed
spelling pubmed-66074242019-08-18 Six-mRNA risk score system and nomogram constructed for patients with ovarian cancer Wang, Qianqian Lu, Zhuwu Ma, Jinqi Zhang, Qingsong Wang, Ni Qian, Li Zhang, Jun Chen, Chen Lu, Bei Oncol Lett Articles Platinum is a commonly used drug for the treatment of ovarian cancer (OC). The aim of the current study was to design and construct a risk score system for predicting the prognosis of patients with OC receiving platinum chemotherapy. The mRNA sequencing data and copy number variation (CNV) information (training set) of patients with OC were downloaded from The Cancer Genome Atlas database. A validation set, GSE63885, was obtained from Gene Expression Omnibus database. The differentially expressed genes (DEGs) and CNV genes (DECNs) between platinum-resistant and platinum-sensitive groups were identified using the limma package. The intersection between DEGs and DECNs were selected. Cox regression analysis was used to identify the genes and clinical factors associated with prognosis. Risk score system assessment and nomogram analysis were performed using the survival and rms packages in R. Gene Set Enrichment Analysis was used to identify the enriched pathways in high and low risk score groups. From 1,144 DEGs and 1,864 DECNs, 48 genes that occurred in the two datasets were selected. A total of six independent prognostic genes (T-box transcription factor T, synemin, tektin 5, growth differentiation factor 3, solute carrier family 22 member 3 and calcium voltage-gated channel subunit α1 C) and platinum response status were revealed to be associated with prognosis. Based on the six independent prognostic genes, a risk score system was constructed and assessed. Nomogram analysis revealed that the patients with the sensitive status and low risk scores had an improved prognosis. Furthermore, the current study revealed that the 574 DEGs identified were involved in eight pathways, including chemokine signaling pathway, toll-like receptor signaling pathway, cytokine-cytokine receptor interaction, RIG I like receptor signaling pathway, natural killer cell mediated cytotoxicity, apoptosis, T cell receptor signaling pathway and Fc ε receptor 1 signaling pathway. The six-mRNA risk score system designed in the present study may be used as prognosis predictor in patients with OC, whereas the nomogram may be valuable for identifying patients with OC who may benefit from platinum chemotherapy. D.A. Spandidos 2019-08 2019-05-27 /pmc/articles/PMC6607424/ /pubmed/31423184 http://dx.doi.org/10.3892/ol.2019.10404 Text en Copyright: © Wang et al. This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.
spellingShingle Articles
Wang, Qianqian
Lu, Zhuwu
Ma, Jinqi
Zhang, Qingsong
Wang, Ni
Qian, Li
Zhang, Jun
Chen, Chen
Lu, Bei
Six-mRNA risk score system and nomogram constructed for patients with ovarian cancer
title Six-mRNA risk score system and nomogram constructed for patients with ovarian cancer
title_full Six-mRNA risk score system and nomogram constructed for patients with ovarian cancer
title_fullStr Six-mRNA risk score system and nomogram constructed for patients with ovarian cancer
title_full_unstemmed Six-mRNA risk score system and nomogram constructed for patients with ovarian cancer
title_short Six-mRNA risk score system and nomogram constructed for patients with ovarian cancer
title_sort six-mrna risk score system and nomogram constructed for patients with ovarian cancer
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6607424/
https://www.ncbi.nlm.nih.gov/pubmed/31423184
http://dx.doi.org/10.3892/ol.2019.10404
work_keys_str_mv AT wangqianqian sixmrnariskscoresystemandnomogramconstructedforpatientswithovariancancer
AT luzhuwu sixmrnariskscoresystemandnomogramconstructedforpatientswithovariancancer
AT majinqi sixmrnariskscoresystemandnomogramconstructedforpatientswithovariancancer
AT zhangqingsong sixmrnariskscoresystemandnomogramconstructedforpatientswithovariancancer
AT wangni sixmrnariskscoresystemandnomogramconstructedforpatientswithovariancancer
AT qianli sixmrnariskscoresystemandnomogramconstructedforpatientswithovariancancer
AT zhangjun sixmrnariskscoresystemandnomogramconstructedforpatientswithovariancancer
AT chenchen sixmrnariskscoresystemandnomogramconstructedforpatientswithovariancancer
AT lubei sixmrnariskscoresystemandnomogramconstructedforpatientswithovariancancer