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Research
Xuli Meng
Zhejiang Provincial People's Hospital
Corresponding Author
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Background
Recent years, the breast cancer became the most commonly diagnosed cancer. The use of neoadjuvant chemotherapy (NACT) makes a significant contribution to chemotherapy in breast cancer. We aimed to develop the novel model as a predictor of distant relapse-free survival (DRFS) in breast cancer patients receiving taxane and anthracycline-based NACT.
Methods
We collected the mRNA expression datasets of patients from GSE25055 and GSE25065 in Gene Expression Omnibus (GEO). Univariate and Multivariate Cox Regression Analyses were conducted to achieve the prognostic genes that associated with DRFS. Moreover, the E2F targets genes were obtained from GSEA. We obtained the intersection genes between the prognostic genes and E2F target genes, then validated in GSE32603 dataset. And we established a nomogram model based on PTTG1 expression level and several clinical characteristics.
Results
A novel nomogram was conducted. The receiver operating characteristic (AUC = 0.849), C-index (0.805) and calibration plots were applied to assess the effect of this model.
Conclusion
Our study found that the E2F target genes, such as the PTTG1 may serve as a potential biomarker in breast cancer, and provided superior estimation of DRFS, which can guide the clinical practice in NACT of breast cancer.
Keywords
breast cancer, neoadjuvant chemotherapy, distant relapse-free survival, PTTG1, nomogram model
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
This is a list of supplementary files associated with this preprint. Click to download.
- Fig.S1.pdf
GO enrichment analysis in PPI network.
- Fig.S2.pdf
KEGG enrichment analysis in PPI network.
- Tab.S1.xls
GO functional analysis in GSE25055.
- Tab.S2.xls
GO functional analysis in GSE25065.
- Tab.S3.xls
The Gene Set Enrichment Analysis in GSE25055 and GSE25065.
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Subject Areas
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A new preprint design is coming!
We have improved readability, clarity, accessibility, and opportunities for engagement.
This is a preprint, a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Research
Xuli Meng
Zhejiang Provincial People's Hospital
Corresponding Author
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
History
CURRENT STATUS: Posted
The most recent version of this article is available here.
No community comments so far
Version 1
Posted 25 May, 2021
No comments provided
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Cancer Biology
License:
This work is licensed under a CC BY 4.0 License. Read Full License
The most recent version of this article is available here.
Background
Recent years, the breast cancer became the most commonly diagnosed cancer. The use of neoadjuvant chemotherapy (NACT) makes a significant contribution to chemotherapy in breast cancer. We aimed to develop the novel model as a predictor of distant relapse-free survival (DRFS) in breast cancer patients receiving taxane and anthracycline-based NACT.
Methods
We collected the mRNA expression datasets of patients from GSE25055 and GSE25065 in Gene Expression Omnibus (GEO). Univariate and Multivariate Cox Regression Analyses were conducted to achieve the prognostic genes that associated with DRFS. Moreover, the E2F targets genes were obtained from GSEA. We obtained the intersection genes between the prognostic genes and E2F target genes, then validated in GSE32603 dataset. And we established a nomogram model based on PTTG1 expression level and several clinical characteristics.
Results
A novel nomogram was conducted. The receiver operating characteristic (AUC = 0.849), C-index (0.805) and calibration plots were applied to assess the effect of this model.
Conclusion
Our study found that the E2F target genes, such as the PTTG1 may serve as a potential biomarker in breast cancer, and provided superior estimation of DRFS, which can guide the clinical practice in NACT of breast cancer.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
This is a list of supplementary files associated with this preprint. Click to download.
- Fig.S1.pdf
GO enrichment analysis in PPI network.
- Fig.S2.pdf
KEGG enrichment analysis in PPI network.
- Tab.S1.xls
GO functional analysis in GSE25055.
- Tab.S2.xls
GO functional analysis in GSE25065.
- Tab.S3.xls
The Gene Set Enrichment Analysis in GSE25055 and GSE25065.
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