A Prognostic Model Based on Colony Stimulating Factors-related Genes in Triple-negative Breast Cancer
10.16476/j.pibb.2024.0281
- VernacularTitle:基于集落刺激因子相关基因开发三阴性乳腺癌的预后模型
- Author:
Yu-Xuan GUO
1
;
Zhi-Yu WANG
1
;
Pei-Yao XIAO
1
;
Chan-Juan ZHENG
1
;
Shu-Jun FU
1
;
Guang-Chun HE
1
;
Jun LONG
2
;
Jie WANG
3
;
Xi-Yun DENG
1
;
Yi-An WANG
1
Author Information
1. Key Laboratory of Model Animals and Stem Cell Biology in Hunan Province, School of Medicine, Hunan Normal University, Changsha 410013, China
2. Shenzhen Key Laboratory of Energy Electrocatalytic Materials, Shenzhen Key Laboratory of Polymer Science and Technology, Guangdong Provincial Key Laboratory of New Energy Materials Service Safety, College of Materials Science and Engineering, Shenzhen University, Shenzhen 518055, China
3. Department of Pathology, Institute of Oncology & Diagnostic Pathology Center, The School of Basic Medical Sciences, Fujian Medical University, Fuzhou 350122, China
- Publication Type:Journal Article
- Keywords:
triple-negative breast cancer;
colony stimulating factors;
prognostic model;
tumor microenvironment;
drug sensitivity
- From:
Progress in Biochemistry and Biophysics
2024;51(10):2741-2756
- CountryChina
- Language:English
-
Abstract:
ObjectiveTriple-negative breast cancer (TNBC) is the breast cancer subtype with the worst prognosis, and lacks effective therapeutic targets. Colony stimulating factors (CSFs) are cytokines that can regulate the production of blood cells and stimulate the growth and development of immune cells, playing an important role in the malignant progression of TNBC. This article aims to construct a novel prognostic model based on the expression of colony stimulating factors-related genes (CRGs), and analyze the sensitivity of TNBC patients to immunotherapy and drug therapy. MethodsWe downloaded CRGs from public databases and screened for differentially expressed CRGs between normal and TNBC tissues in the TCGA-BRCA database. Through LASSO Cox regression analysis, we constructed a prognostic model and stratified TNBC patients into high-risk and low-risk groups based on the colony stimulating factors-related genes risk score (CRRS). We further analyzed the correlation between CRRS and patient prognosis, clinical features, tumor microenvironment (TME) in both high-risk and low-risk groups, and evaluated the relationship between CRRS and sensitivity to immunotherapy and drug therapy. ResultsWe identified 842 differentially expressed CRGs in breast cancer tissues of TNBC patients and selected 13 CRGs for constructing the prognostic model. Kaplan-Meier survival curves, time-dependent receiver operating characteristic curves, and other analyses confirmed that TNBC patients with high CRRS had shorter overall survival, and the predictive ability of CRRS prognostic model was further validated using the GEO dataset. Nomogram combining clinical features confirmed that CRRS was an independent factor for the prognosis of TNBC patients. Moreover, patients in the high-risk group had lower levels of immune infiltration in the TME and were sensitive to chemotherapeutic drugs such as 5-fluorouracil, ipatasertib, and paclitaxel. ConclusionWe have developed a CRRS-based prognostic model composed of 13 differentially expressed CRGs, which may serve as a useful tool for predicting the prognosis of TNBC patients and guiding clinical treatment. Moreover, the key genes within this model may represent potential molecular targets for future therapies of TNBC.
