A lipid metabolism-related gene signature predicts prognosis after tamoxifen treatment in ER plus breast cancer and reflects tumor microenvironment heterogeneity through single-cell analysis

被引:0
作者
Ma, Linxiaoxi [1 ]
Qian, Bei [2 ]
Peng, Chen [3 ]
Liu, Gang [3 ]
Shen, Hao [4 ]
机构
[1] Fudan Univ, Shanghai Med Coll, Dept Oncol,Shanghai Canc Ctr, Dept Breast Surg,Key Lab Breast Canc Shanghai, Shanghai, Peoples R China
[2] Huazhong Univ Sci & Technol, Union Hosp, Tongji Med Coll, Dept Thyroid & Breast Surg, 1277 Jiefang Ave, Wuhan 430022, Peoples R China
[3] Fudan Univ, Inst Biomed Sci, 131 Dongan Rd, Shanghai 200032, Peoples R China
[4] Tongji Univ, Shanghai East Hosp, Sch Med, Dept Thyroid Breast Surg, 150 Jimo Rd, Shanghai 200120, Peoples R China
关键词
Prognosis; Lipid metabolism; ER plus breast cancer; Tamoxifen; EXPRESSION; SUBTYPES; THERAPY; PACKAGE;
D O I
10.1186/s12920-025-02194-5
中图分类号
Q3 [遗传学];
学科分类号
071007 ; 090102 ;
摘要
BackgroundAlthough the clinical outcome of ER + breast cancer patients receiving tamoxifen after surgery is favorable, a proportion of patients experience recurrence or death due to disease progression.MethodsIn this study, by integrating lipid metabolism gene expression and machine learning data, a prognostic model based on gene expression was developed using the TCGA-ER + BRCA dataset (N = 183) and validated with the GSE17705 (N = 298), GSE22219 (N = 134), GSE42568 (N = 70), and GSE58644 (N = 147) datasets. Patients were stratified into high- and low-risk groups based on the median risk score of the signature. Comparative analyses of survival, genomic features, immune infiltration, and drug sensitivity were performed between these groups.ResultsPatients in the high-risk group had worse survival outcomes than those in the low-risk group. The five-year overall survival AUC of the model was 0.858, indicating good performance. High-risk patients were characterized by USH2A and KMT2C mutations, genomic amplification, and enriched JAK-STAT pathway and cytokine-cytokine receptor interaction pathways. Resting CD4 + memory T cells, activated mast cells, and myeloid dendritic cells were significantly enriched in the low-risk group, while M0 macrophages were enriched in the high-risk group. Single-cell sequencing analyses also revealed that the model was significantly associated with macrophages and the percentage of proliferating myeloid cells. The signature was also associated with sensitivity to multiple drugs. Cell-cell interaction difference analyses suggested that cancer-related signaling pathways, especially the SIRP alpha/CD47/IL6 pathway, were decreased in high-risk patients, but these samples exhibited increased SPP1 interactions.ConclusionThe signature captures lipid metabolic reprogramming and immunosuppression, providing a biomarker for prognosis and precision therapy in tamoxifen-treated ER + breast cancer.
引用
收藏
页数:16
相关论文
共 57 条
[1]  
[Anonymous], **DATA OBJECT**
[2]   xCell: digitally portraying the tissue cellular heterogeneity landscape [J].
Aran, Dvir ;
Hu, Zicheng ;
Butte, Atul J. .
GENOME BIOLOGY, 2017, 18
[3]   CXCL9:SPP1 macrophage polarity identifies a network of cellular programs that control human cancers [J].
Bill, Ruben ;
Wirapati, Pratyaksha ;
Messemaker, Marius ;
Roh, Whijae ;
Zitti, Beatrice ;
Duval, Florent ;
Kiss, Mate ;
Park, Jong Chul ;
Saal, Talia M. ;
Hoelzl, Jan ;
Tarussio, David ;
Benedetti, Fabrizio ;
Tissot, Stephanie ;
Kandalaft, Lana ;
Varrone, Marco ;
Ciriello, Giovanni ;
McKee, Thomas A. ;
Monnier, Yan ;
Mermod, Maxime ;
Blaum, Emily M. ;
Gushterova, Irena ;
Gonye, Anna L. K. ;
Hacohen, Nir ;
Getz, Gad ;
Mempel, Thorsten R. ;
Klein, Allon M. ;
Weissleder, Ralph ;
Faquin, William C. ;
Sadow, Peter M. ;
Lin, Derrick ;
Pai, Sara I. ;
Sade-Feldman, Moshe ;
Pittet, Mikael J. .
SCIENCE, 2023, 381 (6657) :515-524
[4]   Mammaprint: a comprehensive review [J].
Brandao, Mariana ;
Ponde, Noam ;
Piccart-Gebhart, Martine .
FUTURE ONCOLOGY, 2019, 15 (02) :207-224
[5]   microRNA-Associated Progression Pathways and Potential Therapeutic Targets Identified by Integrated mRNA and microRNA Expression Profiling in Breast Cancer [J].
Buffa, Francesca M. ;
Camps, Carme ;
Winchester, Laura ;
Snell, Cameron E. ;
Gee, Harriet E. ;
Sheldon, Helen ;
Taylor, Marian ;
Harris, Adrian L. ;
Ragoussis, Jiannis .
CANCER RESEARCH, 2011, 71 (17) :5635-5645
[6]   70-Gene Signature as an Aid to Treatment Decisions in Early-Stage Breast Cancer [J].
Cardoso, F. ;
van't Veer, L. J. ;
Bogaerts, J. ;
Slaets, L. ;
Viale, G. ;
Delaloge, S. ;
Pierga, J. -Y. ;
Brain, E. ;
Causeret, S. ;
DeLorenzi, M. ;
Glas, A. M. ;
Golfinopoulos, V. ;
Goulioti, T. ;
Knox, S. ;
Matos, E. ;
Meulemans, B. ;
Neijenhuis, P. A. ;
Nitz, U. ;
Passalacqua, R. ;
Ravdin, P. ;
Rubio, I. T. ;
Saghatchian, M. ;
Smilde, T. J. ;
Sotiriou, C. ;
Stork, L. ;
Straehle, C. ;
Thomas, G. ;
Thompson, A. M. ;
van der Hoeven, J. M. ;
Vuylsteke, P. ;
Bernards, R. ;
Tryfonidis, K. ;
Rutgers, E. ;
Piccart, M. .
NEW ENGLAND JOURNAL OF MEDICINE, 2016, 375 (08) :717-729
[7]   Aberrant fatty acid profile and FFAR4 signaling confer endocrine resistance in breast cancer [J].
Chu, Xiao ;
Zhou, Qi ;
Xu, Yingchun ;
Jiang, Jingting ;
Li, Qing ;
Zhou, Qianjun ;
Wu, Qiong ;
Jin, Min ;
Wang, Hui ;
Gu, Yuting ;
Wang, Xue ;
Wang, Bei ;
He, Songbing ;
He, Xiaozhou ;
Wu, Changping ;
Zhang, Fengchun ;
Zhang, Yanyun .
JOURNAL OF EXPERIMENTAL & CLINICAL CANCER RESEARCH, 2019, 38 (1)
[8]   Correlating transcriptional networks to breast cancer survival: a large-scale coexpression analysis [J].
Clarke, Colin ;
Madden, Stephen F. ;
Doolan, Padraig ;
Aherne, Sinead T. ;
Joyce, Helena ;
O'Driscoll, Lorraine ;
Gallagher, William M. ;
Hennessy, Bryan T. ;
Moriarty, Michael ;
Crown, John ;
Kennedy, Susan ;
Clynes, Martin .
CARCINOGENESIS, 2013, 34 (10) :2300-2308
[9]   Fatty acid synthesis is required for breast cancer brain metastasis [J].
Ferraro, Gino B. ;
Ali, Ahmed ;
Luengo, Alba ;
Kodack, David P. ;
Deik, Amy ;
Abbott, Keene L. ;
Bezwada, Divya ;
Blanc, Landry ;
Prideaux, Brendan ;
Jin, Xin ;
Possada, Jessica M. ;
Chen, Jiang ;
Chin, Christopher R. ;
Amoozgar, Zohreh ;
Ferreira, Raphael ;
Chen, Ivy X. ;
Naxerova, Kamila ;
Ng, Christopher ;
Westermark, Anna M. ;
Duquette, Mark ;
Roberge, Sylvie ;
Lindeman, Neal I. ;
Lyssiotis, Costas A. ;
Nielsen, Jens ;
Housman, David E. ;
Duda, Dan G. ;
Brachtel, Elena ;
Golub, Todd R. ;
Cantley, Lewis C. ;
Asara, John M. ;
Davidson, Shawn M. ;
Fukumura, Dai ;
Dartois, Veronique A. ;
Clish, Clary B. ;
Jain, Rakesh K. ;
Vander Heiden, Matthew G. .
NATURE CANCER, 2021, 2 (04) :414-+
[10]   KMT2C mediates the estrogen dependence of breast cancer through regulation of ERα enhancer function [J].
Gala, Kinisha ;
Li, Qing ;
Sinha, Amit ;
Razavi, Pedram ;
Dorso, Madeline ;
Sanchez-Vega, Francisco ;
Chung, Young Rock ;
Hendrickson, Ronald ;
Hsieh, James J. ;
Berger, Michael ;
Schultz, Nikolaus ;
Pastore, Alessandro ;
Abdel-Wahab, Omar ;
Chandarlapaty, Sarat .
ONCOGENE, 2018, 37 (34) :4692-4710