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. 2022 Nov:107:106936.
doi: 10.1016/j.ijsu.2022.106936. Epub 2022 Sep 20.

Leveraging diverse cell-death patterns to predict the prognosis and drug sensitivity of triple-negative breast cancer patients after surgery

Yutian Zou  1 , Jindong Xie, Shaoquan Zheng, Wenqing Liu, Yuhui Tang, Wenwen Tian, Xinpei Deng, Linyu Wu, Yue Zhang, Chau-Wei Wong, Duxun Tan, Qing Liu, Xiaoming Xie
Affiliations

Leveraging diverse cell-death patterns to predict the prognosis and drug sensitivity of triple-negative breast cancer patients after surgery

Yutian Zou et al. Int J Surg. 2022 Nov.

Abstract

Background: Postoperative progression and chemotherapy resistance is the major cause of treatment failure in patients with triple-negative breast cancer (TNBC). Currently, there is a lack of an ideal predictive model for the progression and drug sensitivity of postoperative TNBC patients. Diverse programmed cell death (PCD) patterns play an important role in tumor progression, which has the potential to be a prognostic and drug sensitivity indicator for TNBC after surgery.

Materials and methods: Twelve PCD patterns (apoptosis, necroptosis, pyroptosis, ferroptosis, cuproptosis, entotic cell death, netotic cell death, parthanatos, lysosome-dependent cell death, autophagy-dependent cell death, alkaliptosis, and oxeiptosis) were analyzed for model construction. Bulk transcriptome, single-cell transcriptome, genomics, and clinical information were collected from TCGA-BRCA, METABRIC, GSE58812, GSE21653, GSE176078, GSE75688, and KM-plotter cohorts to validate the model.

Results: The machine learning algorithm established a cell death index (CDI) with a 12-gene signature. Validated in five independent datasets, TNBC patients with high CDI had a worse prognosis after surgery. Two molecular subtypes of TNBC with distinct vital biological processes were identified by an unsupervised clustering model. A nomogram with high predictive performance was constructed by incorporating CDI with clinical features. Furthermore, CDI was associated with immune checkpoint genes and key tumor microenvironment components by integrated analysis of bulk and single-cell transcriptome. TNBC patients with high CDI are resistant to standard adjuvant chemotherapy regimens (docetaxel, oxaliplatin, etc.); however, they might be sensitive to palbociclib (an FDA-approved drug for luminal breast cancer).

Conclusion: Generally, we established a novel CDI model by comprehensively analyzing diverse cell death patterns, which can accurately predict clinical prognosis and drug sensitivity of TNBC after surgery. A user-friendly website was created to facilitate the application of this prediction model (https://tnbc.shinyapps.io/CDI_Model/).

Keywords: Cell death index; Drug sensitivity; Postoperative prediction model; Programmed cell death; Triple-negative breast cancer.

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Conflict of interest statement

Declaration of competing interest The authors declare no conflict of interest.

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References

    1. Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. Ca - Cancer J. Clin. 2021;71(3):209-249.
    1. Heer E, Harper A, Escandor N, Sung H, McCormack V, Fidler-Benaoudia MM. Global burden and trends in premenopausal and postmenopausal breast cancer: a population-based study. Lancet Global Health. 2020;8(8):e1027-e1037.
    1. Carey L, Winer E, Viale G, Cameron D, Gianni L. Triple-negative breast cancer: disease entity or title of convenience? Nat. Rev. Clin. Oncol. 2010;7(12):683-692.
    1. Johnson R, Sabnis N, McConathy WJ, Lacko AG. The potential role of nanotechnology in therapeutic approaches for triple negative breast cancer. Pharmaceutics. 2013;5(2):353-370.
    1. Zheng S, Zou Y, Liang JY, Xiao W, Yang A, Meng T, et al. Identification and validation of a combined hypoxia and immune index for triple-negative breast cancer. Mol Oncol. 2020;14(11):2814-2833.

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