ArticleOncology research2025
Ultrasound genomics related mitochondrial gene signature for prognosis and neoadjuvant chemotherapy resistance in triple negative breast cancer.
Article in Oncology research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Co-targeting ferroptosis and immune evasion through small molecules in breast cancer.Journal of translational internal medicine · 2025Article
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Authors and funding
9 authors.
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Abstract
Background: Neoadjuvant chemotherapy (NAC) significantly enhances clinical outcomes in patients with triple-negative breast cancer (TNBC); however, chemoresistance frequently results in treatment failure. Consequently, understanding the mechanisms underlying resistance and accurately predicting this phenomenon are crucial for improving treatment efficacy. Methods: Ultrasound images from 62 patients, taken before and after neoadjuvant therapy, were collected. Mitochondrial-related genes were extracted from a public database. Ultrasound features associated with NAC resistance were identified and correlated with significant mitochondrial-related genes. Subsequently, a prognostic model was developed and evaluated using the GSE58812 dataset. We also assessed this model alongside clinical factors and its ability to predict immunotherapy response. Results: A total of 32 significant differentially expressed genes in TNBC across three groups indicated a strong correlation with ultrasound features. Univariate and multivariate Cox regression analyses identified six genes as independent risk factors for TNBC prognosis. Based on these six mitochondrial-related genes, we constructed a TNBC prognostic model. The model's risk scores indicated that high-risk patients generally have a poorer prognosis compared to low-risk patients, with the model demonstrating high predictive performance ( Conclusion: We identified resistance-related features from ultrasound images and integrated them with genomic data, enabling effective risk stratification of patients and prediction of the efficacy of neoadjuvant chemotherapy and immunotherapy in patients with TNBC.
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