Integrative analysis of ferroptosis regulators for clinical prognosis based on deep learning and potential chemotherapy sensitivity of prostate cancer.

IF 5.1 4区 医学 Q1 MEDICINE, RESEARCH & EXPERIMENTAL
Tuanjie Guo, Zhihao Yuan, Tao Wang, Jian Zhang, Heting Tang, Ning Zhang, Xiang Wang, Siteng Chen
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引用次数: 1

Abstract

Exploring useful prognostic markers and developing a robust prognostic model for patients with prostate cancer are crucial for clinical practice. We applied a deep learning algorithm to construct a prognostic model and proposed the deep learning-based ferroptosis score (DLFscore) for the prediction of prognosis and potential chemotherapy sensitivity in prostate cancer. Based on this prognostic model, there was a statistically significant difference in the disease-free survival probability between patients with high and low DLFscore in the The Cancer Genome Atlas (TCGA) cohort (P < 0.0001). In the validation cohort GSE116918, we also observed a consistent conclusion with the training set (P = 0.02). Additionally, functional enrichment analysis showed that DNA repair, RNA splicing signaling, organelle assembly, and regulation of centrosome cycle pathways might regulate prostate cancer through ferroptosis. Meanwhile, the prognostic model we constructed also had application value in predicting drug sensitivity. We predicted some potential drugs for the treatment of prostate cancer through AutoDock, which could potentially be used for prostate cancer treatment.

Abstract Image

Abstract Image

Abstract Image

基于深度学习和前列腺癌潜在化疗敏感性的铁下垂调节因子对临床预后的综合分析。
探索有用的预后标志物和发展一个强大的预后模型的前列腺癌患者是至关重要的临床实践。我们应用深度学习算法构建预后模型,并提出基于深度学习的铁下垂评分(DLFscore)来预测前列腺癌的预后和潜在的化疗敏感性。基于该预后模型,在the Cancer Genome Atlas (TCGA)队列中,高、低dlf评分患者的无病生存率差异有统计学意义(P P = 0.02)。此外,功能富集分析表明,DNA修复、RNA剪接信号、细胞器组装和中心体周期途径的调节可能通过铁下垂调节前列腺癌。同时,所构建的预后模型在预测药物敏感性方面也具有应用价值。我们通过AutoDock预测了一些治疗前列腺癌的潜在药物,这些药物有可能用于前列腺癌的治疗。
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来源期刊
Precision Clinical Medicine
Precision Clinical Medicine MEDICINE, RESEARCH & EXPERIMENTAL-
CiteScore
10.80
自引率
0.00%
发文量
26
审稿时长
5 weeks
期刊介绍: Precision Clinical Medicine (PCM) is an international, peer-reviewed, open access journal that provides timely publication of original research articles, case reports, reviews, editorials, and perspectives across the spectrum of precision medicine. The journal's mission is to deliver new theories, methods, and evidence that enhance disease diagnosis, treatment, prevention, and prognosis, thereby establishing a vital communication platform for clinicians and researchers that has the potential to transform medical practice. PCM encompasses all facets of precision medicine, which involves personalized approaches to diagnosis, treatment, and prevention, tailored to individual patients or patient subgroups based on their unique genetic, phenotypic, or psychosocial profiles. The clinical conditions addressed by the journal include a wide range of areas such as cancer, infectious diseases, inherited diseases, complex diseases, and rare diseases.
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