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iDICss robustly predicts melanoma immunotherapy response by synergizing genomic and transcriptomic knowledge via independent component analysis.

作者信息

Qiu Jiayue, Jin Nana, Cheng Lixin, Huang Chen

机构信息

Dr. Nesher's Biophysics Laboratory for Innovative Drug Discovery, State Key Laboratory of Quality Research in Chinese Medicine & Faculty of Chinese Medicine, Macau University of Science and Technology, Taipa, Macao SAR, China.

Health Data Science Center, Shenzhen People's Hospital, First Affiliated Hospital of Southern University of Science and Technology, Shenzhen, China.

出版信息

Clin Transl Med. 2025 Jan;15(1):e70183. doi: 10.1002/ctm2.70183.

DOI:10.1002/ctm2.70183
PMID:39778023
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11707425/
Abstract
摘要
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3920/11707425/6abfc4cf46ad/CTM2-15-e70183-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3920/11707425/e28242adc163/CTM2-15-e70183-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3920/11707425/6abfc4cf46ad/CTM2-15-e70183-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3920/11707425/e28242adc163/CTM2-15-e70183-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3920/11707425/6abfc4cf46ad/CTM2-15-e70183-g002.jpg

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本文引用的文献

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Leveraging pharmacovigilance data to predict population-scale toxicity profiles of checkpoint inhibitor immunotherapy.利用药物警戒数据预测检查点抑制剂免疫疗法的人群规模毒性特征。
Nat Comput Sci. 2025 Mar;5(3):207-220. doi: 10.1038/s43588-024-00748-8. Epub 2024 Dec 23.
2
Defining clinically useful biomarkers of immune checkpoint inhibitors in solid tumours.定义实体瘤中免疫检查点抑制剂的临床有用生物标志物。
Nat Rev Cancer. 2024 Jul;24(7):498-512. doi: 10.1038/s41568-024-00705-7. Epub 2024 Jun 12.
3
MMP3C: an in-silico framework to depict cancer metabolic plasticity using gene expression profiles.
MMP3C：一种利用基因表达谱描绘癌症代谢可塑性的计算框架。
Brief Bioinform. 2023 Nov 22;25(1). doi: 10.1093/bib/bbad471.
4
Deep learning identifies a T-cell exhaustion-dependent transcriptional signature for predicting clinical outcomes and response to immune checkpoint blockade.深度学习识别出一种依赖于T细胞耗竭的转录特征，用于预测临床结果和对免疫检查点阻断的反应。
Oncogenesis. 2023 Jul 11;12(1):37. doi: 10.1038/s41389-023-00482-2.
5
bvnGPS: a generalizable diagnostic model for acute bacterial and viral infection using integrative host transcriptomics and pretrained neural networks.bvnGPS：一种基于整合宿主转录组学和预训练神经网络的急性细菌和病毒感染通用诊断模型。
Bioinformatics. 2023 Mar 1;39(3). doi: 10.1093/bioinformatics/btad109.
6
Signal pathways of melanoma and targeted therapy.黑色素瘤的信号通路与靶向治疗。
Signal Transduct Target Ther. 2021 Dec 20;6(1):424. doi: 10.1038/s41392-021-00827-6.
7
Tumor mutational load predicts survival after immunotherapy across multiple cancer types.肿瘤突变负荷可预测多种癌症类型免疫治疗后的生存情况。
Nat Genet. 2019 Feb;51(2):202-206. doi: 10.1038/s41588-018-0312-8. Epub 2019 Jan 14.
8
The genomic landscape of cutaneous melanoma.皮肤黑色素瘤的基因组格局。
Pigment Cell Melanoma Res. 2016 May;29(3):266-83. doi: 10.1111/pcmr.12459. Epub 2016 Mar 4.
9
Combining targeted therapy with immunotherapy in BRAF-mutant melanoma: promise and challenges.BRAF 突变型黑色素瘤中靶向治疗与免疫治疗的联合：前景与挑战。
J Clin Oncol. 2014 Jul 20;32(21):2248-54. doi: 10.1200/JCO.2013.52.1377. Epub 2014 Jun 23.