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皮肤癌中的分子分类器:挑战与前景

Molecular Classifiers in Skin Cancers: Challenges and Promises.

作者信息

Azimi Ali, Fernandez-Peñas Pablo

机构信息

Westmead Clinical School, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW 2145, Australia.

Department of Dermatology, Westmead Hospital, Westmead, NSW 2145, Australia.

出版信息

Cancers (Basel). 2023 Sep 7;15(18):4463. doi: 10.3390/cancers15184463.

DOI:10.3390/cancers15184463
PMID:37760432
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10526380/
Abstract

Skin cancers are common and heterogenous malignancies affecting up to two in three Australians before age 70. Despite recent developments in diagnosis and therapeutic strategies, the mortality rate and costs associated with managing patients with skin cancers remain high. The lack of well-defined clinical and histopathological features makes their diagnosis and classification difficult in some cases and the prognostication difficult in most skin cancers. Recent advancements in large-scale "omics" studies, including genomics, transcriptomics, proteomics, metabolomics and imaging-omics, have provided invaluable information about the molecular and visual landscape of skin cancers. On many occasions, it has refined tumor classification and has improved prognostication and therapeutic stratification, leading to improved patient outcomes. Therefore, this paper reviews the recent advancements in omics approaches and appraises their limitations and potential for better classification and stratification of skin cancers.

摘要

皮肤癌是常见的异质性恶性肿瘤,在70岁之前,多达三分之二的澳大利亚人会受到影响。尽管在诊断和治疗策略方面有了最新进展,但皮肤癌患者的死亡率和管理成本仍然很高。缺乏明确的临床和组织病理学特征使得在某些情况下难以进行诊断和分类,而在大多数皮肤癌中预后也很困难。大规模“组学”研究的最新进展,包括基因组学、转录组学、蛋白质组学、代谢组学和影像组学,为皮肤癌的分子和视觉特征提供了宝贵信息。在许多情况下,它优化了肿瘤分类,改善了预后和治疗分层,从而改善了患者的治疗效果。因此,本文综述了组学方法的最新进展,并评估了它们在皮肤癌更好分类和分层方面的局限性及潜力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e9ad/10526380/5069741d4ba1/cancers-15-04463-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e9ad/10526380/f7073d694fff/cancers-15-04463-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e9ad/10526380/a4da0c04b3f0/cancers-15-04463-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e9ad/10526380/5069741d4ba1/cancers-15-04463-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e9ad/10526380/f7073d694fff/cancers-15-04463-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e9ad/10526380/a4da0c04b3f0/cancers-15-04463-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e9ad/10526380/5069741d4ba1/cancers-15-04463-g002.jpg

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本文引用的文献

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Undisclosed, unmet and neglected challenges in multi-omics studies.多组学研究中未公开、未满足且被忽视的挑战。
Nat Comput Sci. 2021 Jun;1(6):395-402. doi: 10.1038/s43588-021-00086-z. Epub 2021 Jun 21.
2
Predicting breast cancer types on and beyond molecular level in a multi-modal fashion.以多模态方式在分子水平及更高层面预测乳腺癌类型。
NPJ Breast Cancer. 2023 Mar 22;9(1):16. doi: 10.1038/s41523-023-00517-2.
3
Integrated multi-omics reveals cellular and molecular interactions governing the invasive niche of basal cell carcinoma.
砷暴露人群中非黑色素瘤皮肤癌(NMSC)的分子谱分析及体细胞突变与转录组谱的相互作用
Cells. 2024 Jun 18;13(12):1056. doi: 10.3390/cells13121056.
整合多组学揭示了调控基底细胞癌侵袭生态位的细胞和分子相互作用。
Nat Commun. 2022 Aug 20;13(1):4897. doi: 10.1038/s41467-022-32670-w.
4
Multiomics Topic Modeling for Breast Cancer Classification.用于乳腺癌分类的多组学主题建模
Cancers (Basel). 2022 Feb 23;14(5):1150. doi: 10.3390/cancers14051150.
5
The initial rate of tumour response to vismodegib treatment, can predict a complete response outcome for periocular LA-BCC.维莫德吉治疗肿瘤反应的初始率,可以预测眼睑 LA-BCC 的完全缓解结果。
Eye (Lond). 2023 Feb;37(3):531-536. doi: 10.1038/s41433-022-01982-y. Epub 2022 Feb 24.
6
Machine learning for multi-omics data integration in cancer.用于癌症多组学数据整合的机器学习
iScience. 2022 Jan 22;25(2):103798. doi: 10.1016/j.isci.2022.103798. eCollection 2022 Feb 18.
7
H NMR-based metabolomics of skin squamous cell carcinoma and peri-tumoral region tissues.基于 1H-NMR 的皮肤鳞状细胞癌及癌周组织代谢组学研究。
J Pharm Biomed Anal. 2022 Apr 1;212:114643. doi: 10.1016/j.jpba.2022.114643. Epub 2022 Feb 4.
8
Artificial Intelligence-Based Approaches to Reflectance Confocal Microscopy Image Analysis in Dermatology.基于人工智能的皮肤科反射共聚焦显微镜图像分析方法
J Clin Med. 2022 Jan 14;11(2):429. doi: 10.3390/jcm11020429.
9
Multi-omics prediction in melanoma immunotherapy: A new brick in the wall.多组学预测黑色素瘤免疫治疗:新的进展。
Cancer Cell. 2022 Jan 10;40(1):14-16. doi: 10.1016/j.ccell.2021.12.008.
10
Multiomic profiling of checkpoint inhibitor-treated melanoma: Identifying predictors of response and resistance, and markers of biological discordance.检查点抑制剂治疗的黑色素瘤的多组学分析:确定反应和耐药的预测指标以及生物学不一致性的标志物。
Cancer Cell. 2022 Jan 10;40(1):88-102.e7. doi: 10.1016/j.ccell.2021.11.012. Epub 2021 Dec 23.