Chenlu Zhang, Nan Li, Pengxia Zhang, Zhimei Jiang, Yichao Cheng, Huiqing Li, Zhenfei Pang
{"title":"通过多组学技术推进乳腺癌的精准和个性化治疗。","authors":"Chenlu Zhang, Nan Li, Pengxia Zhang, Zhimei Jiang, Yichao Cheng, Huiqing Li, Zhenfei Pang","doi":"10.62347/MWNZ5609","DOIUrl":null,"url":null,"abstract":"<p><p>Breast cancer is the most common malignant tumour in women, with more than 685,000 women dying of breast cancer each year. The heterogeneity of breast cancer complicates both treatment and diagnosis. Traditional methods based on histopathology and hormone receptor status are now no longer sufficient. Recently, advances in multi-omics techniques, including genomic, proteomic, and transcriptomic analyses, have deepened our understanding of breast cancer. Combining these approaches allows for precise molecular subtyping, which is essential for the detection of key mutations, protein interactions and gene expression patterns that are highly relevant to different therapeutic strategies. Genomic analyses have been effectively identifying key mutations in cancer. Meanwhile, proteomics and transcriptomics complement by identifying new therapeutic targets and elucidating gene expression dynamics. Integrating multi-omics and conventional diagnostics improves tumour characterisation and enables prognostic accuracy comparable to established standards and treatment response. Existing and emerging technologies enable real-time enhanced tumour follow-up and data analysis through liquid biopsy and artificial intelligence, respectively. Despite these clinical implementation challenges, multi-omics including clinical phenotyping offers significant potential for precision breast cancer treatment. This article describes recent advances in molecular subtyping and multi-omics technologies that are driving key innovations to optimise patient outcomes and further develop personalised medicine in the context of breast cancer care.</p>","PeriodicalId":7437,"journal":{"name":"American journal of cancer research","volume":"14 12","pages":"5614-5627"},"PeriodicalIF":3.6000,"publicationDate":"2024-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11711544/pdf/","citationCount":"0","resultStr":"{\"title\":\"Advancing precision and personalized breast cancer treatment through multi-omics technologies.\",\"authors\":\"Chenlu Zhang, Nan Li, Pengxia Zhang, Zhimei Jiang, Yichao Cheng, Huiqing Li, Zhenfei Pang\",\"doi\":\"10.62347/MWNZ5609\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Breast cancer is the most common malignant tumour in women, with more than 685,000 women dying of breast cancer each year. The heterogeneity of breast cancer complicates both treatment and diagnosis. Traditional methods based on histopathology and hormone receptor status are now no longer sufficient. Recently, advances in multi-omics techniques, including genomic, proteomic, and transcriptomic analyses, have deepened our understanding of breast cancer. Combining these approaches allows for precise molecular subtyping, which is essential for the detection of key mutations, protein interactions and gene expression patterns that are highly relevant to different therapeutic strategies. Genomic analyses have been effectively identifying key mutations in cancer. Meanwhile, proteomics and transcriptomics complement by identifying new therapeutic targets and elucidating gene expression dynamics. Integrating multi-omics and conventional diagnostics improves tumour characterisation and enables prognostic accuracy comparable to established standards and treatment response. Existing and emerging technologies enable real-time enhanced tumour follow-up and data analysis through liquid biopsy and artificial intelligence, respectively. Despite these clinical implementation challenges, multi-omics including clinical phenotyping offers significant potential for precision breast cancer treatment. This article describes recent advances in molecular subtyping and multi-omics technologies that are driving key innovations to optimise patient outcomes and further develop personalised medicine in the context of breast cancer care.</p>\",\"PeriodicalId\":7437,\"journal\":{\"name\":\"American journal of cancer research\",\"volume\":\"14 12\",\"pages\":\"5614-5627\"},\"PeriodicalIF\":3.6000,\"publicationDate\":\"2024-12-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11711544/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"American journal of cancer research\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.62347/MWNZ5609\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q2\",\"JCRName\":\"ONCOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"American journal of cancer research","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.62347/MWNZ5609","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"ONCOLOGY","Score":null,"Total":0}
Advancing precision and personalized breast cancer treatment through multi-omics technologies.
Breast cancer is the most common malignant tumour in women, with more than 685,000 women dying of breast cancer each year. The heterogeneity of breast cancer complicates both treatment and diagnosis. Traditional methods based on histopathology and hormone receptor status are now no longer sufficient. Recently, advances in multi-omics techniques, including genomic, proteomic, and transcriptomic analyses, have deepened our understanding of breast cancer. Combining these approaches allows for precise molecular subtyping, which is essential for the detection of key mutations, protein interactions and gene expression patterns that are highly relevant to different therapeutic strategies. Genomic analyses have been effectively identifying key mutations in cancer. Meanwhile, proteomics and transcriptomics complement by identifying new therapeutic targets and elucidating gene expression dynamics. Integrating multi-omics and conventional diagnostics improves tumour characterisation and enables prognostic accuracy comparable to established standards and treatment response. Existing and emerging technologies enable real-time enhanced tumour follow-up and data analysis through liquid biopsy and artificial intelligence, respectively. Despite these clinical implementation challenges, multi-omics including clinical phenotyping offers significant potential for precision breast cancer treatment. This article describes recent advances in molecular subtyping and multi-omics technologies that are driving key innovations to optimise patient outcomes and further develop personalised medicine in the context of breast cancer care.
期刊介绍:
The American Journal of Cancer Research (AJCR) (ISSN 2156-6976), is an independent open access, online only journal to facilitate rapid dissemination of novel discoveries in basic science and treatment of cancer. It was founded by a group of scientists for cancer research and clinical academic oncologists from around the world, who are devoted to the promotion and advancement of our understanding of the cancer and its treatment. The scope of AJCR is intended to encompass that of multi-disciplinary researchers from any scientific discipline where the primary focus of the research is to increase and integrate knowledge about etiology and molecular mechanisms of carcinogenesis with the ultimate aim of advancing the cure and prevention of this increasingly devastating disease. To achieve these aims AJCR will publish review articles, original articles and new techniques in cancer research and therapy. It will also publish hypothesis, case reports and letter to the editor. Unlike most other open access online journals, AJCR will keep most of the traditional features of paper print that we are all familiar with, such as continuous volume, issue numbers, as well as continuous page numbers to retain our comfortable familiarity towards an academic journal.