Single-cell sequencing in ovarian cancer: a new frontier in precision medicine
| Autor: | Zenas Chang, Jinhua Wang, Timothy K. Starr, Boris Winterhoff, Shobhana Talukdar |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Treatment response
Cell Separation Computational biology Carcinoma Ovarian Epithelial 03 medical and health sciences 0302 clinical medicine Biomarkers Tumor medicine Carcinoma Humans Precision Medicine Treatment resistance 030219 obstetrics & reproductive medicine business.industry Genetic heterogeneity Gene Expression Profiling High-Throughput Nucleotide Sequencing Obstetrics and Gynecology Sequence Analysis DNA Neoplastic Cells Circulating medicine.disease Precision medicine Gene expression profiling Single cell sequencing 030220 oncology & carcinogenesis Female Single-Cell Analysis Ovarian cancer business |
| Zdroj: | Current Opinion in Obstetrics & Gynecology. 31:49-55 |
| ISSN: | 1473-656X 1040-872X |
| Popis: | Purpose of review This article discusses the advances, applications and challenges of using single-cell RNA sequencing data in guiding treatment decisions for ovarian cancer. Recent findings Genetic heterogeneity is a hallmark of ovarian cancer biology and underlies treatment resistance. Defining the different cell types present within a single ovarian cancer is difficult, but could ultimately lead to improvements in diagnosis and treatment. Next-generation sequencing technologies have rapidly increased our understanding of the molecular landscape of epithelial ovarian cancers, but the majority of these studies are conducted on bulk samples, resulting in data that represents an 'average' of all cells present. Single-cell sequencing provides a means to characterize heterogeneity with a tumor tissue in ovarian cancer patients and opens up opportunity to determine key molecular properties that influence clinical outcomes, including prognosis and treatment response. Summary Single-cell sequencing provides a powerful tool in improving our understanding of tumor cell heterogeneity for the purpose of informing personalized cancer treatment. |
| Databáze: | OpenAIRE |
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