Year: 2017
Type: review
Abstract: It has become increasingly clear that both normal and cancer tissues are composed of heterogeneous populations. Genetic variation can be attributed to the downstream effects of inherited mutations, environmental factors, or inaccurately resolved errors in transcription and replication. When lesions occur in regions that confer a proliferative advantage, it can support clonal expansion, subclonal variation, and neoplastic progression. In this manner, the complex heterogeneous microenvironment of a tumour promotes the likelihood of angiogenesis and metastasis. Recent advances in next-generation sequencing and computational biology have utilized single-cell applications to build deep profiles of individual cells that are otherwise masked in bulk profiling. In addition, the development of new techniques for combining single-cell multi-omic strategies is providing a more precise understanding of factors contributing to cellular identity, function, and growth. Continuing advancements in single-cell technology and computational deconvolution of data will be critical for reconstructing patient specific intra-tumour features and developing more personalized cancer treatments.
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $3,470
Funders: National Institutes of Health, National Institute of General Medical Sciences, National Institute of Environmental Health Sciences, National Institute of Child Health and Human Development, U.S. National Library of Medicine, Eunice Kennedy Shriver National Institute of Child Health and Human Development
Awards: G2711154378, An Integrative Omics Approach to Identify Biomarkers Related to Preeclampsia and Breast Cancer Risks, G3701958466, G4011466185, Institute for Biogenesis Research: COBRE, G4681754827, An Integrative Bioinformatics Approach to Study Single Cancer Cell Heterogeneity, G8604317771, Cancer precision medicine through spatially informative single cell image and transcriptomics data analysis, G9000203449
OpenAlex ID: W2775981375
