- Prof. Jinhua Wang
- Cancer Bioinformatics, Masonic Cancer Center, University of Minnesota, Minneapolis, Minnesota, USA
Special Issue Introduction
Human tumors are complicated ecosystems with diverse cells including malignant, immune, stromal and many other rare subtypes. In the past decade, high-throughput assays on bulk tumor tissues have produced much of the knowledge and shaped our understanding of cancer in patients, but less was done at single cell level to characterize the various cell types, the intra-tumor heterogeneity and the cellular dynamics of tumor evolution and response to treatment.
Single cell genomic techniques and data driven computational methods provide possible solutions capable of overcoming the difficulties inherently associated with bulk tissue analysis. Rare cell types can be identified; gene expression patterns can be assigned to specific cell sub-populations; and cellular spatial and temporal relations can be revealed.
In this issue, we will discuss some of the common themes emerging from single-cell RNA sequencing in different cancer types, review current methodologies, discuss potential applications in cancer biology for which emerging single-cell genomics methods may provide a promising approach.
The special issue should cover the following topics:
1) scRNA for various cancer types, breast, prostate, lung, liver, ovarian, melanoma, colon, leukemia, etc..
2) Analytical methodologies for scRNA-seq data sets, cellular level analysis: cell type annotation, heterogeneity analysis, special / temporal projection
3) Molecular level analysis : copy number variation deduced from scRNAseq, mRNA velocity, splicing analysis, mutation call
4) scRNAseq with clinical outcome prediction, or association, potential clinical applications etc..
KeywordsSingle-Cell RNA Sequencing, Cancer
Submission Deadline30 Jun 2020