Abstract:
An important aspect of understanding cancer biology is to connect the diverse repertoire of genotype-to-phenotype displays in individual specimens and ultimately resolve disease course outcome through informative datasets. A focus of cancer genomics has strived to provide predictive capabilities using genomic information to further inform therapeutic strategies. The advent of single-cell sequencing and analysis now provides a route to decipher high-resolution genomic diversity in individual samples and facilitate detailed understanding of clonal evolution in clinical research settings. In addition to generating high-throughput single-cell genomic SNV and CNV data, this protocol describes a new analytical ability that adds a second dimension which provides for interrogation of surface protein marker expression. The first immediate application of this technology is quite suitable to heme cancer cell studies. This multimodal approach allows for correlation of diverse genomic signatures to key phenotypic biomarkers such as immunophenotypes in leukemic diseases.