Over time, cells accumulate DNA mutations, that if transcribed and translated influence gene expression and/or function of the protein. The increasing number mutations in eg. genes that control cell division eventually lead formation of tumor.

Over time, cells accumulate DNA mutations, that if transcribed and translated influence gene expression and/or function of the protein. The increasing number mutations in eg. genes that control cell division eventually lead formation of tumor. In a study published in Scientific reports (https://www.nature.com/articles/s41598-019-45934-1) researchers use the output of RNA-sequencing experiments to explore mutations and genetic differences between single cells. The analysis method developed can complement gene expression analysis as simultaneous analysis of both DNA and RNA in single cells is still in its infancy.

Scientists reveal genetic variation between tumors as well as within the same tumor through the analysis of more than 3500 single cells. Comparison of the mutation profiles of single cells from different tumors enables identification of unknown mutations related to cancer eg. variants common to all analyzed cancer cells in glioblastoma patients identified in major histocompatibility complex class I F, (https://www.proteinatlas.org/ENSG00000204642-HLA-F/pathology), solute carrier family 38 member 2 (https://www.proteinatlas.org/ENSG00000134294-SLC38A2/pathology) and tubulin folding cofactor D (Tubulin folding cofactor D). Analysis of the genetic variation within a tumor on the other hand identifies sub-populations of cells with varying levels of mutations, making it possible to discriminate between cells. In addition, the results show that lymph node metastases do not vary genetically to the same extent as the primary tumors they originate from.

The publication demonstrates the power and versatility of RNA-based variant analysis.

Link to publication

Cristina Al-Khalili Szigyarto