Abstracts 2018

ABSTRACT: FULL-STACK SINGLE-CELL TRANSCRIPTOMICS PROVIDES A DEEPER UNDERSTANDING OF CANCER METASTASIS

We would like to present the abstract of our keynote speaker –  Juozas Nainys – PhD student, who is pursuing his degree in single-cell transcriptomics field at Vilnius university Life sciences center.

Single cell transcriptomics is a novel and rapidly developing field. It is fast becoming clear that single cell technologies are powerful methods for detailed gene expression analyses, new cell type identification as well as mapping complex cell populations. Recently described high-throughput microfluidic protocols for single cell transcriptomics have substantially reduced labour and reagent costs which makes it possible to analyse tens of thousands of single cells. 

Here we have applied droplet microfluidic based scRNAseq technology to gain deeper understanding of cancer metastasis. Epithelial to mesenchymal transition (EMT) is an important process in cancer metastasis. During EMT cells gradually transition through various intermediate states. It is thought that cancer stem cell may be formed during EMT. To thoroughly analyse this process, we have profiled over 20,000 single cells during 12 days of EMT. To gain more insight into this multidimensional dataset we have developed a novel algorithm called MAGIC (Markov Affinity-based Graph Imputation of Cells). This algorithm uses data diffusion to impute missing values and recover gene networks within single cells. To validate our algorithm, we have performed an independent biological perturbation. We have additionally profiled over 10,000 single cells under Zeb1transcription factoroverexpression. Results provide validation for the MAGIC algorithm as well asthe formed hypothesis.

Work described here reveals the power and utility of high throughput single-cell analyses. New generation microfluidic platform together with the novel algorithms allow for unbiased analyses of intricate gene networks within single-cells.