February 23, 2023

Predicting Subclonal Drug Response from Single-cell Sequencing for Precision Oncology

1st Joint SDSC Call, Data-Intensive Research

Short Summary

Cancer happens when cells grow out of control and develop different genetic changes, which can make them respond unevenly to treatment and harder to cure. By analysing the genes and drug responses of 136 cancer samples, this project aims to predict which treatments will work best for all the different cells within a tumour.

Goals

Effective treatment must work for all the different cells in a cancer. With this project with the SDSC, we wish to be able to better predict which treatments may be effective. We have profiled the gene mutations and genetic activity in 136 cancer samples. We have also measured how cells from these cancer samples respond to a range of drugs. By combining these measurements, we aim to predict the drug response for each cancer cell population.

Significance

This integrative approach could then provide ways to design effective treatments for all cells in a cancer.

Background

Cancer is a disease where cells in the body divide uncontrollably. It is
the second-leading cause of death worldwide. As cancers develop, the
genetic information stored in the cells’ DNA mutates, which can allow
the cancer to proliferate further. Different cells within a cancer may
accumulate different mutations and behaviours. As a consequence,
individual cells within a cancer may respond differently to drug
treatment. As such, cancer cell heterogeneity can make treatment
more difficult and lead to treatment failure.