Journal Article

Clonal transcriptomics identifies mechanisms of chemoresistance and empowers rational design of combination therapies

Cannell, Ian G, Kania, Katarzyna, Nicholls, Ashley, Sawicka, Kirsty, Bressan, Dario, Wild, Sophia A, Hannon, Gregory J

2022

Overview

Tumour heterogeneity is thought to be a major barrier to successful cancer treatment due to the presence of drug resistant clonal lineages. However, identifying the characteristics of such lineages that underpin resistance to therapy has remained challenging. Here, we utilise clonal transcriptomics with WILD-seq; W holistic I nterrogation of L ineage D ynamics by seq uencing, in mouse models of triple-negative breast cancer (TNBC) to understand response and resistance to therapy, including BET bromodomain inhibition and taxane-based chemotherapy. These analyses revealed oxidative stress protection by NRF2 as a major mechanism of taxane resistance and led to the discovery that our tumour models are collaterally sensitive to asparagine deprivation therapy using the clinical stage drug L-asparaginase after frontline treatment with docetaxel. In summary, clonal transcriptomics with WILD-seq identifies mechanisms of resistance to chemotherapy that are also operative in patients and pin points asparagine bioavailability as a druggable vulnerability of taxane-resistant lineages. Cancer begins when a cell multiplies again and again to form a tumour. By the time that tumour measures a centimetre across, it can contain upwards of a hundred million cells. And even though they all came from the same ancestor, they are far from identical. The tumour's family tree has many branches, and each one responds differently to treatment. If some are susceptible to a drug the cells die, the tumour shrinks, and the therapy will appear to be successful. But, if even a small number of cancer cells survive, they will regrow, often more persistently, causing a relapse. Identifying resistant cells, their characteristics, and how to kill them has been challenging due to a lack of good animal models. One way to keep track of a cancer family tree is to insert so-called genetic barcodes into the ancestral cells. As the tumour grows, the cells will pass the barcodes to their descendants. Scientists do this by using viruses that naturally paste their genes into the cells they infect. Applying this technique to an animal model of cancer could reveal which genes allow some cells to survive, and how to overcome them. Wild, Cannell et al. developed a genetic barcoding system called WILD-seq and used it to track all the cells in a mouse tumour. The mice received the same drugs used to treat patients with breast cancer. By scanning the genetic barcodes using recently developed single cell sequencing technologies, Wild, Cannell et al. were able to identify and count each type of cancer cell and work out which genes they were using. This revealed which cells the standard treatment could not kill and exposed their genetic weaknesses. Wild, Cannell et al. used this information to target the cells with a drug currently used to treat leukaemia. The drug identified by this new genetic barcoding approach is already licensed for use in humans. Further investigation could reveal whether it might help to shrink breast tumours that do not respond to standard therapy. Similar experiments could uncover more information about how other types of tumour evolve too.

• Publisher: eLife Sciences Publications Ltd,eLife Sciences Publications, Ltd
• Subject: Animal models / Animals / Asparaginase / Asparagine / Bioavailability / Breast cancer / Cancer Biology / cancer therapy / Chemoresistance / Chemotherapy / Chromosomes and Gene Expression / Cloning / Combination therapy / Design / Drug resistance / Drug Resistance, Neoplasm - genetics / Error correction & detection / Experiments / Gene expression / Humans / L-asparaginase / lineage tracing / Mice / Nuclear Proteins / Oxidative stress / Principal components analysis / single cell genomics / Taxanes / Taxoids - pharmacology / Taxoids - therapeutic use / Transcription Factors / Transcriptome / Transcriptomics / Triple Negative Breast Neoplasms - pathology / tumor heterogeneity / Tumors