Researchers have recently developed an in vitro model that can distinguish between the genetic, epigenetic and stochastic factors underlying tumour heterogeneity.
Tumour heterogeneity is a major obstacle in cancer therapy. Heterogenous tumours are comprised of multiple different cancer cell types, each responding variably to drug treatments. As a result, they are difficult to treat and may even acquire drug resistance.
Tumour heterogeneity has long been considered to arise primarily from genetic mutations in cancer cells within and between tumours. Increasingly, researchers recognise two additional, non-genetic sources of variability. Epigenetic heterogeneity is heritable and results in changes to gene expression without changes to the genome sequence. Meanwhile, stochastic heterogeneity is not heritable and arises from random intrinsic and extrinsic noise. These include gene expression noise, asymmetric cell division and environmental fluctuations.
Researchers have previously proposed a framework to distinguish the three factors underlying tumour heterogeneity. However, this is not widely accepted within the cancer research community due to the lack of strong experimental evidence.
Genetic cancer heterogeneity
Recently, a team of researchers led by Vanderbilt University School of Medicine used experimental and computational modelling techniques to resolve different sources of tumour variability. Their study is published in PLOS Biology.
The researchers used 3 different versions of CL9 as an in vitro model for non-small cell lung cancer (NSCLC). The different cell line versions exhibited drastically different responses to the same drug treatment.
As expected, whole-exome sequencing and copy number variant detection identified significant mutational differences between cell line versions. scRNA-seq also identified gene expression differences between them. In the different cell line versions, the researchers further observed a strong correlation between genome mutations and gene expression. This suggests that genetic distinction underlies transcriptomic differences and drug response in cell line versions.
A framework for tumour heterogeneity
Clonal sublines, derived from one parental CL9 line, also displayed a range of sensitivities to the same treatment. Compared to cell line versions, there was little to no association between genomic and transcriptomic states in the sublines. This suggests that epigenetic differences, rather than genetic differences, underlie variable drug response in sublines.
Clonal drug response assays and stochastic simulations on a birth-death model of cell proliferation supported this finding. These suggest that intrinsic randomness in cell fate decisions may influence the epigenetic state of different sublines. Ultimately, this explains the observed variability in drug response.
By combining experimental and computational modelling, this study supports a framework to differentiate between the sources of tumour heterogeneity. The ability to distinguish between genetic, epigenetic and also stochastic factors underlying tumour variability carries great therapeutic potential. The authors of the paper expressed:
“Looking forward, one can envision future cancer treatment regimens involving genetic profiling of a tumor to identify dominant genetic states, followed by characterisation of the associated epigenetic landscapes using single-cell experimentation and computational modelling. Large-scale in vitro and in silico drug screens could then be performed to devise personalised treatments for patients that can be tested in vivo before being administered clinically.”
Image credit: kjpargeter – Freepik
