A main problem in the treatment of advanced cancers, including gastric cancers and glioblastoma, is the incertitude at which we predict how individual patients will respond to DNA-damaging agents, especially on the long run. Knowing the mechanism behind a patient's response, or the lack thereof, will help us depart from the oversimplified ?more-is-better? and ?one-size- fits-all? principles according to which DNA-damaging agents are administered. This will improve clinical outcome by allowing us to pinpoint those who would respond better and longer to lower doses of DNA-damaging agents, than to higher doses. Under the assumption that the success of DNA-damaging therapy increases with the proliferation rate of a relatively homogeneous tumor population, there was little reason to assume anything other than monotonic dose-response relations. But with the recent paradigm shift that most cancers are in fact DNA mosaic products of ongoing evolution, comes the urgency to reconsider these fundamental principles behind DNA-damaging therapy administration. As the developers of one of the first DNA deconvolution methods and with access to technologies to profile the transcriptomes of up to 10,000 cells simultaneously, we are equipped to embark on first personalized dose-finding strategies for DNA-damaging therapies. We will test the potential of the very long-term legacy that DNA-damage entails on a cell ? genomic instability ? as new biomarker of DNA- damage response. Our preliminary studies showed that, for most cancer types, DNA-damaging agents change a clone's genomic instability and that clones succumb to a limit in the amount of genomic instability they can tolerate. In particular, our results showed that patients with intermediate genomic instability have a very poor outcome and that this relation is only evident among treatment-nave patients, but not among patients treated with DNA-damaging agents. Further they show that we can measure genomic instability per clone and that clones with extreme genomic instability typically don't grow large. Our hypothesis that genomic instability, rather than proliferation rate, determines how sensitive a tumor is to DNA damaging agents on the long-term, is founded on two unexpected findings: (i) Patients with extremely high genomic instability per tumor clone have an exceptionally good outcome.
Aim 1 will integrate exome- and single cell RNA-seq data to characterize clones and to measure how much genomic instability they can tolerate. (ii) Low genomic instability is associated with reduced benefit from DNA-damaging agents.
Aim 2 will use comet assays and treatment history to quantify DNA damage per clone, relating it to the clones' ability to tolerate DNA damage and to changes in the genomic instability of therapy-surviving clones. This would be the first study to test the potential of genomic instability as biomarker of DNA-damage sensitivity. We will also use the clone specific transcriptomes and genomes from this cohort for a discovery study of candidate biomarkers of DNA- damage sensitivity. The first two years of this project will take place in Dr. Hanlee Ji's lab. After this K99 phase, having learned to model pharmakometric interactions between DNA-damaging agents and the diverse clones that coexist in a tumor, Dr. Andor will continue as an independent researcher. Having identified the threshold of genomic instability above which clones have reduced fitness, Dr. Andor will subject these clones to DNA-damaging agents to quantify dose-dependent changes in genomic instability and how a clone's proximity to the genomic instability threshold affects its therapeutic sensitivity (R00).
By measuring the proximity of tumor clones to the maximum genomic instability a cell can tolerate, we are developing one of the first models that base clinical decisions on the characterization of clones rather than tumor bulk. This project will evaluate the potential of this new biomarker to inform how intense DNA-damaging therapy must be in order to shift each clone beyond the tolerated genomic instability limit. This contribution will be significant because it could help guide clinical decisions on how to dose DNA-damaging agents and on whether or not DNA-damaging agents are an appropriate therapy option.
| Xia, Li Charlie; Ai, Dongmei; Lee, Hojoon et al. (2018) SVEngine: an efficient and versatile simulator of genome structural variations with features of cancer clonal evolution. Gigascience 7: |
| Andor, Noemi; Maley, Carlo C; Ji, Hanlee P (2017) Genomic Instability in Cancer: Teetering on the Limit of Tolerance. Cancer Res 77:2179-2185 |
