Dr. Nicholas E. Navin

I'm Nick Navin, and I'm a professor at MD Anderson Cancer Center. And I work on single-cell genomics and studying cancer evolution. We develop technologies to study single cells and cancer, and then we compare individual cells to understand how cancer progresses and cancer evolution. And we're trying to understand, is that diversity important for things like therapeutic resistance, metastasis, progression from preinvasive cancers to invasive cancers, and other topics in cancer research. My lecture here at AACR will be studying DCIS breast cancer, which is the most early form of breast cancer that's routinely diagnosed through mammography. And the big clinical question is which DCIS cancers will progress to invasive cancers, and what are the genomic events associated with that progression? And so we developed some new single-cell technologies that allow you to profile FFPE archival material, which are typically very difficult to work with with single-cell genomics. And we have a nanowell-based platform that can analyze cells and do that in a high throughput way so that we can look at DCIS breast cancers and then the cancers that occur years, to even decades later, to form the invasive disease, which is really the problem for most patients. And so, we can generate large-scale data sets, compute clonal lineages, and understand the genomic events associated with progression. In this study that I'll present tomorrow, we're looking for specific chromosomal aberrations, copy number aberrations, genes that are amplified or lost or gained, and trying to understand which subclones harbor those events, and how are they able to remain dormant for years to decades before they re-emerge and reconstitute a large tumor mass that in some cases might metastasize and kill a patient. So, we're looking for specific genes that... or detect the specific genes associated with those events. This project was an international collaboration through the Cancer Grand Challenge, and we work with a laboratory at the Netherlands Cancer Institute, laboratories in the UK, Duke University here in the U.S., and several investigators at MD Anderson Cancer Center. So, it's really a team science effort, this project. We develop a lot of our own technologies, especially for single-cell DNA sequencing. We also perform a lot of single-cell RNA sequencing, and so for that, we work with companies like 10x Genomics, Mission Bio, and others. A lot of spatial platforms: Resolve Biosciences, Vizgen and others. And so, we both develop new technologies, and we use existing technologies to study problems in cancer evolution and around the tumor microenvironment. We have three separate computational tools that we're reporting here at AACR. The first one is called CopyKAT. And so that method allows you to infer copy number profiles from single-cell RNA data and then look at subclones within the tumor mass. Another method is called CopyKit, which sounds familiar, but it's kit, not kat. And so, with that tool, it's an end-to-end analysis tool for single-cell copy number data, single-cell DNA data, and we can also use that to infer clinical substructure in tumors, reconstruct evolutionary lineages, and really understand how tumors progress at the copy number level. And then, finally, another tool is called CellTrek. And this is a computational method that allows you to take spatial data and single-cell RNA data and integrate them so that you can understand how single cells are distributed across histopathological sections of tumor tissues. Within, kind of, breast cancer and technology development, there are two areas that are really interesting in terms of single-cell genomics. One is, how do you do multi-omics in single cells? So, from the same cell, how do you measure DNA, RNA, and other information like proteins? And that allows you to connect, really, the genotype and the phenotype together so that you can understand how mutations result in aberrant phenotypes in cancer. And the other area is really around spatial technologies and being able to marry, kind of, the histopathology and the images of cancer with genomic and quantitative traits. And there's been a lot of progress in, kind of, RNA modalities, but there's still not a lot around epigenetics and DNA alterations. So that's another kind of technology area that we're really interested in working on.