NEW YORK – The use of CRISPR screens in cancer research is on the rise as investigators learn to use the technology to efficiently interrogate the genome to search for new druggable targets.
During the second virtual session of the American Association for Cancer Research's annual meeting on Monday, University of California, San Francisco researcher Alex Marson and Stanford University's Michael Bassik described the ways they're each using CRISPR as a tool to advance their research of how cancer behaves and how it can be treated.
In his talk, Marson discussed his use of CRISPR to understand how T cells and other immune cells work in the presence of cancer, and how to reprogram them in order to use them to treat cancer and other diseases. His group is working on a strategy to use CRISPR to knock useful genes into and out of immune cells in order to find new treatment targets. The researchers were able to characterize a small set of genes that made immune cells better at proliferating and killing cancer cells when they were knocked out.
In a session on high-throughput screening technology, Bassik discussed his group's use of CRISPR to create 3D models of cancer in a scalable and efficient way. The researchers used CRISPR to knock out genes in lung cancer 2D models and compared them to the 3D models they'd created, finding that the 3D model was better able to recapitulate relevant phenotypes in a mouse xenograft model. They also discovered a novel gene that they believe is important for the growth of lung cancer tumors.
As he kicked off his presentation, Marson noted that medicine is moving beyond small molecules and other biologics to treat disease, and is moving into genetically modified human cells with new properties, which are emerging as a new class of treatment for cancer and other diseases. This is already happening in the clinic with CAR T cells, which are basically human T cells taken out of a person's circulation, modified outside of the body with clinical grade viruses, and then reinfused into patients to treat certain cancers.
Although the US Food and Drug Administration has approved two different CAR T cell treatments in the past few years, Marson said, this class of drugs has certain limitations: they only work for hematological cancers, but not solid tumors, and they're also very expensive because of complications in manufacturing the cells and the viruses that are needed for the modifications. Further, Marson said, the viruses themselves can be imprecise — they insert transgenes into non-target sites in the genome.
CRISPR, however, offers more flexibility and precision, especially as researchers learn more about how to efficiently insert pieces of DNA into the genome through the process of homology-directed repair (HDR) in order to reprogram functional properties of the cell. In January, Marson and his colleagues published a study in Nature Biotechnology in which they described a new delivery strategy to get a CRISPR editing complex into cells that enhanced HDR efficiency approximately two- to fourfold, and yielded approximately two to six times as many viable edited cells across multiple genomic loci in diverse cell types, including various types of T cells.
This type of system can be used to test T cell function for target discovery, and to change the cells' functions as well, Marson said.
In solid tumor cancers, the tumors suppress T cell functions in the body, and there are metabolites in the tumor microenvironment, such as adenosine, that further limit the function of T cells. Using the CRISPR system they'd developed, Marson and his colleagues set up an experiment to systematically knock out one gene at a time in T cells to see if there was one particular knockout that could make the cells most effective to kill cancer cells.
Specifically, they wanted to see if they could make the cells more proliferative when they were restimulated by knocking out certain genes. There are an enormous number of genes that hinder cell division when knocked out, Marson said. And indeed, the researcher found that many genes were essential for making cells divide properly. But they also found a less well-characterized set of genes that enhanced cell division when they were knocked out.
The researchers created T cell lines that had these specific genes knocked out in various combinations, mixed them with cancer cells, and found that one particular cell line with four genes knocked out was the best at killing cancer cells in vitro.
However, they also wanted to make the T cells proliferate more, even in a challenging tumor microenvironment, such as in the presence of a metabolite like adenosine. So, they ran the same experiment again and found two genes that stood out in the presence of adenosine. While this showed that the biological discovery was working, Marson said, the team also discovered a novel gene that has never been connected to the adenosine immunosuppressive signals in T cells — FAM105A.
Most recently, the researchers published a study in Cell describing their efforts to use CRISPR to perform pooled knock-in screening in primary human T cells, in order to test which knock-in gene constructs most potently enhance primary cell functions in vivo in a high-throughput manner. In that paper, pooled knock-in of dozens of unique barcoded templates into the T cell receptor-locus revealed gene constructs that enhanced fitness in vitro and in vivo, the researchers said.
All of this also has implications for the rapid manufacturing of treatments, Marson noted. Combining non-viral forms of CRISPR engineering for the modification of human cells and the use of CRISPR for target discovery in T cells can help create treatments that circumvent some of the challenges that are currently seen with treatments such as CAR Ts, but still provide the same benefits.
Developing Improved Cancer Models
In his talk, Bassik highlighted the benefits of using CRISPR to create next-generation models of cancer that are more accurate, and also have the potential to aid in target discovery.
The central problem in cancer therapy is the need for scalable strategies to find drug targets, he said. Though cancer genome sequencing has revealed many mutations, there are still relatively few driver mutations that have been associated with various cancer types. Bassik and his colleagues have been using CRISPR screens to functionally annotate driver candidates to find possible therapeutic targets and tumor suppressors.
He noted that, in general, he and his colleagues have found that fewer than 1 percent of genes have a positive effect on tumor growth when deleted from the genome. But most of these screens were conducted on 2D monolayer models, so they tried to develop a strategy to conduct these CRISPR screens in 3D spheroids.
Spheroids, organoids, and xenografts have always been found to be more accurate in terms of modeling cancer, but they're more expensive and time-consuming to create, so they're not scalable, Bassik said. However, one of his colleagues devised an efficient strategy to build 3D spheroids using CRISPR, and the team developed a KRAS-driven model of lung cancer model in order to test it.
In the 2D screens, the vast majority of the genes had a negative effect on tumor growth when deleted, Bassik explained. But in the 3D model, the vast majority of those same genes had a positive effect on growth when they were deleted. The most striking thing was that when the researchers looked at which genes had this differential effect, the tumor suppressor genes had a more positive effect when deleted in the 3D model.
Indeed, the researchers published a study in Nature in March noting that the CRISPR phenotypes in 3D more accurately recapitulated those of in vivo tumors, and genes with differential sensitivities between 2D and 3D conditions were highly enriched for genes that are mutated in lung cancers. Their analyses also revealed drivers that are essential for cancer growth in 3D and in vivo, but not in 2D.
When the team took the batch library from all their hits and conducted screens in 2D, 3D spheroids, and xenograft mouse models, they found that the 3D model better recapitulated relevant cancer phenotypes in the xenografts than the 2D models, Bassik said.
One particular pathway, carboxypeptidase D (CPD) stood out to the researchers as particularly important for tumor growth when it was knocked out in the 3D spheroid models, he added. Importantly, this gene was differentially expressed in the 2D model, and so would have been overlooked in conventional cancer modelling.
CPD expression correlates with patient outcomes in patients with lung cancer, and loss of CPD reduced tumor growth. Importantly, Bassik added, it exhibited a strong synergy with KRAS inhibition. When the researchers investigated further, they found that CPD knockout prevented tumor growth in a mouse model of cancer, and that low CPD expression predicted better patient survival in lung cancer patients. This could lead to a treatment strategy for KRAS-driven lung cancer, Bassik said.