Drug discovery is an extensive process. Fundamentally, it requires a sophisticated understanding of the disease and of a drug’s effects. It is also crucial to leverage the optimal tools that can reveal how exactly a diseased tissue responds to therapy.
More and more, single-cell RNA sequencing is getting integrated into preclinical drug development protocols due to its capacity to characterize individual cells’ gene expression in response to drugs.
Dr. Emilie Crouchet is an early adopter of single-cell technology in translational research. She works in the lab of liver disease expert Prof. Thomas Baumert at the Institute of Viral and Hepatic Disease Research of INSERM, unit U1110, in Strasbourg, France. She’s responsible for developing the institute’s single-cell RNA-seq and spatial transcriptomic platform, working with SORT-seq technology and 10x Genomics solutions.
“Our main focus is liver disease,” Crouchet explains. “We work in close collaboration with a hospital, so we have the chance to have access to patient tissues. As our focus is liver disease, we are interested in tissue from patients with liver fibrosis, cirrhosis, or liver cancer.”
Their current goal is not to unearth the cell types present in a healthy or diseased liver, but to go one step further. “In fact, if you check in literature, you already have so many single-cell atlases of the liver and various diseased livers,” Crouchet says. “Rather, we aim to use single-cell technology to understand the mechanism of action of potent drugs: new drugs and approved drugs.”
Preventing liver cancer
One of their largest projects of the last few years resulted in the therapeutic discovery of a new drug candidate for liver cancer prevention. The team published their findings in Nature Communications in September 2021. That project kicked off with the idea that liver cancer treatment could be improved by finding a treatment for precancerous liver fibrosis.
Crouchet: “We know that liver fibrosis can lead to cancer development. Yet treatment for liver fibrosis doesn’t exist. There’s an approved treatment for liver cancer, but no method of chemoprevention. So, our overarching aim was to find a treatment for liver fibrosis to consequently prevent liver cancer. Hepatocellular carcinoma, to be precise.”
“We aim to use single-cell technology to understand the mechanism of action of potent drugs.”
Modeling liver disease
The team leveraged what is known as prognostic liver signature (PLS). PLS is a 186-gene expression signature that predicts the risk of liver fibrosis complication, cirrhosis, and cancer development. Texas-based liver expert Prof. Yujin Hoshida discovered the signature in patients and tested its predictive power in multiple patient cohorts and animal models over a period of fifteen years—proving its potential.
“The Hoshida lab wanted to apply PLS in a cell-based system,” Crouchet explains, because cell-based model systems lend themselves optimally to high-throughput drug screens. “As we are experts in model development for liver disease, they contacted us.”
In a couple of months, Crouchet and colleagues successfully cultured liver cells in which PLS could serve as a readout. The readout works like this: if a drug reverses a PLS poor-prognosis status to a good-prognosis status, it means that the drug could potentially halt liver disease progression.
“We then screened different molecules and identified nizatidine as a candidate chemopreventive agent,” Crouchet says.
Nizatidine as a drug already exists. It’s an antacid used to relieve an upset stomach. But its beneficial effects on the PLS-model were unanticipated. Crouchet: “This was totally new. And we discovered it with a new approach, not described before in literature.” In the following months, the team could validate nizatidine’s effectiveness in animal models and patient-derived 3D liver spheroids—to good effect.
Unraveling the mode and mechanism of action
Now that evidence was accumulating that nizatidine worked, the question remained: how does it work?
Before researchers can take a potential therapeutic into the human test phase of a clinical trial, pharmaceutical regimens demand that drug developers unravel its mode and mechanism of action. Via what chemical interactions does the compound act? What cells does it target? And how does it create its therapeutic effect in an organism?
“Before we give a drug to the patient, we have to know how it works,” Crouchet explains. “You need to present the full story.”
After a number of functional experiments, the team found that nizatidine inhibits the HRH2 signaling pathway in liver cells. This pathway is implicated in cell survival, growth, and inflammation—and is often overexpressed in liver cancer. By partly blocking HRH2 signaling, nizatidine seemed to reverse a PLS poor-prognosis signature, halt liver disease progression and restore normal liver function. But liver cells weren’t the only cell types that could be involved in nizatidine’s mode of action.
Increasingly, scientists are finding out that the recruitment of inflammatory immune cells is a force that drives liver fibrosis and cancer, Crouchet explains. HRH2 is a receptor of histamine, an important communicator in immune regulation. It prompted the team to investigate how the immune system responded to nizatidine treatment. “Our aim became to discover the type of immune cells that are targeted by nizatidine,” Crouchet explains, “and to examine how nizatidine affects these cells.” To achieve this, the team’s attention turned to single-cell RNA sequencing.
Identifying drug targets
For characterizing how a tissue responds to treatment, single-cell RNA sequencing is getting more and more attention as a go-to technology. “I went to a congress about liver disease,” Crouchet recounts. “90% of the talks contain single-cell data or spatial transcriptomics data.”
In prior research, the team had generated a single-cell atlas of healthy human liver. That came in useful. The atlas revealed that HRH2 expression was high in a small group of pro-inflammatory liver macrophages. This marked the cells as potential nizatidine targets. But whether the chemopreventive effect of nizatidine went by these cells had to be investigated with experiments on diseased liver.
Moving forward, the team figured out how to culture white blood cells from patient livers and treat the cells with or without nizatidine to compare the results. Then, to study the effects of nizatidine on the cells, they performed single-cell RNA sequencing.
Finding the right technology
“Because we were interested in analyzing a broad, gene-level response that could also involve lowly expressed genes, we wanted something very deep in terms of sequencing,” Crouchet explains. “And because we had this focus on white blood cells, we did not have a big number of cells to sequence.”
“I checked on the websites of different companies,” she continues. “Who is able to help me answer my question? Advice via your website is easy to find, and I quickly got in touch and had a video meeting within one week. It was very fast. With your advice, we decided to use SORT-seq for this specific scientific question.”
SORT-seq is a flexible single-cell RNA sequencing technology based on 384-well plates. It’s adaptable to most cell types, accommodating for low-input samples, and compatible with high sequencing depth. Its alignment with FACS sorting also enables researchers to focus on specific populations of interest. “That we could enrich for the white blood cells from patient liver samples by FACS-sorting was a big plus for our research,” Crouchet says.
“From the moment that we started the collaboration, we managed to have very good communication with Single Cell Discoveries, also on the data analysis,” Crouchet continues,
“What sometimes happens with other companies is that they will deliver data without explanation or something like that. Not here. That made the collaboration very easy for us.”
Revealing the mode of action
The SORT-seq data verified that the subgroup of cells that responded highly to nizatidine treatment consisted of pro-inflammatory liver macrophages. Nizatidine, the data showed, suppressed signaling pathways in these cells that could normally boost inflammation and speed up liver fibrosis. In response to nizatidine, the macrophages appeared to show some immunoregulatory action.
Crouchet: “We could conclude that the nizatidine treatment is reprogramming the liver macrophages.” This suggests that next to its effect on liver cells, nizatidine’s mode of action lies in reversing macrophage-powered liver fibrosis.
Advancing to clinical trials
With the publication of this research in Nature Communications also came the possibility to advance nizatidine to clinical trials. “Yes, good news!” says Crouchet, “We’re now working on the grant application for the clinical trial. We’ve designed all the clinical trials, we know which kind of patient at which disease stage we need to include, and we have all the teams. So, we know everything at the moment and are, as soon as possible, ready to start the clinical trial on nizatidine for chemoprevention.”
We will find out soon whether the clinical trial extends nizatidine’s preclinical success.
Incorporating single-cell into drug development
Meanwhile, the lab continues applying the same technologies on other projects. Crouchet: “We have another project in the lab where we also discovered new molecules for liver fibrosis and cancer.”
“It’s now in clinics. Again, before all these steps and before going into patients, we had to again show the mechanism of action. Again, we could use single-cell RNA sequencing to understand how the molecule works.”
“We’re also developing this technology further—for our lab and for collaborators. For example, with a team in Germany that focuses on pancreatic cancer, we use exactly the same technologies: 3D culturing of patient tissues, followed by drug treatment experiments, then single-cell technology to understand the drugs’ mechanisms of action.”
Read the full article here.
The image in the header is a scanning electron micrograph of a macrophage. Credit: NIAID, CC-BY 2.0.
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