Next-generation sequencing techniques to determine an individual’s unique genetic code gave rise to personalized treatments. Single-cell sequencing is the next step towards making precision medicine more accurate.
Each cell in our body is unique. Even genetically identical cells can behave differently in response to a certain treatment. With next-generation sequencing, scientists can study how the average cell within a group behaves. However, this can lead to erroneous conclusions.
“It is like population surveys, which tell us the average American family has 1.2 children. That’s useless. That’s not helpful. Not a single family has 1.2 children,” stated Christoph Lengauer, CEO of Celsius Therapeutics, a company that develops precision therapies using machine learning.
“Single-cell sequencing, by contrast, can indicate which family has six children, and which has just one and a dog,” Lengauer said. “It’s orders of magnitude more granular.”
In recent years, there has been a shift in the technology available to perform single-cell sequencing. The global company Fluidigm used to hold the bulk of the market, with products across the entire workflow but has started to face competition from multiple smaller firms.
At the forefront is US-based 10X Genomics. Its sequencing platform allows large populations of cells to be separated and analyzed with high resolution. The company is also developing a technology to study how cells are positioned in 3D, which could be used to see how tumors grow and expand.
Another contender is an alliance between two giants, Bio-Rad Laboratories and Illumina, which developed a single-cell sequencing solution that streamlines the whole workflow. Mission Bio, a spin-off from the University of California San Francisco is selling a single-cell sequencing platform that targets clinical applications with a lower price per run compared to its competitors.
Applications of single-cell sequencing
The use of single-cell sequencing used to be limited to a narrow circle. Over the past years, however, academic facilities such as the Institute Curie in Paris have started providing single-cell sequencing services to researchers.
More recently, several companies have started using single-cell sequencing technology initially developed in academia to identify new biomarkers and drug targets. All seem to have a common goal: personalized medicine.
Research on most diseases caused by genetic or epigenetic mutations could benefit from single-cell sequencing technology. There are also scientific publications applying this technology in microbiology, neurology, immunology, digestive and urinary conditions.
Among them, oncology is probably the most promising and mature application. Previously, bulk analysis of cells from a tumor biopsy only gave information on the predominant type of cells. In contrast, single-cell sequencing can provide information about other tumor cells that might be resistant to treatment and could cause a relapse later on.
This technique is highly sensitive, being able to detect rare cell types from limited amounts of sample material. Combined with technology to isolate circulating tumor cells from a blood sample, single-cell sequencing can also be used to select patients with specific genetic or cellular traits in personalized medicine trials.
US-based IsoPlexis is one of the very few companies with an advanced program to apply single-cell sequencing to proteomic studies that look at the role of protein expression in cancer. The company is developing a technology to measure the levels of a dozen molecules secreted by those immune cells that are primed to recognize and attack a tumor. This has been used to predict, for the first time, the response that a person with blood cancer will have to CAR T-cell therapy. The company claims that it could also be applied to cancer patients treated with checkpoint inhibitor immunotherapy.
Single-cell sequencing can also be combined with CRISPR gene editing to make elaborated large-scale studies of how a genetic modification affects cell behavior. The Austrian company Aelian Biotechnology is combining both techniques to study gene functions with single-cell resolution, establishing a new paradigm for next-generation CRISPR screening. This approach has broad applications, including identifying novel drug targets or studying unknown mechanisms of actions of drugs.
In the wake of the Covid-19 pandemic, single-cell sequencing has also been extensively used to study the response of immune cells to Covid-19. The technology could for example help reveal what makes some people’s immune systems respond better to the virus, resulting in milder symptoms.
Either for research or clinical diagnostics, single-cell sequencing remains challenging and is far from being used routinely. One of the main reasons is that single-cell collection is tricky, as the amount of sample material used is low but the analysis still requires a sufficient amount of cells to make sure all cell types are represented. The time it currently takes to complete an experiment is another major concern. Companies developing single-cell sequencing technology need to work on creating streamlined and optimized workflows that limit these problems.
Complex data analysis
Although experimental methods for single-cell sequencing are increasingly accessible to laboratories, handling the data analysis remains challenging. There are currently limited guidelines as to how to define quality control metrics, the removal of technical artifacts, and the interpretation of the results. With larger experiments, the data analysis burden increases.
“Single-cell data requires the analysis of millions of data points for a single tumor,” said Andrei Zinovyev, who leads a machine learning project focusing on single-cell data analysis at the Institut Curie in Paris.
There are many software tools developed by academics, mostly available in open source. However, their use is limited to a small community of researchers that have been able to successfully combine advanced bioinformatics and statistical skills with in-depth knowledge of the biological systems they study. Companies such as 10X Genomics and Fluidigm also provide software tools, but this area remains in its infancy and gold-standard tools have yet to be developed.
For single-cell analysis to spread to a broader community, user-friendly analysis tools are needed. In this area, Swiss startup Scailyte is developing an AI-based solution to discover biomarkers from single-cell data, analyzing complex datasets in just a few hours. The US startup Cellarity is also working in this area, seeking to combine single-cell sequencing with artificial intelligence and CRISPR gene editing.
The use of single-cell sequencing is limited, due in part to its high cost. Most of the instruments and reagents needed are costly. For someone looking to incorporate single-cell sequencing into their laboratory, 10X Genomics for example sells instruments for about €70,000. A typical run, including cell isolation and sequencing, can cost anywhere between €3,000 and €10,000 per sample, depending on the number of cells.
Due to the high cost, it is becoming popular for laboratories with the equipment to offer single-cell sequencing and analysis as a service. The US company Mission Bio is tackling this issue, aiming to reduce the cost to between $1,000 and $2,000 for a typical run.
As is usually the case in any area with huge market potential, intellectual property conflicts can negatively impact the development of new technologies. Back in 2015, Bio-Rad sued 10X Genomics for patent infringement, and the jury determined it would have to pay €21M in damages. Furthermore, 10X Genomics could not sell their products to new customers, being therefore limited to servicing ‘historical clients’, with all past and future sales subject to a 15% royalty.
Several months later, the US company Becton Dickinson also sued 10X Genomics. After that, the company decided to build a brand new piece of equipment to reinforce its intellectual property position and countersued Becton Dickinson.
The single-cell sequencing market is still very young. With a current value of around €1B, the market is expected to reach over €2B by 2027. Competitors are innovating at an insane rate to take the lead, but there is still a long way to go before single-cell sequencing can be widely used. A huge amount of investment will be needed to fully unlock its potential for research, drug discovery, and diagnostics. Nonetheless, the field has momentum and once it tackles the challenges, there is no doubt that single-cell sequencing will pave the way to breakthrough innovations in personalized medicine.