Next-generation sequencing techniques to determine an individuals 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. Thats useless. Thats not helpful. Not a single family has 1.2 children, stated Christoph Lengauer, CEO of Celsius Therapeutics, in an interview with STAT News. His company has raised more than 60M to develop 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. Its orders of magnitude more granular.

This is a huge paradigm shift. Single-cell sequencing was recognized as method of the year by Nature in 2013. Since then, the number of publications from both academia and the industry exploded.

In recent years, there has been a shift in the technology available to perform single-cell sequencing. Fluidigm used to hold the bulk of the market with products across the entire workflow but is currently suffering from poor sales due to new competitors.

At the forefront is US-based 10X Genomics, founded in 2012, which registered a 20-fold revenue increase between 2015 and 2017. 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 the alliance between two giants, Bio-Rad Laboratories and Illumina. They announced in January 2019 a joint 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.

Despite the rapid market growth, the use of single-cell sequencing is so far limited to a narrow circle of initiates. Over the past years, academic facilities have started providing single-cell sequencing services to researchers. For example, the technology is used at the Institut Curie in Paris to study cancer cells.

More recently, companies have started working in this area, often using 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 related to genetic or epigenetic mutations could benefit at some point from single-cell sequencing. There are already 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, which might be resistant to a certain therapy and result in a relapse after the first line of treatment.

This technique is highly sensitive and is 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 be used to select patients in personalized medicine trials.

IsoPlexis is one of the very few companies with an advanced program to apply single-cell sequencing to proteomic studies looking at the role of protein expression in cancer. The company is developing a technology to measure the levels of a dozen molecules secreted by immune cells that are primed to recognize and attack a tumor. Last year, this was 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 observe 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.

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.

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 its 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 mostly the case in any area with a huge market potential, intellectual property can cause conflict, which can negatively impact the development of new technologies. For example, 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 new piece of equipment to reinforce its intellectual property position. In September, 10X Genomics countersued Becton Dickinson.

The single-cell sequencing market experienced a growth spike between 2017 and 2018 due to several key stakeholders entering the market. But we are only at the beginning. According to most business reports, this market is expected to see a 300% growth, reaching a size of almost 1.4B by 2023.

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 would 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.

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Single-Cell Sequencing: Paving the Way for Precision... - Labiotech.eu