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How single-cell RNA sequencing can improve cancer diagnosis

How single-cell RNA sequencing can improve cancer diagnosis

By studying each cell in a tumour microenvironment, single-cell RNA sequencing technique could change how we treat cancer
RNA Sequencing
Representational image | Shutterstock

No two cancer cells are the same. From body to body, person to person, these cells express themselves in different ways, even though many have shared characteristics. Identifying cancer cells is hard: Not only are they small, but they can get hidden behind organs, or missed out of the trillions of other cells in your body. 

The specific nature of this disease is one of the biggest challenges in diagnosing and treating cancer today. What makes these cells so unique is their mutated genetic makeup. And while diagnostic tests like biopsies have long been used to identify tumours, there is increasing interest in using technology to examine tumour microenvironments.  

Research into conducting gene and protein-based analysis has gained ground. Diagnosing the nature of a cell requires looking at its genetic makeup. 

One candy at a time 

Deoxyribonucleic Acid (DNA) contains all the genetic information. Ribonucleic Acid (RNA) translates genetic information from DNA, which is then used to synthesize proteins 

The traditional method of bulk RNA-sequencing does not target single cells but instead considers a bulk sample comprising many cells. This gives a picture of an “average” gene expression, and fails to represent the heterogeneity of the sample 

Single-cell RNA sequencing can investigate 10,000 cells at a time. But unlike bulk sequencing, it can profile the genes expressed by each individual cell. If bulk sequencing is like tasting a full packet’s worth of assorted candies at once, single-cell RNA sequencing is like studying the unique flavour of each candy in detail. 

Irina Pusher, Senior Bioinformatics Scientist at Children’s Mercy Kansas City, United States, says such analysis is extremely powerful because not only are cancers vastly different across patients, but different cells within a given patient also have unique patterns of gene expression and behave differently.  

The applications are not limited to just cancer. Dr Laxminarayan Rawat, a Postdoc Research Fellow at Harvard Medical School of Cancer Biology, Boston, (Massachusetts, United States) says single-cell RNA sequencing has revolutionary potential and can be used as a diagnostic tool for any disease model.  

“It can identify the abnormal expression of genes and would give the idea about the fate of the cell type. This could be more beneficial in the early detection of cancer, and many other diseases.” 

How soon can we expect this technology to yield therapeutics? 

Dr Pranjal Sarma (Cancer Biologist), Associate Clinical Trial Manager, Medspace, Ohio, United States says that “the pharmaceutical industries are more interested in a particular gene or protein”. Therefore, a detailed understanding of a gene in a particular cell in a certain state would be extremely important to design the treatment. Understanding the regulation of genes in different cells through processes like “Single-cell RNA sequencing” is very important for the development of drugs.  

Irini Pushel says the technology may already have led to drug development. “It is entirely possible that some genes of interest that are identified in a single cell RNA sequencing-based study may have already been selected for the development of novel drugs (or repurposing of existing ones) for the treatment of a particular cancer! It’s just a very long process.” 

Use of single-cell RNA-sequencing in different types of cancer 

The literature suggests the astounding performance of single-cell RNA sequencing to uncover the complexities of the heterogeneous tumour microenvironment. Single-cell RNA sequencing not only tells which genes are expressed but also interprets the chain of reactions happening in each cell. It detects and identifies the glitches in the gene expression. It also demonstrates the physical changes of the cells. 

The ability to study cells at such detail has already yielded actionable research. Here are a few examples: 

  • Glioblastoma Multiforme (GBM): Single cell RNA sequencing was used to identify 31 genes that can be used to diagnose and map therapies for GBM, which is considered the most aggressive and lethal form of cancer. 
  • Glioma: A study used single cell RNA sequencing technique to identify a protein which can help to increase the rate of survival among individuals suffering from glioma. 
  • Colon cancer: One study found a way to improve drug targeting for better diagnosis and treatment of colon cancer. 
  • Breast cancer: Using single cell RNA sequencing, cancer cells were distinguished from immune cells. Immune cells were extracted from individuals having breast cancer and grown on a large scale in laboratory and injected back into cancerous cells, a method which can greatly prevent the spread of cancer. 

The challenge: Cost 

Single-cell RNA sequencing can be up to 7-15 times more expensive than bulk RNA sequencing, which makes it difficult for researchers to get as much data as it would be good to have. The cost is also a big barrier to developing clinical applications for the technology. Data interpretation is another major limitation of this technique, which is tricky and requires a depth of knowledge of the genome and certain gene functions. However, bioinformaticians are working to grow its utility.  

The commercialization of single-cell RNA sequencing services at a wider scale depends on the funding. But there is progress: Fluent Biosciences, a biotechnology company, received a grant of a $1.7 million from the National Institute of General Medical Sciences, United States, to commercialize single-cell RNA sequencing.  

Kure Cancer Research, a non-profit independent organization in the USA has also granted $200,000 to support the treatment of kidney cancer using RNA sequencing methods. 

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