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Single-cell analysis techniques: advances enabling early diagnosis of genetic diseases

In this article Pramod Kumar, a Senior Research Analyst (Healthcare) at P&S Intelligence, explores how single-cell analysis techniques are used for both pharmaceutical R&D and clinical, diagnostic applications.

Blue DNA stand hovering above a genetic sequence

The healthcare industry has recently taken several leaps and bounds when it comes to curing disease. Several diseases that killed millions of people some years back can now be cured completely by taking the proper medication. To achieve this, the healthcare industry depends heavily on ongoing R&D activities. However, even after years of research and despite increasing innovations, various diseases exist that cannot be cured; cancer being the most common example.

Under this scenario, researchers need to look for different and innovative solutions and one emerging option is single-cell analysis. It is due to all these factors that the global single-cell analysis market is predicted to witness an 18.1 percent compound annual growth rate (CAGR) between 2016 and 2022.

What is single-cell analysis?

It was previously assumed that each cell type in living tissues has a distinct function and lineage. However, recent evidence and studies have proved these assumptions incorrect, as it has been discovered that cells are identical, genetically and morphologically. Instead, epigenetics and divergent gene expression is responsible for the heterogeneity (variety) of cells that make up the body. These revelations have been made by studying single cells.

It has further been observed that these differences among cells can have significant consequences when it comes to the health of the population as a whole. Single-cell analysis enables the study of cell-to-cell diversification within a cell population (eg, cell culture, tissue or organ). Single-cell analysis is the only way to study physiological functions in adults and embryos, which, in turn, can aid in the study of drug development and diseases.

Techniques for single-cell analysis

  • Flow cytometry: This method is utilised for analysing the expression of intercellular molecules and cell surfaces, defining and characterising various cell types in a heterogeneous population of cells, evaluating the purity of isolated subpopulations and examining the volume and size of cells. Flow cytometry enables simultaneous multi-parameter single-cell analysis.
  • Next-generation sequencing (NGS): NGS includes a number of techniques and technologies, such as region-specific panel sequencing, whole-genome sequencing and exome sequencing. These enable researchers to sequence strands of ribonucleic acid (RNA) and deoxyribonucleic acid (DNA). The process is utilised for studying genes or individual sections and then identifying the sections of genomes that contribute to biological characteristics or diseases
  • Polymerase chain reaction (PCR): This technique is utilised for analysing short sequences of DNA or RNA and reproducing selected sections of RNA or DNA. Where before the cloning of DNA took weeks, with PCR the process can be completed in a test tube in just a few hours. PCR is primarily performed for diagnosing genetic diseases, DNA fingerprinting, studying human evolution, establishing biological or paternity relationships and finding viruses and bacteria.

DNA strand with colourful DNA sequence read out

  • Microscopy: Also known as light microscopy, microscopy is the technical field of utilising microscopes for viewing samples which cannot be seen with the unaided eye. This method is utilised widely across research centers and other healthcare facilities.

All of these techniques are used by cell banks and in vitro fertilisation (IVF) centers, academic and research institutes, hospitals and diagnostic laboratories, as well as biotechnology and biopharmaceutical companies. Among all these, hospitals and diagnostic laboratories make up the majority of those using single-cell analysis techniques, for both research and diagnostic applications.

Clinical applications of single-cell analysis

For research, single-cell analysis is being utilised in a range of fields, including stem cells, cancer, neurology, immunology and tissue regeneration. Cancer research is one of the key applications of this technology, since the number of cancer patients across the globe has been rising rapidly. These days, a few types of cancer can be managed and even treated, all thanks to R&D activities. However, these advances should not distract from the fact that cancer is still affecting millions of people and the need for a proper cure has not diminished.

Single-cell analysis methods have provided important and powerful tools to get a deeper insight into intratumor heterogeneity, thereby enabling the targeting of therapy at clones that are most malignant. The technology can further be utilised for calculating a diversity index for different cancer patients, this data can then potentially be used for predicting poor response to chemotherapy and poor survival. In addition to this, single-cell analysis could also aid in the early detection of tumour cells in bodily fluids, including blood, sputum and urine.

graphic of a man, chromosome and DNA sequence

Apart from cancer, single-cell analysis is also being leveraged for IVF and pre-implantation genetic diagnosis (PGD). The latter process includes the collection of a single cell from a blastomere set for DNA single-cell sequencing. The aim of this process is to screen for genetic diseases before an embryo is implanted into the uterus.

The utilisation of single-cell analysis can further pave the way for personalised medicine, which is developed to provide specific treatments suited to the needs of the individual. Patients suffering from rare diseases will benefit immensely from the development of personalised medicine.

In conclusion, single-cell analysis is an emerging technology that has a variety of applications in early disease diagnosis and can also be the key to finding treatments for various incurable diseases. Since the domain largely depends on R&D activities, funding is a necessity to drive further development and advancements.

About the author

Pramod Kumar is a Senior Research Analyst (Healthcare) at P&S Intelligence. He has around seven years of experience in market research and consulting services for the healthcare industry. Kumar holds varied experience in market sizing and forecasting with varied models, competition landscape, consumer behaviour analysis, opportunity analysis, product/company benchmarking, data mining and others.

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