How is high-throughput sequencing revolutionising medical research?
Matt Peniket | 27 March 2017

In 1995, the first whole genome of an organism was sequenced. The species? The ‘haemophilus influenzae’, a human pathogen responsible for diseases such as pneumonia, bacteraemia and meningitis [1]. To sequence this genome of 1,830,140 base pairs using the shotgun method took months. However, in 2014, it is possible to sequence an astounding 400 million base pairs in just 10 hours with high- throughput sequencing [2]. Not only is it a lot faster to sequence, but it is a lot cheaper too. As of today, it is possible to sequence the human genome for just $4,000 compared to $95 million as of September 2001 [3]. This low-cost sequencing will hopefully make sequencing of large quantities of genetic material a more viable economic prospect for state-run health systems and as a result, they will be able to reap many benefits. The implications of such fast and low-cost sequencing of genetic material are hugely diverse.

 

Medical research will be revolutionised in the field of diagnosis. The affordable and fast nature of high-throughput sequencing (henceforth HTS) means that personal genome sequencing of individuals will allow early identification of gene markers/mutations associated with diseases or a susceptibility to develop certain conditions. This will enable doctors to advise patients to take prophylactic measures to help stop a disease or condition developing. A prime example is Type 2 diabetes. In this case, doctors would be able to encourage patients to reduce their sugar intake and lower the amount of high GI food in their diet.

 

Primarily, HTS looks likely to revolutionise treatment. The unfortunate reality is that patients with the same disease respond differently to the same drugs, with some not responding at all. Most of the drugs that the pharmaceutical industry produces fail to work on many of the patients they are specifically designed for - a group known as ‘non-responders’. By knowing the genetic profile of a patient, and the genetic basis of his or her disease - and thus which proteins are actively involved in disease processes - doctors will be able to select more personal and cost-effective drug therapies to treat diseases, tailored to the individual.

 

These tailored drugs first have to be discovered. Mutations leading to diseases are commonly found within specific genes. Moreover, knowledge of the gene in which this mutation lies will allow identification of specific proteins that the gene codes for and the role that the proteins play in disease processes. Knowledge of the specific protein involved in causing disease symptoms will allow development of further drugs targeted at this protein to alleviate symptoms. In March of this year, GSK announced a collaboration with the Wellcome Trust Sanger Institute and the European Bioinformatics Institute in Cambridge [4]. The project aims to target the ‘non- responders’ of standard drug therapies by discovering new treatments for diseases and conditions with a genetic basis through analysis of vast quantities of genomic data. As a result, it will be possible to identify new target proteins present in non- responders. Consequently, it will be possible to design novel drugs targeted at these proteins, thus decreasing the currently large number of non-responders and thereby making drugs more effective.

 

Another example of an application of HTS to aid treatment has been in the field of cancer research. Cancer is a disease with a genetic component and occurs primarily as a result of mutations in genes that regulate the cell cycle. High-throughput sequencing has allowed researchers to discover, at the molecular level, the most common mutations of these genes through analysis of genomes of cancer sufferers. The identification of specific pathways in patients can now take place within a clinically relevant timeframe. This has facilitated accurate and fast diagnosis of a cancer and as a result, patients can undergo specific treatment tailored to their genetic profile [5]. Without such speed this would simply not be possible. Sequencing so fast has also allowed HTS of tumours as they develop and thus discoveries relating to the evolution of a cancer and mutations that occur during its existence have been made. For example, at Barts Cancer Institute, through accumulation of a collection of repeat biopsies from sufferers of a B cell malignancy called follicular lymphoma, it has been possible to monitor genetic changes as the disease develops. This allows the identification of key changes which cause normal follicular lymphoma to turn into a more aggressive form [6].

 

Another interesting and useful application of HTS is the ability to evaluate the success of a bone marrow transplant to cure a blood-related condition, for example, myeloma, leukaemia or lymphoma in a particular patient. After bone marrow transplant of ‘non-self’ bone marrow into a patient, a competition takes place between the donor’s healthy bone marrow and the residual cancerous bone marrow, if it has not been destroyed as a result of the course of intense chemotherapy that comes before the transplant. Through analysis of the bone marrow, clinicians have the ability to see whether the body has accepted the new, healthy bone marrow or rejected it. The presence of only one cancerous cell in one million normal cells results in the patient being diagnosed as having minimal residual disease. This knowledge helps to suggest that treatment should be given and, as a result, relapse can be prevented. All of this is achieved by quantitative analysis of the prevalence of the genes of the host, cancerous bone marrow. One method by which this is done is the analysis of genes, which code for specific T cell receptors. This acts as a biological indicator of minimal residual disease as these genes will differ between the host and donor bone marrow [7].

 

In conclusion, HTS has revolutionised medical research and will continue to do so. I am excited by the way in which HTS promises to further enhance our understanding of our genome. In particular, it will help us to understand what happens when the genome goes wrong, thus bringing a more personalised form of medicine to us all.

 

 

References

 

http://www.cdc.gov/hi-disease/ (date accessed: 21/3/14)

http://www.sumanasinc.com/webcontent/animations/content/highthroughput2.html (21/3/14)

http://www.genome.gov/sequencingcosts/ (21/3/14)

http://www.independent.co.uk/news/science/publicprivate-deal-heralds- revolution-in-search-for-new-drug-treatments-9217520.html (8/4/14)

http://www.ncbi.nlm.nih.gov/pubmed/21505136?access_num=21505136&link _type=MED&dopt=Abstract (31/3/14)

http://www.bci.qmul.ac.uk/news/publications/327-fitzgibbon-paper.html (10/4/14)

http://m.stm.sciencemag.org/content/5/214/214ra171.abstract (23/3/14)

James Routledge 2016