Changes in our understanding of cancer

07/10/2017
Decoded content
07/10/2017

Since DNA was first observed in the 1970s, we have been constantly expanding our understanding of how our genes influence the development of certain diseases such as cancer or diabetes.

The ability to fully sequence the human DNA now means we are not only able to offer personalised treatments for each patient based on their genetic make-up, but also to anticipate the development of possible diseases and offering them the best therapeutic solution as soon as possible.

 

A technological revolution: from DNA sequencing to biotechnology

DNA is an individual’s genetic blueprint. Like an instruction manual, it contains all the information the cells need to work properly. For example, it is in the DNA, or more specifically in DNA fragments or sequences (genes), that a muscle cell finds the instructions it needs for how to contract.

 

Sequencing

Sequencing is when we translate the set of unique molecules found in a gene into a computer language, a bit like transcribing colours using a colour code.

The blue colour of this square has the computer code #005db9

Continuing this analogy, a gene is like a pattern of several colours, and how they are combined gives a specific colour which corresponds to a particular function within the human body.

Sequencing allows us to analyse this general colour, by listing all the component colours which have been mixed together. It also gives us a better understanding of how the pattern influences the colour of the gene, and thus its function.

For example, if a normal gene is green and an abnormal gene is purple, sequencing allows us to determine the composition of the gene and identify the point within the gene where the normal colour has been replaced with an abnormal colour. In this case, sequencing tells us that yellow has been replaced with red.

Normal gene: blue + yellow = green

Abnormal gene: blue + red = purple

 

The human gene is made up of several thousands of colours, and a single abnormality is enough to trigger a disease. The advantage of sequencing is that we can translate these colour patterns into a computer language so that they can be easily identified.

The first time DNA was extracted from cells and the gene sequences were observed was back in 1972, when we discovered the instruction manual for how humans work. Since then we have been able to link DNA with certain diseases which are caused by an abnormality within these genes.

The first whole DNA sequencing was achieved in 2002. The project took twelve years and cost $3 billion. Today, with advances in technology, sequencing has become a routine procedure. Whole DNA sequencing takes just a few hours and costs about $1000.
One of the first direct applications of sequencing was to produce medicines, such as insulin, from living organisms.

Insulin is a protein that the body makes in order to lower the amount of sugar in the blood, especially after meals. Like all proteins, insulin is a set of amino acids. It is therefore produced by natural human mechanisms, which differ fundamentally from traditional chemical techniques.

This protein is made from a gene which has its own particular sequence (or its own colour pattern, using he previous analogy) which was decoded and identified using sequencing. This sequence was then extracted from humans and inserted into cultured cells in order to be able to mass-produce insulin.

However, this is a very particular use of sequencing; as well as allowing us to manufacture medicines using biotechnology, this breakthrough has resulted in a vast amount of new knowledge for scientists, in particular their understanding of genetic diseases such as cancer.

 

Changes in our understanding of cancer

Over the past few decades, scientists tasked themselves with identifying correlations between gene sequences and their direct effects on cell function. This work has paved the way for biotechnologies, a range of sciences and inventions which use DNA mechanisms to improve human health.

Today, when a patient with suspected cancer goes to see an oncologist, the doctor takes a biopsy – a small sample of the possibly cancerous cells. The DNA of these cells is extracted in a laboratory and 400-500 genes known as the usual suspects are sequenced. These are the genes most commonly involved in the development of cancer. The results of the sequencing give the doctors key information which they use to select the most suitable treatment.

Work has also been underway for several years into the predictive potential of these sequences. Thanks to developments in computer science, it is now possible to identify our predisposition diseases and therefore take preventive and curative action much earlier on. However, sequencing only provides a partial explanation for genetic conditions, since environmental factors are often major triggers. Sequencing therefore needs to be used in combination with other therapeutic approaches, such as imaging, biopsies and biomarker screening.

 

The advent of biomarkers

Biomarkers are biological signs that can be identified and measured inside our bodies and which tell us whether a cell or an organ is working normally or is diseased. After a heart attack which damages the cardiac cells, the heart releases proteins into the bloodstream which can be detected in a blood sample. By measuring the amount of these proteins, we can determine the extent of damage to the heart and also know when the patient is in remission, since the volume of proteins will fall.

Identifying and quantifying these biomarkers is therefore a way of assessing a particular function, with a view to forming a diagnosis, and thus they provide a way to determine the efficacy of a treatment or even to screen for certain conditions.

They also play a key role in our search for new medicines and help us study their toxicity and efficacy. Doctors can also use them to diagnose diseases and even monitor how well a treatment is working.

 

An example of a biomarker: fluid biopsy

With the development of more accurate and sensitive technologies, researchers and clinicians have for several years had tools which can screen for biomarkers specific to cancer cells. In certain cases, this avoids the need for an invasive biopsy; the biomarkers can not only identify cancer cells but also help classify them into subtypes for which specific treatments may be available.

 

Translational research: putting the patient first

Thanks to current technological advances, whether in terms of big data or calculation potential, medical sciences have been transformed. However, this opens as many doors as it creates new challenges. The first of which is undoubtedly how to transform this data into knowledge.

Modern medicine is experiencing a paradigm shift whereby clinical development and research are becoming indistinguishable. We talk of a continuum and of “translational research”, where clinical researchers and scientists cooperate in order to better identify the treatment targets of tomorrow and as-yet unmet therapeutic needs. Research no longer starts with molecules in the laboratory, but with the patient.

At Servier, we ensure constant dialogue between our research and clinical teams. Patient-led research, in particular the study of biomarkers, has therefore resulted in valuable analysis which has accelerated the research process. The main aim is to provide new and more effective treatments for patients, as soon as possible and with fewer side effects.

 

Stratified medicine and precision medicine

Alongside these advances in research, medical practice is also undergoing major changes. Patient-focused medicine is the new trend, a phenomenon often described as “personalised medicine”.

However, Servier prefers to talk of precision medicine, because even though the patient is at the heart of its medical policy, the treatment is designed first and foremost to target the disease, with ever increasing precision.
This has in particular been made possible thanks to the technological evolutions described in this article, a combination of sequencing and biomarkers which has for many years been used to define disease subtypes in order to give patients ever more customised treatments, improve medical efficacy and reduce side effects.

For example, with breast cancer there are at least ten different subtypes of cancer cells. Each has a different origin, progression, prognosis and treatment. For one of these cancer cell subtypes, for example, there may be one or several genes responsible for a cell feature. And this feature may be targeted by a particular cancer drug. Therefore, depending on whether this gene is expressed, a patient may or may not benefit from this particular treatment. It is DNA sequencing that tells us which.

 

Servier Laboratories in Croissy

 

Conclusion

These various revolutions, which have allowed us to work with ever-increasing volumes of more and more accurate data about both diseases and our patients, have triggered major changes in the field of medical research as well as in the treatments we provide. However, despite the importance of these changes and their benefits, they have their limits.

This new knowledge and these new techniques have in fact triggered a certain over-optimism. DNA sequencing can currently be used to diagnose a disease and rapidly design the most suitable treatment; it can also be used to determine any pathological predispositions of a particular patient well in advance. However, whether a person develops a particular disease depends on a large number of factors, such as environmental conditions; it is therefore impossible to say with absolute certainty, regardless of how accurately we can read a patient’s DNA, what diseases he will definitely get, or when.

Ethically, we must therefore be extremely careful of how we use this newly available data. For example, telling a patient he has a 40% chance of getting Alzheimer’s based on his DNA analysis will drastically affect his outlook on life, even though he has less than a 1 in 2 chance of getting the disease.

This technological evolution, or even revolution, together with this paradigm shift where the patient is now at the centre of research and where treatments are becoming more and more targeted, as well as recent advances in oncology, all represent a quantum leap never before seen in the field of medicine.