The aim of my PhD project is to develop a sensor capable of detecting cancer biomarkers (biological molecules that may indicate the presence of cancer). The aim is to help enable early-stage cancer diagnosis, and also help provide essential information regarding likely disease progression, and probable response to treatment. With 1 in 2 people expected to be diagnosed with cancer in their lifetime1, development of early stage diagnostics is essential.
Cancer is defined as the unregulated growth of cells due to a change in their DNA. However, cancer is also extremely dynamic, and during the course of the disease, an accumulation of further DNA changes can lead to extreme diversity in the cells making up a single tumour. As a result of this, one of the key problems in cancer diagnostics is intratumoural heterogeneity – wherein the cells making up a tumour have a lot of variation.
DNA can be thought of as a recipe book, containing all the recipes your cells need for creating proteins and other molecules. If this book gets damaged, this could change lead to a recipe change, and impact the proteins and molecules made (biologically, damage to DNA can lead to alterations or “mutations” in the DNA sequence). This could alter the amounts in the recipe, leading to abnormally high or low quantities of proteins or molecules being made, or change the ingredients, possibly leading to a different protein or molecule being made – or sometimes a page could be completely torn out, and the protein or molecule isn’t made at all! Further, the best treatment route could vary depending in what way the recipe is changed. Some recipe changes are completely harmless, and no treatment is necessary. On the other hand, if intervention is necessary, analysing the final protein or molecule can provide insight into the most effective treatment.
In order to identify changes to this recipe book, we could possibly go through it page by page, looking for abnormalities in recipes. However, this could take a long time, and as mentioned, not all changes may even be harmful. On the other hand, it may not be necessary to look in the recipe book at all if we can identify the types and quantities of proteins and molecules made by each cell. We note that due to intratumoural heterogeneity however, the ability to analyse biopsies cell-by-cell is key, as each cell has its own recipe book which may have its own damage and resultant recipe changes, and information could be lost through cell averaging techniques.
While various single-cell methods do already exist, they typically rely on amplification – a mechanism used to increase the number of copies of a gene present – which is not possible for proteins. Alternatively, proteins may be analysed using mass spectroscopy, but this is expensive, and sample preparation is complex. Further, targeted approaches such as fluorescence microscopy require us to know what we are looking for – this is a particular issue as biomarkers for cancer are continually being identified. Hence, a tool capable of identifying both proteins and molecules within a single cell could be extremely useful.
My aim is to develop a platform capable of taking a molecular “fingerprint” of single cells in tumours, to identify biomarkers of cancer using a combination of nanophotonics and nanopore sensing. While the former is capable of performing the cell fingerprinting, the latter is key for cross-correlation and validation of the results.
Returning to our recipe book, in scenarios where despite a change in ingredients, the final product doesn’t look terribly different (such as accidentally adding salt instead of sugar to cookies), a method to analyse the ingredients in a dish would be useful. In the proposed sensor, this is achieved through a nanophotonics method called Surface Enhanced Raman Spectroscopy. Here, light inelastically collides with a protein or molecule of interest, resulting in a frequency shift based on its vibrational properties. Hence, by collecting the scattered light spectrum, we can identify the molecules or proteins in a sample.
Alternatively, in scenarios where the ingredients are the same or extremely similar, but the protein or molecule has a noticeably different size or shape (e.g. forgetting to add yeast to bread), we can better identify the error using nanopore sensing. In this method, an electrolyte is split into two reservoirs by a nanoscale hole, with the proteins or molecules added to the reservoir on one side. Due to the charge of the electrolyte, when a potential is applied between the reservoirs, the electrolyte and its contents then move through the hole to the reservoir on the other side. When a molecule or protein passes through the hole, it occupies a volume that partially restricts the flow of ions, producing a signature ionic current drop which can be analysed to determine size and shape. The complementarity between these techniques can also be used to ensure that the “ingredient” and shape information are in agreement and being analysed correctly.
By detecting changes in the molecules and proteins synthesised at the single cell level, this tool helps enable specific and early-stage identification of cancers, without the need for analysing DNA. By combining two existing techniques, this tool is expected to be able to analyse the breadth of molecules and proteins synthesised by human cells, without the necessary complexity, cost, or knowledge of the sample.
- Cancer Research UK. 2021. Lifetime risk of cancer. [online] Available at: <https://www.cancerresearchuk.org/health-professional/cancer-statistics/risk/lifetime-risk#heading-Zero> [Accessed 29 July 2021].
NanoDTC PhD Student, c2020