How chemotherapy impacts the body

Current standard cancer treatments, such as chemotherapy and radiotherapy, can have lasting effects on the body. Chemotherapy for example is associated with many side effects, such as nausea and anaemia, due to the impact of the toxins on healthy tissue as well as the tumour.

Neoadjuvant therapy, whereby therapies are administered before the main treatment, to help reduce the size of a tumor or kill cancer cells that have spread, has previously been suggested to contribute to changes in the composition of a patient’s body. This includes reduction in muscle mass (or ‘sarcopenia’) which is a natural result of aging, but in those with cancer it can lead to some post-operative complications and other diseases further down the line.

A new study from Mr Nick Maynard, Oxford University Hospitals Trust, has assessed the changes in muscle mass in gastro-oesophageal cancer patients, to better understand the long-lasting impact therapies have on the body and if it can be used to predict the risk of post-op complications. From a sample of 199 patients, they observed a decrease in skeletal mass in all individuals, with 91 participants losing more than 5% of their original skeletal mass. Those with a high rate of muscle mass depletion were generally male and significantly older, i.e. over the age of 67 years old.

50% of patients in the study experienced post-operative complications, such as pneumonia, with 13% having severe complications. However, Nick and the team observed that this was not related to the patient’s loss of skeletal mass.

Fortunately, this means that patients undergoing surgery for oesophageal cancer with large reductions in muscle mass are not necessarily at an increased risk of post-operative complications. Whilst these results do not produce any new method for predicting post-op complications, as sarcopenia did not determine the frequency of post-op complications in the sampled patients, they provide a deeper understanding of how neoadjuvant therapies can impact the body. This is important as post-operative loss of muscle mass has been previously associated with a lower survival rate for oesophageal cancer patients, so this will help to inform clinicians which patients may need to be more closely monitored.

New AI technology to help research into cancer metastasis

Cell migration is the process of cells moving around the body, such as immune cells moving through the body’s tissues to fight off disease, or the cells that move to fill the gap where a tissue has been injured. Whilst cell migration is an important process for regeneration and growth, it is also the process that allows cancer cells to invade and spread across the body.

Therefore understanding the factors that regulate and instruct cells to move is an important part of understanding how we can prevent the metastasis of many cancers. One method of doing this is through scratch assays, which as the title suggests, involves inflicting a wound or ‘scratch’ on cells grown in a petri-dish and analysing how the surrounding cells react and migrate to ‘heal’ the scratch under a microscope.

Although cell migration is intensively studied, we still do not have efficient therapies to target it in the context of cancer metastasis. Observing cancer cell behaviour to artificial wounding and how this can be altered in response to pharmacological drug treatment or gene editing is important to fully understand the factors that drive this process in tumours and provide insights on the processes that drive such behaviours. Whilst current microscopic analysis methods of wound healing data are hindered by the limited image resolution in these assays. Therefore, there is a need to develop new methods that overcome current challenges and help to answer these questions.

Dr Heba Sailem a Research Fellow from the Department of Engineering, has led a study to develop a new deep learning technology known as DeepScratch. DeepScratch can detect cells from heterogenous image data with a limited resolution, allowing researchers to better characterise changes in tissue arrangement in response to wounding and how this affect cell migration.

Tests using the technology have found that DeepScratch can accurately detect cells in both membrane and nuclei images under different treatment conditions that affected cell shape or adhesion, with over 95% accuracy. This out-performs traditional analysis methods, and can also be used when the scratch assays in question are applied to genetically mutated cells or under the influence of pharmaceutical drugs – which makes this technology applicable to cancer cell research too.

Dr Heba Sailem says;

“Scratch assays are prevalent tool in biomedical studies, however only the wound area is typically measured in these assays. The change in wound area does not reflect the cellular mechanisms that are affected by genetic or pharmacological treatments.

“By analysing the patterns formed by single cells during healing process, we can learn much more on the biological mechanisms influenced by certain genetic or drug treatments than what we can learn from the change in wound area alone.”

Using this technology, the team have already observed that cells respond to wounds by changing their spatial organisation, whereby cells that are more distant from the wound have higher local cell density and are less spread out. Such reorganisation is affected differently when perturbing different cellular mechanisms. This approach can be useful for identifying more specific therapeutic targets and advance our understanding of mechanisms driving cancer invasion.

The team predicts that DeepScratch will prove useful in cancer research that studies changes in cell structures during migration and improve the understanding of various disease processes and engineering regenerative medicine therapies. You can read more about DeepScratch and its applications in a recent study published in Computational and Structural Biotechnology.

About Heba

Dr Heba Sailem is a Sir Henry Wellcome Research Fellow at the Big Data Institute and Institute of Biomedical Engineering at the University of Oxford. Her research is focused on developing intelligent systems that help further biological discoveries in the field of cancer.

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