Humans havearound400olfactorysmell-sensing genes the largest gene familyin humansthat are turnedon in the noseand other parts of the body, allowing us to smell at least one trillion different odours.Up until now, the role of theseolfactorygenes outside the nose has been largely unknown.
A recent study, published in Molecular Systems Biology, usedmultiple layers of artificial intelligence (AI) toidentifythesegenes involved inthe organisation ofcolon cancer cells. Thisrevealed thatsmell-sensinggenescancontribute to this cancer-associated processalong with keycoloncancer genesandhighlighted their potential role indisease spread andprognosis.
The discoverywas enabled by thedevelopmentof an innovativeAI system, calledKnowledge-and Context-driven Machine Learning (KCML)that enables researchers to studymicroscopy imagesin greater detail to understand more about the function of genes in specific context. KCML has first been applied to colon cancerbut is widely applicable in other diseases too.
The researchers usedcomputer vision algorithm to detect changes in cell appearance and organisation. The algorithm was fed information from robotic microscopy, in collaboration with researchers from the University of Zurich, to image millions of colon cancer cells.By reducing the expression of the smelling genes within these cells, they were able to understand more about the role they play in carcinogenesis.
Expression is whengenes are activated to produce certain proteinsand molecules. Researchers in this study found that reducing the expression of smell-sensing genes in colon cancer cells, a process known as perturbation,can inhibit cells from spreading, potentially by restraining the ability of cells to move. The same behaviour is also observed in the perturbation of key cancer genes.
Dr Heba Sailem,Sir Henry Wellcome Research Fellow at theInstitute of Biomedical Engineering in the UK, alead author on the study,explained: With all this big imaging data, we have a powerfulmeans tobetter understand how every single gene contributes to cancer cell behaviour. I have developed an AI system that is guided by prior knowledge of gene function that allows us to learn much more from this data than would be possible using existing methods.
When humans look atcomplex scenes, theyinterpret the images in light of their previous experience and visual memories (prior knowledge). However, computersjust seeimages asalargematrix of numbers, they will not see shapes and structures.Computer vision is about training the computer to see whatthe human can see. Through AI, we are able to identifyhow turning genes off affectsthe characteristics, shape and structureof cells and tissue. Usually, it is a very lengthy process for humans to interpret numbers from thousands of images, each with thousands of cells.Computer vision can achieve that in a few days,she added.
Dr Sailemswork has focussed on studying cells in culture, and the next step will beto link these findingsthroughto real patient data. She is also keen to apply her AI modelto study the behaviour of genes indifferent cancers, including prostrate, breast and lung.
WHY IT MATTERS
Colorectal cancer is the third most common cancer in the UK and the second most common cause of cancer deaths.
Professor Mark Lawler, chair in translational cancer genomics, Centre for Cancer Research and Cell Biology, Queens University Belfast and Bowel Cancer UK medical advisor,welcomed the application of the new AI model in colorectal cancer, commenting the study showed the power of data in revealing new mechanisms.
One of the biggest challenges in colorectal cancer is metastasis. This is the point at which most patients die. Something that tells us more about that and maybe indicates how this could be controlled is verypromising, he added.
Dr Sailem explained:Cancer is not one disease - itcan be classified intomany diseases depending ontissue type and origin. Wecan takecellsfrom diseased tissueand look at what the genes in theseparticular cellsare doing. We can then identify genes to target for therapy or genesfor which targeted therapies already exist.
THE LARGER TREND
AIand machine learningis increasingly being used to acceleratethe development oftargeted therapies in cancer and other diseases, with leading technology and pharmaceuticalcompanies forming high profile partnerships in recent months.
One such collaboration between Novartis and Microsoft was announced in October to transform medicine with AI. Vas Narasimhan, CEO of Novartis, said, As Novartis continues evolving into a focused medicines company powered by advanced therapy platforms and data science, alliances like this will help us deliver on our purpose to reimagine medicine to improve and extend lives. Pairing our deep knowledge of human biology and medicine with Microsofts leading expertise in AI could transform the way we discover and develop medicines for the world.
ON THE RECORD
Professor Tim Maughan,professor of clinical oncology at the University of Oxford and advisor to Bowel Cancer UK,saidDr Sailemsstudy linked to his own research into howcellswithin tumourstalkto each other.
He said: What they say to each other is determined by molecular make up but also by the conversation going on between the cells. The shape that the cellshave, theway that theyareorganised, the distance they are apart, how close the immune cells get into the cancer,is all a result of the conversation going on between the different cell types within a cancer
DrSailemin this study has found that inadditiontoidentifyingwhole new genes which are important in bowel cancer, she has also picked up that genes that are part of thatolfactorysmell system play a part of this conversation.
Commentingon the research, Professor Lawler said:It is saying something about why there areolfactorygenes in other parts of the body and how they might be responding to the microbiome in the gut. It will be interesting to see what stimulates these genes to upregulate or down regulate in their environment. From there we may be able to identify important biomarkers.
He added: Big data for better health makes sense. You can use that data to change lives, diagnose patients earlier, develop better treatment and improve their quality of life and above all, data can really save lives.
For more information on bowel cancer go to http://www.bowelcanceruk.org.uk.
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