The threat of cancer continues to grow as the disease claims around ten million lives worldwide each year, with the World Health Organization predicting that the global cancer burden will increase 60% by 2040.
While the world is still seeking a cure for cancer, technology’s ability to accelerate the pace of innovation while reducing the cost is changing the dynamic of the struggle in myriad ways.
The scalability and relative affordability of cloud technology is enabling healthcare professionals (HCPs) and patients to tackle the disease more effectively at every stage, from discovery to remission. Artificial intelligence (AI) and machine learning (ML) are generating deeper insights from genetic, clinical and image data, accelerating the pace of data analysis; researchers around the world can now collaborate in real time and share key findings, and remote monitoring and telemedicine have enabled patients to take more of the fight into their own hands.
Mapping the cancer landscape through genome sequencing
Cancer is a disease caused by the uncontrolled division of abnormal cells, and in the vast majority of cases this results from some form of genetic alteration. This makes most cancer a disease of the DNA. The challenges of treating it stem from the fact that, as genes mutate, they change, and as tumours grow, they continue changing. Each type of cancer might have a mutational signature, but the genes in each tumour and the cells within each tumour are different.
Mapping this genetic diversity requires the generation and analysis of an immense amount of data. Equipping physicians with the insights they need involves collecting that data in a way that protects patient privacy, storing it securely – and transforming it through visualisation and analysis to guide both patient treatment and new drug development.
The Cancer Genome Atlas has collected data from nearly 20,000 tumours and comparative normal tissue samples from 11,328 patients across 33 cancer types. The visualisations produced through this data illustrate how different cancers develop and spread, including patterns in the cells where they originate, the role of different virus variants in triggering mutations and the signalling pathways within the body that can be leveraged for effective treatments.
Scaling this data-led approach to decoding cancer depends on sequencing the DNA of each potential patient cost-effectively. That’s the goal of California-based Ultima Genomics. It’s developing a genetic sequencer on AWS that can make individual DNA sequencing, which cost $1,000 a decade ago, available to patients for as little as $100.
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