New online app could better diagnose cancers
New York: Scientists have developed a new online app that would help scientists and clinicians better identify and diagnose cancer by comparing genetic fingerprints of individual cells.
Seemingly similar cells often have significantly different genomes. This is often true of cancer cells which may differ one from another even within a small tumour sample, as genetic mutations within the cells spread in staccato-like bursts.
Detailed knowledge of these mutations, called copy number variations (CNV), in individual cells can point to specific treatment regimens, researchers said.
The problem is that current techniques for acquiring this knowledge are difficult and produce unreliable results.
The new open-source software called Gingko will improve scientists’ ability to study this important type of genetic anomaly and could help clinicians better target medications based on cells’ specific mutation profiles, the researchers said.
Mutations come in many forms. For example, in the most common type of mutation, variations may exist among individual people – or cells – at a single position in a DNA sequence.
Another common mutation is CNV, in which large chunks of DNA are either deleted from or added to the genome. When there are too many or too few copies of a given gene or genes, due to CNVs, disease can occur.
Such mutations have been linked not only with cancer but a host of other illnesses, including autism and schizophrenia.
Researchers can learn a lot by analysing CNVs in bulk samples – from a tumour biopsy, for example – but they can learn more by investigating CNVs in individual cells.
“You may think that every cell in a tumour would be the same, but that’s actually not the case,” said Michael Schatz, associate professor at Cold Spring Harbor Laboratory in US.
“We’re realising that there can be a lot of changes inside even a single tumour. If you’re going to treat cancer, you need to diagnose exactly what subclass of cancer you have,” said Schatz.
One powerful single-cell analytic technique for exploring CNV is whole genome sequencing.
However, before sequencing can be done, the cell’s DNA has to be amplified many times over. This process can show errors, with some chunks of DNA being amplified more than others.
In addition, because many labs use their own software to examine CNVs, there is little consistency in how researchers analyse their results.
To address these challenges, Schatz and his colleagues created Gingko. The interactive, web-based programme automatically processes sequence data, maps the sequences to a reference genome, and creates CNV profiles for every cell that can then be viewed with a user-friendly graphical interface.
In addition, Gingko constructs phylogenetic trees based on the profiles, allowing cells with similar copy number mutations to be grouped together.
Schatz and his team named their software after the gingko tree, which has many well-documented therapeutic benefits. The study was published in the journal Nature Methods.