The social network…of cancer!?

Let’s do a quick exercise (may be slower for others depending on…well, you’ll see): pick a social media platform, any social media platform, that you’re on. Look at who you follow, maybe even look who follows you if you want to make it complicated, but mostly look at who you follow. What does that say about you? I can already hear your answers: ‘it’s complicated.’ (that, or ‘no comment’). I bring that up to set up today’s Featured Article, which looks at genetics. Let’s just get this out of the way: it is complicated. Sure, it starts off with four chemicals, the bases, but it will get very complicated in a short amount of time. Sequences of these bases form the genes that are expressed in the human body as eye color, skin color, and the various other things that make each person unique. I’ve written about how genetic sequences are really just pieces of information.

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Public Domain (Author: Brandon Bolender, 2016

However, genetics isn’t that simple (oh, really!?). In reviewing the literature, the authors found that the expression of these individual genes are not often what causes certain characteristics, the phenotypes, to actually show up. For example, a single mutation isn’t going to suddenly make you green-eyed, or I’m going to wake up to find that I have fourteen toes. Lucky for you and/or your shoes, phenotypes are often expressed because of a network of genes, and a bunch of things have to happen correctly before a ‘mutation’ actually shows up.

One of the key ideas behind genetics is replication, which is how DNA is copied in organisms, down to other cells (they don’t live forever, you know) and perhaps future generations of that organism. A quick semi-related aside: I’m writing this on 13 May, so a belated Happy Mother’s Day to my subscribers and readers! (perhaps consider subscribing to science.casual if you haven’t already? I don’t know how to advertise…) Anyway, ‘mutation’ in the genetic sense doesn’t mean spontaneously developing green eyes and fourteen toes, it means that genes were not identically copied during replication. The wrong genetic base may have been used, a piece was removed or added, it may have prematurely stopped – a genetic mutation is really just a clerical error. However, many of these clerical errors aren’t necessarily devastating, unlike your most recent autocorrect fail.

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Flickr/Public Domain (Author: The U. S. National Archives, 1995)

In the rare cases that they are devastating, the result of genetic mutations are cancer. However, note that cancer doesn’t often have causes; insteadmost reference material on cancer have to do with ‘risk factors.’ You’re not guaranteed to get cancer from exposure to those risk factors. The right genetic mutations still have to happen, but you are stacking the deck in favor of getting cancer because of those risk factors.

Back to the Featured Article – the authors created a method to find relationships with the really complicated social network of genetics that they called the ‘Altered Partitions Across Community Architectures’, or ALPACA (a snappy acronym makes for good marketing, you know). You could read the article yourself if you’re interested in the fine details, but the short of it is that they look at what happens to the network when you change a certain part of it. Once they got it to work on a simulated network, they tried it on genomes from patients with ovarian cancer. ALPACA found some interesting structures in the network: gene groups that have to do with production of certain compounds related to inflammation, development of blood vessels, responses to immune system regulators, and so on.

Much like your social network, genetics is often complicated, and cancer more so. Perhaps by learning more about the relationships between certain genetic anomalies, we can get a better idea of what we can target in cancer treatments to make them more effective. Thanks to some very difficult math that is likely similar to targeted Facebook ads and the general weirdness that shows up next on YouTube, perhaps we can stack the deck in our favor.

Thoughts? Comments? Let me know in the space below, and you don’t need to be a WordPress member to do it! If you’re not doing so already, please follow (if you’re into scientific research with snarky commentary from an overly-caffeinated blogger-scientist) and thanks again for stopping by.

Featured Article: Padi M, Quackenbush J. (2018). Detecting phenotype-driven transitions in regulatory network structure. NPJ Systems Biology and Applications 4(1). DOI: 10.1038/s41540-018-0052-5.

Featured Image: Public Domain (Author: Christine Schmidt, 2013)

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