
More than a thousand scientists have built the most detailed picture of cancer - hhs
https://www.bbc.com/news/health-51391151
======
z3t4
How can a software developer contribute to cancer reasearch/treatment? Is
there any hard problems? or manual work that could be automated?

~~~
tejtm
Work for Universities (for P.I.s housed at universities) for less than you are
worth on the open market. (And still be resented by profs making less)

Soylent data (it is made of people), is hard because it has all these lawyers
attached to it. Figure out a trivial/foolproof way for EHRs to be
satisfactorily anonymous for the legal departments to allow sharing but still
be useful. (I won't be holding my breath)

A concrete thing without any "hard" bits There is an open source tool named
Protege that is ... err... the best tool of its class ... fix it or make a
replacement

[][https://protege.stanford.edu/](https://protege.stanford.edu/)

~~~
optymizer
I worked for 5+ years for a PI at a prestigious institution.

Overall my experience there was great. It was a lot of fun too. I got to
design and implement fairly large projects early on as a junior engineer. I
could use any tech that I wanted. I had maybe two dozen users at best, but I
interacted with them weekly if not daily.

That said, I was barely making 50k. Now I'm a senior engineer at a FAANG and
though I am more financially stable, I am not having as much fun. I routinely
push code to millions of users now, but I don't see any of them.

I suppose the FAANG is a different kind of fun, but sometimes I just miss
being the guy who's coding this awesome tool that's going to further
scientific research, and your post reminded me of that.

Maybe when I retire I'll go back to help some PIs with their software issues.
I know they need the help.

~~~
iandanforth
To put you on the spot. It would be great if "maybe when I retire ..." was an
actual plan you had. It sounds like you have the opportunity and ability to
personally make a difference, I sincerely hope you do. :)

~~~
optymizer
Thanks for the vote of confidence. I think it's early to make concrete plans
though. I have a few other ideas to try out before I turn to academic
research.

------
tejtm
TFA
[https://www.nature.com/articles/s41586-020-1969-6](https://www.nature.com/articles/s41586-020-1969-6)

or

DOI
[https://doi.org/10.1038/s41586-020-1969-6](https://doi.org/10.1038/s41586-020-1969-6)

------
Expez
> Scientists also developed a way of "carbon dating" mutations. They showed
> that more than a fifth of them occurred years or even decades before a
> cancer is found.

> He added: "Unlocking these patterns means it should now be possible to
> develop new diagnostic tests, that pick up signs of cancer much earlier."

The journalist probably pressed this last point, because it can't possibly be
true in a practical sense. Even if you can detect these changes early on in
cells, we can't possibly test every cell in the body for mutations on e.g. a
yearly basis, right?

~~~
DrScientist
Correct. And even if you could, you would find everybody has some of these
potentially dangerous mutations somewhere.

The problem only comes if get the right combination in a single cell and then
the cells starts to multiply.

At that stage you might then be able to pick up evidence from circulating
tumor DNA (
[https://ghr.nlm.nih.gov/primer/testing/circulatingtumordna](https://ghr.nlm.nih.gov/primer/testing/circulatingtumordna)
) from a blood test.

~~~
allovernow
We'll hold on now. If we assume that mutations tend to cluster around cells
exposed to particular carcinogens, and assume there is some number N>≈5
mutations required, in theory we could look for cases where many cells present
with x% of the necessary mutations. And it becomes much easier to detect
because you presumably have many cells which mutate stochastically together.

~~~
DrScientist
You are describing a cervical smear test - target cells more likely to be
mutated - assume that if you find problem cells in your test ( after you have
destroyed during the test ) that there are similar ones still left in the body
( not because they were mutated together - but because they are related - one
cell inherited a mutation from another ).

So sure. That's done already and having a test which detects 'precancerous'
based on genetics _might_ be useful. One of the problems at the moment is the
treatment is often almost as bad as the cure - so you might only be able to
step up frequency of the tests.

The problem with this approach is only certain bits of the body are easily
accessible in this way - that's why people like the ctDNA tests - but they
have their own challenges.

Another non-destructive way would be imaging - either thermal ( cancer cells
are more active and so hotter than normal ), or using some sort of labelling
markers - however can't see a way to target arbitrary early genetic mutations
with this.

------
chacham15
I know that this is going to sound "flavor of the day," but seeing as how
genetics is essentially a large data set of variables and we aren't certain
about which of then are indicative of cancer, doesn't this seem to be very
strongly correlated with the problem that most ML/deep learning tries to
solve?

~~~
abhikshah
ML is fairly common in genomics, but for identifying predictive variables for
cancer status, it's difficult. The training set is a matrix where rows are
people (where some have cancer and some don't) and columns are genomic
features (mutation, methylation, etc). You can easily have hundreds of
thousands of features but getting even a thousand cancer patients enrolled in
a study and sequenced is expensive and slow.

So, even though there are many "AI in biotech" companies out there, for
predicting cancer status, most eventually end up hand crafting a small number
of features based on extensive knowledge of cancer biology. The ML model tends
to be simple and far less important than the features.

------
hd32
Now if we can get thousands of software devs to get together across orgs, and
develop a detailed picture of all possible software bugs then imagine...oh
wait we already do that...and we still have a zillion bugs on bug trackers the
world over.

How come?

As Gandhi said we "attach an exaggerated importance to prolonging mans earthly
existence"

The software industry has realized keeping old code alive (specifically by
fixing ancient bugs in outdated systems) creates more problems than it solves.
Sooner or later we will realize the same thing about Cancer.

------
rodiger
Haven't heard that before...

~~~
dang
" _Please don 't post shallow dismissals, especially of other people's work. A
good critical comment teaches us something._"

[https://news.ycombinator.com/newsguidelines.html](https://news.ycombinator.com/newsguidelines.html)

------
Gatsky
Nice work, very comprehensive， ‘A’ for effort, good for citing in reviews. The
results are well known from other studies (eg sequencing cancer precursor
lesions) and theoretical predictions over 40 years old.

They try to elevate the significance by saying the results could be useful in
early detection, but the companies doing early detection through circulating
tumour DNA have already moved on from looking at mutations to methylation and
other epigenetic changes.

