Question: pathogenicity predictors of cancer mutations
0
gravatar for Bogdan
7 weeks ago by
Bogdan340
Palo Alto, CA, USA
Bogdan340 wrote:

Dear all,

talking about the pathogenicity predictors on cancer mutations, what algorithms or meta-predictors would you recommend to use ? Among possible choices : CADD, MutationTaster, FATHMM, CHASM, Condel CanDrA , or any other predictors/meta-predictors.

thank you,

bogdan

ADD COMMENTlink modified 7 weeks ago by Kevin Blighe11k • written 7 weeks ago by Bogdan340
1

this just came out today: https://genomebiology.biomedcentral.com/articles/10.1186/s13059-017-1353-5

ADD REPLYlink written 7 weeks ago by Jeremy Leipzig17k

Great timing!

ADD REPLYlink written 7 weeks ago by Kevin Blighe11k
1

thank you gentlemen !

ADD REPLYlink written 7 weeks ago by Bogdan340

If you are additionally interested in creating PDB files from novel/mutated amino acid sequences, and then checking how protein conformation may have changed due to the mutation, then look at the Protein Model Portal. I have added this to my list below.

ADD REPLYlink modified 7 weeks ago • written 7 weeks ago by Kevin Blighe11k

Do you know if there is a paper that assesses the performance of this approach on somatic mutations? Analyzing mutational clustering in protein structures has shown to perform well, but I'm not aware of successful methods taking a pure biophysical/protein conformation approach for cancer.

ADD REPLYlink modified 7 weeks ago • written 7 weeks ago by Collin470

please take a look here : http://bioinformatics.burnham.org/pages/publication.html;

especially : https://www.ncbi.nlm.nih.gov/pubmed/28714987

or : https://academic.oup.com/nar/article/43/D1/D968/2438384

ADD REPLYlink written 7 weeks ago by Bogdan340
2

I tweaked the wording of my reply so it is less ambiguous. I was actually talking about the approach Kevin suggested by analyzing protein conformation changes when the actual amino acid is substituted in the protein structure. I actually know Eduard personally (the first author on the papers you linked), and I developed HotMAPS which looks at mutational clustering in protein structures (https://www.ncbi.nlm.nih.gov/pubmed/27197156 ).

ADD REPLYlink written 7 weeks ago by Collin470

Thank you for the link to HotMAPS. We have been doing some whole genome sequencing analysis and we hope to link at some moment the mutation to the changes in the protein conformation.

ADD REPLYlink written 7 weeks ago by Bogdan340

Hi Collin - great work. I will take a read.

ADD REPLYlink written 7 weeks ago by Kevin Blighe11k

Are you interested in somatic mutations or germline mutations? The answer depends on your intended use.

ADD REPLYlink written 7 weeks ago by Collin470

Thank you Collin for your question : we would primarily be interested in somatic mutations.

ADD REPLYlink written 7 weeks ago by Bogdan340

The top 4 I would recommend for missense mutations would be CHASM, CanDrA (version "plus", with "cancer-in-general"), FATHMM cancer, or ParsSNP. From examining prior benchmarks and my own benchmarks, these seem to perform better. Some methods which are designed for germline mutations are decent (eg., VEST3 and REVEL), but generally the cancer focused methods are better.

ADD REPLYlink written 7 weeks ago by Collin470

thank you Collin. For Cancer Somatic mutations, could we also use some pathogenicity predictors like CADD and MCAP ? (that initially have been designed for germline mutations) .

ADD REPLYlink written 7 weeks ago by Bogdan340

I've personally aggregated a set of 8 benchmarks for missense mutations comprising in vitro experiments, in vivo experiments, and literature curated databases (OncoKB). CADD and MCAP didn't perform as well.

ADD REPLYlink written 7 weeks ago by Collin470

Thank you. I will look into : CHASM, CanDrA, FATHMM cancer, or ParsSNP. Talking about REVEL -- does it do a good work on somatic mutations ?

ADD REPLYlink written 7 weeks ago by Bogdan340

It does the best that I've seen for methods not tailored to cancer/somatic mutations. I'd recommend to stick with the cancer specific predictors unless you need to assess some other type of alteration that is not missense.

ADD REPLYlink written 7 weeks ago by Collin470
8
gravatar for Kevin Blighe
7 weeks ago by
Kevin Blighe11k
London/Brazil
Kevin Blighe11k wrote:

Take your pick...

This is not a complete listing, as there are many more.

Missense predictions

Splice predictions

Protein modelling (from amino acid sequence)

[uses various modelling algorithms and produces PDB files, which can be loaded into protein viewers like Jmol]

-------------------------

For further reading:

ADD COMMENTlink modified 7 weeks ago • written 7 weeks ago by Kevin Blighe11k
1

thank you very much ;)

ADD REPLYlink written 7 weeks ago by Bogdan340
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