PredictONCO: A web tool supporting decision-making in precision oncology by extending the bioinformatics predictions with advanced computing and machine learning

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F65269705%3A_____%2F23%3A00079453" target="_blank" >RIV/65269705:_____/23:00079453 - isvavai.cz</a>

Alternative codes found

RIV/00159816:_____/24:00079453 RIV/00216224:14310/24:00135293

Result on the web

<a href="https://academic.oup.com/bib/article/25/1/bbad441/7463300" target="_blank" >https://academic.oup.com/bib/article/25/1/bbad441/7463300</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1093/bib/bbad441" target="_blank" >10.1093/bib/bbad441</a>

Result language

angličtina

Original language name

PredictONCO: A web tool supporting decision-making in precision oncology by extending the bioinformatics predictions with advanced computing and machine learning

Original language description

PredictONCO 1.0 is a unique web server that analyzes effects of mutations on proteins frequently altered in various cancer types. The server can assess the impact of mutations on the protein sequential and structural properties and apply a virtual screening to identify potential inhibitors that could be used as a highly individualized therapeutic approach, possibly based on the drug repurposing. PredictONCO integrates predictive algorithms and state-of-the-art computational tools combined with information from established databases. The user interface was carefully designed for the target specialists in precision oncology, molecular pathology, clinical genetics and clinical sciences. The tool summarizes the effect of the mutation on protein stability and function and currently covers 44 common oncological targets. The binding affinities of Food and Drug Administration/ European Medicines Agency -approved drugs with the wild-type and mutant proteins are calculated to facilitate treatment decisions. The reliability of predictions was confirmed against 108 clinically validated mutations. The server provides a fast and compact output, ideal for the often time-sensitive decision-making process in oncology. Three use cases of missense mutations, (i) K22A in cyclin-dependent kinase 4 identified in melanoma, (ii) E1197K mutation in anaplastic lymphoma kinase 4 identified in lung carcinoma and (iii) V765A mutation in epidermal growth factor receptor in a patient with congenital mismatch repair deficiency highlight how the tool can increase levels of confidence regarding the pathogenicity of the variants and identify the most effective inhibitors. The server is available at https://loschmidt.chemi.muni.cz/predictonco.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

10609 - Biochemical research methods

Project

Result was created during the realization of more than one project. More information in the Projects tab.

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2023

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Briefings in Bioinformatics

ISSN

1467-5463

e-ISSN

1477-4054

Volume of the periodical

25

Issue of the periodical within the volume

1

Country of publishing house

US - UNITED STATES

Number of pages

10

Pages from-to

"bbad441"

UT code for WoS article

001173375300096

EID of the result in the Scopus database

2-s2.0-85180282604