Identification of "BRAF-Positive" Cases Based on Whole-Slide Image Analysis

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14310%2F17%3A00097871" target="_blank" >RIV/00216224:14310/17:00097871 - isvavai.cz</a>

Result on the web

<a href="http://dx.doi.org/10.1155/2017/3926498" target="_blank" >http://dx.doi.org/10.1155/2017/3926498</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1155/2017/3926498" target="_blank" >10.1155/2017/3926498</a>

Result language

angličtina

Original language name

Identification of "BRAF-Positive" Cases Based on Whole-Slide Image Analysis

Original language description

A key requirement for precision medicine is the accurate identification of patients that would respond to a specific treatment or those that represent a high-risk group, and a plethora of molecular biomarkers have been proposed for this purpose during the last decade. Their application in clinical settings, however, is not always straightforward due to relatively high costs of some tests, limited availability of the biological material and time, and procedural constraints. Hence, there is an increasing interest in constructing tissue-based surrogate biomarkers that could be applied with minimal overhead directly to histopathology images and which could be used for guiding the selection of eventual further molecular tests. In the context of colorectal cancer, we present a method for constructing a surrogate biomarker that is able to predict with high accuracy whether a sample belongs to the "BRAF-positive" group, a high-risk group comprising V600E BRAF mutants and BRAF-mutant-like tumors. Our model is trained to mimic the predictions of a 64-gene signature, the current definition of BRAF-positive group, thus effectively identifying histopathology image features that can be linked to a molecular score. Since the only required input is the routine histopathology image, the model can easily be integrated in the diagnostic workflow.

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

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

<a href="/en/project/LM2015085" target="_blank" >LM2015085: CERIT Scientific Cloud</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Publication year

2017

Confidentiality

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

Name of the periodical

Biomed Research International

ISSN

2314-6133

e-ISSN

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Volume of the periodical

Neuveden

Issue of the periodical within the volume

April

Country of publishing house

US - UNITED STATES

Number of pages

7

Pages from-to

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UT code for WoS article

000399970000001

EID of the result in the Scopus database

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