Tanja Belčič Mikič (Avtor), Tadej Pajič (Avtor), Samo Zver (Avtor), Matjaž Sever (Avtor)

Povzetek

CALR mutations are a revolutionary discovery and represent an important hallmark of myeloproliferative neoplasms (MPN), especially essential thrombocythemia and primary myelofibrosis. To date, several CALR mutations were identified, with only frameshift mutations linked to the diseased phenotype. It is of diagnostic and prognostic importance to properly define the type of CALR mutation and subclassify it according to its structural similarities to the classical mutations, a 52-bp deletion (type 1 mutation) and a 5-bp insertion (type 2 mutation), using a statistical approximation algorithm (AGADIR). Today, the knowledge on the pathogenesis of CALR-positive MPN is expanding and several cellular mechanisms have been recognized that finally cause a clonal hematopoietic expansion. In this review, we discuss the current basis of the cellular effects of CALR mutants and the understanding of its implementation in the current diagnostic laboratorial and medical practice. Different methods of CALR detection are explained and a diagnostic algorithm is shown that aids in the approach to CALR-positive MPN. Finally, contemporary methods joining artificial intelligence in accordance with molecular-genetic biomarkers in the approach to MPN are presented.

Ključne besede

kalcij;mieloproliferativne neoplazme;diagnostika;trombocitemija;umetna inteeligenca;calreticulin;chaperone;calcium;myeloproliferative neoplasm;diagnostics;thrombocythemia;artificial intelligence;

Podatki

Jezik: Angleški jezik
Leto izida:
Tipologija: 1.02 - Pregledni znanstveni članek
Organizacija: UL MF - Medicinska fakulteta
UDK: 616.1
COBISS: 57640451 Povezava se bo odprla v novem oknu
ISSN: 1422-0067
Št. ogledov: 123
Št. prenosov: 40
Ocena: 0 (0 glasov)
Metapodatki: JSON JSON-RDF JSON-LD TURTLE N-TRIPLES XML RDFA MICRODATA DC-XML DC-RDF RDF

Ostali podatki

Sekundarni jezik: Slovenski jezik
Sekundarne ključne besede: kalcij;mieloproliferativne neoplazme;diagnostika;trombocitemija;umetna inteligenca;
Vrsta dela (COBISS): Članek v reviji
Strani: str. 1-16
Letnik: ǂVol. ǂ22
Zvezek: ǂiss. ǂ7
Čas izdaje: 2021
DOI: 10.3390/ijms22073371
ID: 14657165
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