RGD Reference Report - Computational development of a molecular-based approach to improve risk stratification of endometrial cancer patients. - Rat Genome Database

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Computational development of a molecular-based approach to improve risk stratification of endometrial cancer patients.

Authors: Torricelli, Federica  Nicoli, Davide  Bellazzi, Riccardo  Ciarrocchi, Alessia  Farnetti, Enrico  Mastrofilippo, Valentina  Zamponi, Raffaella  La Sala, Giovanni Battista  Casali, Bruno  Mandato, Vincenzo Dario 
Citation: Torricelli F, etal., Oncotarget. 2018 May 22;9(39):25517-25528. doi: 10.18632/oncotarget.25354. eCollection 2018 May 22.
RGD ID: 13673916
Pubmed: PMID:29876005   (View Abstract at PubMed)
PMCID: PMC5986657   (View Article at PubMed Central)
DOI: DOI:10.18632/oncotarget.25354   (Journal Full-text)

Histological classification and staging are the gold standard for the prognosis of endometrial cancer (EC). However, in morphologically intermediate and doubtful cases this approach results largely insufficient, defining the need for better classification criteria. In this work we developed an algorithm that based on EC genetic alterations and in combination with the current histological classification, improves EC patients prognostic stratification, in particular in doubtful cases. A panel of 26 cancer related genes was analyzed in 89 EC patients and somatic functional mutations were investigated in association with different histology and outcome. An unsupervised hierarchical clustering analysis revealed that two groups of patients with different tumor grade and different prognosis can be distinguished by mutational profile. In particular, the mutational status of APC, CTNNB1, PIK3CA, PTEN, SMAD4 and TP53 resulted to be principal drivers of prognostic clustering. Consistently, a decisional tree generated by a data mining approach summarizes the consequential molecular criteria for patients prognostic stratification. The model proposed by this work provides the clinician with a tool able to support the prognosis of EC patients and consequently drives the choice of the most appropriated therapeutic strategy and follow up.

RGD Manual Disease Annotations    Click to see Annotation Detail View
TermQualifierEvidenceWithReferenceNotesSourceOriginal Reference(s)
endometrial cancer severityIAGP 13673916DNA:mutations and haplotype:cds:multiple (human)RGD 
endometrial cancer severityISOAPC (Homo sapiens)13673916; 13673916DNA:mutations and haplotype:cds:multiple (human)RGD 

Objects Annotated

Genes (Rattus norvegicus)
Apc  (APC regulator of WNT signaling pathway)

Genes (Mus musculus)
Apc  (APC, WNT signaling pathway regulator)

Genes (Homo sapiens)
APC  (APC regulator of WNT signaling pathway)


Additional Information