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Selective analysis of cancer-cell intrinsic transcriptional traits defines novel clinically relevant subtypes of colorectal cancer

Articolo
Data di Pubblicazione:
2017
Citazione:
Selective analysis of cancer-cell intrinsic transcriptional traits defines novel clinically relevant subtypes of colorectal cancer / Isella, Claudio; Brundu, Francesco Gavino; Bellomo, Sara E.; Galimi, Francesco; Zanella, Eugenia; Consalvo Petti, Roberta; Fiori, Alessandro; Orzan, Francesca; Senetta, Rebecca; Boccaccio, Carla; Ficarra, Elisa; Marchionni, Luigi; Trusolino, Livio; Medico, Enzo; Bertotti, Andrea. - In: NATURE COMMUNICATIONS. - ISSN 2041-1723. - 8:(2017), pp. 1-16. [10.1038/ncomms15107]
Abstract:
Stromal content heavily impacts the transcriptional classification of colorectal cancer (CRC), with clinical and biological implications. Lineage-dependent stromal transcriptional components could therefore dominate over more subtle expression traits inherent to cancer cells. Since in patient-derived xenografts (PDXs) stromal cells of the human tumour are substituted by murine counterparts, here we deploy human-specific expression profiling of CRC PDXs to assess cancer-cell intrinsic transcriptional features. Through this approach, we identify five CRC intrinsic subtypes (CRIS) endowed with distinctive molecular, functional and phenotypic peculiarities: (i) CRIS-A: mucinous, glycolytic, enriched for microsatellite instability or KRAS mutations; (ii) CRIS-B: TGF-β pathway activity, epithelial–mesenchymal transition, poor prognosis; (iii) CRIS-C: elevated EGFR signalling, sensitivity to EGFR inhibitors; (iv) CRIS-D: WNT activation, IGF2 gene overexpression and amplification; and (v) CRIS-E: Paneth cell-like phenotype, TP53 mutations. CRIS subtypes successfully categorize independent sets of primary and metastatic CRCs, with limited overlap on existing transcriptional classes and unprecedented predictive and prognostic performances.
Tipologia CRIS:
Articolo su rivista
Keywords:
Colon Rectal Cancer; CRC; cancer subtype classification; machine learning; NTP-based classifier; Non-negative Matrix Factorization (NMF); bioinformatics
Elenco autori:
Isella, Claudio; Brundu, Francesco Gavino; Bellomo, Sara E.; Galimi, Francesco; Zanella, Eugenia; Consalvo Petti, Roberta; Fiori, Alessandro; Orzan, Francesca; Senetta, Rebecca; Boccaccio, Carla; Ficarra, Elisa; Marchionni, Luigi; Trusolino, Livio; Medico, Enzo; Bertotti, Andrea
Autori di Ateneo:
FICARRA ELISA
Link alla scheda completa:
https://iris.unimore.it/handle/11380/1240334
Link al Full Text:
https://iris.unimore.it//retrieve/handle/11380/1240334/339026/ncomms15107.pdf
Pubblicato in:
NATURE COMMUNICATIONS
Journal
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URL

https://www.nature.com/articles/ncomms15107
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