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Loupakis, Fotios; Biason, Paola; Prete, Alessandra Anna; Cremolini, Chiara; Pietrantonio, Filippo; Pella, Nicoletta; Dell'Aquila, Emanuela; Sperti, Elisa; Zichi, Clizia; Intini, Rossana; Dadduzio, Vincenzo; Schirripa, Marta; Bergamo, Francesca; Antoniotti, Carlotta; Morano, Federica; Cortiula, Francesco; De Maglio, Giovanna; Rimassa, Lorenza; Smiroldo, Valeria; Calvetti, Lorenzo; Aprile, Giuseppe; Salvatore, Lisa; Santini, Daniele; Munari, Giada; Salmaso, Roberta; Guzzardo, Vincenza; Mescoli, Claudia; Lonardi, Sara; Rugge, Massimo; Zagonel, Vittorina; Di Maio, Massimo; Fassan, Matteo
British journal of cancer, 10/2019, Letnik: 121, Številka: 7Journal Article
BRAF mutated metastatic colorectal cancer (mCRC) is a subtype (10%) with overall poor prognosis, but the clinical experience suggests a great heterogeneity in survival. It is still unexplored the real distribution of traditional and innovative biomarkers among BRAF mutated mCRC and which is their role in the improvement of clinical prediction of survival outcomes. Data and tissue specimens from 155 BRAF mutated mCRC patients treated at eight Italian Units of Oncology were collected. Specimens were analysed by means of immunohistochemistry profiling performed on tissue microarrays. Primary endpoint was overall survival (OS). CDX2 loss conferred worse OS (HR = 1.72, 95%CI 1.03-2.86, p = 0.036), as well as high CK7 expression (HR = 2.17, 95%CI 1.10-4.29, p = 0.026). According to Consensus Molecular Subtypes (CMS), CMS1 patients had better OS compared to CMS2-3/CMS4 (HR = 0.37, 95%CI 0.19-0.71, p = 0.003). Samples showing less TILs had worse OS (HR = 1.72, 95%CI 1.16-2.56, p = 0.007). Progression-free survival analyses led to similar results. At multivariate analysis, CK7 and CMS subgrouping retained their significant correlation with OS. The present study provides new evidence on how several well-established biomarkers perform in a homogenous BRAF mutated mCRC population, with important and independent information added to standard clinical prognosticators. These data could be useful to inform further translational research, for patients' stratification in clinical trials and in routine clinical practice to better estimate patients' prognosis.
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JCR | SNIP | JCR | SNIP | JCR | SNIP | JCR | SNIP |
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in: SICRIS
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