Literature DB >> 28677228

VEGF and TWIST1 in a 16-biomarker immunoprofile useful for prognosis of breast cancer patients.

Laura Schirosi1, Simona De Summa2, Stefania Tommasi2, Angelo Paradiso3, Giampietro Gasparini4, Ondina Popescu5, Giovanni Simone5, Anita Mangia1.   

Abstract

This study concerns the expression of biomarkers involved in diverse pathways, such as progression, DNA repair mechanisms and angiogenesis to establish an immunoprofile capable of characterizing sporadic versus familial breast cancers (BCs). The aim was to identify a patient subgroup with a different clinical outcome, which could then be directed towards new targeted therapies. Hierarchical cluster analysis (HCA) was carried out using the immunohistochemical score from tissue microarray sections of an initial cohort of 183 (88 sporadic and 95 familial) patients with invasive BC. For the survival analysis, only those patients with complete follow-up were considered. The HCA revealed a 16-protein immunoprofile, nine of which represent the core, as was also found when familial and sporadic BCs were analysed individually. The 16-biomarker immunoprofile was able to identify a group of patients (Group 1) with a more aggressive tumour phenotype. Survival analyses showed that VEGF+ /TWIST1- patients with familial BC of Group 1 tended to demonstrate a lower DFS than the VEGF- /TWIST1+ sporadic BC patients of Group 2 (p = 0.052). Moreover, the entire cohort of VEGF+ /TWIST1- patients showed a statistically worse DFS than the patients with VEGF- /TWIST1+ expression (p = 0.034). In conclusion, we found that tumour stratification based on an immunoprofile is useful to predict the patient clinical behaviour. In particular, our study indicates that the clustering of tumors on the basis of this immunoprofile suggests the possibility to differentiate familial from sporadic BCs and to clinically select those patients who are more likely to benefit from inhibition of the VEGF pathway.
© 2017 UICC.

Entities:  

Keywords:  TMA; biomarker; breast cancer; hierarchical clustering analysis; immunoprofile

Mesh:

Substances:

Year:  2017        PMID: 28677228     DOI: 10.1002/ijc.30868

Source DB:  PubMed          Journal:  Int J Cancer        ISSN: 0020-7136            Impact factor:   7.396


  8 in total

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  8 in total

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