Literature DB >> 12817881

Angiogenesis as determined by computerised image analysis and the risk of early relapse in women with invasive ductal breast carcinoma.

Sławomir Olewniczak1, Maria Chosia, Blanka Kołodziej, Artur Kwas, Andrzej Kram, Wenancjusz Domagała.   

Abstract

The purpose of this study was to define the value of angiogenesis as a prognostic factor indicating early relapse. We assessed the relationship between parameters of angiogenesis (microvessel count--MVC, microvessel area--MVA and microvessel perimeter--MVP) and relapse-free survival at 50 months in 226 women with invasive ductal breast carcinoma. Anti CD31 antibody was used as a marker of endothelial cells. Microvessel density was measured according to Weidner et al. using a computerised image analysis. The mean parameters of angiogenesis were significantly higher in women with relapse than in those without recurrence within 50 months after surgery. In node negative patients relapse did not occur if MVC was below 38.7. In node-negative subgroup with grade II carcinomas parameters of angiogenesis in the primary tumour differed significantly depending on the presence or absence of relapse. Univariate and multivariate analysis showed the prognostic value of angiogenesis parameters in all study groups with respect to 50-month relapse-free survival. In node negative subgroup only 62.5% of women with tumors with high MVC and as much as 94.9% with low MVC survived 50 months without recurrence. In the Cox analysis of node-negative subgroup only MVC, MVP and MVA were the independent prognostic factors. In women with node-negative disease the evaluation of angiogenesis can identify a subgroup of patients with high risk of relapse, hence it may help in decisions concerning adjuvant therapy. Computerised image analysis is a good and objective technique for evaluating the intensity of angiogenesis in breast cancer.

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Year:  2003        PMID: 12817881

Source DB:  PubMed          Journal:  Pol J Pathol        ISSN: 1233-9687            Impact factor:   1.072


  7 in total

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6.  Targeting neuropilin-1 to inhibit VEGF signaling in cancer: Comparison of therapeutic approaches.

Authors:  Feilim Mac Gabhann; Aleksander S Popel
Journal:  PLoS Comput Biol       Date:  2006-11-16       Impact factor: 4.475

7.  Compartment model predicts VEGF secretion and investigates the effects of VEGF trap in tumor-bearing mice.

Authors:  Stacey D Finley; Manjima Dhar; Aleksander S Popel
Journal:  Front Oncol       Date:  2013-07-30       Impact factor: 6.244

  7 in total

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