INTRODUCTION: The use of bevacizumab combined with chemotherapy represents a recent advance in clinical oncology for significantly improving the survival of patients who have non-small cell lung cancer (NSCLC). There is an unmet need for biomarkers that can predict response to such treatment and identify patients sensitive to it. Our study was designed to investigate the predictive value of intratumoral microvascular density (MVD) in patients with NSCLC treated with bevacizumab. METHODS: Sixteen patients with NSCLC who underwent chemotherapy combined with bevacizumab were included into this study. Paraffin-embedded tumor samples were sectioned and stained immunohistochemically for the blood vessel markers CD34 and CD31 to characterize the intratumoral vasculature. A computerized image analysis program was used to quantitatively calculate the intratumoral MVD. Treatment response was evaluated by computed tomography scanning. RESULTS: Two types of blood vessels, undifferentiated (CD31*/CD34*) and differentiated (CD34*), were identified. A positive correlation was found between the largest percentage of tumor shrinkage and the MVD of undifferentiated (CD31*/CD34*) vessels, with Spearman correlation coefficient being 0.576 (p = 0.019). No correlation between tumor shrinkage and differentiated vessel MVD (CD34*) was found. Moreover, seven of the eight patients with more undifferentiated vessels showed a partial response, versus only one of the seven patients with fewer undifferentiated vessels (p = 0.009). CONCLUSIONS: There are two major types of microvessel in lung cancer vasculature. The MVD of undifferentiated vessels is a favorable predictor for patients with NSCLC treated with a chemotherapy regimen plus bevacizumab, with a higher MVD value correlating with better treatment response. Further studies are needed to verify the predictive role of MVD in treatment of NSCLC with bevacizumab.
INTRODUCTION: The use of bevacizumab combined with chemotherapy represents a recent advance in clinical oncology for significantly improving the survival of patients who have non-small cell lung cancer (NSCLC). There is an unmet need for biomarkers that can predict response to such treatment and identify patients sensitive to it. Our study was designed to investigate the predictive value of intratumoral microvascular density (MVD) in patients with NSCLC treated with bevacizumab. METHODS: Sixteen patients with NSCLC who underwent chemotherapy combined with bevacizumab were included into this study. Paraffin-embedded tumor samples were sectioned and stained immunohistochemically for the blood vessel markers CD34 and CD31 to characterize the intratumoral vasculature. A computerized image analysis program was used to quantitatively calculate the intratumoral MVD. Treatment response was evaluated by computed tomography scanning. RESULTS: Two types of blood vessels, undifferentiated (CD31*/CD34*) and differentiated (CD34*), were identified. A positive correlation was found between the largest percentage of tumor shrinkage and the MVD of undifferentiated (CD31*/CD34*) vessels, with Spearman correlation coefficient being 0.576 (p = 0.019). No correlation between tumor shrinkage and differentiated vessel MVD (CD34*) was found. Moreover, seven of the eight patients with more undifferentiated vessels showed a partial response, versus only one of the seven patients with fewer undifferentiated vessels (p = 0.009). CONCLUSIONS: There are two major types of microvessel in lung cancer vasculature. The MVD of undifferentiated vessels is a favorable predictor for patients with NSCLC treated with a chemotherapy regimen plus bevacizumab, with a higher MVD value correlating with better treatment response. Further studies are needed to verify the predictive role of MVD in treatment of NSCLC with bevacizumab.
Authors: Jooae Choe; Sang Min Lee; Kyung-Hyun Do; Jung Bok Lee; Sang Min Lee; June-Goo Lee; Joon Beom Seo Journal: Eur Radiol Date: 2018-07-27 Impact factor: 5.315
Authors: S J An; Y S Huang; Z H Chen; J F Han; J J Yang; Q Zhou; Z Xie; Y Yang; H H Yan; Y L Wu Journal: Cancer Gene Ther Date: 2014-02-28 Impact factor: 5.987
Authors: Saadia A Aziz; Joshua Sznol; Adebowale Adeniran; John W Colberg; Robert L Camp; Harriet M Kluger Journal: J Transl Med Date: 2013-01-14 Impact factor: 5.531
Authors: A Giatromanolaki; M I Koukourakis; E Sivridis; K C Gatter; T Trarbach; G Folprecht; M M Shi; D Lebwohl; T Jalava; D Laurent; G Meinhardt; A L Harris Journal: Br J Cancer Date: 2012-08-21 Impact factor: 7.640
Authors: Saadia A Aziz; Joshua A Sznol; Laurence Albiges; Christopher Zito; Lucia B Jilaveanu; Robert L Camp; Bernard Escudier; Harriet M Kluger Journal: Cancer Cell Int Date: 2014-01-14 Impact factor: 5.722