Literature DB >> 22968518

Relationship between high density of peritumoral lymphatic vessels and biological behavior of cervical cancer.

Song En-Lin1, Yu Wei-Wei, Xiong Xiao-Liang, Xu Juan.   

Abstract

OBJECTIVE: To investigate the relationship between lymphangiogenesis and lymphatic metastasis in cervical squamous carcinoma.
METHODS: Eighty cases of invasive cervical squamous cancer were selected as objects of our study. Double immunohistochemical staining with antibodies against lymphatic vessel endothelial hyaluronan receptor 1 and Ki-67 was used to label the lymphatic vessels and mark the proliferative lymphatic vessels in cervical squamous cancer. The peritumoral lymphatic vessel density and intratumoral lymphatic vessel density was assessed. The lymphatic vessels proliferation index was evaluated by calculating Ki-67 proliferation index (PI) to reflect the lymphangiogenesis of cervical squamous cancer. Then the correlation between lymphangiogenesis and clinicopathologic features of cervical squamous cancer was analyzed.
RESULTS: The LVD of cervical cancer (15.23 ± 3.6) was clearly higher than that of the adjacent normal cervical subepithelial tissues (9.9 ± 2.5, P < 0.001). The peritumoral lymphatic vessel density of cervical cancer (18.75 ± 4.3) was significantly higher than the intratumoral lymphatic vessel density of cervical cancer (11.71 ± 4.9, P < 0.001). Lymphatic PI (LPI) of cervical cancer (0.258 ± 0.07) was higher than that of the adjacent normal cervical subepithelial tissues (0.068 ± 0.08, P < 0.001). The peritumoral lymphatic vessel PI of cervical cancer (0.324 ± 0.06) was notably higher than the intratumoral lymphatic vessel PI of cervical cancer (0.232 ± 0.06, P < 0.001). Peritumoral lymphatic vessel density and peritumoral lymphatic vessel were clearly associated with the lymph node metastasis (P = 0.001 and P = 0.002, respectively) and lymphovascular space invasion (P = 0.024 and P = 0.01, respectively).
CONCLUSIONS: The high density of peritumoral lymphatic vessels is a potential predictor of more aggressive phenotype of cervical squamous cancer.

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Year:  2012        PMID: 22968518     DOI: 10.1097/IGC.0b013e31826aa702

Source DB:  PubMed          Journal:  Int J Gynecol Cancer        ISSN: 1048-891X            Impact factor:   3.437


  1 in total

1.  A multi-scanner study of MRI radiomics in uterine cervical cancer: prediction of in-field tumor control after definitive radiotherapy based on a machine learning method including peritumoral regions.

Authors:  Akiyo Takada; Hajime Yokota; Miho Watanabe Nemoto; Takuro Horikoshi; Jun Matsushima; Takashi Uno
Journal:  Jpn J Radiol       Date:  2020-01-06       Impact factor: 2.374

  1 in total

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