康斯坦丁地区乳腺癌分子分类:一项流行病学研究

Sara Khelf, Leila Guedjali, S. Haddad, D. Satta
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乳腺癌(CS)是世界范围内最常见的女性癌症,其发病率和死亡率在阿尔及利亚排名第一。分子分类已区分出至少四种分子类型:luminal A, luminal B, HER2和basal-like。我们的目的是研究女性乳腺癌的表型特征,以及不同分子群的不同临床、免疫组织化学和治疗方面的差异。我们在2016年10月至2017年12月期间进行了回顾性研究。这项研究涉及121个文件。人群按年龄分布情况显示,受影响最大的年龄组为[53-63],占35%。分子分类结果显示,最常见的类型为管腔A型(37.19%),其次为管腔B型(27.27%)、基底样型(19.83%)和HER2型(15.70%)。表达[ER]的管腔型乳腺癌占所有乳腺癌的70 - 80%,其中以管腔A组最为常见,分别为58.5%和54.3%,而其他组之间存在差异。分子分类在治疗中起着非常重要的作用。这一结果表明,腔型A是最常见的,绝经后妇女最容易患乳腺癌。这种分类对于治疗的方向是非常重要的。由此产生的分子分类有望更好地对肿瘤进行个性化治疗。乳腺癌,分子分类,免疫组织化学,激素受体,HER2状态
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Molecular Classification of Breast Cancer in the Region of Constantine: An Epidemiological Study
Breast cancer (CS) is the most common female cancer worldwide, ranking first in Algeria for its frequency and mortality .Molecular classification has distinguished at least four molecular types: luminal A, luminal B, HER2 and basal-like. Our objective is to study the phenotypic profile of breast cancer in women with cancer as well as the different clinical, immunohistochemical and therapeutic aspects of different molecular groups.We undertook a retrospective study between October 2016 and December 2017. This study involved 121 files. The distribution of the population according to age showed that the most affected age group is [53-63] years old with 35%. Molecular classification results showed that the most common type was luminal A at 37.19%, followed by luminal type B at 27.27%, basal-like at 19.83%, and HER2 at 15.70%. Breast cancer of luminal type, expressing[ ER], accounts for 70 to 80% of all mammary carcinomas and that the luminal group A is the most common with proportions of 58 , 5% and 54.3% respectively while the distinction is observed in the other groups. Molecular classification plays a very important role in the treatment. This result shows that luminal type A is the most common, and that postmenopausal women are most likely to have breast cancer. This classification is very important in the orientation of the treatment. The resulting molecular classification is expected to better classify tumors to a personalized therapy. Breast cancer, molecular classification, immunohistochemistry, hormone receptors, HER2 status
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