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辅助淋巴结和口腔细胞的 p-和 q-个体染色体中的新型进化模型和周期表。

Novel evolutionary models and periodic charts in p- and q-individual chromosomes of auxiliary lymph node and buccal cells.

机构信息

Department of Medical Genetics, School of Medicine, Tehran University of Medical Sciences, P.O. Box 14176-13151, Tehran, Iran.

Department of Surgery, Day General Hospital, Tehran, Iran ; Cancer Institute, Tehran University of Medical Sciences, Tehran, Iran.

出版信息

Dis Markers. 2013;35(6):833-45. doi: 10.1155/2013/570946. Epub 2013 Nov 28.

Abstract

Signal copy number (SCN) and signal intensity (SI) of subtelomeres (ST) are investigated in auxiliary lymph node (ALN) and buccal (BUC) cells by fluorescence in situ hybridization. The extracted total cell of 38256 and 2309 was, respectively, analyzed from the benign ALN- and BUC-cells of an affected breast cancer patient. The Periodic model was based on ST behavior including normal-, down-, and upregulated clones with diverse SCN. The arm-p/q ratio based signature, as a subtelomeric array, reflects discordance and concordance of ST-behavior within individual chromosomes as a concept of "Individualization of Cells" rather than "Global Insight of Cells". The Periodic charts could be considered as a reliable and refreshable platform through which the cellular evolution could be patterned and characterized. Signature of ST-profile in the BUC and ALN cells and the nature of diverse SCN and SI as quantitative and qualitative value led to modeling the real personalized perspective of cellular evolution. Protein expression of Ki67, Cyclin D1, and Cyclin E was assayed, as a complementary panel. These targets could be applied as the predictive and preventive markers for an early detection at BUC and ALN levels to plan the required managements in the breast cancer patients.

摘要

通过荧光原位杂交技术,研究了辅助淋巴结(ALN)和口腔(BUC)细胞中的信号拷贝数(SCN)和信号强度(SI)。从受影响乳腺癌患者的良性 ALN 和 BUC 细胞中分别提取了 38256 和 2309 个总细胞。周期性模型基于包括具有不同 SCN 的正常、下调和上调克隆的 ST 行为。基于臂 p/q 比的特征作为端粒阵列,反映了个体染色体内部 ST 行为的不一致和一致,这是一种“细胞个体化”的概念,而不是“细胞整体洞察”。周期性图表可以被认为是一个可靠和可更新的平台,通过它可以对细胞进化进行模式化和特征化。BUC 和 ALN 细胞中 ST 谱的特征以及不同 SCN 和 SI 的性质作为定量和定性值,导致对细胞进化的真实个性化视角进行建模。Ki67、Cyclin D1 和 Cyclin E 的蛋白表达也进行了检测,作为补充面板。这些靶点可作为 BUC 和 ALN 水平早期检测的预测和预防标志物,以计划乳腺癌患者的所需管理。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9472/3863476/f820f24bd679/DM35-06-570946.001.jpg

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