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从乳腺 X 线摄影检测到的乳腺癌的细针吸取细胞学标本中进行高通量分子分析。

High-throughput molecular analysis from leftover of fine needle aspiration cytology of mammographically detected breast cancer.

机构信息

Department of Biomedical Sciences and Human Oncology, University of Turin, Turin, Italy.

出版信息

Transl Oncol. 2012 Jun;5(3):180-9. doi: 10.1593/tlo.11343. Epub 2012 Jun 1.

Abstract

We investigated whether residual material from diagnostic smears of fine needle aspirations (FNAs) of mammographically detected breast lesions can be successfully used to extract RNA for reliable gene expression analysis. Twenty-eight patients underwent FNA of breast lesions under ultrasonographic guidance. After smearing slides for cytology, residual cells were rinsed with TRIzol to recover RNA. RNA yield ranged from 0.78 to 88.40 µg per sample. FNA leftovers from 23 nonpalpable breast cancers were selected for gene expression profiling using oligonucleotide microarrays. Clusters generated by global expression profiles partitioned samples in well-distinguished subgroups that overlapped with clusters obtained using "biologic scores" (cytohistologic variables) and differed from clusters based on "technical scores" (RNA/complementary RNA/microarray quality). Microarray profiling used to measure the grade of differentiation and estrogen receptor and ERBB2/HER2 status reflected the results obtained by histology and immunohistochemistry. Given that proliferative status in the FNA material is not always assessable, we designed and performed on FNA leftover a multiprobe genomic signature for proliferation genes that strongly correlated with the Ki67 index examined on histologic material. These findings show that cells residual to cytologic smears of FNA are suitable for obtaining high-quality RNA for high-throughput analysis even when taken from small nonpalpable breast lesions.

摘要

我们研究了从乳腺影像学检查发现的病变的细针穿刺抽吸术(FNA)的诊断涂片的残留材料是否可以成功地用于提取 RNA 进行可靠的基因表达分析。28 名患者在超声引导下进行了乳腺病变的 FNA。在细胞学涂片后,用 TRIzol 冲洗残留细胞以回收 RNA。每个样本的 RNA 产量范围从 0.78 到 88.40µg。选择 23 例不可触及乳腺癌的 FNA 残留物进行寡核苷酸微阵列的基因表达谱分析。使用全局表达谱生成的聚类将样本分为明显的亚组,这些亚组与使用“生物学评分”(细胞组织学变量)获得的聚类重叠,并与基于“技术评分”(RNA/互补 RNA/微阵列质量)的聚类不同。用于测量分化程度和雌激素受体和 ERBB2/HER2 状态的微阵列分析反映了组织学和免疫组织化学的结果。鉴于 FNA 材料中的增殖状态并非总是可评估的,我们设计并在 FNA 残留物上进行了用于增殖基因的多探针基因组特征分析,该分析与在组织学材料上检查的 Ki67 指数强烈相关。这些发现表明,即使从小的不可触及的乳腺病变中获得,细胞学涂片的残留细胞也适合用于获得高质量的 RNA 进行高通量分析。

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