The effect of the stromal component of breast tumours on prediction of clinical outcome using gene expression microarray analysis.
The effect of the stromal component of breast tumours on prediction of clinical outcome using gene expression microarray analysis.
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DOI：
10.1186/bcr1506
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发表时间：
2006
期刊：
影响因子：
--
通讯作者：
Dowsett M
中科院分区：
文献类型：
--
作者：
Cleator SJ;Powles TJ;Dexter T;Fulford L;Mackay A;Smith IE;Valgeirsson H;Ashworth A;Dowsett M
本研究的目的是检查活检细胞组成对乳腺肿瘤对新辅助阿霉素和环磷酰胺（AC）化疗反应的多基因预测因子错误率的影响。在 AC 之前对 43 名患者的原发性乳腺肿瘤进行了核心活检，并记录了随后的临床反应。其中 16 个样本可获得化疗后（第 21 天）样本。每个核心的冰冻切片用于估计三个水平上浸润性癌和其他组织成分的比例。使用包含 4,600 个元件的 cDNA 阵列进行转录分析。 23 名 (53%) 名患者表现出“良好”临床反应，20 名 (47%) 名患者表现出“差”临床反应。从这些患者收集的核心活检中，浸润性肿瘤的百分比存在显着差异。尽管如此，样本表达谱的聚集聚类表明，来自同一肿瘤的几乎所有活检样本都聚集为最近的邻居。 SAM（微阵列显着性分析）回归分析确定了 144 个基因，可区分高百分比和低百分比侵袭性肿瘤活检，错误发现率不超过 5%。使用治疗前活检的微阵列数据（留一法交叉验证）预测临床反应的错误分类误差为 28%。当对恶性细胞和基质细胞比例更均匀的样本子集进行预测时，错误分类误差要低得多（8%–13%，排列时 p < 0.05）。乳腺癌样本的非肿瘤含量对基因表达谱有显着影响。考虑这个因素可以提高通过表达阵列分析进行响应预测的准确性。未来的基因表达阵列预测研究应考虑到这一点。
The aim of this study was to examine the effect of the cellular composition of biopsies on the error rates of multigene predictors of response of breast tumours to neoadjuvant adriamycin and cyclophosphamide (AC) chemotherapy. Core biopsies were taken from primary breast tumours of 43 patients prior to AC, and subsequent clinical response was recorded. Post-chemotherapy (day 21) samples were available for 16 of these samples. Frozen sections of each core were used to estimate the proportion of invasive cancer and other tissue components at three levels. Transcriptional profiling was performed using a cDNA array containing 4,600 elements. Twenty-three (53%) patients demonstrated a 'good' and 20 (47%) a 'poor' clinical response. The percentage invasive tumour in core biopsies collected from these patients varied markedly. Despite this, agglomerative clustering of sample expression profiles showed that almost all biopsies from the same tumour aggregated as nearest neighbours. SAM (significance analysis of microarrays) regression analysis identified 144 genes which distinguished high- and low-percentage invasive tumour biopsies at a false discovery rate of not more than 5%. The misclassification error of prediction of clinical response using microarray data from pre-treatment biopsies (on leave-one-out cross-validation) was 28%. When prediction was performed on subsets of samples which were more homogeneous in their proportions of malignant and stromal cells, the misclassification error was considerably lower (8%–13%, p < 0.05 on permutation). The non-tumour content of breast cancer samples has a significant effect on gene expression profiles. Consideration of this factor improves accuracy of response prediction by expression array profiling. Future gene expression array prediction studies should be planned taking this into account.
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乳腺癌的分子分析：临床意义。
影响因子：
8.8
作者：
Cleator, S;Ashworth, A
通讯作者：
Ashworth, A
影响因子：
7.4
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50.5
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7.4
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