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自动预后模式检测显示滤泡性淋巴瘤中FOXP3(+)调节性T细胞呈良好的弥漫性模式。

Automated prognostic pattern detection shows favourable diffuse pattern of FOXP3(+) Tregs in follicular lymphoma.

作者信息

Nelson Lilli S, Mansfield James R, Lloyd Roslyn, Oguejiofor Kenneth, Salih Zena, Menasce Lia P, Linton Kim M, Rose Chris J, Byers Richard J

机构信息

Medical School, The University of Manchester, Oxford Road, Manchester M13 9PT, UK.

Perkin-Elmer, 68 Elm Street, Hopkinton, Massachusetts 01748, USA.

出版信息

Br J Cancer. 2015 Oct 20;113(8):1197-205. doi: 10.1038/bjc.2015.291. Epub 2015 Oct 6.

Abstract

BACKGROUND

Histopathological prognostication relies on morphological pattern recognition, but as numbers of biomarkers increase, human prognostic pattern-recognition ability decreases. Follicular lymphoma (FL) has a variable outcome, partly determined by FOXP3 Tregs. We have developed an automated method, hypothesised interaction distribution (HID) analysis, to analyse spatial patterns of multiple biomarkers which we have applied to tumour-infiltrating lymphocytes in FL.

METHODS

A tissue microarray of 40 patient samples was used in triplex immunohistochemistry for FOXP3, CD3 and CD69, and multispectral imaging used to determine the numbers and locations of CD3(+), FOXP3/CD3(+) and CD69/CD3(+) T cells. HID analysis was used to identify associations between cellular pattern and outcome.

RESULTS

Higher numbers of CD3(+) (P=0.0001), FOXP3/CD3(+) (P=0.0031) and CD69/CD3(+) (P=0.0006) cells were favourable. Cross-validated HID analysis of cell pattern identified patient subgroups with statistically significantly different survival (35.5 vs 142 months, P=0.00255), a more diffuse pattern associated with favourable outcome and an aggregated pattern with unfavourable outcome.

CONCLUSIONS

A diffuse pattern of FOXP3 and CD69 positivity was favourable, demonstrating ability of HID analysis to automatically identify prognostic cellular patterns. It is applicable to large numbers of biomarkers, representing an unsupervised, automated method for identification of undiscovered prognostic cellular patterns in cancer tissue samples.

摘要

背景

组织病理学预后判断依赖于形态学模式识别,但随着生物标志物数量的增加,人类的预后模式识别能力会下降。滤泡性淋巴瘤(FL)的预后各不相同,部分由FOXP3调节性T细胞决定。我们开发了一种自动化方法,即假设相互作用分布(HID)分析,以分析多种生物标志物的空间模式,并将其应用于FL中的肿瘤浸润淋巴细胞。

方法

使用包含40个患者样本的组织微阵列进行FOXP3、CD3和CD69的三重免疫组织化学检测,并利用多光谱成像确定CD3(+)、FOXP3/CD3(+)和CD69/CD3(+) T细胞的数量和位置。采用HID分析来确定细胞模式与预后之间的关联。

结果

CD3(+)(P=0.0001)、FOXP3/CD3(+)(P=0.0031)和CD69/CD3(+)(P=0.0006)细胞数量较多预示着预后良好。对细胞模式进行交叉验证的HID分析确定了生存时间具有统计学显著差异的患者亚组(35.5个月对142个月,P=0.00255),更弥散的模式与良好预后相关,而聚集模式与不良预后相关。

结论

FOXP3和CD69阳性的弥散模式预示着预后良好,这表明HID分析能够自动识别预后细胞模式。它适用于大量生物标志物,代表了一种用于识别癌症组织样本中未发现的预后细胞模式的无监督自动化方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e179/4647874/ae484f51cdc0/bjc2015291f1.jpg

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