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从全血转录组测量预测乳腺癌转移。

Predicting breast cancer metastasis from whole-blood transcriptomic measurements.

机构信息

Department of Computer Science, UiT - The Arctic University of Norway, Tromsø, Norway.

Laboratoire MAP5 (UMR CNRS 8145), Université Paris Descartes, Université de Paris, Paris, France.

出版信息

BMC Res Notes. 2020 May 20;13(1):248. doi: 10.1186/s13104-020-05088-0.

Abstract

OBJECTIVE

In this exploratory work we investigate whether blood gene expression measurements predict breast cancer metastasis. Early detection of increased metastatic risk could potentially be life-saving. Our data comes from the Norwegian Women and Cancer epidemiological cohort study. The women who contributed to these data provided a blood sample up to a year before receiving a breast cancer diagnosis. We estimate a penalized maximum likelihood logistic regression. We evaluate this in terms of calibration, concordance probability, and stability, all of which we estimate by the bootstrap.

RESULTS

We identify a set of 108 candidate predictor genes that exhibit a fold change in average metastasized observation where there is none for the average non-metastasized observation.

摘要

目的

在这项探索性工作中,我们研究血液基因表达测量是否可以预测乳腺癌转移。早期发现转移风险增加可能具有挽救生命的潜力。我们的数据来自挪威妇女与癌症的流行病学队列研究。提供这些数据的女性在接受乳腺癌诊断前一年提供了血液样本。我们估计了惩罚最大似然逻辑回归。我们根据.bootstrap 来评估校准、一致性概率和稳定性。

结果

我们确定了一组 108 个候选预测基因,它们在平均转移观察中表现出折叠变化,而在平均非转移观察中则没有。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bc48/7238609/076aa8c23ab2/13104_2020_5088_Fig1_HTML.jpg

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