Aggregated Molecular Phenotype Scores: Enhancing Assessment and Visualization of Mass Spectrometry Imaging Data for Tissue-Based Diagnostics.
Aggregated Molecular Phenotype Scores: Enhancing Assessment and Visualization of Mass Spectrometry Imaging Data for Tissue-Based Diagnostics.
复制标题
汇总分子表型评分：增强基于组织诊断的质谱成像数据的评估和可视化。
DOI：
10.1021/acs.analchem.3c02389
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发表时间：
2023-08-29
影响因子：
7.4
通讯作者：
Baker, Erin S.
中科院分区：
文献类型：
--
作者：
Chappel, Jessie R.;King, Mary E.;Fleming, Jonathon;Eberlin, Livia S.;Reif, David M.;Baker, Erin S.
质谱成像 (MSI) 由于能够识别和可视化异质样本中不同表型特有的分子特征，因此在基于组织的诊断中越来越受欢迎。 MSI 实验的数据通常使用各种监督和非监督统计方法进行评估和可视化。然而，这些方法往往无法识别和简洁地可视化微妙的、与表型相关的分子变化。为了解决这些缺点，我们开发了聚合分子表型（AMP）评分。 AMP 分数是使用集成机器学习方法生成的，首先选择区分表型的特征，使用逻辑回归对特征进行加权，然后结合权重和特征丰度。然后，AMP 分数在 0 和 1 之间缩放，较低的值通常对应于 1 类表型（通常为对照），较高的分数与 2 类表型相关。因此，AMP 分数允许同时评估多个特征，并展示这些特征与各种表型的相关程度。由于采用集成方法，AMP 评分能够克服与单个模型相关的限制，从而实现高诊断准确性和可解释性。此处，使用从解吸电喷雾电离 MSI 收集的代谢组数据评估 AMP 评分表现。人体癌组织与正常或良性组织的初步比较表明，AMP 评分能够以高精度、敏感性和特异性区分表型。此外，当与空间坐标相结合时，AMP 评分可以在一张具有明显表型边界的图谱中可视化组织切片，突出其诊断实用性。
Mass spectrometry imaging (MSI) has gained increasing popularity for tissue-based diagnostics due to its ability to identify and visualize molecular characteristics unique to different phenotypes within heterogeneous samples. Data from MSI experiments are often assessed and visualized using various supervised and unsupervised statistical approaches. However, these approaches tend to fall short in identifying and concisely visualizing subtle, phenotype-relevant molecular changes. To address these shortcomings, we developed aggregated molecular phenotype (AMP) scores. AMP scores are generated using an ensemble machine learning approach to first select features differentiating phenotypes, weight the features using logistic regression, and combine the weights and feature abundances. AMP scores are then scaled between 0 and 1, with lower values generally corresponding to class 1 phenotypes (typically control) and higher scores relating to class 2 phenotypes. AMP scores, therefore, allow the evaluation of multiple features simultaneously and showcase the degree to which these features correlate with various phenotypes. Due to the ensembled approach, AMP scores are able to overcome limitations associated with individual models, leading to high diagnostic accuracy and interpretability. Here, AMP score performance was evaluated using metabolomic data collected from desorption electrospray ionization MSI. Initial comparisons of cancerous human tissues to their normal or benign counterparts illustrated that AMP scores distinguished phenotypes with high accuracy, sensitivity, and specificity. Furthermore, when combined with spatial coordinates, AMP scores allow visualization of tissue sections in one map with distinguished phenotypic borders, highlighting their diagnostic utility.
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影响因子：
7.4
作者：
Porcari AM;Zhang J;Garza KY;Rodrigues-Peres RM;Lin JQ;Young JH;Tibshirani R;Nagi C;Paiva GR;Carter SA;Sarian LO;Eberlin MN;Eberlin LS
通讯作者：
Eberlin LS
影响因子：
9.3
作者：
Ifa DR;Eberlin LS
通讯作者：
Eberlin LS
影响因子：
4.6
作者：
Igbokwe, Anne;Lopez-Terrada, Dolores H.
通讯作者：
Lopez-Terrada, Dolores H.
影响因子：
6
作者：
Pes, Barbara
通讯作者：
Pes, Barbara
影响因子：
4.1
作者：
Pell, Robert;Oien, Karin;Morden, James
通讯作者：
Morden, James