MmCMS: mouse models' consensus molecular subtypes of colorectal cancer.
MmCMS: mouse models' consensus molecular subtypes of colorectal cancer.
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DOI：
10.1038/s41416-023-02157-6
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发表时间：
2023-03
影响因子：
8.8
通讯作者：
Dunne PD
中科院分区：
文献类型：
--
作者：
Amirkhah R;Gilroy K;Malla SB;Lannagan TRM;Byrne RM;Fisher NC;Corry SM;Mohamed NE;Naderi-Meshkin H;Mills ML;Campbell AD;Ridgway RA;Ahmaderaghi B;Murray R;Llergo AB;Sanz-Pamplona R;Villanueva A;Batlle E;Salazar R;Lawler M;Sansom OJ;Dunne PD
结直肠癌（CRC）原发肿瘤在分子上分为四种一致的分子亚型（CMS1-4）。基因工程小鼠模型旨在忠实地模拟人类癌症的复杂性，并且在适当的情况下，代表理想的临床前系统来测试新的药物治疗。尽管它很重要，但由于缺乏可靠的方法，双物种分类一直受到限制。在这里，我们利用、开发和测试了一组用于人-小鼠结直肠癌组织CMS分类的选项。利用来自已建立的CRC肿瘤集合的转录数据，包括人类（TCGA队列，n = 577）和小鼠（n = 57，共n = 8个基因型）肿瘤，结合随机森林和最接近模板预测算法，以及基因本体集合，我们全面评估了一套新的双物种分类器的性能。我们开发了三种方法：MmCMS-A；基因级分类器MmCMS-B；本体级方法和MmCMS-C；一个包含多种生物和组织学信号级联的组合通路系统。尽管所有选择都可以识别与基质丰富的cms4样生物学相关的肿瘤，但MmCMS-A无法准确分类小鼠肿瘤中上皮样亚型（CMS2/3）的生物学基础。当将基于人类的转录分类器应用于小鼠肿瘤数据时，途径水平的分类器，而不是单个基因水平的系统，是最佳的。我们的R包使研究人员能够选择合适的人类CRC亚型小鼠模型进行实验测试。
Colorectal cancer (CRC) primary tumours are molecularly classified into four consensus molecular subtypes (CMS1–4). Genetically engineered mouse models aim to faithfully mimic the complexity of human cancers and, when appropriately aligned, represent ideal pre-clinical systems to test new drug treatments. Despite its importance, dual-species classification has been limited by the lack of a reliable approach. Here we utilise, develop and test a set of options for human-to-mouse CMS classifications of CRC tissue. Using transcriptional data from established collections of CRC tumours, including human (TCGA cohort; n = 577) and mouse (n = 57 across n = 8 genotypes) tumours with combinations of random forest and nearest template prediction algorithms, alongside gene ontology collections, we comprehensively assess the performance of a suite of new dual-species classifiers. We developed three approaches: MmCMS-A; a gene-level classifier, MmCMS-B; an ontology-level approach and MmCMS-C; a combined pathway system encompassing multiple biological and histological signalling cascades. Although all options could identify tumours associated with stromal-rich CMS4-like biology, MmCMS-A was unable to accurately classify the biology underpinning epithelial-like subtypes (CMS2/3) in mouse tumours. When applying human-based transcriptional classifiers to mouse tumour data, a pathway-level classifier, rather than an individual gene-level system, is optimal. Our R package enables researchers to select suitable mouse models of human CRC subtype for their experimental testing.
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影响因子：
12.3
作者：
Pfefferle AD;Herschkowitz JI;Usary J;Harrell JC;Spike BT;Adams JR;Torres-Arzayus MI;Brown M;Egan SE;Wahl GM;Rosen JM;Perou CM
通讯作者：
Perou CM
影响因子：
12.4
作者：
Linnekamp, Janneke F.;van Hooff, Sander R.;Medema, Jan Paul
通讯作者：
Medema, Jan Paul
影响因子：
50.3
作者：
Jackstadt, Rene;van Hooff, Sander R.;Sansom, Owen J.
通讯作者：
Sansom, Owen J.
影响因子：
16.6
作者：
Isella C;Brundu F;Bellomo SE;Galimi F;Zanella E;Porporato R;Petti C;Fiori A;Orzan F;Senetta R;Boccaccio C;Ficarra E;Marchionni L;Trusolino L;Medico E;Bertotti A
通讯作者：
Bertotti A
影响因子：
16.6
作者：
Yoshihara, Kosuke;Shahmoradgoli, Maria;Martinez, Emmanuel;Vegesna, Rahulsimham;Kim, Hoon;Torres-Garcia, Wandaliz;Trevino, Victor;Shen, Hui;Laird, Peter W.;Levine, Douglas A.;Carter, Scott L.;Getz, Gad;Stemke-Hale, Katherine;Mills, Gordon B.;Verhaak, Roel G. W.
通讯作者：
Verhaak, Roel G. W.