Chakraborty Priyanka, George Jason T, Woodward Wendy A, Levine Herbert, Jolly Mohit Kumar
Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India.
Center for Theoretical Biological Physics, Rice University, Houston, TX 77005, USA; Medical Scientist Training Program, Baylor College of Medicine, Houston, TX 77005, USA.
Transl Oncol. 2021 Apr;14(4):101026. doi: 10.1016/j.tranon.2021.101026. Epub 2021 Jan 31.
Inflammatory breast cancer (IBC) is a highly aggressive breast cancer that metastasizes largely via tumor emboli, and has a 5-year survival rate of less than 30%. No unique genomic signature has yet been identified for IBC nor has any specific molecular therapeutic been developed to manage the disease. Thus, identifying gene expression signatures specific to IBC remains crucial. Here, we compare various gene lists that have been proposed as molecular footprints of IBC using different clinical samples as training and validation sets and using independent training algorithms, and determine their accuracy in identifying IBC samples in three independent datasets. We show that these gene lists have little to no mutual overlap, and have limited predictive accuracy in identifying IBC samples. Despite this inconsistency, single-sample gene set enrichment analysis (ssGSEA) of IBC samples correlate with their position on the epithelial-hybrid-mesenchymal spectrum. This positioning, together with ssGSEA scores, improves the accuracy of IBC identification across the three independent datasets. Finally, we observed that IBC samples robustly displayed a higher coefficient of variation in terms of EMT scores, as compared to non-IBC samples. Pending verification that this patient-to-patient variability extends to intratumor heterogeneity within a single patient, these results suggest that higher heterogeneity along the epithelial-hybrid-mesenchymal spectrum can be regarded to be a hallmark of IBC and a possibly useful biomarker.
炎性乳腺癌（IBC）是一种侵袭性很强的乳腺癌，主要通过肿瘤栓子转移，5年生存率低于30%。目前尚未确定IBC的独特基因组特征，也未开发出任何特定的分子疗法来治疗该疾病。因此，确定IBC特有的基因表达特征仍然至关重要。在这里，我们使用不同的临床样本作为训练集和验证集，并使用独立的训练算法，比较了各种被提议作为IBC分子足迹的基因列表，并确定它们在三个独立数据集中识别IBC样本的准确性。我们发现这些基因列表几乎没有相互重叠，在识别IBC样本方面的预测准确性有限。尽管存在这种不一致性，但IBC样本的单样本基因集富集分析（ssGSEA）与其在上皮-混合-间充质谱系上的位置相关。这种定位以及ssGSEA评分提高了在三个独立数据集中识别IBC的准确性。最后，我们观察到，与非IBC样本相比，IBC样本在EMT评分方面的变异系数明显更高。在确认这种患者间的变异性是否扩展到单个患者的肿瘤内异质性之前，这些结果表明，上皮-混合-间充质谱系上更高的异质性可被视为IBC的一个标志，也是一个可能有用的生物标志物。
