Identifying better predictive and prognostic biomarkers for the diagnosis and treatment of triple negative breast cancer (TNBC) is complicated by tumor heterogeneity ranging from responses to therapy, mutational burden, and clonal evolution. To overcome the gap in our understanding of tumor heterogeneity, we hypothesized that isolating and studying the gene expression profile of invasive tumor cell subpopulations would be a crucial step towards achieving this goal. In this report, we utilized a fluidic device previously reported to be capable of supporting long-term three-dimensional growth and invasion dynamics of cancer cells. Live invading and matched non-invading SUM149 inflammatory breast cancer cells were enriched using this device and these two functionally distinct subpopulations were tested for differences in gene expression using a gene expression microarray. 305 target genes were identified to have altered expression in the invading cells compared to the non-invading tumoroid cells. Gene ontology analysis of the gene panel identified multiple biological roles ranging from extracellular matrix reorganization to modulation of the immune response and Rho signaling. Interestingly, the genes associated with the invasion front differ between different samples, consistent with inter- and intra-tumor heterogeneity. This work suggests the impact of heterogeneity in biomarker discovery should be considered as cancer therapy increasingly heads towards a personalized approach.

肿瘤异质性从响应到治疗，突变负担和克隆进化等方面都难以确定，从而可以更好地预测和预后诊断三阴性乳腺癌（TNBC）的生物标志物。为了克服我们对肿瘤异质性理解的空白，我们假设分离和研究侵袭性肿瘤细胞亚群的基因表达谱将是实现这一目标的关键步骤。在本报告中，我们利用了先前报道的能够支持癌细胞的长期三维生长和侵袭动态的流体装置。使用该装置富集了活侵袭和匹配的非侵袭性SUM149炎性乳腺癌细胞，并使用基因表达微阵列测试了这两个功能不同的亚群的基因表达差异。与非侵袭性类瘤细胞相比，鉴定出305个靶基因在侵袭性细胞中具有改变的表达。基因组的基因本体分析确定了多种生物学作用，范围从细胞外基质重组到免疫应答和Rho信号传导的调节。有趣的是，与入侵前沿相关的基因在不同样品之间不同，这与肿瘤间和肿瘤内异质性相一致。