Flexible multiplatform RNA profiling at the single cell level applied to enriched cancer initiating cells: RT-PCR

Accurate profiling of RNA expression of single cells is a valuable approach for broadening our understanding of cancer biology and mechanisms of dissemination, but requires the development of reliable methods for their molecular characterization. Here we evaluate a single cell methodology which generates microgram amounts of cDNA suitable for next generation sequencing (RNA-Seq), high throughput RT-qPCR and Affymetrix array analysis. The approach was tested by comparing expression profiles of amplified single MCF7 and MCF10A cells to profiles generated from unamplified RNA. The expression profiles were compared by Affymetrix-U133 arrays, RNA-Seq and high-density qPCR. There were strong cross-platform correlations of >80% and concordance between single cell and unamplified material of >70%. We exemplify the approach through analysis of rare sorted cancer initiating cells (CICs) derived from a NSCLC patient-derived xenograft. Populations of 10 cells from total tumour and two distinct subsets of CIC, putatively involved in primary tumor maintenance or metastasis formation were FACS sorted then directly amplified. CIC expression profiles strongly correlated with published stem-cell and epithelial-mesenchymal transition (EMT) signatures. Our results confirm the utility of the amplification system and our methodology to detect and distinguish RNA profiles in rare cell populations that inform on EMT and stem-cell characteristics. This GEO dataset comprises the RT-qPCR data for MCF7 and MCF10A unamplified cDNA from 1μg RNA, RNA-AMP cDNA from 1ng RNA and RNA-AMP cDNA from single cell samples. 22 samples. 3 biological replicates each for MCF7 cDNA generated from 1ng amplified RNA, MCF10A cDNA generated from 1ng amplified RNA, MCF7 cDNA generated from 1 μg unamplified RNA and MCF10A cDNA generated from 1 μg unamplified RNA. 5 biological replicates each for MCF7 cDNA generated from RNA amplified from a single cell and MCF10A cDNA generated from RNA amplified from a single cell. Expression of genes in MCF7 and MCF10A was compared in each of the sample types, and these results from each sample type were compared.

精准分析单细胞RNA表达谱，是加深我们对癌症生物学及肿瘤播散机制理解的重要手段，但目前仍需开发可靠的分子表征方法。本研究评估了一种单细胞实验方法，该方法可生成微克级的互补脱氧核糖核酸（cDNA），适用于下一代测序（RNA-Seq）、高通量实时定量聚合酶链式反应（RT-qPCR）以及Affymetrix芯片分析。本研究通过将扩增后的单个MCF7与MCF10A细胞的表达谱，与未扩增RNA制备的表达谱进行比对，对该方法进行了验证。研究采用Affymetrix U133芯片、RNA-Seq以及高密度qPCR对表达谱进行了比对分析。结果显示，不同平台间的相关性均超过80%，单细胞样本与未扩增样本的一致性高于70%。我们通过分析非小细胞肺癌（NSCLC）患者来源异种移植瘤中稀有分选得到的肿瘤起始细胞（CICs），展示了该方法的应用场景。研究人员从实体瘤中分离出10个细胞的群体，以及两个被推测分别参与原发性肿瘤维持与转移形成的CIC亚群，通过荧光激活细胞分选（FACS）获取后直接进行扩增。CIC的表达谱与已发表的干细胞特征及上皮间质转化（EMT）特征显著相关。本研究结果证实了该扩增体系与实验方法的实用性，可用于检测并区分稀有细胞群体中反映EMT与干细胞特性的RNA表达谱。本基因表达综合数据库（GEO）数据集包含以下样本的RT-qPCR数据：从1μg总RNA制备的未扩增MCF7与MCF10A cDNA、从1ng RNA扩增得到的RNA-AMP cDNA，以及单细胞样本的RNA-AMP cDNA，共包含22个样本。其中，从1ng扩增RNA制备的MCF7 cDNA、从1ng扩增RNA制备的MCF10A cDNA、从1μg未扩增RNA制备的MCF7 cDNA，以及从1μg未扩增RNA制备的MCF10A cDNA，每组均设置3个生物学重复；从单个细胞RNA扩增得到的MCF7 cDNA与MCF10A cDNA，每组均设置5个生物学重复。本研究对各样本类型中MCF7与MCF10A的基因表达进行了比较，并对不同样本类型的分析结果进行了交叉比对。