Multiscale profiling of enzyme activity in cancer [scRNA-seq]. Multiscale profiling of enzyme activity in cancer [scRNA-seq]

Purpose: The goal of this study was to use enzyme activity as a proxy for profiling tumor progression and treatment response in an autochthonous mouse model of Alk-mutant non-small-cell lung cancer (NSCLC). The Eml4-Alk model was originally described in Maddalo et al., Nature 2014. Single-cell transcriptomic profiling of the Eml4-Alk NSCLC model was performed for unbiased discovery of the phenotypic landscape of Eml4-Alk and wild type mice. Methods: Single cell suspensions were prepared from excised lungs of Eml4-Alk and sex- and age-matched healthy, wild type C57/Bl6J mice. Suspensions were pooled from n=3 mice per condition, and then were enriched for cell viability and depleted for CD45+ cells. Single cells were processed using the 10X Genomics Single Cell 3’ platform using the Chromium Single Cell 3’ Library & Gel Bead Kit V2 kit (10X Genomics), per manufacturer’s protocol. Approximately 10,000 cells were loaded onto each channel and partitioned into Gel Beads in Emulsion (GEMs) in the 10x Chromium instrument. Following lysis of the captured cells, the released RNA was barcoded through reverse transcription in individual GEMs, and complementary DNA was generated and amplified. Libraries were constructed using a Single Cell 3’ Library and Gel Bead kit. The libraries were sequenced using an Illumina NovaSeq6000 sequencer on an Illumina NovaSeq SP flow cell. Results: Gene expression matrices were generated for each sample by the Cell Ranger (v.3.0.2) Pipeline coupled with mouse reference version GRCm38. The output filtered gene expression matrices were analyzed by Python software (v.3.9.0) with the scanpy package (v.1.7.2). For final analysis, genes expressed in at least three cells in the data and cells with > 200 genes detected were selected for further analyses, and low quality cells were removed based on number of total counts and percentage of mitochondrial genes expressed. Conclusions: This study provides the first (to the best of our knowledge) single-cell RNA-seq dataset of the Eml4-Alk autochthonous model of NSCLC. Overall design: Lung single-cell RNA profiles of sex- and age-matched wild type (WT) and Eml4-Alk (EA) mice. One sample for each of WT and Eml4-Alk (EA), with each sample representing a pooled sample of n=3 individual mice.

研究目的：本研究旨在以酶活性作为替代指标，对ALK突变型非小细胞肺癌（non-small-cell lung cancer, NSCLC）内源自发小鼠模型（autochthonous mouse model）中的肿瘤进展与治疗响应进行谱型分析。Eml4-Alk模型最初由Maddalo等人于2014年发表于《Nature》。本研究同时对该模型开展单细胞转录组谱分析，以无偏方式解析Eml4-Alk与野生型小鼠的表型谱。
方法：从Eml4-Alk模型小鼠以及性别、年龄匹配的健康野生型C57/Bl6J小鼠的切除肺部制备单细胞悬液。每组取3只小鼠的单细胞悬液进行混合，随后富集活细胞并去除CD45+免疫细胞。按照制造商官方方案，使用10X Genomics单细胞3’端测序平台及Chromium单细胞3’文库与磁珠试剂盒V2（10X Genomics）处理单细胞。每个测序通道加载约10000个细胞，在10x Chromium仪器中制备为油包水磁珠微滴（Gel Beads in Emulsion, GEMs）。捕获的细胞裂解后，释放的RNA在单个GEM中通过逆转录反应完成条形码标记，随后生成并扩增互补脱氧核糖核酸（complementary DNA, cDNA）。采用单细胞3’文库与磁珠试剂盒完成文库构建。使用Illumina NovaSeq6000测序仪在Illumina NovaSeq SP流动槽上完成文库测序。
结果：采用Cell Ranger（v.3.0.2）分析流程结合小鼠参考基因组版本GRCm38，为每个样本生成基因表达矩阵。使用Python（v.3.9.0）及scanpy包（v.1.7.2）对输出的过滤后基因表达矩阵进行数据分析。最终分析阶段，筛选出至少在3个细胞中表达的基因，以及检测到超过200个基因的细胞，并基于总计数数与线粒体基因表达百分比去除低质量细胞。
结论：据我们所知，本研究首次提供了Eml4-Alk NSCLC内源自发模型的单细胞RNA测序数据集。
整体实验设计：纳入性别与年龄匹配的野生型（WT）及Eml4-Alk（EA）小鼠的肺部单细胞RNA谱。野生型与Eml4-Alk（EA）组各设置1个混合样本，每个样本均由3只个体小鼠的样本混合制备。