RNA-seq of live cell 3-D models with engineered genetic sub-types of lung cancer

An experimental system was designed to screen for targetable signaling pathways linked to early 3D invasion in molecular subtypes, TP53 and LKB1, of KRAS-driven lung adenocarcinoma (LUAD). Live-cell imaging of human bronchial epithelial cells during 3D invasion was combined with RNA transcriptome profiling shown here. RNA-seq was performed in triplicate on for each sub-type. Total RNA was extracted from the spheroids at day 7 of 3D spheroid invasion assay using a RNeasy Kit (Qiagen, Valencia, CA, USA). The quantitation, integrity and purity of the extracted total RNA samples were assessed by the Emory Integrated Genomics Core (EIGC) using 2100 Bioanalyzer (Agilent) and RNA sequencing was performed by Novogene, Co., Ltd. Data processing, quality control, read alignment and statistical analyses were performed by the Emory Biostatistics and Bioinformatics Shared Resource, as previously described​(21)​. Raw read data (fastq) QC was performed using FastQC v0.11.7. Post-filtered reads were mapped against Ensemble Human GRCh38.p12 release 95 reference genome using the STARaligner v2.7.0e. Expression quantification was obtained using featureCounts. Normalization and pairwise differential analysis were determined using median-ratios method in DESeq2 and log2 transformed. Differentially expressed genes (DEGs) were identified using a moderated t-test as implemented in the Limma R package. Heatmaps were created by unsupervised clustering of log2 transformed normalized expression data for the significant DEGs, and the resulting data were analyzed using a Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG).

本研究设计了一套实验系统，用于筛选KRAS驱动型肺腺癌（KRAS-driven lung adenocarcinoma, LUAD）的TP53与LKB1分子亚型中，与早期三维（3D）侵袭相关的可靶向信号通路。本研究将人支气管上皮细胞三维侵袭过程中的活细胞成像与本文展示的RNA转录组分析相结合，对每个亚型均开展了三次生物学重复的RNA测序（RNA-seq）。
本研究在三维球体侵袭实验第7天，从细胞球体中提取总RNA，所用试剂为RNeasy试剂盒（Qiagen，美国加利福尼亚州瓦伦西亚）。提取的总RNA样本的定量、完整性与纯度由埃默里大学整合基因组学核心实验室（Emory Integrated Genomics Core, EIGC）采用安捷伦（Agilent）2100生物分析仪完成检测，RNA测序工作则由诺禾致源（Novogene, Co., Ltd.）承接。
数据处理、质量控制、序列比对与统计分析均由埃默里大学生物统计与生物信息学共享资源中心完成，具体流程参照此前发表的文献(21)。原始读段数据（FASTQ格式）的质量控制（QC）采用FastQC v0.11.7工具完成。经过滤后的读段通过STARaligner v2.7.0e工具比对至Ensembl人类参考基因组GRCh38.p12第95版。基因表达定量采用featureCounts工具完成。标准化处理与组间差异分析采用DESeq2软件中的中位数比率法实现，并对结果进行log2对数转换。差异表达基因（Differentially Expressed Genes, DEGs）的筛选采用Limma R软件包内置的校正t检验完成。对显著差异表达基因的log2转换后标准化表达数据进行无监督聚类以绘制热图，并对所得数据开展基因本体（Gene Ontology, GO）富集分析与京都基因与基因组百科全书（Kyoto Encyclopedia of Genes and Genomes, KEGG）通路富集分析。