SRP404172 PRJNA893542 GSE216396 In vivo growth of subclones derived from Lewis lung carcinoma is determined by the tumor microenvironment not intrinsic proliferative ability Heterogeneity is a fundamental feature of human tumors and plays a major role in drug resistance and disease progression. In the present study, we selected single-cell-derived cell lines (SCDCLs) derived from Lewis lung carcinoma (LLC1) cells to investigate tumorigenesis and heterogeneity. SCDCLs were generated using limiting dilution. Five SCDCLs were subcutaneously injected into wild-type C57BL/6N mice; however, they displayed significant differences in tumor growth. Subclone SCC1 grew the fastest in vivo, whereas it grew slower in vitro. The growth pattern of SCC2 was the opposite to that of SCC1. Genetic differences in these two subclones showed marked differences in cell adhesion and proliferation. Pathway enrichment results indicate that signal transduction and immune system responses were the most significantly altered functional categories in SCC2 cells compared to SCC1 cells in vitro. The number and activation of CD3+ and CD8+ T cells and NK cells in the tumor tissue of tumor-bearing mice inoculated with SCC2 were significantly higher, whereas those of myeloid cells were significantly lower, than those in the SCC1 and LLC1 groups. Our results suggest that the in vivo growth of two subclones derived from LLC1 was determined by the tumor microenvironment rather than their intrinsic proliferative cell characteristics. Overall design: Total RNA was extracted using the mirVana miRNA Isolation Kit (Ambion), following the manufacturer's protocol. RNA integrity was evaluated using the Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). Samples with an RNA integrity number = 7 were subjected to subsequent analysis. Libraries were constructed using the TruSeq Stranded mRNA LTSample Prep Kit (Illumina, San Diego, CA, USA) according to the manufacturer's instructions. These libraries were then sequenced on an Illumina HiSeq X Ten platform and 150 bp paired-end reads were generated.Transcriptome sequencing and analysis were conducted by OE Biotech (Shanghai, China). Raw data were processed using Trimmomatic software. Reads containing poly-N and low-quality reads were removed to obtain clean reads. The clean reads were then mapped to the reference genome using hisat2. The FPKM value of each gene was calculated using cufflinks, and the read counts of each gene were obtained by HTSeq-count. Differentially expressed genes (DEGs) were identified using the DESeq (2012) R package to estimate the size factors. A p-value < 0.05 and a fold-change > 2 or < 0.5 were set as the thresholds for significant differential expression. Hierarchical cluster analysis of DEGs was performed to explore gene expression patterns. GO enrichment and KEGG pathway enrichment analyses of DEGs were performed using the software R based on a hypergeometric distributions. GSE216396