The histologic phenotype of lung cancers is associated with transcriptomic features rather than genomic characteristics

Histology plays an essential role in therapeutic decision-making for lung cancer patients. However, the molecular determinants of lung cancer histology are largely unknown. We conducted whole-exome sequencing (WES) and microarray profiling on 19 micro-dissected tumor regions of different histologic subtypes from 9 patients with lung cancers of mixed histology. A median of 68.9% of point mutations and 83% of copy number aberrations were shared between different histologic components within the same tumors. Furthermore, different histologic components within the tumors demonstrated similar subclonal architecture. On the other hand, transcriptomic profiling revealed shared pathways between the same histologic subtypes from different patients, which was supported by the analyses of the transcriptomic data from 141 cell lines and 343 lung cancers of different histologic subtypes. These data derived from mixed histologic subtypes in the setting of identical genetic background and exposure history support that the histologic fate of lung cancer cells is associated with transcriptomic features rather than the genomic profiles. The in-house clariom.s.human microarray data were analyzed using Bioconductor packages Oligo, pd.clariom.s.human, and limma following standard workflow. Gene set enrichment analysis using Hallmark dataset was carried out using fgsea Bioconductor package and the genes are pre-ranked by (signed log2FoldChange) * -log10(p-value) for all the public datasets. For the in-house microarray data, we computed the fold change between distinct histologies within the same patient and rank the genes by the fold change. 19 different tumor tissues, from 9 patients, including 6 LUAD, 6 LCNEC, 3 SCLC, 3 LUSC, and one poorly differentiated NSCLC-NOS were subjected to WES and microarray RNA profiling. The in-house clariom.s.human microarray data were analyzed using Bioconductor packages Oligo, pd.clariom.s.human, and limma62 following standard workflow.