Lung cancer exhibits substantial inter- and intra-tumor heterogeneity, with features that present significant challenges in advancing biomarker discovery and the development of targeted therapeutics. To fill this gap, we employed single-cell RNA sequencing (scRNA-seq) and advanced bioinformatics tools to evaluate the transcriptomic heterogeneity of immortalized, non-transformed (BEAS2B) and transformed (H460) lung epithelial cell lines and their responses to carcinogen challenge. Gene expression profiles resolved four primary clusters further discretized into unique subclusters based on genetic signatures and phenotypic profiles. Profiles of long non-coding RNAs (lncRNAs) identified microRNA host genes, antisense RNA genes, divergent transcript, and long intergenic non-coding RNAs as contributors to cellular heterogeneity. These findings indicate that distinct patterns of gene expression, remarkably in lncRNAs, define cellular heterogeneity in non-transformed versus transformed cells. These features can be exploited for the development of therapies directed at specific cell subpopulations in precancerous lesions and within lung tumors.