KRAS-driven lung adenocarcinoma is molecularly heterogeneous; however, evaluation of mutation-associated programs requires matched mutation and clinical metadata. Here, three GDC STAR-count RNA-sequencing files annotated with GENCODE v36 were analyzed to determine which transcriptomic conclusions could be supported from the available data alone. Protein-coding TPM values were used for library-level quality assessment, transcriptome-wide correlation, principal component analysis, sample-specific expression contrasts, and exploratory scoring of curated KRAS/MAPK, PI3K–AKT–mTOR, cell-cycle, epithelial-lineage, epithelial–mesenchymal transition, hypoxia, inflammatory, interferon, apoptosis, and NRF2-related gene sets. The samples contained 24.3–49.5 million assigned reads and 12,808–14,574 protein-coding genes with TPM ≥1. Pairwise transcriptome correlations ranged from r=0.745 to 0.825. Marked biological heterogeneity was observed. Sample 1 showed a secretory epithelial profile characterized by PAEP, CEACAM5, CEACAM6, BPIFA1, and EPCAM. Sample 2 displayed a keratinizing/squamous-like program dominated by KRT5, KRT6A, KRT14, KRT17, SPRR family genes, and elevated NRF2-associated and glycolytic scores. Sample 3 exhibited a strong alveolar-lineage and immune-associated profile, with high SFTPA1, SFTPA2, SFTPB, SFTPC, HLA-DRA, CD74, and inflammatory pathway scores. KRAS expression was detectable in all samples (16.33–30.09 TPM), but RNA expression alone could not establish KRAS mutation status. These findings demonstrate substantial lineage and pathway heterogeneity among the three transcriptomes and provide a hypothesis-generating framework for subsequent mutation-informed analysis. Mutation-stratified differential expression, prognostic modeling, and survival analysis were not performed because mutation and clinical outcome data were unavailable.