Beyond Histology: A Unified Transcriptomic Atlas Defines Lung Cancer Biologic States and Subtypes

Arora, S.; Suresh, L.; Thirmanne, H. N.; Jensen, M.; Glatzer, G.; Fatherree, J.; Konnick, E.; Levine, K.; Brooks, A. N.; Houghton, A. M.; Pritchard, C.; MacPherson, D.; Berger, A.; Holland, E. C.

doi:10.64898/2026.03.16.712177

bioRxiv · 10.64898/2026.03.16.712177

Beyond Histology: A Unified Transcriptomic Atlas Defines Lung Cancer Biologic States and Subtypes

Arora, S.·Suresh, L.·Thirmanne, H. N.·Jensen, M.·Glatzer, G.·Fatherree, J.·Konnick, E.·Levine, K.·Brooks, A. N.·Houghton, A. M.·Pritchard, C.·MacPherson, D.·Berger, A.·Holland, E. C.

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Abstract

Lung cancer encompasses multiple histological entities with substantial molecular heterogeneity that remain incompletely resolved at population scale. Here, we constructed a unified reference landscape of lung cancer by analyzing raw RNA sequencing data from 1,824 tumors spanning adenocarcinoma (n=966), squamous cell carcinoma (n=628), small cell lung cancer (n=150), and unclassified non small cell lung cancer (n=80). Following batch correction, samples were analyzed using consensus clustering and visualized with PaCMAP to generate a molecular atlas annotated with clinical and biological metadata. Rather than segregating by pathological diagnosis, tumors organized along conserved transcriptional axes defined by tumor-intrinsic biology including proliferative or metabolic programs and immune-infiltrated states. Consensus clustering resolved nine robust molecular clusters, including an adenocarcinoma-associated subgroup, a neuroendocrine-like adenocarcinoma marked by ASCL1 activation, immune-associated regions, and bifurcation of both small cell and squamous carcinomas into biologically distinct states. Spatially restricted expression of selected clinically relevant transcripts nominated state-specific therapeutic hypotheses requiring future functional and clinical validation. Projection of patient tumors and patient-derived xenografts onto the atlas demonstrated preservation of transcriptional identity and enabled quantitative assessment of model fidelity. This integrated framework organizes lung cancer as a structured continuum of transcriptional states and provides a reference resource for biological interpretation and future translational studies.

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Arora, S., Suresh, L., Thirmanne, H. N., Jensen, M., Glatzer, G., Fatherree, J., Konnick, E., Levine, K., Brooks, A. N., Houghton, A. M., Pritchard, C., MacPherson, D., Berger, A., Holland, E. C.. 2026-03-18. Beyond Histology: A Unified Transcriptomic Atlas Defines Lung Cancer Biologic States and Subtypes. https://doi.org/10.64898/2026.03.16.712177

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