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bioRxiv · 10.64898/2026.01.15.699695

Reconstructing clone-resolved transcriptional programs from bulk tumor sequencing

Lai, J.·Yang, Y.·Noller, K.·Liu, Y.·Balan, A.·Nagendra, P.·Kagohara, L. T.·Fertig, E. J.·Wood, L. D.·Karchin, R.
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Abstract

Tumor clones acquire distinct transcriptional programs as they evolve, but bulk RNA-seq averages over clonal mixtures and obscures the lineage-specific biology that DNA-sequencing reveals. We present PICTographPlus, the first method to infer clone-resolved transcriptional programs by integrating bulk DNA-derived clonal phylogenies and proportions with bulk RNA-seq alone, without single-cell data. Benchmarked against experimentally measured ground truth, scDNA/scRNA co-profiled cells from a wellDR-seq cancer dataset, across 320 pseudo-bulk replicates spanning four tumor purities and four sample counts and evaluated under seven regularization models, PICTographPlus recovers clone-level expression at mean Pearson r [≥] 0.92 and localizes pathway gains and losses to correct evolutionary branches (median F1 0.31-0.40, well above a no-deconvolution baseline). Applied to multi-region NSCLC, pancreatic precursor lesions, and rapid-autopsy PDAC, it localizes metabolic reprogramming, precursor-to-invasive transitions, and organ-adapted metastatic states to specific clonal branches. PICTographPlus turns standard bulk assays into clone-resolved transcriptional maps, enabling retrospective analyses where single-cell profiling is impractical.

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Lai, J., Yang, Y., Noller, K., Liu, Y., Balan, A., Nagendra, P., Kagohara, L. T., Fertig, E. J., Wood, L. D., Karchin, R.. 2026-01-15. Reconstructing clone-resolved transcriptional programs from bulk tumor sequencing. https://doi.org/10.64898/2026.01.15.699695

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