Transcriptomic similarity guides source selection beyond tissue lineage

Perturbational and pharmacogenomic maps remain incomplete across cellular contexts, leaving a practical source-selection question before response prediction: which measured context should inform an unmeasured target? We tested whether baseline transcriptomic similarity ranks candidate sources for held-out targets, separating source ranking from aggregation and transfer-uncertainty decisions. Similarity tracked matched-response concordance in LINCS and GSE306429; selected-source utility exceeded random expectation in GSE306429 (ΔU = 0.034; P = 0.002) and in exact-time-matched MIX-Seq tasks (ΔU = 0.046). In the full GDSC2 analysis, the drug-balanced ranking effect was 0.359 (95% CI, 0.337-0.383). In a lineage-restricted analysis of the same eligible subset, within-tissue ranking remained positive at 0.130 (95% CI, 0.119-0.141), retaining 35.8% of the same-subset global effect (0.363; 95% CI, 0.342-0.386). Global transcriptomic top-1 selection exceeded tissue-matched random selection by 0.154 (95% CI, 0.143-0.164). Thus, baseline similarity adds source-ranking information after tissue matching in the evaluated setting, while ranking alone does not resolve whether to aggregate sources or how to quantify transfer uncertainty.

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Publication Details

Journal
bioRxiv (Cold Spring Harbor Laboratory)
Published
2026-10-29
DOI
https://doi.org/10.64898/2026.10.26.761823
Primary Topic
Computational Drug Discovery Methods
Type
preprint

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preprint

Transcriptomic similarity guides source selection beyond tissue lineage

Haojun Zhang, Xiai Wu, Jiahong Pang, Li Jiang et al.
1 links
bioRxiv (Cold Spring Harbor Laboratory)
Computational Drug Discovery Methods
preprint

Transcriptomic similarity guides source selection beyond tissue lineage

Haojun Zhang, Xiai Wu, Jiahong Pang, Li Jiang, Bote Luo, Xin Li
preprint en

Abstract

Perturbational and pharmacogenomic maps remain incomplete across cellular contexts, leaving a practical source-selection question before response prediction: which measured context should inform an unmeasured target? We tested whether baseline transcriptomic similarity ranks candidate sources for held-out targets, separating source ranking from aggregation and transfer-uncertainty decisions. Similarity tracked matched-response concordance in LINCS and GSE306429; selected-source utility exceeded random expectation in GSE306429 (ΔU = 0.034; P = 0.002) and in exact-time-matched MIX-Seq tasks (ΔU = 0.046). In the full GDSC2 analysis, the drug-balanced ranking effect was 0.359 (95% CI, 0.337-0.383). In a lineage-restricted analysis of the same eligible subset, within-tissue ranking remained positive at 0.130 (95% CI, 0.119-0.141), retaining 35.8% of the same-subset global effect (0.363; 95% CI, 0.342-0.386). Global transcriptomic top-1 selection exceeded tissue-matched random selection by 0.154 (95% CI, 0.143-0.164). Thus, baseline similarity adds source-ranking information after tissue matching in the evaluated setting, while ranking alone does not resolve whether to aggregate sources or how to quantify transfer uncertainty.

bioRxiv (Cold Spring Harbor Laboratory)
Chinese Academy of Sciences (CN), China-Japan Friendship Hospital (CN), Academy of Mathematics and Systems Science (CN), Shaanxi University of Chinese Medicine (CN)
National Natural Science Foundation of China
Good health and well-being
Computational Drug Discovery Methods
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Transcriptomic similarity guides source selection beyond tissue lineage — Haojun Zhang, Xiai Wu, et al. · bioRxiv (Cold Spring Harbor Laboratory) (2026) | TGRS Research Map | TGRS