The rapid expansion of the oncology literature has outpaced manual curation of clinically relevant gene-cancer-drug associations and oncogenic driver evidence. Existing automated approaches often lack transparency or are difficult to scale across heterogeneous data sources. To address this gap, we developed megaMine, a transparent, rule-based, and context-aware literature-mining framework that integrates therapeutic and driver evidence from PubMed, PubTator, and Europe PMC by combining entity recognition, hierarchical heuristics, and contextual labeling. In therapy mode, megaMine was applied to approximately 100,000 oncology articles published between 2015 and 2025, yielding more than 23,000 structured sentence-level evidence records, with standardized annotations for drug response, resistance, and study context. Internal evaluation of context labels showed the strong separability between efficacy and non-efficacy evidence using ridge logistic regression (AUROC = 0.915; AUPRC = 0.941). Benchmarking against NCI/OncoKB-supported drug-cancer associations showed that curated clinical associations had higher megaMine composite evidence scores than unlabeled comparison pairs [median (IQR): 25.6 (9.07-72.5) vs. 3.61 (1.69-8.69); Wilcoxon rank-sum test, P < 2.2 × 10−16]. In driver mode, megaMine retrieved mutation- and biomarker-related evidence from an ERBB-focused gastric cancer query, generating 750 evidence rows from 200 PMIDs. These results demonstrate that deterministic and interpretable approaches can support scalable evidence extraction for downstream applications such as knowledge graph construction and literature-based evidence synthesis.
Muhammad Junaid, K. Prazanowska, Ha-Eun Jeong et al.· bioRxiv· 0 citations
De novo variants in the ubiquitin-proteasome pathway are linked to autism spectrum disorder (ASD), yet their functional impact on neurodevelopment remains poorly understood. We investigated USP15, a deubiquitinating enzyme with rare damaging variants identified in individuals with ASD, using isogenic human iPSC-derived brain organoids and single-cell transcriptomics. USP15-mutant organoids showed genotype-dependent, progenitor-centered alterations during corticogenesis. Heterozygous organoids modeling haploinsufficiency displayed a shift toward later pseudotime states together with altered maturation and synaptic organization of deep-layer neurons. In contrast, homozygous organoids showed broader phenotypes, including mitotic suppression, aberrant HOX gene expression, and stress-response activation. Regulon analysis showed reduced activity of progenitor-associated regulons, including SOX2, NR2F1, and NR2F2, in heterozygous organoids, whereas homozygous organoids exhibited broader changes in transcriptional regulatory networks. Furthermore, USP15 mutant-associated gene expression patterns were significantly enriched for established ASD risk genes. Comparison with the mouse brain perturbation atlas showed that the transcriptional signature of the USP15 mutant showed notable overlap with those of Fezf2 and Foxp1 mutants, key regulators of deep-layer projection neuron identity. These findings characterize genotype-dependent neurodevelopmental phenotypes associated with reduced USP15 dosage and provide a human neural framework for investigating ASD-relevant developmental mechanisms in the context of a rare ubiquitin-pathway variant.
Tae-Hwan Park, I. Koh, Seoyoung Sung et al.· Molecules and Cells· 0 citations