Cancer Cell最新文献

Medulloblastoma, the most common malignant brain tumor of childhood, exhibits significant biological complexity that demands deeper exploration. Here, we present a large multiomics dataset integrating data from 384 primary medulloblastoma patient samples across five omic layers: CpG methylome, transcriptome, proteome, phosphoproteome, and metabolome, paired with associated clinical metadata. Data integration revealed intertumoral heterogeneity of lipid metabolism across proteomic subtypes. Notably, while the MYC-FASN-SCD axis drives lipid biosynthesis, pathway inhibition elicits a compensatory escape mechanism in vivo through exogenous fatty acid uptake. Unexpectedly, we demonstrated that MYC triggers lipid storage, creating a unique dependency on lipid droplet-mitochondria communications to sustain tumor maintenance in vivo. Together, this comprehensive analysis reveals a targetable vulnerability downstream of MYC that constitutes a promising therapeutic approach to treat currently untreatable medulloblastoma subtypes.

The rapid expansion of molecularly informed therapies in oncology, coupled with evolving regulatory food and drug administration (FDA) approvals, poses a challenge for oncologists seeking to integrate precision oncology medicine into patient care. Large language models (LLMs) have clinical potential, but their reliance on general knowledge limits their ability to provide up-to-date and niche treatment recommendations. Here, we developed a retrieval-augmented generation (RAG)-LLM workflow using the molecular oncology almanac (MOAlmanac) and benchmarked it against an LLM-only approach for biomarker-driven treatment recommendations. Our RAG-LLM achieved up to 95% accuracy on synthetic queries and 93% on real-world queries collected from practicing oncologists. Finally, our study explored several prompting and retrieval strategies to enhance performance. Taken together, this approach may serve as valuable guidance for deploying LLMs to support cancer patients' treatment decisions in precision oncology clinical settings.

Clinical trials targeting cancer-associated fibroblasts (CAFs)-crucial pro-tumoral factors in cancer-have almost all failed. This may be ascribed to their intrinsic functional plasticity and the opaque regulatory circuits underlying their heterogeneous phenotypes within tumors. We address these by developing a systematic screening approach for patient-derived fibroblasts using complementary CRISPR interference (CRISPRi) and activation (CRISPRa)-based Perturb-seq. An anti-tumoral interferon (IFN)-I response-associated program is identified as the primary antagonism axis counteracting TGF-β-driven pro-tumoral myofibroblast activation. ADAM12 emerges as a molecular checkpoint mediating this relationship. Its ablation elicits IFN-I-responsive programs, reconfigures myofibroblast population structures into progenitor-like states, revitalizes T cell-based immune responses, and induces tumor rejection across various murine models. Further combined with human genomics data analysis, our findings position ADAM12 as a potential target for fibroblasts, paving the way for actionable therapeutic interventions.

Genetic and gene expression subtypes of diffuse large B cell lymphoma (DLBCL) have been defined using bulk tumor analysis. To explore their biology, we derived single-cell RNA and ATAC sequencing data from 103 DLBCL biopsies and identified malignant B cells by their non-diploid DNA copy number profiles. Using malignant B cell gene expression, we developed and validated signatures of each DLBCL genetic subtype, revealing their distinctive characters. Most biopsies had genetic subclones, defined by distinct patterns of aneuploidy, that were distinguished by expression of biological themes reflecting B cell differentiation state, cell proliferation, and cell growth. This analysis revealed REL amplification as a mechanism to block terminal memory B cell differentiation. The genetic subtype signatures and biological themes varied independently, had distinctive transcription factor networks, and were associated with survival following chemotherapy. This single-cell resource illuminates intra- and inter-tumoral biological variation, facilitating studies of DLBCL pathogenesis and therapeutic response.