资源环境科技发展态势分析平台

Single-cell analyses have revealed extensive heterogeneity between and within human tumours(1-4), but complex single-cell phenotypes and their spatial context are not at present reflected in the histological stratification that is the foundation of many clinical decisions. Here we use imaging mass cytometry(5) to simultaneously quantify 35 biomarkers, resulting in 720 high-dimensional pathology images of tumour tissue from 352 patients with breast cancer, with long-term survival data available for 281 patients. Spatially resolved, single-cell analysis identified the phenotypes of tumour and stromal single cells, their organization and their heterogeneity, and enabled the cellular architecture of breast cancer tissue to be characterized on the basis of cellular composition and tissue organization. Our analysis reveals multicellular features of the tumour microenvironment and novel subgroups of breast cancer that are associated with distinct clinical outcomes. Thus, spatially resolved, single-cell analysis can characterize intratumour phenotypic heterogeneity in a disease-relevant manner, with the potential to inform patient-specific diagnosis.

A single-cell, spatially resolved analysis of breast cancer demonstrates the heterogeneity of tumour and stroma tissue and provides a more-detailed method of patient classification than the current histology-based system.

Cancer genomics has revealed many genes and core molecular processes that contribute to human malignancies, but the genetic and molecular bases of many rare cancers remains unclear. Genetic predisposition accounts for 5 to 10% of cancer diagnoses in children(1,2), and genetic events that cooperate with known somatic driver events are poorly understood. Pathogenic germline variants in established cancer predisposition genes have been recently identified in 5% of patients with the malignant brain tumour medulloblastoma(3). Here, by analysing all protein-coding genes, we identify and replicate rare germline loss-of-function variants across ELP1 in 14% of paediatric patients with the medulloblastoma subgroup Sonic Hedgehog (MBSHH). ELP1 was the most common medulloblastoma predisposition gene and increased the prevalence of genetic predisposition to 40% among paediatric patients with MBSHH. Parent-offspring and pedigree analyses identified two families with a history of paediatric medulloblastoma. ELP1-associated medulloblastomas were restricted to the molecular SHH alpha subtype(4) and characterized by universal biallelic inactivation of ELP1 owing to somatic loss of chromosome arm 9q. Most ELP1-associated medulloblastomas also exhibited somatic alterations in PTCH1, which suggests that germline ELP1 loss-of-function variants predispose individuals to tumour development in combination with constitutive activation of SHH signalling. ELP1 is the largest subunit of the evolutionarily conserved Elongator complex, which catalyses translational elongation through tRNA modifications at the wobble (U-34) position(5,6). Tumours from patients with ELP1-associated MBSHH were characterized by a destabilized Elongator complex, loss of Elongator-dependent tRNA modifications, codon-dependent translational reprogramming, and induction of the unfolded protein response, consistent with loss of protein homeostasis due to Elongator deficiency in model systems(7-9). Thus, genetic predisposition to proteome instability may be a determinant in the pathogenesis of paediatric brain cancers. These results support investigation of the role of protein homeostasis in other cancer types and potential for therapeutic interference.