Osteosarcoma tumors maintain intra-tumoral transcriptional heterogeneity during bone and lung colonization.

BACKGROUND: Tumors are complex tissues containing collections of phenotypically diverse malignant and nonmalignant cells. We know little of the mechanisms that govern heterogeneity of tumor cells nor of the role heterogeneity plays in overcoming stresses, such as adaptation to different microenvironments. Osteosarcoma is an ideal model for studying these mechanisms-it exhibits widespread inter- and intra-tumoral heterogeneity, predictable patterns of metastasis, and a lack of clear targetable driver mutations. Understanding the processes that facilitate adaptation to primary and metastatic microenvironments could inform the development of therapeutic targeting strategies. RESULTS: We investigated single-cell RNA-sequencing profiles of 47,977 cells obtained from cell line and patient-derived xenograft models as cells adapted to growth within primary bone and metastatic lung environments. Tumor cells maintained phenotypic heterogeneity as they responded to the selective pressures imposed during bone and lung colonization. Heterogenous subsets of cells defined by distinct transcriptional profiles were maintained within bone- and lung-colonizing tumors, despite high-level selection. One prominent heterogenous feature involving glucose metabolism was clearly validated using immunofluorescence staining. Finally, using concurrent lineage tracing and single-cell transcriptomics, we found that lung colonization enriches for multiple clones with distinct transcriptional profiles that are preserved across cellular generations. CONCLUSIONS: Response to environmental stressors occurs through complex and dynamic phenotypic adaptations. Heterogeneity is maintained, even in conditions that enforce clonal selection. These findings likely reflect the influences of developmental processes promoting diversification of tumor cell subpopulations, which are retained, even in the face of selective pressures.

Silencing of H4R inhibits the production of IL-1ß through SAPK/JNK signaling in human mast cells.

CONTEXT: Mast cell (MC) activation through H4R releases various inflammatory mediators which are associated with allergic asthma. OBJECTIVES: To investigate the siRNA-mediated gene silencing effect of H4R on human mast cells (HMCs) functions and the activation of stress-activated protein kinases (SAPK)/jun amino-terminal kinases (JNK) signaling pathways for the release of ineterleukin-1ß (IL-1ß) in HMCs. MATERIALS AND METHODS: H4R expression was analyzed by RT-PCR and western blotting in human mast cell line-1 (HMC-1) cells and H4RsiRNA transfected cells. The effect of H4RsiRNA and H4R-antagonist on H4R mediated MC functions such as intracellular Ca2+ release, degranulation, IL-6 and IL-1ß release, and the activation SAPK/JNK signaling pathways were studied. HMC-1 cells were stimulated with 10 µM of histamine (His) and 4-methylhistamine (4-MH) and pretreated individually with H4R-antagonist JNJ7777120 (JNJ), histamine H1 receptor (H1R)-antagonist mepyramine, and signaling molecule inhibitors SP600125 (SP) and Bay117082. RESULTS: We found that the HMC-1 cells expressed H4R and H4RsiRNA treatment down regulated the H4R expression in HMC-1 cells. Both His and 4-MH induced the intracellular Ca2+ release and degranulation whereas; H4R siRNA and JNJ inhibited the effect. Furthermore, the activation of H4R caused the phosphorylation of SAPK/JNK pathways. H4R gene silencing and pretreatment with SP and JNJ decreased His and 4-MH induced phosphorylation of SAPK/JNK. We found that the activation of H4R caused the release of IL-1ß (124.22 pg/ml) and IL-6 (122.50 pg/ml) on HMC-1 cells. Whereas, SAPK/JNK inhibitor (68.36 pg/ml) inhibited the H4R mediated IL-1ß release. CONCLUSIONS: Taken together, the silencing of H4R inhibited the H4R mediated MC functions and SAPK/JNK phosphorylation. Furthermore, the H4R activation utilized SAPK/JNK signaling pathway for IL-1ß release in HMC-1 cells.

Structurally Complex Osteosarcoma Genomes Exhibit Limited Heterogeneity within Individual Tumors and across Evolutionary Time.

Osteosarcoma is an aggressive malignancy characterized by high genomic complexity. Identification of few recurrent mutations in protein coding genes suggests that somatic copy-number aberrations (SCNA) are the genetic drivers of disease. Models around genomic instability conflict-it is unclear whether osteosarcomas result from pervasive ongoing clonal evolution with continuous optimization of the fitness landscape or an early catastrophic event followed by stable maintenance of an abnormal genome. We address this question by investigating SCNAs in >12,000 tumor cells obtained from human osteosarcomas using single-cell DNA sequencing, with a degree of precision and accuracy not possible when inferring single-cell states using bulk sequencing. Using the CHISEL algorithm, we inferred allele- and haplotype-specific SCNAs from this whole-genome single-cell DNA sequencing data. Surprisingly, despite extensive structural complexity, these tumors exhibit a high degree of cell-cell homogeneity with little subclonal diversification. Longitudinal analysis of patient samples obtained at distant therapeutic timepoints (diagnosis, relapse) demonstrated remarkable conservation of SCNA profiles over tumor evolution. Phylogenetic analysis suggests that the majority of SCNAs were acquired early in the oncogenic process, with relatively few structure-altering events arising in response to therapy or during adaptation to growth in metastatic tissues. These data further support the emerging hypothesis that early catastrophic events, rather than sustained genomic instability, give rise to structural complexity, which is then preserved over long periods of tumor developmental time. Significance: Chromosomally complex tumors are often described as genomically unstable. However, determining whether complexity arises from remote time-limited events that give rise to structural alterations or a progressive accumulation of structural events in persistently unstable tumors has implications for diagnosis, biomarker assessment, mechanisms of treatment resistance, and represents a conceptual advance in our understanding of intratumoral heterogeneity and tumor evolution.