Primary brain tumors, residing behind the blood-brain-barrier (BBB), have few infiltrated T cells. We hypothesized that Toxoplasma gondii, a microorganism that naturally traffics to the brain to elicit a Th1 response, can promote T cell infiltration into brain tumors. Using a mouse genetic model for medulloblastoma, we found that T. gondii infection was well-controlled in tumor-bearing mice, induced robust infiltration of T cells into the tumor, and led to myeloid cell transcriptional reprogramming toward a T cell-supportive state. The study demonstrates that the immune modulatory capacity of T. gondii could be leveraged to promote brain tumor immunotherapy through future efforts.
Janes, Kevin A.; Albeck, John G.; Gaudet, Suzanne; Nielsen, Ulrik B.; Sorger, Peter K.; Lauffenburger, Douglas A.; Yaffe, Michael B. Author Information
Abstract Cell-to-cell variations and asymmetries in gene and protein expression play an important role in development and tumorigenesis. But, how do we identify the heterogeneities in the first place? In this talk, I will present results from a new technique called “stochastic sampling” that attempts to address this general problem. Stochastic sampling involves the repeated, random selection of very small cell populations (∼10 cells) followed by quantitative gene-expression profiling and simple statistical analysis (Nat Methods 7:311-7 [2010]). We combined laser-capture microdissection, a customized single-cell amplification protocol, quantitative PCR, and oligonucleotide microarrays to implement stochastic sampling in a 3-D in vitro model of breast-epithelial acinar morphogenesis. Our analysis identified hundreds of genes whose expression dichotomizes when human breast-epithelial cells are cultured as gland-like acinar structures. Very few of these non-uniformities could have been predicted from standard microarray data, indicating the unique information provided by the stochastic-profiling approach. We are currently working to unravel the mechanisms that interconnect a reciprocal dichotomy between transforming growth factor-β (TGFβ) signaling and the junD transcription factor. We find that TGFβ receptor 3 (TGFBR3) is heterogeneously induced during morphogenesis, and blocking its non-uniform induction causes branching morphogenesis in 3-D culture. Addition of recombinant growth-differentation factor 11 (GDF11), a TGFβ-family ligand whose endogenous expression is heterogeneous, potently suppresses branching caused by TGFBR3 knockdown. Single-cell expression of these TGFβ-family genes is anticorrelated with JUND mRNA, and constitutive expression of JUND causes a distinct phenotype reminiscent of cribiform ductal carcinoma in situ. The interconnections between TGFβ signaling, TGFBR3, and JUND create a network motif that could give rise to oscillations, and our preliminary work suggests that TGFβ signaling activity oscillates sporadically with a period of ∼6-8 hr. Asynchronous single-cell oscillations provide an explanation for why TGFBR3, GDF11, and JUND were first revealed by stochastic profiling. This endogenous TGFBR-JUND pathway may be particularly relevant for a subtype of breast cancer, called basal-like carcinoma, which is known to be strongly heterogeneous at the single-cell level. In 3-D culture, the basal cytokeratin KRT5 is tightly coexpressed with JUND in cells attached to basement membrane. Remarkably, this correlation switches to an anticorrelation when cells are detached from basement membrane, and we observe the same dependencies in basal-like breast cancers with heterogeneous Krt5 protein expression. The single-cell programs identified by stochastic profiling in the 3-D culture model may thus have particular translational relevance to heterogeneous basal-like breast cancer, which is the most lethal subtype yet described. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr SY17-01. doi:10.1158/1538-7445.AM2011-SY17-01
<p>Pseudotime estimates for RHEGs classified as cyclers and for ten non-RHEGs classified as top cyclers by Cyclebase 3.0. The IMAGE clone used for the microarray study of synchronized HeLa cells is listed, and data from the first two cycles used for the analysis in Supplementary Fig. S10B are highlighted.</p>
Acute myeloid leukemia (AML) is an aggressive disease with complex and heterogeneous biology. Although several genomic classifications have been proposed, there is a growing interest in going beyond genomics to stratify AML. In this study, we profile the sphingolipid family of bioactive molecules in 213 primary AML samples and 30 common human AML cell lines. Using an integrative approach, we identify two distinct sphingolipid subtypes in AML characterized by a reciprocal abundance of hexosylceramide (Hex) and sphingomyelin (SM) species. The two Hex-SM clusters organize diverse samples more robustly than known AML driver mutations and are coupled to latent transcriptional states. Using transcriptomic data, we develop a machine-learning classifier to infer the Hex-SM status of AML cases in TCGA and BeatAML clinical repositories. The analyses show that the sphingolipid subtype with deficient Hex and abundant SM is enriched for leukemic stemness transcriptional programs and comprises an unappreciated high-risk subgroup with poor clinical outcomes. Our sphingolipid-focused examination of AML identifies patients least likely to benefit from standard of care and raises the possibility that sphingolipidomic interventions could switch the subtype of AML patients who otherwise lack targetable alternatives.
