SUMMARY Alteration of the PTEN/PI3K pathway is associated with late stage and castrate resistant prostate cancer (CRPC). However, how PTEN loss involves in CRPC development is not clear. Here we show that castration-resistant growth is an intrinsic property of Pten-null prostate cancer (CaP) cells, independent of cancer development stage. PTEN loss suppresses androgen-responsive gene expressions by modulating androgen receptor (AR) transcription factor activity. Conditional deletion of Ar in the epithelium promotes the proliferation of Pten-null cancer cells, at least in part, by down-regulating androgen-responsive gene Fkbp5 and preventing PHLPP-mediated AKT inhibition. Our findings identify PI3K and AR pathway crosstalk as a mechanism of CRPC development, with potentially important implications for CaP etiology and therapy.

Comparing independent high-throughput gene-expression experiments can generate hypotheses about which gene-expression programs are shared between particular biological processes. Current techniques to compare expression profiles typically involve choosing a fixed differential expression threshold to summarize results, potentially reducing sensitivity to small but concordant changes. We present a threshold-free algorithm called Rank–rank Hypergeometric Overlap (RRHO). This algorithm steps through two gene lists ranked by the degree of differential expression observed in two profiling experiments, successively measuring the statistical significance of the number of overlapping genes. The output is a graphical map that shows the strength, pattern and bounds of correlation between two expression profiles. To demonstrate RRHO sensitivity and dynamic range, we identified shared expression networks in cancer microarray profiles driving tumor progression, stem cell properties and response to targeted kinase inhibition. We demonstrate how RRHO can be used to determine which model system or drug treatment best reflects a particular biological or disease response. The threshold-free and graphical aspects of RRHO complement other rank-based approaches such as Gene Set Enrichment Analysis (GSEA), for which RRHO is a 2D analog. Rank–rank overlap analysis is a sensitive, robust and web-accessible method for detecting and visualizing overlap trends between two complete, continuous gene-expression profiles. A web-based implementation of RRHO can be accessed at http://systems.crump.ucla.edu/rankrank/.

Neutrophil abscess formation is critical in innate immunity against many pathogens. Here, the mechanism of neutrophil abscess formation was investigated using a mouse model of Staphylococcus aureus cutaneous infection. Gene expression analysis and in vivo multispectral noninvasive imaging during the S. aureus infection revealed a strong functional and temporal association between neutrophil recruitment and IL-1β/IL-1R activation. Unexpectedly, neutrophils but not monocytes/macrophages or other MHCII-expressing antigen presenting cells were the predominant source of IL-1β at the site of infection. Furthermore, neutrophil-derived IL-1β was essential for host defense since adoptive transfer of IL-1β-expressing neutrophils was sufficient to restore the impaired neutrophil abscess formation in S. aureus-infected IL-1β-deficient mice. S. aureus-induced IL-1β production by neutrophils required TLR2, NOD2, FPR1 and the ASC/NLRP3 inflammasome in an α-toxin-dependent mechanism. Taken together, IL-1β and neutrophil abscess formation during an infection are functionally, temporally and spatially linked as a consequence of direct IL-1β production by neutrophils.

Activating epidermal growth factor receptor (EGFR) mutations are common in many cancers including glioblastoma. However, clinical responses to EGFR inhibitors are infrequent and short-lived. We show that the Src family kinases (SFK) Fyn and Src are effectors of oncogenic EGFR signaling, enhancing invasion and tumor cell survival in vivo. Expression of a constitutively active EGFR mutant, EGFRvIII, resulted in activating phosphorylation and physical association with Src and Fyn, promoting tumor growth and motility. Gene silencing of Fyn and Src limited EGFR-and EGFRvIIIdependent tumor cell motility. The SFK inhibitor dasatinib inhibited invasion, promoted tumor regression, and induced apoptosis in vivo, significantly prolonging survival of an orthotopic glioblastoma model expressing endogenous EGFRvIII. Dasatinib enhanced the efficacy of an anti-EGFR monoclonal antibody (mAb 806) in vivo, further limiting tumor growth and extending survival. Examination of a large cohort of clinical samples showed frequent coactivation of EGFR and SFKs in glioblastoma patients. These results establish a mechanism linking EGFR signaling with Fyn and Src activation to promote tumor progression and invasion in vivo and provide rationale for combined anti-EGFR and anti-SFK targeted therapies. [Cancer Res 2009;69(17):6889-98]

In contrast to normal cells, cancer cells avidly take up glucose and metabolize it to lactate even when oxygen is abundant, a phenomenon referred to as the Warburg effect. This fundamental alteration in glucose metabolism in cancer cells enables their specific detection by Positron Emission Tomography (PET) following intravenous injection of the glucose analogue 18F-fluorodeoxy-glucose (18FDG). However, this useful imaging technique is limited by the fact that not all cancers avidly take up FDG. To identify molecular determinants of 18FDG-retention, we interogated the transcriptomes of human cancer cell lines and primary tumors for metabolic pathways associated with 18FDG radiotracer uptake. From 95 metabolic pathways that were interrogated, the glycolysis and several glycolysis-related pathways (pentose-phosphate, carbon fixation, aminoacyl-tRNA biosynthesis, one-carbon-pool by folate) showed the greatest transcriptional enrichment. This “FDG signature” predicted FDG-uptake in breast cancer cell lines and overlapped with established gene expression signatures for the “basal-like” breast cancer subtype and MYC-induced tumorigenesis in mice. Human breast cancers with nuclear MYC staining and high RNA expression of MYC target genes showed high 18FDG-PET uptake (p < 0.005). Presence of the FDG signature was similarly associated with MYC gene copy gain, increased MYC transcript levels, and elevated expression of metabolic MYC target genes in a human breast cancer genomic dataset. Together, our findings link clinical observations of glucose uptake with a pathologic and molecular subtype of human breast cancer. Further, they suggest related approaches to derive molecular determinants of radiotracer retention for other PET-imaging probes.

Platform and study differences in prognostic signatures from metastatic melanoma (MM) gene expression reports often hinder consensus arrival. We performed survival/outcome-based pairwise comparisons of three independent MM gene expression profiles using the threshold-free algorithm rank-rank hypergeometric overlap analysis (RRHO). We found statistically significant overlap for genes overexpressed in favorable outcome (FO) groups, but no overlap for poor outcome (PO) groups. This “favorable outcome signature” (FOS) of 228 genes coinciding on all three overlapping gene lists showed immune function predominated in FO MM. Surprisingly, specific cell signature-enrichment analysis showed B cell-associated genes enriched in FO MM, along with T cell-associated genes. Higher levels of B and T cells (p<0.05) and their relative proximity (p<0.05) were detected in FO-to-PO tumor comparisons from an independent MM patients cohort. Finally, expression of FOS in two independent Stage III MM tumor datasets correctly predicted clinical outcome in 12/14 and 44/70 patients using a weighted gene voting classifier (area under the curve values 0.96 and 0.75, respectively). This RRHO-based, cross-study analysis emphasizes the RRHO approach power, confirms T cells relevance for prolonged MM survival, supports a favorable role for B cells in anti-melanoma immunity, and suggests B cells potential as means of intervention in melanoma treatment.

PTEN-controlled PI3K-AKT-mTOR pathway represents one of the most deregulated signaling pathways in human cancers. With many small molecule inhibitors that target PI3K-AKT-mTOR pathway being exploited clinically, sensitive and reliable ways of stratifying patients according to their PTEN functional status and determining treatment outcomes are urgently needed. Heterogeneous loss of PTEN is commonly associated with human cancers and yet PTEN can also be regulated on epigenetic, transcriptional or post-translational levels, which makes the use of simple protein or gene expression-based analyses in determining PTEN status less accurate. In this study, we used network component analysis to identify 20 transcription factors (TFs) whose activities deduced from their target gene expressions were immediately altered upon the re-expression of PTEN in a PTEN-inducible system. Interestingly, PTEN controls the activities (TFA) rather than the expression levels of majority of these TFs and these PTEN-controlled TFAs are substantially altered in prostate cancer mouse models. Importantly, the activities of these TFs can be used to predict PTEN status in human prostate, breast and brain tumor samples with enhanced reliability when compared to straightforward IHC-based or expression-based analysis. Furthermore, our analysis indicates that unique sets of PTEN-controlled TFAs significantly contribute to specific tumor types. Together, our findings reveal that TFAs may be used as “signatures” for predicting PTEN functional status and elucidate the transcriptional architectures underlying human cancers caused by PTEN loss.

Background Pregnancy complications vary based on the fetus’s genetic sex, which may, in part, be modulated by the placenta. Furthermore, developmental differences early in life can have lifelong health outcomes. Yet, sex differences in gene expression within the placenta at different timepoints throughout pregnancy and comparisons to adult tissues remains poorly characterized. Methods Here, we collect and characterize sex differences in gene expression in term placentas (≥ 36.6 weeks; 23 male XY and 27 female XX). These are compared with sex differences in previously collected first trimester placenta samples and 42 non-reproductive adult tissues from GTEx. Results We identify 268 and 53 sex-differentially expressed genes in the uncomplicated late first trimester and term placentas, respectively. Of the 53 sex-differentially expressed genes observed in the term placentas, 31 are also sex-differentially expressed genes in the late first trimester placentas. Furthermore, sex differences in gene expression in term placentas are highly correlated with sex differences in the late first trimester placentas. We found that sex-differential gene expression in the term placenta is significantly correlated with sex differences in gene expression in 42 non-reproductive adult tissues (correlation coefficient ranged from 0.892 to 0.957), with the highest correlation in brain tissues. Sex differences in gene expression were largely driven by gene expression on the sex chromosomes. We further show that some gametologous genes (genes with functional copies on X and Y) will have different inferred sex differences if the X-linked gene expression in females is compared to the sum of the X-linked and Y-linked gene expression in males. Conclusions We find that sex differences in gene expression are conserved in late first trimester and term placentas and that these sex differences are conserved in adult tissues. We demonstrate that there are sex differences associated with innate immune response in late first trimester placentas but there is no significant difference in gene expression of innate immune genes between sexes in healthy full-term placentas. Finally, sex differences are predominantly driven by expression from sex-linked genes.