Targeting the intragraft microenvironment and the development of chronic allograft rejection.

In this review, we discuss a paradigm whereby changes in the intragraft microenvironment promote or sustain the development of chronic allograft rejection. A key feature of this model involves the microvasculature including (a) endothelial cell (EC) destruction, and (b) EC proliferation, both of which result from alloimmune leukocyte- and/or alloantibody-induced responses. These changes in the microvasculature likely create abnormal blood flow patterns and thus promote local tissue hypoxia. Another feature of the chronic rejection microenvironment involves the overexpression of vascular endothelial growth factor (VEGF). VEGF stimulates EC activation and proliferation and it has potential to sustain inflammation via direct interactions with leukocytes. In this manner, VEGF may promote ongoing tissue injury. Finally, we review how these events can be targeted therapeutically using mTOR inhibitors. EC activation and proliferation as well as VEGF-VEGFR interactions require PI-3K/Akt/mTOR intracellular signaling. Thus, agents that inhibit this signaling pathway within the graft may also target the progression of chronic rejection and thus promote long-term graft survival.

Characterization and clinical evaluation of CD10+ stroma cells in the breast cancer microenvironment.

PURPOSE: There is growing evidence that interaction between stromal and tumor cells is pivotal in breast cancer progression and response to therapy. Based on earlier research suggesting that during breast cancer progression, striking changes occur in CD10(+) stromal cells, we aimed to better characterize this cell population and its clinical relevance. EXPERIMENTAL DESIGN: We developed a CD10(+) stroma gene expression signature (using HG U133 Plus 2.0) on the basis of the comparison of CD10 cells isolated from tumoral (n = 28) and normal (n = 3) breast tissue. We further characterized the CD10(+) cells by coculture experiments of representative breast cancer cell lines with the different CD10(+) stromal cell types (fibroblasts, myoepithelial, and mesenchymal stem cells). We then evaluated its clinical relevance in terms of in situ to invasive progression, invasive breast cancer prognosis, and prediction of efficacy of chemotherapy using publicly available data sets. RESULTS: This 12-gene CD10(+) stroma signature includes, among others, genes involved in matrix remodeling (MMP11, MMP13, and COL10A1) and genes related to osteoblast differentiation (periostin). The coculture experiments showed that all 3 CD10(+) cell types contribute to the CD10(+) stroma signature, although mesenchymal stem cells have the highest CD10(+) stroma signature score. Of interest, this signature showed an important role in differentiating in situ from invasive breast cancer, in prognosis of the HER2(+) subpopulation of breast cancer only, and potentially in nonresponse to chemotherapy for those patients. CONCLUSIONS: Our results highlight the importance of CD10(+) cells in breast cancer prognosis and efficacy of chemotherapy, particularly within the HER2(+) breast cancer disease.

Predicting adverse events in children with fever and chemotherapy-induced neutropenia: the prospective multicenter SPOG 2003 FN study.

PURPOSE To develop a score predicting the risk of adverse events (AEs) in pediatric patients with cancer who experience fever and neutropenia (FN) and to evaluate its performance. PATIENTS AND METHODS Pediatric patients with cancer presenting with FN induced by nonmyeloablative chemotherapy were observed in a prospective multicenter study. A score predicting the risk of future AEs (ie, serious medical complication, microbiologically defined infection, radiologically confirmed pneumonia) was developed from a multivariate mixed logistic regression model. Its cross-validated predictive performance was compared with that of published risk prediction rules. Results An AE was reported in 122 (29%) of 423 FN episodes. In 57 episodes (13%), the first AE was known only after reassessment after 8 to 24 hours of inpatient management. Predicting AE at reassessment was better than prediction at presentation with FN. A differential leukocyte count did not increase the predictive performance. The score predicting future AE in 358 episodes without known AE at reassessment used the following four variables: preceding chemotherapy more intensive than acute lymphoblastic leukemia maintenance (weight = 4), hemoglobin > or = 90 g/L (weight = 5), leukocyte count less than 0.3 G/L (weight = 3), and platelet count less than 50 G/L (weight = 3). A score (sum of weights) > or = 9 predicted future AEs. The cross-validated performance of this score exceeded the performance of published risk prediction rules. At an overall sensitivity of 92%, 35% of the episodes were classified as low risk, with a specificity of 45% and a negative predictive value of 93%. CONCLUSION This score, based on four routinely accessible characteristics, accurately identifies pediatric patients with cancer with FN at risk for AEs after reassessment.

Marker-independent identification of glioma-initiating cells.

Tumor-initiating cells with stem cell properties are believed to sustain the growth of gliomas, but proposed markers such as CD133 cannot be used to identify these cells with sufficient specificity. We report an alternative isolation method purely based on phenotypic qualities of glioma-initiating cells (GICs), avoiding the use of molecular markers. We exploited intrinsic autofluorescence properties and a distinctive morphology to isolate a subpopulation of cells (FL1(+)) from human glioma or glioma cultures. FL1(+) cells are capable of self-renewal in vitro, tumorigenesis in vivo and preferentially express stem cell genes. The FL1(+) phenotype did not correlate with the expression of proposed GIC markers. Our data propose an alternative approach to investigate tumor-initiating potential in gliomas and to advance the development of new therapies and diagnostics.

PROX1 Promotes Metabolic Adaptation and Fuels Outgrowth of Wnt(high) Metastatic Colon Cancer Cells.

The Wnt pathway is abnormally activated in the majority of colorectal cancers, and significant knowledge has been gained in understanding its role in tumor initiation. However, the mechanisms of metastatic outgrowth in colorectal cancer remain a major challenge. We report that autophagy-dependent metabolic adaptation and survival of metastatic colorectal cancer cells is regulated by the target of oncogenic Wnt signaling, homeobox transcription factor PROX1, expressed by a subpopulation of colon cancer progenitor/stem cells. We identify direct PROX1 target genes and show that repression of a pro-apoptotic member of the BCL2 family, BCL2L15, is important for survival of PROX1(+) cells under metabolic stress. PROX1 inactivation after the establishment of metastases prevented further growth of lesions. Furthermore, autophagy inhibition efficiently targeted metastatic PROX1(+) cells, suggesting a potential therapeutic approach. These data identify PROX1 as a key regulator of the transcriptional network contributing to metastases outgrowth in colorectal cancer.

Association of socioeconomic status with inflammatory markers: a two cohort comparison.

OBJECTIVE: To assess the association between socioeconomic status (SES) and inflammatory markers using two different European population samples. METHODS: We used data from the CoLaus (N=6412, Lausanne, Switzerland) and EPIPorto (N=1205, Porto, Portugal) studies. Education and occupational position were used as indicators of socioeconomic status (SES). High-sensitivity C-reactive protein (hs-CRP) was available for both cohorts. Interleukin-6 (IL-6) and tumour necrosis factor-α (TNF-α) were available in CoLaus; leukocyte count and fibrinogen in EPIPorto. RESULTS: We showed that low SES was significantly associated with high inflammation in both studies. We also showed that behavioural factors contributed the most to SES differences in inflammation. In both studies the larger difference between the lowest and the highest SES was observed for hs-CRP. In the Swiss sample, a linear association between education and hs-CRP persisted after adjustment for all mediating factors and confounders considered (p for linear trend <0.001). CONCLUSION: Large social differences exist in inflammatory activity, in part independently from demographic and behavioural factors, chronic conditions and medication use. SES differences in inflammation are also similar in countries with different underlying socioeconomic conditions.

Mapping Bias Overestimates Reference Allele Frequencies at the HLA Genes in the 1000 Genomes Project Phase I Data.

Next-generation sequencing (NGS) technologies have become the standard for data generation in studies of population genomics, as the 1000 Genomes Project (1000G). However, these techniques are known to be problematic when applied to highly polymorphic genomic regions, such as the human leukocyte antigen (HLA) genes. Because accurate genotype calls and allele frequency estimations are crucial to population genomics analyses, it is important to assess the reliability of NGS data. Here, we evaluate the reliability of genotype calls and allele frequency estimates of the single-nucleotide polymorphisms (SNPs) reported by 1000G (phase I) at five HLA genes (HLA-A, -B, -C, -DRB1, and -DQB1). We take advantage of the availability of HLA Sanger sequencing of 930 of the 1092 1000G samples and use this as a gold standard to benchmark the 1000G data. We document that 18.6% of SNP genotype calls in HLA genes are incorrect and that allele frequencies are estimated with an error greater than ±0.1 at approximately 25% of the SNPs in HLA genes. We found a bias toward overestimation of reference allele frequency for the 1000G data, indicating mapping bias is an important cause of error in frequency estimation in this dataset. We provide a list of sites that have poor allele frequency estimates and discuss the outcomes of including those sites in different kinds of analyses. Because the HLA region is the most polymorphic in the human genome, our results provide insights into the challenges of using of NGS data at other genomic regions of high diversity.