Transcription and methylation analyses of preleukemic promyelocytes indicate a dual role for PML/RARA in leukemia initiation.

Acute promyelocytic leukemia is an aggressive malignancy characterized by the accumulation of promyelocytes in the bone marrow. PML/RARA is the primary abnormality implicated in this pathology, but the mechanisms by which this chimeric fusion protein initiates disease are incompletely understood. Identifying PML/RARA targets in vivo is critical for comprehending the road to pathogenesis. Utilizing a novel sorting strategy, we isolated highly purified promyelocyte populations from normal and young preleukemic animals, carried out microarray and methylation profiling analyses, and compared the results from the two groups of animals. Surprisingly, in the absence of secondary lesions, PML/RARA had an overall limited impact on both the transcriptome and methylome. Of interest, we did identify down-regulation of secondary and tertiary granule genes as the first step engaging the myeloid maturation block. Although initially not sufficient to arrest terminal granulopoiesis in vivo, such alterations set the stage for the later, complete differentiation block seen in leukemia. Further, gene set enrichment analysis revealed that PML/RARA promyelocytes exhibit a subtle increase in expression of cell cycle genes, and we show that this leads to both increased proliferation of these cells and expansion of the promyelocyte compartment. Importantly, this proliferation signature was absent from the poorly leukemogenic p50/RARA fusion model, implying a critical role for PML in the altered cell-cycle kinetics and ability to initiate leukemia. Thus, our findings challenge the predominant model in the field and we propose that PML/RARA initiates leukemia by subtly shifting cell fate decisions within the promyelocyte compartment.

Gene expression profile identifies tyrosine kinase c-Met as a targetable mediator of antiangiogenic therapy resistance.

PURPOSE: To identify mediators of glioblastoma antiangiogenic therapy resistance and target these mediators in xenografts. EXPERIMENTAL DESIGN: We conducted microarray analysis comparing bevacizumab-resistant glioblastomas (BRG) with pretreatment tumors from the same patients. We established novel xenograft models of antiangiogenic therapy resistance to target candidate resistance mediator(s). RESULTS: BRG microarray analysis revealed upregulation versus pretreatment of receptor tyrosine kinase c-Met, which underwent further investigation because of its prior biologic plausibility as a bevacizumab resistance mediator. BRGs exhibited increased hypoxia versus pretreatment in a manner correlating with their c-Met upregulation, increased c-Met phosphorylation, and increased phosphorylation of c-Met-activated focal adhesion kinase and STAT3. We developed 2 novel xenograft models of antiangiogenic therapy resistance. In the first model, serial bevacizumab treatment of an initially responsive xenograft generated a xenograft with acquired bevacizumab resistance, which exhibited upregulated c-Met expression versus pretreatment. In the second model, a BRG-derived xenograft maintained refractoriness to the MRI tumor vasculature alterations and survival-promoting effects of bevacizumab. Growth of this BRG-derived xenograft was inhibited by a c-Met inhibitor. Transducing these xenograft cells with c-Met short hairpin RNA inhibited their invasion and survival in hypoxia, disrupted their mesenchymal morphology, and converted them from bevacizumab-resistant to bevacizumab-responsive. Engineering bevacizumab-responsive cells to express constitutively active c-Met caused these cells to form bevacizumab-resistant xenografts. CONCLUSION: These findings support the role of c-Met in survival in hypoxia and invasion, features associated with antiangiogenic therapy resistance, and growth and therapeutic resistance of xenografts resistant to antiangiogenic therapy. Therapeutically targeting c-Met could prevent or overcome antiangiogenic therapy resistance.

Microarray analysis verifies two distinct phenotypes of glioblastomas resistant to antiangiogenic therapy.

PURPOSE: To identify mechanisms and mediators of resistance to antiangiogenic therapy in human glioblastoma. EXPERIMENTAL DESIGN: We carried out microarray gene expression analysis and immunohistochemistry comparing 21 recurrent glioblastomas progressing during antiangiogenic treatment with VEGF neutralizing antibody bevacizumab to paired pretreatment tumors from the same patients. RESULTS: Microarray analysis revealed that bevacizumab-resistant glioblastomas (BRG) had two clustering patterns defining subtypes that reflect radiographic growth patterns. Enhancing BRGs (EBRG) exhibited MRI enhancement, a long-established criterion for glioblastoma progression, and expressed mitogen-activated protein kinases, neural cell adhesion molecule-1 (NCAM-1), and aquaporin 4. Compared with their paired pretreatment tumors, EBRGs had unchanged vascularity and hypoxia, with increased proliferation. Nonenhancing BRGs (NBRG) exhibited minimal MRI enhancement but had FLAIR-bright expansion, a newer criterion for glioblastoma recurrence since the advent of antiangiogenic therapy, and expressed integrin α5, laminin, fibronectin1, and PDGFRß. NBRGs had less vascularity, more hypoxia, and unchanged proliferation than their paired pretreatment tumors. Primary NBRG cells exhibited more stellate morphology with a 3-fold increased shape factor and were nearly 4-fold more invasive in Matrigel chambers than primary cells from EBRGs or bevacizumab-naive glioblastomas (P < 0.05). CONCLUSION: Using microarray analysis, we found two resistance patterns during antiangiogenic therapy with distinct molecular profiles and radiographic growth patterns. These studies provide valuable biologic insight into the resistance that has limited antiangiogenic therapy to date.

Fractional genomic alteration detected by array-based comparative genomic hybridization independently predicts survival after hepatic resection for metastatic colorectal cancer.

PURPOSE: Although liver resection is the primary curative therapy for patients with colorectal hepatic metastases, most patients have a recurrence. Identification of molecular markers that predict patients at highest risk for recurrence may help to target further therapy. EXPERIMENTAL DESIGN: Array-based comparative genomic hybridization was used to investigate the association of DNA copy number alterations with outcome in patients with colorectal liver metastasis resected with curative intent. DNA from 50 liver metastases was labeled and hybridized onto an array consisting of 2,463 bacterial artificial chromosome clones covering the entire genome. The total fraction of genome altered (FGA) in the metastases and the patient's clinical risk score (CRS) were calculated to identify independent prognostic factors for survival. RESULTS: An average of 30 +/- 14% of the genome was altered in the liver metastases (14% gained and 16% lost). As expected, a lower CRS was an independent predictor of overall survival (P = 0.03). In addition, a high FGA also was an independent predictor of survival (P = 0.01). The median survival time in patients with a low CRS (score 0-2) and a high (> or =20%) FGA was 38 months compared with 18 months in patients with a low CRS and a low FGA. Supervised analyses, using Prediction Analysis of Microarrays and Significance Analysis of Microarrays, identified a set of clones, predominantly located on chromosomes 7 and 20, which best predicted survival. CONCLUSIONS: Both FGA and CRS are independent predictors of survival in patients with resected hepatic colorectal cancer metastases. The greater the FGA, the more likely the patient is to survive.

Fully automatic quantification of microarray image data.

DNA microarrays are now widely used to measure expression levels and DNA copy number in biological samples. Ratios of relative abundance of nucleic acids are derived from images of regular arrays of spots containing target genetic material to which fluorescently labeled samples are hybridized. Whereas there are a number of methods in use for the quantification of images, many of the software systems in wide use either encourage or require extensive human interaction at the level of individual spots on arrays. We present a fully automatic system for microarray image quantification. The system automatically locates both subarray grids and individual spots, requiring no user identification of any image coordinates. Ratios are computed based on explicit segmentation of each spot. On a typical image of 6000 spots, the entire process takes less than 20 sec. We present a quantitative assessment of performance on multiple replicates of genome-wide array-based comparative genomic hybridization experiments. By explicitly identifying the pixels in each spot, the system yields more accurate estimates of ratios than systems assuming spot circularity. The software, called, runs on Windows platforms and is available free of charge for academic use.