Vascular Profile Characterization of Liver Tumors by Magnetic Resonance Imaging Using Hemodynamic Response Imaging in Mice12

Recently, we have demonstrated the feasibility of using hemodynamic response imaging (HRI), a functional magnetic resonance imaging (MRI) method combined with hypercapnia and hyperoxia, for monitoring vascular changes during liver pathologies without the need of contrast material. In this study, we evaluated HRI ability to assess changes in liver tumor vasculature during tumor establishment, progression, and antiangiogenic therapy. Colorectal adenocarcinoma cells were injected intrasplenically to model colorectal liver metastasis (CRLM) and the Mdr2 knockout mice were used to model primary hepatic tumors. Hepatic perfusion parameters were evaluated using the HRI protocol and were compared with contrast-enhanced (CE) MRI. The hypovascularity and the increased arterial blood supply in well-defined CRLM were demonstrated by HRI. In CRLM-bearing mice, the entire liver perfusion was attenuated as the HRI maps were significantly reduced by 35%. This study demonstrates that the HRI method showed enhanced sensitivity for small CRLM (1–2 mm) detection compared with CE-MRI (82% versus 38%, respectively). In addition, HRI could demonstrate the vasculature alteration during CRLM progression (arborized vessels), which was further confirmed by histology. Moreover, HRI revealed the vascular changes induced by rapamycin treatment. Finally, HRI facilitates primary hepatic tumor characterization with good correlation to the pathologic differentiation. The HRI method is highly sensitive to subtle hemodynamic changes induced by CRLM and, hence, can function as an imaging tool for understanding the hemodynamic changes occurring during CRLM establishment, progression, and antiangiogenic treatment. In addition, this method facilitated the differentiation between different types of hepatic lesions based on their vascular profile noninvasively

Embryonic Stem Cell (ES)-Specific Enhancers Specify the Expression Potential of ES Genes in Cancer.

Cancers often display gene expression profiles resembling those of undifferentiated cells. The mechanisms controlling these expression programs have yet to be identified. Exploring transcriptional enhancers throughout hematopoietic cell development and derived cancers, we uncovered a novel class of regulatory epigenetic mutations. These epimutations are particularly enriched in a group of enhancers, designated ES-specific enhancers (ESSEs) of the hematopoietic cell lineage. We found that hematopoietic ESSEs are prone to DNA methylation changes, indicative of their chromatin activity states. Strikingly, ESSE methylation is associated with gene transcriptional activity in cancer. Methylated ESSEs are hypermethylated in cancer relative to normal somatic cells and co-localized with silenced genes, whereas unmethylated ESSEs tend to be hypomethylated in cancer and associated with reactivated genes. Constitutive or hematopoietic stem cell-specific enhancers do not show these trends, suggesting selective reactivation of ESSEs in cancer. Further analyses of a hypomethylated ESSE downstream to the VEGFA gene revealed a novel regulatory circuit affecting VEGFA transcript levels across cancers and patients. We suggest that the discovered enhancer sites provide a framework for reactivation of ES genes in cancer

Developmental DNA methylation changes in regulatory sites.

<p><b>A.</b> Fractions of methylation sites that lose, maintain, or gain H3K4 chromatin marks in hematopoietic (HSC) stem cells versus ES cells. <b>B.</b> Methylation levels of later (y axes) versus earlier (x axes) developmental stages for sites that lose (red), retain (yellow), or gain (green) H3K4me1 signals during differentiation. Methylation levels in T and B cells are given as well. <b>C.</b> Methylation differences between later to earlier stages as a function of the earlier methylation level, for sites that lose (red), retain (yellow), or gain (green) H3K4me1 signals. <b>D.</b> Sites that are hypo-, hyper- or similarly methylated in HSC compared with ES, categorized by H3K4me1 marking in HSC versus ES. <b>Left:</b> sites that became hypomethylated (at least 20% methylation loss). <b>Middle:</b> sites that became hypermethylated (at least 20% methylation gain). <b>Right:</b> sites that maintained similar methylation levels (less than 20% methylation difference). <b>E.</b> Distribution of DNA methylation differences between HSC and ES for ES-specific enhancers and promoters.</p

Validating a predicted ESSE as a novel VEGFA enhancer.

<p><b>A.</b> Genomic map of the chromatin state around the predicted ESSE site in K562 cells showing the typical chromatin signature (H3K4me1/H3K27ac) of active enhancers. The location of a VEGFA-associated SNP (rs9472155) is indicated. The location of the correlative CpG methylation site is marked by a vertical dashed line. <b>B.</b> Focused (<600 bp) cluster of transcription factor binding sites (Chip-seq data) within the predicted enhancer. The factors bound in K562 cells are listed. This is the only cluster within 20 kb around the ESSE. <b>C.</b> Sequence of the guide RNA used to target the Cas9 endonuclease at the correlative methylation site, and the resulting mutation (insertion) in two independently-analyzed single-cell clones of the transfected K562 cells. <b>D.</b> Expression levels of the endogenous VEGFA gene in the mutated clones relative to mock-treated cell. Results of three independent qPCR experiments with three technical replications of each experiment are shown.</p

ESSE methylation and across-patient VEGFA expression variation.

<p><b>A. Left:</b> Average methylation of VEGF ESSE in cancer and normal samples. P-values of the cancer-normal differences are indicated for analyses including more than one normal and cancer sample. <b>Right:</b> Same analyses for VEGF expression level. <b>B. Left:</b> Correlation between methylation of VEGFA ESSE and VEGFA expression levels across DLBC patients. <b>Right:</b> Correlation between methylation of the VEGFA promoter (average of nine methylation sites within 1 kb of TSS) and VEGFA expression levels across DLBC patients. <b>C.</b> Same analyses as in B for normal and cancerous colon and liver samples.</p

Methylation trends of ESSEs in fresh cancer samples.

<p><b>A.</b> Average cancer-normal methylation differences of the ESSEs that were differentially methylated between Jurkat and normal T cells, in diffuse large B-cell lymphoma (DLBC), colorectal cancer (CRC), or hepatocellular carcinoma (HCC). The number of fresh tumor samples is indicated. <b>B.</b> Overlay of hyper- and hypomethylated ESSEs in Jurkat and other cancers.</p

Polycomb-repressed genes have hypermethylated enhancers.

<p><b>A.</b> Overlap between ESSE sites that gain methylation in cancer and ESSE sites that are undermethylated in ES. <b>B.</b> DNA methylation levels of ES-undermethylated-cancer-hypermethylated ESSEs during development. <b>C.</b> Foreground and background sets for the analyses shown in D and E. <b>D.</b> Gene set enrichment analysis of the gene ontology groups adjacent to sites in the background versus the foreground sets. The most significantly-enriched gene ontology groups proximal to hypermethylated ESSEs are indicated. <b>E.</b> Fractions of enhancer sites carrying H3K27me3 marks in ES. <b>F.</b> An example of cancer-hypermethylated ESSE in theGS Homeobox 1 (GSX1) gene region. Gray boxes indicate a region around the gene (left) and an ESSE region 25 kb upstream from the gene (right) marked by H3K27me3 and bound by the polycomb-related protein EZH2 in ES cells. These regions are hypermethylated in cancer.</p

Hemodynamic response imaging: a potential tool for the assessment of angiogenesis in brain tumors.

Blood oxygenation level dependence (BOLD) imaging under either hypercapnia or hyperoxia has been used to study neuronal activation and for assessment of various brain pathologies. We evaluated the benefit of a combined protocol of BOLD imaging during both hyperoxic and hypercapnic challenges (termed hemodynamic response imaging (HRI)). Nineteen healthy controls and seven patients with primary brain tumors were included: six with glioblastoma (two newly diagnosed and four with recurrent tumors) and one with atypical-meningioma. Maps of percent signal intensity changes (ΔS) during hyperoxia (carbogen; 95%O2+5%CO2) and hypercapnia (95%air+5%CO2) challenges and vascular reactivity mismatch maps (VRM; voxels that responded to carbogen with reduced/absent response to CO2) were calculated. VRM values were measured in white matter (WM) and gray matter (GM) areas of healthy subjects and used as threshold values in patients. Significantly higher response to carbogen was detected in healthy subjects, compared to hypercapnia, with a GM/WM ratio of 3.8 during both challenges. In patients with newly diagnosed/treatment-naive tumors (n = 3), increased response to carbogen was detected with substantially increased VRM response (compared to threshold values) within and around the tumors. In patients with recurrent tumors, reduced/absent response during both challenges was demonstrated. An additional finding in 2 of 4 patients with recurrent glioblastoma was a negative response during carbogen, distant from tumor location, which may indicate steal effect. In conclusion, the HRI method enables the assessment of blood vessel functionality and reactivity. Reference values from healthy subjects are presented and preliminary results demonstrate the potential of this method to complement perfusion imaging for the detection and follow up of angiogenesis in patients with brain tumors

Accelerated carcinogenesis following liver regeneration is associated with chronic inflammation-induced double-strand DNA breaks

Hepatocellular carcinoma (HCC) is the third leading cause of cancer mortality worldwide and is considered to be the outcome of chronic liver inflammation. Currently, the main treatment for HCC is surgical resection. However, survival rates are suboptimal partially because of tumor recurrence in the remaining liver. Our aim was to understand the molecular mechanisms linking liver regeneration under chronic inflammation to hepatic tumorigenesis. Mdr2-KO mice, a model of inflammation-associated cancer, underwent partial hepatectomy (PHx), which led to enhanced hepatocarcinogenesis. Moreover, liver regeneration in these mice was severely attenuated. We demonstrate the activation of the DNA damage-response machinery and increased genomic instability during early liver inflammatory stages resulting in hepatocyte apoptosis, cell-cycle arrest, and senescence and suggest their involvement in tumor growth acceleration subsequent to PHx. We propose that under the regenerative proliferative stress induced by liver resection, the genomic unstable hepatocytes generated during chronic inflammation escape senescence and apoptosis and reenter the cell cycle, triggering the enhanced tumorigenesis. Thus, we clarify the immediate and long-term contributions of the DNA damage response to HCC development and recurrence