Using Dynamic Contrast-Enhanced Magnetic Resonance Imaging Data to Constrain a Positron Emission Tomography Kinetic Model: Theory and Simulations

We show how dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) data can constrain a compartmental model for analyzing dynamic positron emission tomography (PET) data. We first develop the theory that enables the use of DCE-MRI data to separate whole tissue time activity curves (TACs) available from dynamic PET data into individual TACs associated with the blood space, the extravascular-extracellular space (EES), and the extravascular-intracellular space (EIS). Then we simulate whole tissue TACs over a range of physiologically relevant kinetic parameter values and show that using appropriate DCE-MRI data can separate the PET TAC into the three components with accuracy that is noise dependent. The simulations show that accurate blood, EES, and EIS TACs can be obtained as evidenced by concordance correlation coefficients >0.9 between the true and estimated TACs. Additionally, provided that the estimated DCE-MRI parameters are within 10% of their true values, the errors in the PET kinetic parameters are within approximately 20% of their true values. The parameters returned by this approach may provide new information on the transport of a tracer in a variety of dynamic PET studies

Computational Prediction and Experimental Verification of New MAP Kinase Docking Sites and Substrates Including Gli Transcription Factors

In order to fully understand protein kinase networks, new methods are needed to identify regulators and substrates of kinases, especially for weakly expressed proteins. Here we have developed a hybrid computational search algorithm that combines machine learning and expert knowledge to identify kinase docking sites, and used this algorithm to search the human genome for novel MAP kinase substrates and regulators focused on the JNK family of MAP kinases. Predictions were tested by peptide array followed by rigorous biochemical verification with in vitro binding and kinase assays on wild-type and mutant proteins. Using this procedure, we found new ‘D-site’ class docking sites in previously known JNK substrates (hnRNP-K, PPM1J/PP2Czeta), as well as new JNK-interacting proteins (MLL4, NEIL1). Finally, we identified new D-site-dependent MAPK substrates, including the hedgehog-regulated transcription factors Gli1 and Gli3, suggesting that a direct connection between MAP kinase and hedgehog signaling may occur at the level of these key regulators. These results demonstrate that a genome-wide search for MAP kinase docking sites can be used to find new docking sites and substrates

Gene expression profiling of U2AF2 dependent RNA-protein interactions during CD4+ T cell activation

CD4 T cell activation is a central component of the mammalian adaptive immune response and is underscored by a dramatic change in the gene expression profile in these cells. The changes in gene expression that occur during T cell activation are regulated in multiple ways including post-transcriptionally by complexes of RNA-binding proteins. Recently, our study explored the role of the RNA-binding protein U2AF2 and its interacting proteins in mediating posttranscriptional changes in constitutive and alternative splicing during T cell activation. First, we used RNA-seq to identify the global changes in gene expression and splicing that occur with T cell activation. Next, we used RIP-seq to identify the specific genes bound to U2AF2 during T cell activation. After identification of the protein interacting partners of U2AF2, we used splicing sensitive microarrays to measure the effects on global gene expression of using siRNAs to knock down a sampling of these proteins. Finally, we used RIP-chip to measure the effects of the same siRNA knockdown on the transcripts specifically bound to U2AF2. Here we provide the experimental details and analysis of the gene expression data for each of these techniques, which have been deposited into Gene Expression Omnibus (GEO) with the Superseries ID: GSE62923

Organic Anion Transporters (OAT) and Other SLC22 Transporters in Progression of Renal Cell Carcinoma

(1) Background: Many transporters of the SLC22 family (e.g., OAT1, OAT3, OCT2, URAT1, and OCTN2) are highly expressed in the kidney. They transport drugs, metabolites, signaling molecules, antioxidants, nutrients, and gut microbiome products. According to the Remote Sensing and Signaling Theory, SLC22 transporters play a critical role in small molecule communication between organelles, cells and organs as well as between the body and the gut microbiome. This raises the question about the potential role of SLC22 transporters in cancer biology and treatment. (2) Results: In two renal cell carcinoma RNA-seq datasets found in TCGA, KIRC and KIRP, there were multiple differentially expressed (DE) SLC22 transporter genes compared to normal kidney. These included SLC22A6, SLC22A7, SLC22A8, SLC22A12, and SLC22A13. The patients with disease had an association between overall survival and expression for most of these DE genes. In KIRC, the stratification of patient data by pathological tumor characteristics revealed the importance of SLC22A2, SLC22A6, and SLC22A12 in disease progression. Interaction networks combining the SLC22 with ADME genes supported the centrality of SLC22 transporters and other transporters (ABCG2, SLC47A1) in disease progression. (3) Implications: The fact that many of these genes are uric acid transporters is interesting because altered uric acid levels have been associated with kidney cancer. Moreover, these genes play key roles in processing metabolites and chemotherapeutic compounds, thus making them potential therapeutic targets. Finally, our analyses raise the possibility that current approaches may undertreat certain kidney cancer patients with low SLC22 expression and only localized disease while possibly overtreating more advanced disease in patients with higher SLC22 expression. Clinical studies are needed to investigate these possibilities

A quantitative comparison of the influence of individual versus population-derived vascular input functions on dynamic contrast enhanced-MRI in small animals

For quantitative analysis of DCE-MRI data, the time course of the concentration of the contrast agent in the blood plasma, or vascular input function (VIF), is required. We compared pharmacokinetic parameters derived using individual and population-based VIFs in mice for two different contrast agents, Gd-DTPA and P846. Eleven mice with subcutaneous 4T1 breast cancer xenografts were imaged at 7T. A pre-contrast T(1) map was acquired along with dynamic T(1)-weighted gradient echo images before, during, and after a bolus injection of contrast agent delivered via a syringe pump. Each animal's individual VIF (VIF(ind)) and derived population-averaged VIF (VIF(pop)) were used to extract parameters from the signal-time curves of tumor tissue at both the region of interest (ROI) and voxel level. The results indicate that for both contrast agents, K(trans) values estimated using VIF(pop) have a high correlation (CCC > 0.85) with K(trans) values estimated using VIF(ind) on both an ROI and voxel level. This work supports the validity of using of a population-based VIF with a stringent injection protocol in pre-clinical DCE-MRI studies

Trastuzumab Improves Tumor Perfusion And Vascular Delivery Of Cytotoxic Therapy In A Murine Model Of Her2+ Breast Cancer: Preliminary Results

To employ in vivo imaging and histological techniques to identify and quantify vascular changes early in the course of treatment with trastuzumab in a murine model of HER2+ breast cancer. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) was used to quantitatively characterize vessel perfusion/permeability (via the parameter Ktrans) and the extravascular extracellular volume fraction (ve) in the BT474 mouse model of HER2+ breast cancer (N = 20) at baseline, day one, and day four following trastuzumab treatment (10 mg/kg). Additional cohorts of mice were used to quantify proliferation (Ki67), microvessel density (CD31), pericyte coverage (α-SMA) by immunohistochemistry (N = 44), and to quantify human VEGF-A expression (N = 29) throughout the course of therapy. Longitudinal assessment of combination doxorubicin ± trastuzumab (N = 42) tested the hypothesis that prior treatment with trastuzumab will increase the efficacy of subsequent doxorubicin therapy. Compared to control tumors, trastuzumab-treated tumors exhibited a significant increase in Ktrans (P = 0.035) on day four, indicating increased perfusion and/or vessel permeability and a simultaneous significant increase in ve (P = 0.01), indicating increased cell death. Immunohistochemical and ELISA analyses revealed that by day four the trastuzumab-treated tumors had a significant increase in vessel maturation index (i.e., the ratio of α-SMA to CD31 staining) compared to controls (P \u3c 0.001) and a significant decrease in VEGF-A (P = 0.03). Additionally, trastuzumab dosing prior to doxorubicin improved the overall effectiveness of the therapies (P \u3c 0.001). This study identifies and validates improved perfusion characteristics following trastuzumab therapy, resulting in an improvement in trastuzumab-doxorubicin combination therapy in a murine model of HER2+ breast cancer. This data suggests properties of vessel maturation. In particular, the use of DCE-MRI, a clinically available imaging method, following treatment with trastuzumab may provide an opportunity to optimize the scheduling and improve delivery of subsequent cytotoxic therapy

Computational Prediction and Experimental Verification of New MAP Kinase Docking Sites and Substrates Including Gli Transcription Factors

In order to fully understand protein kinase networks, new methods are needed to identify regulators and substrates of kinases, especially for weakly expressed proteins. Here we have developed a hybrid computational search algorithm that combines machine learning and expert knowledge to identify kinase docking sites, and used this algorithm to search the human genome for novel MAP kinase substrates and regulators focused on the JNK family of MAP kinases. Predictions were tested by peptide array followed by rigorous biochemical verification with in vitro binding and kinase assays on wild-type and mutant proteins. Using this procedure, we found new 'D-site' class docking sites in previously known JNK substrates (hnRNP-K, PPM1J/PP2Czeta), as well as new JNK-interacting proteins (MLL4, NEIL1). Finally, we identified new D-site-dependent MAPK substrates, including the hedgehog-regulated transcription factors Gli1 and Gli3, suggesting that a direct connection between MAP kinase and hedgehog signaling may occur at the level of these key regulators. These results demonstrate that a genome-wide search for MAP kinase docking sites can be used to find new docking sites and substrates

The Activation-Induced Assembly of an RNA/Protein Interactome Centered on the Splicing Factor U2AF2 Regulates Gene Expression in Human CD4 T Cells.

Activation of CD4 T cells is a reaction to challenges such as microbial pathogens, cancer and toxins that defines adaptive immune responses. The roles of T cell receptor crosslinking, intracellular signaling, and transcription factor activation are well described, but the importance of post-transcriptional regulation by RNA-binding proteins (RBPs) has not been considered in depth. We describe a new model expanding and activating primary human CD4 T cells and applied this to characterizing activation-induced assembly of splicing factors centered on U2AF2. We immunoprecipitated U2AF2 to identify what mRNA transcripts were bound as a function of activation by TCR crosslinking and costimulation. In parallel, mass spectrometry revealed the proteins incorporated into the U2AF2-centered RNA/protein interactome. Molecules that retained interaction with the U2AF2 complex after RNAse treatment were designated as "central" interactome members (CIMs). Mass spectrometry also identified a second class of activation-induced proteins, "peripheral" interactome members (PIMs), that bound to the same transcripts but were not in physical association with U2AF2 or its partners. siRNA knockdown of two CIMs and two PIMs caused changes in activation marker expression, cytokine secretion, and gene expression that were unique to each protein and mapped to pathways associated with key aspects of T cell activation. While knocking down the PIM, SYNCRIP, impacts a limited but immunologically important set of U2AF2-bound transcripts, knockdown of U2AF1 significantly impairs assembly of the majority of protein and mRNA components in the activation-induced interactome. These results demonstrated that CIMs and PIMs, either directly or indirectly through RNA, assembled into activation-induced U2AF2 complexes and play roles in post-transcriptional regulation of genes related to cytokine secretion. These data suggest an additional layer of regulation mediated by the activation-induced assembly of RNA splicing interactomes that is important for understanding T cell activation