Facilitation of Pavlovian conditioned cardiodecelerations following preshock in immobilized rats

Two experiments are reported that examine the effects of unsignalled, inescapable prior shock exposure (PSE) on shock-motivated Pavlovian conditioned heart rate (HR) decelerations in rats. Both studies involved 2 CS-US contingencies (paired and unpaired) and 2 preshock treatments (preshock and no preshock). The 2 designs differed in the type of immobilization procedures to which the rats were submitted and the number of conditioning sessions. In Experiment 1 rats were conditioned for 2 consecutive 35 trial sessions while physically restrained, whereas only one conditioning session was used in Experiment 2 on animals that were paralyzed with d-tubocurarine chloride (dTC). The results demonstrated that PSE augmented the magnitude of the HR conditioned response (CR) in both the physically restrained and paralyzed preparations. In addition, PSE improved the rate of acquisition of the conditioned cardiodeceleration in physically restrained rats and tended to facilitate reinstatement of the HR CR during the second conditioning session. These data support the notion that certain nonspecific stress processes that are relatively independent of the CS-US contingency but related to the occurrence of response suppression are intimately involved in Pavlovian HR conditioning.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/21940/1/0000347.pd

Paradoxical decrease in norepinephrine content of adult mouse spleen and heart after neonatal nerve growth factor treatment

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/21945/1/0000352.pd

Characterizing genomic alterations in cancer by complementary functional associations.

Systematic efforts to sequence the cancer genome have identified large numbers of mutations and copy number alterations in human cancers. However, elucidating the functional consequences of these variants, and their interactions to drive or maintain oncogenic states, remains a challenge in cancer research. We developed REVEALER, a computational method that identifies combinations of mutually exclusive genomic alterations correlated with functional phenotypes, such as the activation or gene dependency of oncogenic pathways or sensitivity to a drug treatment. We used REVEALER to uncover complementary genomic alterations associated with the transcriptional activation of β-catenin and NRF2, MEK-inhibitor sensitivity, and KRAS dependency. REVEALER successfully identified both known and new associations, demonstrating the power of combining functional profiles with extensive characterization of genomic alterations in cancer genomes

Comprehensive molecular characterization of gastric adenocarcinoma

Gastric cancer is a leading cause of cancer deaths, but analysis of its molecular and clinical characteristics has been complicated by histological and aetiological heterogeneity. Here we describe a comprehensive molecular evaluation of 295 primary gastric adenocarcinomas as part of The Cancer Genome Atlas (TCGA) project. We propose a molecular classification dividing gastric cancer into four subtypes: tumours positive for Epstein–Barr virus, which display recurrent PIK3CA mutations, extreme DNA hypermethylation, and amplification of JAK2, CD274 (also known as PD-L1) and PDCD1LG2 (also knownasPD-L2); microsatellite unstable tumours, which show elevated mutation rates, including mutations of genes encoding targetable oncogenic signalling proteins; genomically stable tumours, which are enriched for the diffuse histological variant and mutations of RHOA or fusions involving RHO-family GTPase-activating proteins; and tumours with chromosomal instability, which show marked aneuploidy and focal amplification of receptor tyrosine kinases. Identification of these subtypes provides a roadmap for patient stratification and trials of targeted therapies

The Somatic Genomic Landscape of Glioblastoma

We describe the landscape of somatic genomic alterations based on multi-dimensional and comprehensive characterization of more than 500 glioblastoma tumors (GBMs). We identify several novel mutated genes as well as complex rearrangements of signature receptors including EGFR and PDGFRA. TERT promoter mutations are shown to correlate with elevated mRNA expression, supporting a role in telomerase reactivation. Correlative analyses confirm that the survival advantage of the proneural subtype is conferred by the G-CIMP phenotype, and MGMT DNA methylation may be a predictive biomarker for treatment response only in classical subtype GBM. Integrative analysis of genomic and proteomic profiles challenges the notion of therapeutic inhibition of a pathway as an alternative to inhibition of the target itself. These data will facilitate the discovery of therapeutic and diagnostic target candidates, the validation of research and clinical observations and the generation of unanticipated hypotheses that can advance our molecular understanding of this lethal cancer

Multiplatform Analysis of 12 Cancer Types Reveals Molecular Classification within and across Tissues of Origin

Recent genomic analyses of pathologically-defined tumor types identify “within-a-tissue” disease subtypes. However, the extent to which genomic signatures are shared across tissues is still unclear. We performed an integrative analysis using five genome-wide platforms and one proteomic platform on 3,527 specimens from 12 cancer types, revealing a unified classification into 11 major subtypes. Five subtypes were nearly identical to their tissue-of-origin counterparts, but several distinct cancer types were found to converge into common subtypes. Lung squamous, head & neck, and a subset of bladder cancers coalesced into one subtype typified by TP53 alterations, TP63 amplifications, and high expression of immune and proliferation pathway genes. Of note, bladder cancers split into three pan-cancer subtypes. The multi-platform classification, while correlated with tissue-of-origin, provides independent information for predicting clinical outcomes. All datasets are available for data-mining from a unified resource to support further biological discoveries and insights into novel therapeutic strategies

Developing antagonists for the Met-HGF/SF protein-protein interaction using a fragment-based approach

In many cancers, aberrant activation of the Met receptor tyrosine kinase leads to dissociation of cells from the primary tumor, causing metastasis. Accordingly, Met is a high-profile target for the development of cancer therapies, and progress has been made through development of small molecule kinase inhibitors and antibodies. However, both approaches pose significant challenges with respect to either target specificity (kinase inhibitors) or the cost involved in treating large patient cohorts (antibodies). Here, we use a fragment-based approach in order to target the protein-protein interaction (PPI) between the α-chain of hepatocyte growth factor/scatter factor (HGF/SF; the NK1 fragment) and its high-affinity binding site located on the Met Sema domain. Surface plasmon resonance was used for initial fragment library screening and hits were developed into larger compounds using substructure (similarity) searches. We identified compounds able to interfere with NK1 binding to Met, disrupt Met signaling, and inhibit tumorsphere generation and cell migration. Using molecular docking, we concluded that some of these compounds inhibit the PPI directly, whereas others act indirectly. Our results indicate that chemical fragments can efficiently target the HGF/SF-Met interface and may be used as building blocks for generating biologically active lead compounds. This strategy may have broad application for the development of a new class of Met inhibitors, namely receptor antagonists, and in general for the development of small molecule PPI inhibitors of key therapeutic targets when structural information is not available