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Hepatocellular carcinoma (HCC) is one of the most deadly cancers worldwide and has no effective treatment, yet the molecular basis of hepatocarcinogenesis remains largely unknown. Here we report findings from a whole-genome sequencing (WGS) study of 88 matched HCC tumor/normal pairs, 81 of which are Hepatitis B virus (HBV) positive, seeking to identify genetically altered genes and pathways implicated in HBV-associated HCC. We find beta-catenin to be the most frequently mutated oncogene (15.9%) and TP53 the most frequently mutated tumor suppressor (35.2%). The Wnt/beta-catenin and JAK/STAT pathways, altered in 62.5% and 45.5% of cases, respectively, are likely to act as two major oncogenic drivers in HCC. This study also identifies several prevalent and potentially actionable mutations, including activating mutations of Janus kinase 1 (JAK1), in 9.1% of patients and provides a path toward therapeutic intervention of the disease. [ABSTRACT FROM AUTHOR]

Unlabelled: Cancer is a genetic disease with frequent somatic DNA alterations. Studying recurrent copy number aberrations (CNAs) in human cancers would enable the elucidation of disease mechanisms and the prioritization of candidate oncogenic drivers with causal roles in oncogenesis. We have comprehensively and systematically characterized CNAs and the accompanying gene expression changes in tumors and matched nontumor liver tissues from 286 hepatocellular carcinoma (HCC) patients. Our analysis identified 29 recurrently amplified and 22 recurrently deleted regions with a high level of copy number changes. These regions harbor established oncogenes and tumor suppressors, including CCND1 (cyclin D1), MET (hepatocyte growth factor receptor), CDKN2A (cyclin-dependent kinase inhibitor 2A) and CDKN2B (cyclin-dependent kinase inhibitor 2B), as well as many other genes not previously reported to be involved in liver carcinogenesis. Pathway analysis of cis-acting genes in the amplification and deletion peaks implicates alterations of core cancer pathways, including cell-cycle, p53 signaling, phosphoinositide 3-kinase signaling, mitogen-activated protein kinase signaling, Wnt signaling, and transforming growth factor beta signaling, in a large proportion of HCC patients. We further credentialed two candidate driver genes (BCL9 and MTDH) from the recurrent focal amplification peaks and showed that they play a significant role in HCC growth and survival., Conclusion: We have demonstrated that characterizing the CNA landscape in HCC will facilitate the understanding of disease mechanisms and the identification of oncogenic drivers that may serve as potential therapeutic targets for the treatment of this devastating disease., (Copyright © 2013 by the American Association for the Study of Liver Diseases.)

Background: The androgen receptor plays a critical role throughout the progression of prostate cancer and is an important drug target for this disease. While chromatin immunoprecipitation coupled with massively parallel sequencing (ChIP-Seq) is becoming an essential tool for studying transcription and chromatin modification factors, it has rarely been employed in the context of drug discovery., Results: Here we report changes in the genome-wide AR binding landscape due to dose-dependent inhibition by drug-like small molecules using ChIP-Seq. Integration of sequence analysis, transcriptome profiling, cell viability assays and xenograft tumor growth inhibition studies enabled us to establish a direct cistrome-activity relationship for two novel potent AR antagonists. By selectively occupying the strongest binding sites, AR signaling remains active even when androgen levels are low, as is characteristic of first-line androgen ablation therapy. Coupled cistrome and transcriptome profiling upon small molecule antagonism led to the identification of a core set of AR direct effector genes that are most likely to mediate the activities of targeted agents: unbiased pathway mapping revealed that AR is a key modulator of steroid metabolism by forming a tightly controlled feedback loop with other nuclear receptor family members and this oncogenic effect can be relieved by antagonist treatment. Furthermore, we found that AR also has an extensive role in negative gene regulation, with estrogen (related) receptor likely mediating its function as a transcriptional repressor., Conclusions: Our study provides a global and dynamic view of AR's regulatory program upon antagonism, which may serve as a molecular basis for deciphering and developing AR therapeutics.

Targeting cancers with amplified or abnormally activated c-Met (hepatocyte growth factor receptor) may have therapeutic benefit based on nonclinical and emerging clinical findings. However, the eventual emergence of drug resistant tumors motivates the pre-emptive identification of potential mechanisms of clinical resistance. We rendered a MET amplified gastric cancer cell line, GTL16, resistant to c-Met inhibition with prolonged exposure to a c-Met inhibitor, PF-04217903 (METi). Characterization of surviving cells identified an amplified chromosomal rearrangement between 7q32 and 7q34 which overexpresses a constitutively active SND1-BRAF fusion protein. In the resistant clones, hyperactivation of the downstream MAPK pathway via SND1-BRAF conferred resistance to c-Met receptor tyrosine kinase inhibition. Combination treatment with METi and a RAF inhibitor, PF-04880594 (RAFi) inhibited ERK activation and circumvented resistance to either single agent. Alternatively, treatment with a MEK inhibitor, PD-0325901 (MEKi) alone effectively blocked ERK phosphorylation and inhibited cell growth. Our results suggest that combination of a c-Met tyrosine kinase inhibitor with a BRAF or a MEK inhibitor may be effective in treating resistant tumors that use activated BRAF to escape suppression of c-Met signaling.

Multiproperty lead optimization that satisfies multiple biological endpoints remains a challenge in the pursuit of viable drug candidates. Optimization of a given lead compound to one having a desired set of molecular attributes often involves a lengthy iterative process that utilizes existing information, tests hypotheses, and incorporates new data. Within the context of a data-rich corporate setting, computational tools and predictive models have provided the chemists a means for facilitating and streamlining this iterative design process. This chapter discloses an actual library design scenario for following up a lead compound that inhibits 11β-hydroxysteroid dehydrogenase type 1 (11β-HSD1) enzyme. The application of computational tools and predictive models in the targeted library design of adamantyl amide 11β-HSD1 inhibitors is described. Specifically, the multiproperty profiling using our proprietary PGVL (Pfizer Global Virtual Library) Hub is discussed in conjunction with the structure-based component of the library design using our in-house docking tool AGDOCK. The docking simulations were based on a piecewise linear potential energy function in combination with an efficient evolutionary programming search engine. The library production protocols and results are also presented.

P-cadherin is a calcium-dependent cell-cell adhesion glycoprotein. P-cadherin expression is restricted to the myoepithelial cells in normal breast tissue, and aberrant staining has also been described in invasive tumors. Several small studies have reported P-cadherin as a marker of poor outcome in breast cancer patients but its prognostic significance in relation to other variables has not been established in a large series of breast cancers. A tissue microarray was constructed from 3992 cases of invasive breast carcinoma, and P-cadherin expression was evaluated using immunohistochemistry. Median follow-up was 12.5 years. The immunohistochemistry-based definitions of cancer subtypes were luminal (ER+ or PR+/HER2-), luminal/HER2+ (ER+ or PR+/HER2+), HER2+ (ER-/PR-/HER2+), and basal (ER-/PR-/HER2-/CK5/6+ or EGFR+). Clinical covariate and biomarker associations were assessed using contingency tables, and Pearson's χ(2) or Fisher's exact test. Survival associations were assessed using Kaplan-Meier plots, logrank and Breslow tests, and Cox proportional hazards regression analysis. P-cadherin was expressed in 34.8% (1290/3710, 50% cut point) of cases. P-cadherin staining was strongly associated with HER2+ and basal carcinoma subtypes (P<0.0005). P-cadherin-positive patients showed significantly poorer short-term (0-10 years) overall survival, disease-specific survival, distant relapse-free interval, and locoregional relapse-free interval in univariable models (P<0.05). In multivariable Cox models containing standard clinical covariates and cancer subtypes, P-cadherin did not show independent prognostic value. P-cadherin expression was positively associated with histological grade, chemotherapy, Ki-67, EGFR, CK5/6, p53, YB-1, and HER2 expression (P<0.002), and negatively associated with age at diagnosis, ER, PR, and Bcl-2 expression (P<0.0005). This study shows the value of P-cadherin as a marker of poor prognosis. The large sample size of this series clarifies contradictory findings of many smaller studies. P-cadherin positivity is associated with high-grade tumor subtypes and well-established markers of poor prognosis, and may represent a promising antibody therapeutic target.

A microscopic study of functional disorder-order folding transitions coupled to binding is performed for the p27 protein, which derives a kinetic advantage from the intrinsically disordered unbound form on binding with the phosphorylated cyclin A-cyclin-dependent kinase 2 (Cdk2) complex. Hierarchy of structural loss during p27 coupled unfolding and unbinding is simulated by using high-temperature Monte Carlo simulations initiated from the crystal structure of the tertiary complex. Subsequent determination of the transition-state ensemble and the proposed atomic picture of the folding mechanism coupled to binding provide a microscopic rationale that reconciles the initiation recruitment of p27 at the cyclin A docking site with the kinetic benefit for a disordered alpha-helix in the unbound form of p27. The emerging structural polarization in the ensemble of unfolding/unbinding trajectories and in the computationally determined transition-state ensemble is not determined by the intrinsic folding preferences of p27 but rather is attributed to the topological requirements of the native intermolecular interface to order beta-hairpin and beta-strand of p27 that could be critical for nucleating rapid folding transition coupled to binding. In agreement with the experimental data, the disorder-order folding transition for p27 is largely determined by the functional requirement to form a specific intermolecular interface that ultimately dictates the folding mechanism and overwhelms any local folding preferences for creating a stable alpha-helix in the p27 structure before overcoming the major free energy barrier.

Structure and energetics of the Src Src Homology 2 (SH2) domain binding with the recognition phosphopeptide pYEEI and its mutants are studied by a hierarchical computational approach. The proposed structure prediction strategy includes equilibrium sampling of the peptide conformational space by simulated tempering dynamics with the simplified, knowledge-based energy function, followed by structural clustering of the resulting conformations and binding free energy evaluation of a single representative from each cluster, a cluster center. This protocol is robust in rapid screening of low-energy conformations and recovers the crystal structure of the pYEEI peptide. Thermodynamics of the peptide-SH2 domain binding is analyzed by computing the average energy contributions over conformations from the clusters, structurally similar to the predicted peptide bound structure. Using this approach, the binding thermodynamics for a panel of studied peptides is predicted in a better agreement with the experiment than previously suggested models. However, the overall correlation between computed and experimental binding affinity remains rather modest. The results of this study show that small differences in binding free energies between the Ala and Gly mutants of the pYEEI peptide are considerably more difficult to predict than the structure of the bound peptides, indicating that accurate computational prediction of binding affinities still remains a major methodological and technical challenge.