Tumor Dormancy, Oncogene Addiction, Cellular Senescence, and Self-Renewal Programs.
Tumor Dormancy, Oncogene Addiction, Cellular Senescence, and Self-Renewal Programs.
Filed under: Addiction Rehab
Adv Exp Med Biol. 2013; 734: 91-107
Bellovin DI, Das B, Felsher DW
Cancers are frequently addicted to initiating oncogenes that elicit aberrant cellular proliferation, self-renewal, and apoptosis. Restoration of oncogenes to normal physiologic regulation can elicit dramatic reversal of the neoplastic phenotype, including reduced proliferation and increased apoptosis of tumor cells (Science 297(5578):63-64, 2002). In some cases, oncogene inactivation is associated with compete elimination of a tumor. However, in other cases, oncogene inactivation induces a conversion of tumor cells to a dormant state that is associated with cellular differentiation and/or loss of the ability to self-replicate. Importantly, this dormant state is reversible, with tumor cells regaining the ability to self-renew upon oncogene reactivation. Thus, understanding the mechanism of oncogene inactivation-induced dormancy may be crucial for predicting therapeutic outcome of targeted therapy. One important mechanistic insight into tumor dormancy is that oncogene addiction might involve regulation of a decision between self-renewal and cellular senescence. Recent evidence suggests that this decision is regulated by multiple mechanisms that include tumor cell-intrinsic, cell-autonomous mechanisms and host-dependent, tumor cell-non-autonomous programs (Mol Cell 4(2):199-207, 1999; Science 297(5578):102-104, 2002; Nature 431(7012):1112-1117, 2004; Proc Natl Acad Sci U S A 104(32):13028-13033, 2007). In particular, the tumor microenvironment, which is known to be critical during tumor initiation (Cancer Cell 7(5):411-423, 2005; J Clin Invest 121(6):2436-2446, 2011), prevention (Nature 410(6832):1107-1111, 2001), and progression (Cytokine Growth Factor Rev 21(1):3-10, 2010), also appears to dictate when oncogene inactivation elicits the permanent loss of self-renewal through induction of cellular senescence (Nat Rev Clin Oncol 8(3):151-160, 2011; Science 313(5795):1960-1964, 2006; N Engl J Med 351(21):2159-21569, 2004). Thus, oncogene addiction may be best modeled as a consequence of the interplay amongst cell-autonomous and host-dependent programs that define when a therapy will result in tumor dormancy.
HubMed – addiction
Molecular Mechanisms Underlying Behaviors Related to Nicotine Addiction.
Filed under: Addiction Rehab
Cold Spring Harb Perspect Med. 2012 Nov 9;
Picciotto MR, Kenny PJ
Tobacco smoking results in more than 5 million deaths each year and accounts for almost 90% of all deaths from lung cancer. Nicotine, the major reinforcing component of tobacco smoke, acts in the brain through the neuronal nicotinic acetylcholine receptors (nAChRs). The nAChRs are allosterically regulated, ligand-gated ion channels consisting of five membrane-spanning subunits. Twelve mammalian ? subunits (?2-?10) and ? subunits (?2-?4) have been cloned. The predominant nAChR subtypes in mammalian brain are those containing ?4 and ?2 subunits (denoted as ?4?2* nAChRs). The ?4?2* nAChRs mediate many behaviors related to nicotine addiction and are the primary targets for currently approved smoking cessation agents. Considering the large number of nAChR subunits in the brain, it is likely that nAChRs containing subunits in addition to ?4 and ?2 also play a role in tobacco smoking. Indeed, genetic variation in the CHRNA5-CHRNA3-CHRNB4 gene cluster, encoding the ?5, ?3, and ?4 nAChR subunits, respectively, has been shown to increase vulnerability to tobacco dependence and smoking-associated diseases including lung cancer. Moreover, mice in which expression of ?5 or ?4 subunits has been genetically modified have profoundly altered patterns of nicotine consumption. In addition to the reinforcing properties of nicotine, the effects of nicotine on appetite, attention, and mood are also thought to contribute to establishment and maintenance of the tobacco smoking habit. Here we review recent insights into the behavioral actions of nicotine and the nAChRs subtypes involved, which likely contribute to the development of tobacco dependence in smokers.
HubMed – addiction
Understanding resistance to targeted cancer drugs through loss of function genetic screens.
Filed under: Addiction Rehab
Drug Resist Updat. 2012 Nov 8;
Berns K, Bernards R
Comprehensive analysis of cancer genomes has provided important insights in the critical alterations that confer proliferation and survival advantage to the tumor, so-called driver mutations. Tumors harboring these genetic changes frequently exhibit striking sensitivities to inhibition of these oncogenic driver pathways, a principle referred to as oncogene addiction. Substantial progress has been made in the development of drugs that specifically target components of the pathways that are associated with these driver mutations. This has enabled the first steps in a shift from the use of cytotoxic drugs to highly selective targeted therapeutic agents for the treatment of cancer. Unfortunately, despite the expanding development of targeted anti-cancer strategies, treatment failure due to primary or acquired resistance is still an almost inevitable outcome in most advanced human cancers. Understanding drug resistance mechanisms will help design more efficient combination treatment strategies that help block resistance mechanisms before they become clinically manifest. In this review, we discuss how RNA interference functional genetic screens can be used to identify clinically relevant mechanisms of drug resistance and how this technology can be used to develop effective combination therapies.
HubMed – addiction
Fine-grain analysis of the treatment effect of topiramate on methamphetamine addiction with latent variable analysis.
Filed under: Addiction Rehab
Drug Alcohol Depend. 2012 Nov 8;
Ma JZ, Johnson BA, Yu E, Weiss D, McSherry F, Saadvandi J, Iturriaga E, Ait-Daoud N, Rawson RA, Hrymoc M, Campbell J, Gorodetzky C, Haning W, Carlton B, Mawhinney J, Weis D, McCann M, Pham T, Stock C, Dickinson R, Elkashef A, Li MD
BACKGROUND: As reported previously, 140 methamphetamine-dependent participants at eight medical centers in the U.S. were assigned randomly to receive topiramate (N=69) or placebo (N=71) in a 13-week clinical trial. The study found that topiramate did not appear to reduce methamphetamine use significantly for the primary outcome (i.e., weekly abstinence from methamphetamine in weeks 6-12). Given that the treatment responses varied considerably among subjects, the objective of this study was to identify the heterogeneous treatment effect of topiramate and determine whether topiramate could reduce methamphetamine use effectively in a subgroup of subjects. METHODS: Latent variable analysis was used for the primary and secondary outcomes during weeks 6-12 and 1-12, adjusting for age, sex, and ethnicity. RESULTS: Our analysis of the primary outcome identified 30 subjects as responders, who either reduced methamphetamine use consistently over time or achieved abstinence. Moreover, topiramate recipients had a significantly steeper slope in methamphetamine reduction and accelerated to abstinence faster than placebo recipients. For the secondary outcomes in weeks 6-12, we identified 40 subjects as responders (who had significant reductions in methamphetamine use) and 65 as non-responders; topiramate recipients were more than twice as likely as placebo recipients to be responders (odds ratio=2.67; p=0.019). Separate analyses of the outcomes during weeks 1-12 yielded similar results. CONCLUSIONS: Methamphetamine users appear to respond to topiramate treatment differentially. Our findings show an effect of topiramate on the increasing trend of abstinence from methamphetamine, suggesting that a tailored intervention strategy is needed for treating methamphetamine addiction.
HubMed – addiction
High and low sensation seeking adolescents show distinct patterns of brain activity during reward processing.
Filed under: Addiction Rehab
Neuroimage. 2012 Nov 8;
Cservenka A, Herting MM, Seghete KL, Hudson KA, Nagel BJ
Previous research has shown that personality characteristics, such as sensation seeking (SS), are strong predictors of risk-taking behavior during adolescence. However, the relationship between levels of SS and brain response has not been studied during this time period. Given the prevalence of risky behavior during adolescence, it is important to understand neurobiological differences in reward sensitivity between youth with high and low SS personalities. To this end, we used functional magnetic resonance imaging (fMRI) to examine differences in brain activity in an adolescent sample that included 27 high (HSS) and 27 low sensation seekers (LSS), defined by the Impulsive Sensation Seeking scale of the Zuckerman-Kuhlman Personality Questionnaire (Zuckerman et al., 1993). In the scanner, participants played a modified Wheel of Fortune decision-making task (Cservenka and Nagel, 2012) that resulted in trials with monetary Wins or No Wins. We compared age- and sex-matched adolescent HSS and LSS (mean age = 13.94 ± 1.05) on brain activity by contrasting Win versus No Win trials. Our findings indicate that HSS show greater bilateral insular and prefrontal cortex (PFC) brain response on Win vs. No Win compared to LSS. Analysis of simple effects showed that while LSS showed comparable brain activity in these areas during Wins and No Wins, HSS showed significant differences in brain response to winning (activation) versus not winning (deactivation), with between-group comparison suggesting significant differences in brain response, largely to reward absence. Group differences in insular activation between reward receipt and absence may suggest weak autonomic arousal to negative outcomes in HSS compared with LSS. Additionally, since the PFC is important for goal-directed behavior and attention, the current results may reflect that HSS allocate fewer attentional resources to negative outcomes than LSS. This insensitivity to reward absence in HSS may lead to a greater likelihood of maladaptive choices when negative consequences are not considered, and may be an early neural marker of decreased loss sensitivity that has been seen in addiction. This neurobiological information may ultimately be helpful in establishing prevention strategies aimed at reducing youth risk-taking and suggests value in further examination of neural associations with personality characteristics during adolescence.
HubMed – addiction
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