Pharmacology - Cancer - Detailed

Expression profiling and individualisation of treatment for ovarian cancer.

Agarwal R & Kaye SB, 2006. Curr Opin Pharmacol. 6(4):345-9.

Section of Medicine, Institute for Cancer Research, Royal Marsden Hospital, Sycamore House, Downs Road, Sutton, Surrey, SM2 5PT, UK.

Ovarian cancer is the commonest cause of gynaecological cancer-related mortality. Patients with this disease generally undergo surgery followed by platinum-taxane chemotherapy, with additional chemotherapy at relapse. Although the prognosis for patients with advanced cancer is poor--a five-year survival of only 30-40%--there is a wide range of outcomes for individual patients. To date, clinico-pathological variables such as age, stage, grade, histology, debulking status and response to chemotherapy continue to provide the basis on which treatment decisions are made for individual patients. Immunohistochemical markers and information on p53 mutation status have been extensively evaluated in ovarian cancer, but have not yet been shown to be sufficiently informative to influence clinical decisions on a routine basis. The recent advent of expression profiling has provided a new impetus to identifying clinically useful prognostic markers. The ambition of personalised medicine through microarray-based profiling appears to be realistic, but further studies on large uniform cohorts are needed before this potential is fully realised.

Journal link:  Available through Science Direct | PMID

Neonatal phenobarbital imprints overexpression of cytochromes P450 with associated increase in tumorigenesis and reduced life span.

Agrawal AK, Shapiro BH, 2005. FASEB J. 19(3):470-2.

Perinatal exposure to phenobarbital produces a range of permanent reproductive, growth, locomoter, and learning dysfunctions in animals as well as humans. In addition, the affected individuals exhibit latently expressed (i.e., postpubertal) above normal activity levels of hepatic multicytochrome P450-dependent drug metabolizing enzymes. We report that in spite of apparent normal health for the better part of their lives, daily administration of therapeutic-like doses of phenobarbital to male and female rat pups during the first postpartum week reduced life expectancy by approximately 20%. Necropsy at the time of natural death revealed an associated two- to threefold increase in the incidence of tumors in barbiturate-exposed rats of both sexes and a three- to fourfold increase in urinary tract pathologies in male rats. At 2 yr of age, in agreement with an overexpression of hepatic CYP2C6 and CYP2C7, both in vitro and in vivo drug metabolism was more rapid in the phenobarbital-imprinted male and female animals. Moreover, when the senescent rats were rechallenged with a nominal dose of the barbiturate, males and females neonatally exposed to phenobarbital exhibited a dramatic overinduction of multicytochrome P450-dependent drug metabolizing enzymes as well as an overexpression of individual isoforms of cytochrome P450 implicated in enhanced susceptibility to tumorigenesis. Our findings support the growing realization that many adult diseases have their origins in early life by emphasizing that unlike adults, the new born is "plastic," and even therapeutic drugs may produce "silent" programming defects that subtly, but irrevocably, jeopardize life-long well-being.

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Predicting the outcome of chemotherapy for colorectal cancer.

Allen WL et al., 2006. Curr Opin Pharmacol. 6(4):332-6.

Colorectal cancer is the second leading cause of cancer-related deaths in the Western world. Recently, improvements have been made in treating patients with advanced colorectal cancer; however, response rates still remain low at only 40-50% following combination therapy. The major limitation in treating these patients is the development of drug resistance. Therefore, there is a need to identify which patients will respond to a given chemotherapy regime so that they will be spared the unnecessary time and toxicity of being placed on a regime from which they will derive no benefit. It is also widely accepted that exposure to these chemotherapies themselves can induced acute resistance. Recent developments have been made in predicting response to chemotherapy using global approaches, with the ultimate aim of individualising patient treatment and improving overall survival rates.

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Proteomics in clinical trials and practice: present uses and future promise.

Azad NS et al., 2006. Mol Cell Proteomics 5(10):1819-29.

The study of clinical proteomics is a promising new field that has the potential to have many applications, including the identification of biomarkers and monitoring of disease, especially in the field of oncology. Expression proteomics evaluates the cellular production of proteins encoded by a particular gene and exploits the differential expression and post-translational modifications of proteins between healthy and diseased states. These biomarkers may be applied towards early diagnosis, prognosis, and prediction of response to therapy. Functional proteomics seeks to decipher protein-protein interactions and biochemical pathways involved in disease biology and targeted by newer molecular therapeutics. Advanced spectrometry technologies and new protein array formats have improved these analyses and are now being applied prospectively in clinical trials. Further advancement of proteomics technology could usher in an era of personalized molecular medicine, where diseases are diagnosed at earlier stages and where therapies are more effective because they are tailored to the protein expression of a patient's malignancy.

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Gene expression signature-based chemical genomic prediction identifies a novel class of HSP90 pathway modulators.

Hieronymus H et al., 2006. Cancer Cell 10(4):321-30.

Although androgen receptor (AR)-mediated signaling is central to prostate cancer, the ability to modulate AR signaling states is limited. Here we establish a chemical genomic approach for discovery and target prediction of modulators of cancer phenotypes, as exemplified by AR signaling. We first identify AR activation inhibitors, including a group of structurally related compounds comprising celastrol, gedunin, and derivatives. To develop an in silico approach for target pathway identification, we apply a gene expression-based analysis that classifies HSP90 inhibitors as having similar activity to celastrol and gedunin. Validating this prediction, we demonstrate that celastrol and gedunin inhibit HSP90 activity and HSP90 clients, including AR. Broadly, this work identifies new modes of HSP90 modulation through a gene expression-based strategy.

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CYP2D6 genotype, antidepressant use, and tamoxifen metabolism during adjuvant breast cancer treatment.

Jin et al., 2005. J. Natl. Cancer Inst. 97(1):30-39.

Background: The efficacy of tamoxifen therapy for the treatment of breast cancer varies widely among individuals. Plasma concentrations of the active tamoxifen metabolite endoxifen are associated with the cytochrome P450 (CYP) 2D6 genotype. We examined the effects of concomitant use of selective serotonin reuptake inhibitor antidepressants, which are CYP2D6 enzyme inhibitors commonly prescribed to treat hot flashes in women who take tamoxifen, and genotypes for genes that encode tamoxifen-metabolizing enzymes on plasma concentrations of tamoxifen and its metabolites. Methods: Eighty patients with newly diagnosed with breast cancer who were beginning tamoxifen therapy (20 mg/day orally), 24 of whom were taking CYP2D6 inhibitors, were genotyped for common alleles of the CYP2D6, CYP2C9, CYP3A5, and sulfotransferase (SULT) 1A1 genes. Plasma concentrations of tamoxifen and its metabolites were measured after 1 and 4 months of tamoxifen therapy. Differences in plasma concentrations of tamoxifen and its metabolites between genotype groups were analyzed by the Wilcoxon rank sum test. All statistical tests were two-sided. Results: Among all women, plasma endoxifen concentrations after 4 months of tamoxifen therapy were statistically significantly lower in subjects with a CYP2D6 homozygous variant genotype (20.0 nM, 95% confidence interval [CI] = 11.1 to 28.9 nM) or a heterozygous genotype (43.1 nM, 95% CI = 33.3 to 52.9 nM) than in those with a homozygous wild-type genotype (78.0 nM, 95%CI = 65.9 to 90.1 nM) (both P = .003). Among subjects who carried a homozygous wild-type genotype, the mean plasma endoxifen concentration for those who were using CYP2D6 inhibitors was 58% lower than that for those who were not (38.6 nM versus 91.4 nM, difference = -52.8 nM, 95% CI = -86.1 to -19.5 nM, P = .0025). The plasma endoxifen concentration was slightly reduced in women taking venlafaxine, a weak inhibitor of CYP2D6, whereas the plasma endoxifen concentration was reduced substantially in subjects who took paroxetine (a potent inhibitor of CYP2D6). Genetic variations of CYP2C9, CYP3A5, or SULT1A1 had no statistically significant associations with plasma concentrations of tamoxifen or its metabolites. Conclusion: Interactions between CYP2D6 polymorphisms and coadministered antidepressants and other drugs that are CYP2D6 inhibitors may be associated with altered tamoxifen activity.

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Comment

This study highlights the significant relationship between a patient's genome, her chemotherapy for breast cancer and associated psychotherapies for the depression that may accompany breast cancer and its treatment.  The focus is on cytochrome P450 enzymes that metabolize tamoxifen and SSRI antidepressants that also inhibitor them.

Utah's Family High Risk Program: bridging the gap between genomics and public health.

Johnson J et al., 2005. Prev Chronic Dis. 2(2):A24.

Family history is a simple yet powerful genomic tool that can identify individuals and entire populations at risk for diseases such as heart disease, cancer, and diabetes. Despite its use for predicting disease, family history has traditionally been underused in the public health setting. CONTEXT: A program for identifying families at risk for a variety of chronic diseases was implemented in Utah. Utah has population characteristics that are unique among the United States. Although the land area is large, most residents live within a relatively small geographic area. The religion of 70% of the residents encourages the recording of detailed family histories, and many families have access to records dating back to the 1800s. METHODS: From 1983 through 1999, the Utah Department of Health, local health departments, school districts, the University of Utah, and the Baylor College of Medicine implemented and conducted the Family High Risk Program, which identified families at risk for chronic diseases using the Health Family Tree Questionnaire in Utah high schools. CONSEQUENCES: The collection of family history is a cost-effective method for identifying and intervening with high-risk populations. More than 80% of eligible families consented to fully participate in the program. A total of 80,611 usable trees were collected. Of the 151,188 Utah families who participated, 8546 families identified as high-risk for disease(s) were offered follow-up interventions. INTERPRETATION: The program was revolutionary in design and demonstrated that family history can bridge the gap between genetic advances and public health practice.

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Do we need genomic research for the prevention of common diseases with environmental causes?

Khoury MJ et al., 2005. Am J Epidemiol. 161(9):799-805.

Office of Genomics and Disease Prevention, Coordinating Center on Health Promotion, Centers for Disease Control and Prevention, Atlanta, GA 30341, USA. muk1@cdc.gov

Concerns have been raised about the value of genomic research for prevention and public health, especially for complex diseases with risk factors that are amenable to environmental modification. Given that gene-environment interactions underlie almost all human diseases, the public health significance of genomic research on common diseases with modifiable environmental risks is based not necessarily on finding new genetic "causes" but on improving existing approaches to identifying and modifying environmental risk factors to better prevent and treat disease. Such applied genomic research for environmentally caused diseases is important, because 1) it could help stratify disease risks and differentiate interventions for achieving population health benefits; 2) it could help identify new environmental risk factors for disease or help confirm suspected environmental risk factors; and 3) it could aid our understanding of disease occurrence in terms of transmission, natural history, severity, etiologic heterogeneity, and targets for intervention at the population level. While genomics is still in its infancy, opportunities exist for developing, testing, and applying the tools of genomics to clinical and public health research, especially for conditions with known or suspected environmental causes. This research is likely to lead to population-wide health promotion and disease prevention efforts, not only to interventions targeted according to genetic susceptibility.

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Estrogen-metabolizing gene polymorphisms in the assessment of female hormone-dependent cancer risk.

Mikhailova ON et al., 2006. Pharmacogenomics J. 6(3):189-93

Allelic variants of cytochrome P450: CYP1A1, CYP1A2, CYP19 (Aromatase) and II-phase enzyme Sulfotransferase (SULT1A1) genes are associated with a high risk of hormone-dependent cancers. We estimated a frequency of these allelic variants in the female Caucasian population of the Novosibirsk region of Russia and their association with the elevated risk of ovarian and endometrial cancer. A DNA bank of gynecologic oncology patients, patients with benign gynecologic diseases and healthy women was created, and the following single nucleotide polymorphisms (SNPs) were examined: CYP1A1 M1 polymorphism, that is, T264 --> C transition in the 3'-noncoding region; CYP1A2*1F polymorphism, that is, C734 --> A transversion in CYP1A2 gene; C --> T transition (Arg264Cys) in exon 7 of CYP19; SULT1A1*2 polymorphism, that is, G638 --> A transition (Arg213His) in SULT1A1 gene. A positive correlation of C allele of CYP1A2*1F and G allele of SULT1A1*2 with hormone-dependent cancers in women was found. Thus, these genes are appropriate candidates for studying the contribution of genetic factors to endocrine disorder and environmentally determined diseases susceptibility. In contrast, no association of CYP19 and CYP1A1 polymorphisms with increased cancer risk was revealed.

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Modulation of multidrug resistance efflux pump activity to overcome chemoresistance in cancer.

Modok S et al., 2006. Curr Opin Pharmacol. 6(4):350-4.

Early publications using cultured cancer cells immediately recognized the phenomenon of resistance to anticancer agents. However, it was not until 1973 that it was first demonstrated that a major factor in the resistance of cancer cells was that of reduced drug accumulation. This year marks the 30th anniversary of the discovery by Juliano and Ling that P-glycoprotein mediates this active efflux of chemotherapeutic drugs from cancer cells. Since this seminal finding, the investigation of P-glycoprotein (MDR1, ATP binding cassette [ABC]B1) has proceeded with great vigour. However, it soon became apparent that P-glycoprotein was not expressed in all drug-resistant cells that displayed an accumulation deficiency, which led to the discovery of other ABC transporters involved in drug efflux. In 1992, the multidrug resistance-associated protein (MRP1, ABCC1) was identified in small cell lung cancer followed by breast cancer resistance protein (mitoxantrone resistance protein, ABCG2) in 1999. After three decades of research, can we confidently define the contribution of multidrug resistance transporters to chemoresistance and do we have clinically useful drugs to sensitize cancers?

Journal link:  Available through Science Direct | PMID

Can personalized drug therapy be achieved? A closer look at pharmaco-metabonomics.

Nebert DW, Vesell ES, 2006. Trends Pharmacol Sci. 27(11):580-6. Erratum in: Trends Pharmacol Sci. 2007, 28(2):50.

Between 1930 and 1990, several dozen high-penetrance, predominantly monogenic disorders were identified and characterized, which led some investigators to speculate that individualized drug treatment was just around the corner. Informative DNA tests were sought to determine genetic predisposition to toxicity and cancer, thereby identifying individuals in which a drug was likely to be effective and those at increased risk of drug toxicity. These assays represent the leading edge of phenotype-genotype association studies, which are a major goal of clinical pharmacology and pharmacogenomics. Because of the complexity of the genome, however, the task is more challenging than anticipated originally. In the past decade we have come to appreciate how difficult it is to determine unequivocally either an exact phenotype or genotype. In the near future it seems unlikely that, by themselves, either transcriptomics or proteomics will be particularly helpful in achieving individualized drug therapy. However, recent advances in metabonomics are exciting and show promise. In the future, and perhaps in combination with proteomics, metabonomics might complement genomics in achieving personalized drug therapy.

Journal link:  Available through Science Direct | PMID

Population proteomics: the concept, attributes, and potential for cancer biomarker research.

Nedelkov D et al., 2006. Mol Cell Proteomics.5(10):1811-8.

This review outlines the concept of population proteomics and its implication in the discovery and validation of cancer-specific protein modulations. Population proteomics is an applied subdiscipline of proteomics engaging in the investigation of human proteins across and within populations to define and better understand protein diversity. Population proteomics focuses on interrogation of specific proteins from large number of individuals, utilizing top-down, targeted affinity mass spectrometry approaches to probe protein modifications. Deglycosylation, sequence truncations, side-chain residue modifications, and other modifications have been reported for myriad of proteins, yet little is know about their incidence rate in the general population. Such information can be gathered via population proteomics and would greatly aid the biomarker discovery efforts. Discovery of novel protein modifications is also expected from such large scale population proteomics, expanding the protein knowledge database. In regard to cancer protein biomarkers, their validation via population proteomics-based approaches is advantageous as mass spectrometry detection is used both in the discovery and validation process, which is essential for the detection of those structurally modified protein biomarkers.

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A genomic strategy to refine prognosis in early-stage non-small-cell lung cancer.

Potti Aet al., 2006. N Engl J Med. 355(6):570-80.  Erratum in: N Engl J Med. 2007, 356(2):201-2.

Clinical trials have indicated a benefit of adjuvant chemotherapy for patients with stage IB, II, or IIIA--but not stage IA--non-small-cell lung cancer (NSCLC). This classification scheme is probably an imprecise predictor of the prognosis of an individual patient. Indeed, approximately 25 percent of patients with stage IA disease have a recurrence after surgery, suggesting the need to identify patients in this subgroup for more effective therapy. We identified gene-expression profiles that predicted the risk of recurrence in a cohort of 89 patients with early-stage NSCLC (the lung metagene model). We evaluated the predictor in two independent groups of 25 patients from the American College of Surgeons Oncology Group (ACOSOG) Z0030 study and 84 patients from the Cancer and Leukemia Group B (CALGB) 9761 study. The lung metagene model predicted recurrence for individual patients significantly better than did clinical prognostic factors and was consistent across all early stages of NSCLC. Applied to the cohorts from the ACOSOG Z0030 trial and the CALGB 9761 trial, the lung metagene model had an overall predictive accuracy of 72 percent and 79 percent, respectively. The predictor also identified a subgroup of patients with stage IA disease who were at high risk for recurrence and who might be best treated by adjuvant chemotherapy. The lung metagene model provides a potential mechanism to refine the estimation of a patient's risk of disease recurrence and, in principle, to alter decisions regarding the use of adjuvant chemotherapy in early-stage NSCLC.

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Predicting the outcome of chemotherapy for lung cancer.

Rosell R et al., 2006. Curr Opin Pharmacol. 323-31. Erratum in: Curr Opin Pharmacol. 2007 Feb;7(1):119.

Lung cancer is a worldwide problem. At the time of diagnosis, 50% of patients have advanced incurable disease. Different chemotherapy combinations--with or without targeted therapies--yield similar results despite the continuous efforts of clinicians. However, molecular biological studies have already shed a great deal of light on the existence of multiple genetic aberrations that can be useful for customizing treatment. mRNA transcripts involved in DNA repair pathways, such as ERCC1 and BRCA1, confer selective resistance to cisplatin or taxanes, whereas thioredoxin confers a broad spectrum of chemoresistance. Polymorphisms in DNA repair genes and methylation of checkpoint genes in circulating serum DNA could become important predictive markers of survival in certain cisplatin-based regimens. Epidermal growth factor receptor tyrosine kinase mutations are the crux of targeted therapies, whereas epithelial-mesenchymal transitions and HER3 mRNA levels are promising ancillary markers for treatment with epidermal growth factor receptor tyrosine kinase inhibitors.

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Exploiting the role of O6-methylguanine-DNA-methyltransferase (MGMT) in cancer therapy.

Sabharwal A, Middleton MR, 2006. Curr Opin Pharmacol. 6(4):355-63.

Improving the efficacy of standard chemotherapy by targeting DNA repair mechanisms remains an important area of research. O6-methylguanine-DNA-methyltransferase (MGMT), which repairs alkylating agent damage, is one such target. Downregulation of the gene through epigenetic silencing has been shown to predict response to alkylating agent therapy in selected malignancies. Platinums have also been found to downregulate MGMT expression and this approach is currently under exploration. Another way to deplete O6-alkylguanine DNA alkyltransferase (AGT) levels is to modify methylating agent scheduling. Extended dosing has met with early favourable results. However, pseudosubstrates used to inhibit AGT activity have had limited success because of dose-limiting myelotoxicity. Topoisomerase I is 'trapped' on DNA by alteration of ligation kinetics following alkylating agent damage, leading to interest in combining AGT inhibitors or O6-alkylating agents with topoisomerase I inhibitors. DNA repair by AGT is an interesting target for cancer therapy that remains to be fully evaluated. The best results are likely to be achieved where its inhibition is part of treatment targeting multiple DNA damage processing pathways.

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