Integrative epidemiology: from risk assessment to outcome prediction

Roadmap for translating results from the micronucleus assay into clinical practice: From observational studies to randomized controlled trials

According to the definition delivred by the WHO, a biomarker, independently from its role that may be indicative of exposure, response or effect, is inevitably linked to a clinical outcome or to a disease. The presence of a continuum from early biological events to therapy, and prognosis is the unifying mechanism that justifies this conclusion. Traditionally, the technical and inter-individual variability of the assays, together with the long duration between early pathogenetic events and the disease, prevented clinical applications to these biomarkers. These limitations became less important with the emerging of personalized preventive medicine because of the focus on disease prediction and prevention, and the recommended use of all data concerning measurable patient's features. Several papers have been published on the best validation procedures for translating biomarkers to real life. The history of cholesterol concentration is extensively discussed as a reliable example of a biomarker that - after a long and controversial validation process - is currently used in clinical practice. The frequency of micronucleated cells is a reliable biomarker for the pathogenesis of cancer and other non-communicable diseases, and the link with clinical outcomes is substantiated by epidemiological evidence and strong mechanistic basis. Available literature concerning the use of the micronucleus assay in clinical studies is discussed, and a suitable three-levels road-map driving this biomarker towards clinical practice is presented. Under the perspective of personalized medicine, the use of the micronucleus assays can play a decisive role in addressing preventive and therapeutic strategies of chronic diseases. In many cases the MN assay is either currently used in clinical practice or classified as adequate to consider translation into practice. The roadmap to clinical validation of the micronucleus assay finds inspiration from the history of biomarkers such as cholesterol, which clearly showed that the evidence from prospective studies or RCTs is critical to achieve the required level of trust from the healthcare profession. (307 words).

E-Cadherin and Metalloproteinase-1 and -7 Polymorphisms in Colorectal Cancer

Purpose

E-cadherin (CDH1) and metalloproteinase (MMP) polymorphisms could play a crucial role in cancer invasion. Our aim was to investigate the influence of the -160C/A CDH1, -1607ins/delG MMP-1 and -181A/G MMP-7 polymorphisms on the frequency and progression of colorectal cancer (CRC).

Experimental design

A total of 130 patients with CRC and 130 noncancer controls were studied. The -160C/A CDH1, -1607ins/delG MMP-1 and -181A/G MMP-7 genotypes were analyzed by polymerase chain reaction-restriction fragment length polymorphism.

Results

Patients with the 1G allele and a family history of CRC showed a six times higher risk of developing CRC (OR: 6.45, 95%CI: 2.02–20.6, p=0.001). The A/A CDH1 genotype was associated with a higher risk of metastatic disease (OR: 3.43, 95%CI: 1.27–9.27, p=0.023). A higher marginal risk of metastatic disease was observed for MMP-1 genotypes 1G/1G and 1G/2G (OR: 2.97, 95%CI: 0.93–9.47, p=0.098).

Conclusions

The -160C/A CDH1, -1607ins/delG MMP-1 and -181A/G MMP-7 single nucleotide polymorphisms did not modify the risk of CRC development. Patients with the 1G/1G or 1G/2G genotype and a family history of CRC presented a higher risk of CRC. The AA CDH1 and 1G/1G and 1G/2G MMP-1 genotypes might be associated with advanced metastatic disease, but are not markers of lymphatic metastasis.

A genetic sequence variant (GSV) at susceptibility loci of 5p15.33 (TERT-CLPTM1L) is associated with survival outcome in locally advanced and metastatic non-small-cell lung cancer (NSCLC)

INTRODUCTION

Lung cancer is a leading cause of cancer-related mortality in North America. In addition to tobacco smoking, inherited genetic factors can also influence the development of lung cancer. These genetic factors may lead to biologically distinct subsets of cancers that have different outcomes. We evaluated whether genetic sequence variants (GSVs) associated with lung cancer risk are associated with overall survival (OS) and progression-free survival (PFS) in stage-III-IV non-small-cell lung cancer (NSCLC) patients.

METHODS

A total of 20 candidate GSVs in 12 genes previously reported to be associated with lung cancer risk were genotyped in 564 patients with stage-III or IV NSCLC. Multivariate Cox proportional hazard models adjusted for potential clinical prognostic factors were generated for OS and PFS.

RESULTS

After taking into account multiple comparisons, one GSV remained significant: rs4975616 on chromosome 5p15.33, located near the TERT-CLPTM1L gene. The adjusted hazard ratio (aHR) for OS was 0.75 (0.69-0.91), p = 0.002; for PFS aHR was 0.74 (0.62-0.89), p < 0.001 for each protective variant allele. Results were similar in both Stage III (OS: aHR = 0.70; PFS: aHR = 0.71) and Stage IV patients (OS: aHR = 0.81; PFS: aHR = 0.77).

CONCLUSION

A GSV on 5p15.33 is not only a risk factor for lung cancer but may also be associated with survival in patients with late stage NSCLC. If validated, GSVs may define subsets of patients with different risk and prognosis of NSCLC.

Prognostic relevance of urinary bladder cancer susceptibility loci

In the last few years, susceptibility loci have been identified for urinary bladder cancer (UBC) through candidate-gene and genome-wide association studies. Prognostic relevance of most of these loci is yet unknown. In this study, we used data of the Nijmegen Bladder Cancer Study (NBCS) to perform a comprehensive evaluation of the prognostic relevance of all confirmed UBC susceptibility loci. Detailed clinical data concerning diagnosis, stage, treatment, and disease course of a population-based series of 1,602 UBC patients were collected retrospectively based on a medical file survey. Kaplan-Meier survival analyses and Cox proportional hazard regression were performed, and log-rank tests calculated, to evaluate the association between 12 confirmed UBC susceptibility variants and recurrence and progression in non-muscle invasive bladder cancer (NMIBC) patients. Among muscle-invasive or metastatic bladder cancer (MIBC) patients, association of these variants with overall survival was tested. Subgroup analyses by tumor aggressiveness and smoking status were performed in NMIBC patients. In the overall NMIBC group (n = 1,269), a statistically significant association between rs9642880 at 8q24 and risk of progression was observed (GT vs. TT: HR = 1.08 (95% CI: 0.76-1.54), GG vs. TT: HR = 1.81 (95% CI: 1.23-2.66), P for trend = 2.6 × 10(-3)). In subgroup analyses, several other variants showed suggestive, though non-significant, prognostic relevance for recurrence and progression in NMIBC and survival in MIBC. This study provides suggestive evidence that genetic loci involved in UBC etiology may influence disease prognosis. Elucidation of the causal variant(s) could further our understanding of the mechanism of disease, could point to new therapeutic targets, and might aid in improvement of prognostic tools.

Epidemiological study of prostate cancer (EPICAP): a population-based case-control study in France

BACKGROUND

Prostate cancer is the most common cancer in male in most Western countries, including France. Despite a significant morbidity and mortality to a lesser extent, the etiology of prostate cancer remains largely unknown. Indeed, the only well-established risk factors to date are age, ethnicity and a family history of prostate cancer. We present, here, the rationale and design of the EPIdemiological study of Prostate CAncer (EPICAP), a population-based case-control study specifically designed to investigate the role of environmental and genetic factors in prostate cancer. The EPICAP study will particularly focused on the role of circadian disruption, chronic inflammation, hormonal and metabolic factors in the occurrence of prostate cancer.

METHODS/DESIGN

EPICAP is a population-based case-control study conducted in the département of Hérault in France. Eligible cases are all cases of prostate cancers newly diagnosed in 2012-2013 in men less than 75 years old and residing in the département of Hérault at the time of diagnosis. Controls are men of the same age as the cases and living in the département of Hérault, recruited in the general population.The sample will include a total of 1000 incident cases of prostate cancer and 1000 population-based controls over a 3-year period (2012-2014).The cases and controls are face-to-face interviewed using a standardized computed assisted questionnaire. The questions focus primarily on usual socio-demographic characteristics, personal and family medical history, lifestyle, leisure activities, residential and occupational history. Anthropometric measures and biological samples are also collected for cases and controls.

DISCUSSION

The EPICAP study aims to answer key questions in prostate cancer etiology: (1) role of circadian disruption through the study of working hours, chronotype and duration/quality of sleep, (2) role of chronic inflammation and anti-inflammatory drugs, (3) role of hormonal and metabolic factors through a detailed questionnaire, (4) role of individual genetic susceptibility of genes involved in biological pathways of interest. The EPICAP study will also allow us to study prognostic factors and tumor aggressiveness.Taken together, the EPICAP study will provide a comprehensive framework to go further in the understanding of prostate cancer occurrence and its prognosis.

Integrating cell-based and clinical genome-wide studies to identify genetic variants contributing to treatment failure in neuroblastoma patients

High-risk neuroblastoma is an aggressive malignancy with high rates of treatment failure. We evaluated genetic variants associated with in vitro sensitivity to two derivatives of cyclophosphamide for association with clinical response in a separate replication cohort of neuroblastoma patients (n=2,709). Lymphoblastoid cell lines (LCLs) were exposed to increasing concentrations of 4-hydroperoxycyclophosphamide [4HC n=422] and phosphoramide mustard [PM n=428] to determine sensitivity. Genome-wide association studies (GWAS) were performed to identify single nucleotide polymorphisms (SNPs) associated with 4HC and PM sensitivity. SNPs consistently associated with LCL sensitivity were analyzed for associations with event-free survival in patients. Two linked SNPs, rs9908694 and rs1453560, were found to be associated with PM sensitivity in LCLs across populations and were associated with event-free survival in all patients (P=0.01) and within the high-risk subset (P=0.05). Our study highlights the value of cell-based models to identify candidate variants that may predict response to treatment in patients with cancer.

Omics in population studies: a molecular epidemiology perspective

The convergence of striking developments in (bio)-technology, increasing availability of biobanked samples, and advances in biostatistics and bio-informatics allow an optimistic outlook for epidemiological research. In this special issue on Omics in Population Studies: A Molecular Epidemiology Perspective we explore and reflect on the potential of these new developments in both exposure science and clinical research since they provide the essential link between exposure and disease and may enable scientists to improve their understanding of disease origin and progression. As noted in this special issue, this is an exciting time for epidemiology. While cancer and other noncommunicable diseases rise in number worldwide, various new tools can be applied effectively to increase understanding of the underlying causes and potential for progression to improve their prevention and treatment.

Polymorphism and overexpression of HER2/neu among ovarian carcinoma women from Tiruchirapalli, Tamil Nadu, India

PURPOSE

Alteration and overexpression of HER2 proto-oncogene have been implicated in the carcinogenesis and prognosis of ovarian cancer. We evaluated this hypothesis among women with ovarian carcinoma patients from Tiruchirapalli, Tamil Nadu, India.

METHODS

Genomic DNA was extracted from 72 case patients and 288 control subjects and was examined for I655V polymorphism by PCR-RFLP based assay. Immunohistochemistry analysis was carried out in order to study the overexpression of HER2 protein. The observed number of each genotype was compared with that expected for a population in the Hardy-Weinberg equilibrium. In analysing the relation between genotype and overexpression of HER2 protein, Cochran-Mantel-Haenszel statistics was used.

RESULTS

We found that 20.8% of the case patients and 16.3% of the control subjects were heterozygous for the Val allele and 10 case patients (13.8%) and 3 control subjects (1.1%) were homozygous for this allele (P < 0.001). Compared with women with Ile/Ile genotype, women with Val/Val genotype had an elevated risk of ovarian cancer. The genotype distributions were consistent with the Hardy-Weinberg equilibrium. The risk increased with the number of Val allele and women homozygous for the Val allele had 15-fold (OR = 15.3; 95%CI = 4.09-57.31) increased risk of cancer. The patients homozygous for the Valine allele showed strong HER2 protein expression.

CONCLUSION

The results showed that the valine allele may be an indicator of genetic susceptibility to ovarian carcinoma in the study population.

Integrative cancer epidemiology--the next generation

We outline an integrative approach to extend the boundaries of molecular cancer epidemiology by integrating modern and rapidly evolving "omics" technologies into state-of-the-art molecular epidemiology. In this way, one can comprehensively explore the mechanistic underpinnings of epidemiologic observations in cancer risk and outcome. We highlight the exciting opportunities to collaborate across large observational studies and to forge new interdisciplinary collaborative ventures.

Genetically InFormed therapies--a "GIFT" for children with cancer

The national investment that was made in oncology research with the passage of the National Cancer Act in 1971 is now coming to fruition. Nowhere is this more apparent than in the exciting prospects for genetically informed precision medicine as applied to the treatment of children with cancer. The wealth of information gleaned from intensive genetic analyses and NexGen sequencing studies has identified a number of viable targets in leukemias and solid tumors. Our rapidly evolving understanding of the enzymatic controls that regulate chromatin dynamics during normal differentiation of stem cells and their mutation or dysregulation in tumor cells is leading to a new library of therapeutically tractable tumor targets. The recent identification of germline variants associated with toxicity and/or response to therapy has further enhanced our ability to deliver individualized treatments for pediatric cancer patients. Our challenge today is to determine how best to use genomic data and integrate it into evolving clinical protocols to provide more efficacious therapies and a better quality of life for children with cancer.

Epidemiology--found in translation

We highlight the value of carefully designed observational epidemiologic analyses in translating basic science discoveries to clinical application and in providing the impetus for exploring underlying mechanisms for observed associations. Coupling epidemiologic data with an in vitro screen of commonly used therapeutic agents may identify novel applications for further clinical testing.

The use of genomic information to optimize cancer chemotherapy

The field of pharmacogenomics is focused on the characterization of genetic factors contributing to the response of patients to pharmacological interventions. Drug response and toxicity are complex traits; therefore the effects are likely influenced by multiple genes. The investigation of the genetic basis of drug response has evolved from a focus on single genes to relevant pathways to the entire genome. Preclinical (cell-based models) and clinical genome-wide association studies (GWAS) in oncology provide an unprecedented opportunity for a comprehensive and unbiased assessment of the heritable factors associated with drug response. The primary challenge with attempting to identify pharmacogenomic markers from clinical studies is that they require a homogeneous population of patients treated with the same dosage regimen and minimal confounding variables. Therefore, the development of cell-based models for pharmacogenomic marker identification has utility for the field since performing these types of studies in humans is difficult and costly. This review intends to provide a current report on the status of genomic studies in oncology, the methods for discovery, and implications for patient care. We present a perspective and summary of the challenges and opportunities in translating heritable genomic discoveries to patients.

GWAS-identified colorectal cancer susceptibility locus associates with disease prognosis

PURPOSE

Extensive evidence has suggested that risk factors of cancer development may also modulate cancer clinical outcome. Recent genome-wide association (GWA) studies identified several single nucleotide polymorphisms (SNPs) predisposing to colorectal cancer (CRC). Given the pivotal importance of these variants in CRC, we sought to evaluate their associations with clinical outcomes of the disease.

EXPERIMENTAL DESIGN

In a well-characterised cohort including 380 Chinese CRC patients, we genotyped seven SNPs identified in previous multi-stage GWA studies and analysed their associations with patient recurrence and survival.

RESULTS

One SNP on chromosome 15q13, rs4779584 was associated with reduced risk of death with a hazard ratio (HR) of 0.33 (95% confidence interval [CI] 0.15-0.72, P = 0.007). Another SNP in a gene-desert region on chromosome 10p14, rs10795668, was associated with a reduced risk of recurrence with an HR of 0.55 (95% CI 0.30-1.00, P = 0.05). In a stratified analysis, this association was only evident in patients receiving chemotherapy (HR = 0.32, 95% CI 0.14-0.78, P = 0.01, log rank P = 0.004), but not in those without chemotherapy (HR = 1.08, 95% CI 0.43-2.73, P = 0.87, log rank P = 0.66). Moreover, we found that the effects of chemotherapy on CRC recurrence was only evident in patients with the variant-containing genotypes (HR = 0.35, 95% CI 0.13-0.94, P = 0.04) but not in those with the wild-type genotype of rs10795668. Further analyses indicated a borderline significant interaction effect (P interaction = 0.05) between rs10795668 and chemotherapy on patient recurrence.

CONCLUSIONS

Our data suggested that rs10795668, a CRC susceptibility variant identified by GWA studies, might be used as a biomarker to identify CRC patients with high risk of recurrence after chemotherapy.

Genomics of the NF-κB signaling pathway: hypothesized role in ovarian cancer

OBJECTIVE

We sought to review evidence linking nuclear factor-kappa B (NF-κB) to ovarian cancer and to identify genetic variants involved in NF-κB signaling.

METHODS

PubMed was reviewed to inform on ovarian cancer biology and NF-κB signaling and to identify key genes. Public linkage disequilibrium (LD) data were analyzed to identify informative inherited variants (tagSNPs) using ldSelect.

RESULTS

We identified 319 key NF-κB genes including five NF-κB subunits, 167 activating genes, and 55 inhibiting genes. We found that the 1000 Genomes Project was the most informative LD source for most genes (92.8%), and we identified 13,027 LD bins (r (2) ≥ 0.9, minor allele frequency ≥ 0.05) and 1,018 putative-functional variants worthy of investigation. We also report that reliance on a commonly used genome-wide SNP array and genotype imputation with HapMap Phase II data provides data on only 74% of the common inherited NF-κB SNPs of interest.

CONCLUSIONS

Compelling evidence suggests that NF-κB plays a critical role in ovarian cancer, yet inherited variation in these genes has not been thoroughly assessed in relation to disease risk or outcome. We present a collection of variants in key genes and suggest creation of a custom genotyping array as an optimal approach.

Racial and ethnic disparities in risk and survival in children with neuroblastoma: a Children's Oncology Group study

PURPOSE

Although health disparities are well-described for many cancers, little is known about racial and ethnic disparities in neuroblastoma. To evaluate differences in disease presentation and survival by race and ethnicity, data from the Children's Oncology Group (COG) were analyzed.

PATIENTS AND METHODS

The racial/ethnic differences in clinical and biologic risk factors, and outcome of patients with neuroblastoma enrolled on COG ANBL00B1 between 2001 and 2009 were investigated.

RESULTS

A total of 3,539 patients (white, 72%; black, 12%; Hispanic, 12%; Asian, 4%; and Native American, < 1%) with neuroblastoma were included. The 5-year event-free survival (EFS) rates were 67% for whites (95% CI, 65% to 69%), 69% for Hispanics (95% CI, 63% to 74%), 62% for Asians (95% CI, 51% to 71%), 56% for blacks (95% CI, 50% to 62%), and 37% for Native American (95% CI, 17% to 58%). Blacks (P < .001) and Native Americans (P = .04) had a higher prevalence of high-risk disease than whites, and significantly worse EFS (P = .01 and P = .002, respectively). Adjustment for risk group abrogated these differences. However, closer examination of the EFS among high-risk patients who remained event free for 2 years or longer, revealed a higher prevalence of late-occurring events among blacks compared with whites (hazard ratio, 1.5; 95% CI, 1.0 to 2.3; P = .04).

CONCLUSION

Black and Native American patients with neuroblastoma have a higher prevalence of high-risk disease, accounting for their worse EFS when compared with whites. The higher prevalence of late-occurring events among blacks with high-risk disease suggests that this population may be more resistant to chemotherapy. Studies focused on delineating the genetic basis for the racial disparities observed in this study are planned.

Genetic variations in microRNA-related genes are associated with survival and recurrence in patients with renal cell carcinoma

We took a polygenic approach to evaluate the effects of 41 potentially functional single-nucleotide polymorphisms (SNPs) in microRNAs (miRNAs)-related genes on survival and recurrence among renal cell carcinoma (RCC) patients. During a median follow-up of 21.8 months, among 316 RCC patients, 64 died and 56 developed recurrence. In single-SNP analysis, we identified seven SNPs significantly associated with RCC survival and five SNPs with recurrence. The most significant associations were SNPs in GEMIN4 with the variant alleles of both rs7813 and rs910925 associated with 1.74-fold [95% confidence interval (CI) = 1.15-2.62] increased risk of death, whereas the variant allele of rs3744741 conferred a decreased risk of death [hazard ratio (HR) = 0.39; 95% CI = 0.19-0.77]. Several SNPs belonging to the pre-miRNA and were identified to be significantly associated with RCC recurrence. Haplotypes of DICER and DROSHA were also associated with altered patient survival and recurrence. More importantly, we observed cumulative effects of multiple SNPs on RCC survival. Compared with subjects carrying zero to two unfavorable genotypes, those carrying three to five and six and more unfavorable genotypes had an increased risk of death with a HR of 2.49 (95% CI = 1.24-5.00) and 6.66 (95% CI = 2.49-17.86), respectively, with significant dose-response trend (P for trend<0.001). As the first study of miRNA-related genetic polymorphisms on RCC clinical outcome, our results strongly suggested that miRNA-related SNPs may impact the recurrence and survival in RCC patients. Future investigation in larger populations and functional characterizations are necessary to validate these results.

Genetic variation in microRNA networks: the implications for cancer research

Many studies have highlighted the role that microRNAs have in physiological processes and how their deregulation can lead to cancer. More recently, it has been proposed that the presence of single nucleotide polymorphisms in microRNA genes, their processing machinery and target binding sites affects cancer risk, treatment efficacy and patient prognosis. In reviewing this new field of cancer biology, we describe the methodological approaches of these studies and make recommendations for which strategies will be most informative in the future.

The evolving discipline of molecular epidemiology of cancer

Classical epidemiologic studies have made seminal contributions to identifying the etiology of most common cancers. Molecular epidemiology was conceived of as an extension of traditional epidemiology to incorporate biomarkers with questionnaire data to further our understanding of the mechanisms of carcinogenesis. Early molecular epidemiologic studies employed functional assays. These studies were hampered by the need for sequential and/or prediagnostic samples, viable lymphocytes and the uncertainty of how well these functional data (derived from surrogate lymphocytic tissue) reflected events in the target tissue. The completion of the Human Genome Project and Hapmap Project, together with the unparalleled advances in high-throughput genotyping revolutionized the practice of molecular epidemiology. Early studies had been constrained by existing technology to use the hypothesis-driven candidate gene approach, with disappointing results. Pathway analysis addressed some of the concerns, although the study of interacting and overlapping gene networks remained a challenge. Whole-genome scanning approaches were designed as agnostic studies using a dense set of markers to capture much of the common genome variation to study germ-line genetic variation as risk factors for common complex diseases. It should be possible to exploit the wealth of these data for pharmacogenetic studies to realize the promise of personalized therapy. Going forward, the temptation for epidemiologists to be lured by high-tech 'omics' will be immense. Systems Epidemiology, the observational prototype of systems biology, is an extension of classical epidemiology to include powerful new platforms such as the transcriptome, proteome and metabolome. However, there will always be the need for impeccably designed and well-powered epidemiologic studies with rigorous quality control of data, specimen acquisition and statistical analysis.

Genetic variations as cancer prognostic markers: review and update

Cancer molecular epidemiology traditionally studies the relationship between genetic variations and cancer risk. However, recent studies have also focused on disease outcomes. The application and design of disease outcome studies have been an extension of disease risk assessment. Yet there are a number of unique considerations important in outcome assessments. We review how genetic approaches used for disease susceptibility, such as candidate gene and genome-wide association study (GWAS) approaches, can be adapted carefully to systematically identify cancer prognostic and predictive alleles. We discuss the interrelatedness among the disease susceptibility, treatment response, and prognosis at the genetic level and focus on how the emerging technologies and approaches can uniquely benefit the genetic prognosis studies.

Polymorphisms in tissue inhibitors of metalloproteinases-2 and -3 and breast cancer susceptibility and survival

Tissue inhibitors of metalloproteinases (TIMPs) are endogenous inhibitors of matrix metalloproteinases which are involved in normal cellular processes and also in cancer development and progression. The purpose of this study was to evaluate polymorphisms in the TIMP-2 and TIMP-3 genes for their associations with breast cancer susceptibility and survival. Using data from the Shanghai Breast Cancer Study, 19 SNPs for each gene were evaluated for associations with breast cancer risk among 1,062 cases and 1,069 controls; associations with disease-free and overall survival were evaluated among the cases. For TIMP-2, women with the rs7501477 TT genotype were 3 times more likely to be breast cancer cases than women with the CC genotype (OR: 2.9, 95% CI: 1.2-7.0). For TIMP-3, women with the rs9609643 AA genotype were 60% less likely to be breast cancer cases than women with the GG genotype (OR: 0.4, 95% CI: 0.2-1.0), whereas women with the rs8136803 TT genotype were 5 times more likely to be cases than women with the GG genotype (OR: 5.1, 95% CI: 1.1-24.3). Further, breast cancer cases with rs8136803 TT were almost 4 times more likely to have decreased disease-free survival (HR: 3.9, 95% CI: 1.4-10.6) and had a trend toward decreased overall survival (HR: 1.9, 95% CI: 0.6-6.1). An important study limitation was that these 3 SNPs (rs7501477, rs9609643, rs8136803) had low minor allele frequencies which resulted in small numbers of homozygote individuals. Genetic variation in the TIMP-2 and TIMP-3 genes may contribute to individual differences in breast cancer susceptibility and survival.

Studying genetic variations in cancer prognosis (and risk): a primer for clinicians

Rare, high-penetrance genetic variations account for a small portion of genetic cancer syndromes. In contrast, most cancers develop from a combination of minor genetic influences and environmental factors. There are numerous publications on cancer susceptibility. In contrast, genetic studies in treatment response and outcome analyses are a rapidly emerging field. Approaches used in disease susceptibility can be adapted for genetic outcome studies. In this review, we summarize the current knowledge on how candidate genes and genetic variations are selected to evaluate gene-outcome, gene-prognosis, and gene-treatment response relationships as applicable to the practicing oncologist.

Advances in breast cancer: pathways to personalized medicine

Breast cancer is a complex disease caused by the progressive accumulation of multiple gene mutations combined with epigenetic dysregulation of critical genes and protein pathways. There is substantial interindividual variability in both the age at diagnosis and phenotypic expression of the disease. With an estimated 1,152,161 new breast cancer cases diagnosed worldwide per year, cancer control efforts in the postgenome era should be focused at both population and individual levels to develop novel risk assessment and treatment strategies that will further reduce the morbidity and mortality associated with the disease. The discovery that mutations in the BRCA1 and BRCA2 genes increase the risk of breast and ovarian cancers has radically transformed our understanding of the genetic basis of breast cancer, leading to improved management of high-risk women. A better understanding of tumor host biology has led to improvements in the multidisciplinary management of breast cancer, and traditional pathologic evaluation is being complemented by more sophisticated genomic approaches. A number of genomic biomarkers have been developed for clinical use, and increasingly, pharmacogenetic end points are being incorporated into clinical trial design. For women diagnosed with breast cancer, prognostic or predictive information is most useful when coupled with targeted therapeutic approaches, very few of which exist for women with triple-negative breast cancer or those with tumors resistant to chemotherapy. The immediate challenge is to learn how to use the molecular characteristics of an individual and their tumor to improve detection and treatment, and ultimately to prevent the development of breast cancer. The five articles in this edition of CCR Focus highlight recent advances and future directions on the pathway to individualized approaches for the early detection, treatment, and prevention of breast cancer.

Molecular epidemiology, cancer-related symptoms, and cytokines pathway

The Human Genome Project and HapMap have led to a better appreciation of the importance of common genetic variation in determining cancer risk, created potential for predicting response to therapy, and made possible the development of targeted prevention and therapeutic interventions. Advances in molecular epidemiology can be used to explore the role of genetic variation in modulating the risk for severe and persistent symptoms, such as pain, depression, and fatigue, in patients with cancer. The same genes that are implicated in cancer risk might also be involved in the modulation of therapeutic outcomes. For example, polymorphisms in several cytokine genes are potential markers for genetic susceptibility both for cancer risk and for cancer-related symptoms. These genetic polymorphisms are stable markers and easily and reliably assayed to explore the extent to which genetic variation might prove useful in identifying patients with cancer at high-risk of symptom development. Likewise, they could identify subgroups who might benefit most from symptom intervention, and contribute to developing personalized and more effective therapies for persistent symptoms.

Genetic variants of miRNA sequences and non-small cell lung cancer survival

Recent evidence indicates that small noncoding RNA molecules known as microRNAs (miRNAs) can function as tumor suppressors and oncogenes. Mutation, misexpression, and altered mature miRNA processing are implicated in carcinogenesis and tumor progression. Because SNPs in pre-miRNAs could alter miRNA processing, expression, and/or binding to target mRNA, we conducted a systematic survey of common pre-miRNA SNPs and their surrounding regions and evaluated in detail the association of 4 of these SNPs with the survival of individuals with non-small cell lung cancer (NSCLC). When we assumed that disease susceptibility was inherited as a recessive phenotype, we found that the rs11614913 SNP in hsa-mir-196a2 was associated with survival in individuals with NSCLC. Specifically, survival was significantly decreased in individuals who were homozygous CC at SNP rs11614913. In the genotype-phenotype correlation analysis of 23 human lung cancer tissue samples, rs11614913 CC was associated with a statistically significant increase in mature hsa-mir-196a expression but not with changes in levels of the precursor, suggesting enhanced processing of the pre-miRNA to its mature form. Furthermore, binding assays revealed that the rs11614913 SNP can affect binding of mature hsa-mir-196a2-3p to its target mRNA. Therefore, the rs11614913 SNP in hsa-mir-196a2 may be a prognostic biomarker for NSCLC. Further characterization of miRNA SNPs may open new avenues for the study of cancer and therapeutic interventions.

Identifying genetic variants that contribute to chemotherapy-induced cytotoxicity

Patients treated with anticancer chemotherapy exhibit variation, both in terms of tumor response and the incidence and severity of adverse effects. The etiology of this variation is multifactorial with genetic factors likely contributing to a significant extent. Pharmacogenetic and genomic studies can be used to identify the genetic variants that contribute to interindividual variation in susceptibility to chemotherapy-induced cytotoxicity. This review will describe candidate and whole-genome approaches, describe the advantages and disadvantages of each, and illustrate how they can be used to obtain clinically relevant information. Specific emphasis is given to recent advances emerging from the International HapMap Project and to the development of genetic signatures, as opposed to expression signatures, to explain drug sensitivity and resistance.

A rapid outcomes ascertainment system improves the quality of prognostic and pharmacogenetic outcomes from observational studies

PURPOSE

Case-control and observational studies are popular choices for evaluating molecular prognostic/pharmacogenetic outcomes, but data quality is rarely tested. Using clinical trial and epidemiologic methods, we assessed the quality of prognostic and outcomes data obtainable from a large case-control study of lung cancer.

METHODS

We developed an explicit algorithm (set of standard operating procedures forming a rapid outcomes ascertainment system) that encompassed multiple tests of quality assurance, and quality of data for a range of prognostic and outcomes variables, in several cancers, across several centers and two countries were assessed. Based on these assessments, the algorithm was revised and physicians' clinical practice changed. We reevaluated the quality of outcomes after these revisions.

RESULTS

Development of an algorithm with internal quality controls showed specific patterns of data collection errors, which were fixable. Although the major discrepancy rate in retrospective data collection was low (0.6%) when compared with external validated sources, complete data were found in <50% of patients for treatment response rate, toxicity, and documentation of patient palliative symptoms. Prospective data collection and changes to clinical practice led to significantly improved data quality. Complete data on response rate increased from 45% to 76% (P = 0.01, Fisher's exact test), for toxicity data, from 26% to 56% (P = 0.02), and for palliative symptoms, from 25% to 70% (P < 0.05), in one large lung cancer case-control study.

CONCLUSIONS

Observational studies can be a useful source for studying molecular prognostic and pharmacogenetic outcomes. A rapid outcomes ascertainment system with strict ongoing quality control measures is an excellent means of monitoring key variables.

Race and triple negative threats to breast cancer survival: a population-based study in Atlanta, GA

BACKGROUND

Breast cancers with a triple negative tumor (TNT) subtype (as defined by lacking protein expression of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2)) preclude the use of available targeted therapies and may contribute to poor outcome and to the historically poorest survival observed among African-American (AA) women. This study examines association of the ER/PR/HER2 subtypes with race and breast cancer survival.

METHODS

Breast tumors from a population-based cohort of 116 AA and 360 white Atlanta women aged 20-54, diagnosed from 1990 to 1992 were centrally reviewed and tested by immunohistochemistry. Multivariate survival analyses within subtypes (TNT, ER-PR-HER2+, ER+/PR+HER2+, ER+/PR+HER2-) were conducted using weighted Cox regression and included socio-demographic, prognostic, and treatment factors.

RESULTS

TNTs were more prevalent among young women and particularly among AA women (Odds Ratio [OR] = 1.9, 95% Confidence Interval [CI] 1.2-2.9), adjusting for age, stage, grade, and poverty index. Overall mortality was higher for AA women (Hazard Ratio [HR] = 1.9, 95% CI, 1.5-2.5) and differed by subtypes (P < 0.001). Within the TNT subtype, racial differences in survival persisted, after additional adjustment for treatment and comorbidities (HR = 2.0, 95% CI 1.0-3.7). TNTs were uniquely associated with high expression of p16, p53, and Cyclin E; and low Bcl-2 and Cyclin D1 expression.

CONCLUSIONS

The high prevalence of TNTs among younger women and particularly younger AA women, along with unique protein expression patterns and poorer survival, suggests varying gene-environment etiologies with respect to age and race/ethnicity and a need for effective therapies.

Genetic polymorphisms and disease prevention

Building upon the resources of traditional epidemiology, molecular epidemiology has extended our understanding that disease risk varies based not only upon acquired factors (e.g., exposures, behaviors, demographics), but also as a function of inherited factors (e.g., genetic polymorphisms). Individual susceptibility to cancer is influenced by polymorphisms in phase I enzymes (e.g., activation), phase 2 enzymes (e.g., detoxification), defects in the repair of DNA damage and other cancer susceptibility genes. Because tobacco use and nutrition represent behaviors/exposures which account for a significant number of cancer cases and deaths, these two factors are used to illustrate the relationship between genetic polymorphisms and disease prevention. Susceptibility to the health risks of smoking appears to be influenced by genetic factors that impact initiation, dependence, and nicotine metabolism. Nutrient metabolism also involves polymorphic enzyme pathways and gene-nutrient interactions may influence cancer risk. While the discipline of molecular epidemiology continues to face methodologic challenges related to the need to study large numbers of subjects, current knowledge can be applied to prevention activities. Genetic polymorphisms, and other molecular markers, can be used to develop clinical prevention studies targeted to unique subsets of persons at the highest risk of developing disease. Knowledge about the relationships between polymorphisms and disease outcomes can also be used for reinforcing healthy lifestyles, motivating positive behavior changes, helping to target medical therapy, and aiding in better focusing surveillance activities.

UDP-Glucuronosyltransferase 1A1 Gene Polymorphisms and Total Bilirubin Levels in an Ethnically Diverse Cohort of Women

The objective of this study was to investigate variations in UGT1A1 polymorphisms and haplotypes among African-American and Caucasian women and to assess whether variants other than UGT1A1*28 are associated with total serum bilirubin levels. The (TA)(n) repeats and 14 single nucleotide polymorphisms (SNPs) in the UGT1A1 gene were genotyped in 335 African Americans and 181 Caucasians. Total serum bilirubin levels were available in a subset of 125 women. Allele frequencies of all SNPs and (TA)(n) repeats were significantly different between African Americans and Caucasians. In Caucasians, three common haplotypes accounted for 71.8% of chromosomes, whereas five common haplotypes accounted for only 46.6% of chromosomes in African Americans. Mean total serum bilirubin levels were significantly lower (p = 0.005) in African Americans (0.36 mg/dl) than in Caucasians (0.44 mg/dl). The (TA)(n) repeats explained a significant amount of variation in total bilirubin levels (R(2) = 0.27, p < 0.0001), whereas other SNPs were less correlative. Thus, significant variations in UGT1A1 haplotype structure exist between African Americans and Caucasians in this relatively large cohort of women. The correlation of UGT1A1 with total bilirubin levels was mainly due to (TA)(n) repeats in Caucasians but a clear correlation was not observed in African Americans because of the high diversity of haplotypes and the small sample size. These data have implications for the design of epidemiologic studies of cancer susceptibility and pharmacogenetic studies for adverse drug reactions in populations of African ancestry.

Effect of population and gender on chemotherapeutic agent-induced cytotoxicity

Large interindividual variance is observed in both response and toxicity associated with chemotherapy. Our goal is to identify factors that contribute to chemotherapy-induced toxicity. To this end, we used EBV-transformed B-lymphoblastoid HapMap cell lines derived from 30 Yoruban trios (African descent) and 30 Centre d' Etude du Polymorphisme Humain (CEPH) trios (European descent) to evaluate population- and gender-specific differences in cytotoxicity of carboplatin, cisplatin, daunorubicin, and etoposide using a high-throughput, short-term cytotoxicity assay. The IC(50) was compared for population- and gender-specific differences for the four drugs. We observed large interindividual variance in IC(50) values for carboplatin, cisplatin, daunorubicin, and etoposide for both Yoruban and CEPH populations (range from 8- to 433-fold). Statistically significant differences in carboplatin and daunorubicin IC(50) were shown when comparing Yoruban cell lines (n = 89) to CEPH cell lines (n = 87; P = 0.002 and P = 0.029, respectively). This population difference in treatment induced cytotoxicity was not seen for either cisplatin or etoposide. In the Yoruban population, cell lines derived from females were less sensitive to platinating agents than males [median carboplatin IC(50), 29.1 versus 24.6 micromol/L (P = 0.012); median cisplatin IC(50), 7.0 versus 6.0 micromol/L (P = 0.020) in female and male, respectively]. This difference was not observed in the CEPH population. These results show that population and gender may affect risk for toxicities associated with certain chemotherapeutic agents.

Lung cancer risk prediction: a tool for early detection

Although 45% of men and 39% of women will be diagnosed with cancer in their lifetime, it is difficult to predict which individuals will be affected. For some cancers, substantial progress in individual risk estimation has already been made. However, relatively few models have been developed to predict lung cancer risk beyond effects of age and smoking. This paper reviews published models for lung cancer risk prediction, discusses their potential contribution to clinical and research settings and suggests improvements to the risk modeling strategy for lung cancer. The sensitivity and specificity of existing cancer risk models is less than optimal. Improvement in individual risk prediction is important for selection of individuals for prevention or early detection interventions. In addition to smoking, factors related to occupational exposure, personal medical history and family history of cancer can add to the predictive power. A good risk prediction model is one that can identify a small fraction of the population in which a large proportion of the disease cases will occur. In the future, genetic and other biological markers are likely to be useful, although they will require rigorous evaluation. Validation is essential to establish the predictive effect and for ongoing monitoring of the model's continued relevance.

Cancer Biology and Implications for Practice

The media seem to announce a new scientific discovery related to cancer daily. Oncology nurses are challenged to keep up with the explosion of new knowledge and to understand how it ultimately relates to the care of patients with cancer. A framework for classifying new knowledge can be useful as nurses seek to understand the biology of cancer and its related implications for practice. To understand the molecular roots of cancer, healthcare practitioners specializing in cancer care require insight into genes, their messages, and the proteins produced from those messages, as well as the new tools of molecular biology.

Genetic risk profiles for cancer susceptibility and therapy response

Cells in the body are permanently attacked by DNA-reactive species, both from intracellular and environmental sources. Inherited and acquired deficiencies in host defense mechanisms against DNA damage (metabolic and DNA repair enzymes) can modify cancer susceptibility as well as therapy response. Genetic profiles should help to identify high-risk individuals who subsequently can be enrolled in preventive measures or treated by tailored therapy regimens. Some of our attempts to define such risk profiles are presented. Cancer susceptibility: Single nucleotide polymorphisms (SNPs) in metabolic and repair genes were investigated in a hospital-based lung cancer case-control study. When evaluating the risk associated with different genotypes for N-acetyltransferases (Wikman et al. 2001) and glutathione-S-transferases (Risch et al. 2001), it is mandatory to distinguish between the three major histological subtypes of lung tumors. A promoter polymorphism of the myeloperoxidase gene MPO was shown to decrease lung cancer susceptibility mainly in small cell lung cancer (SCLC) (Dally et al. 2002). The CYP3A4*1B allele was also linked to an increased SCLC risk and in smoking women increased the risk of lung cancer eightfold (Dally et al. 2003b). Polymorphisms in DNA repair genes were shown to modulate lung cancer risk in smokers, and reduced DNA repair capacity elevated the disease risk (Rajaee-Behbahani et al. 2001). Investigations of several DNA repair gene variants revealed that lung cancer risk was only moderately affected by a single variant but was enhanced up to approximately threefold by specific risk allele combinations (Popanda et al. 2004). Therapy response: Inter-individual differences in therapy response are consistently observed with cancer chemotherapeutic agents. Initial results from ongoing studies showed that certain polymorphisms in drug transporter genes (ABCB1) differentially affect response outcome in histological subgroups of lung cancer. Stronger beneficial effects were seen in non-small cell lung cancer (NSCLC) patients following gemcitabine and in SCLC patients following etoposide-based treatment. Several DNA repair parameters (polymorphisms, RNA expression, and DNA repair capacity) were measured in vitro in lymphocytes of patients before radiotherapy and correlated with the occurrence of acute side effects (radio-hypersensitivity). Our initial analysis of several repair gene variants in breast cancer patients (n = 446) who received radiotherapy revealed no association of single polymorphisms and the development of side effects (moist desquamation of the irradiated normal skin). The risk for this side effect was, however, strongly reduced in normal weight women carrying a combination of XRCC1 399Gln and APE1 148Glu alleles, indicating that these variants afford some protection against radio-hypersensitivity (Chang-Claude et al. 2005). Based on these data we conclude that specific metabolic and DNA repair gene variants can affect cancer risk and therapy outcome. Predisposition to hereditary cancer syndromes is dominated by the strong effects of some high-penetrance tumor susceptibility genes, while predisposition to sporadic cancer is influenced by the combination of multiple low-penetrance genes, of which as a major challenge, many disease-relevant combinations remain to be identified. Before translating these findings into clinical use and application for public health measures, large population-based studies and validation of the results will be required.

Bronchial malondialdehyde DNA adducts, tobacco smoking, and lung cancer

Tobacco smoking is a major risk factor for lung cancer causing, among other effects, oxidative stress and lipid peroxidation. Malondialdehyde (MDA)-DNA adducts can be induced by direct DNA oxidation and by lipid peroxidation. We measured the relationship between bronchial MDA-DNA adducts and tobacco smoking, cancer status, and selected polymorphisms in 43 subjects undergoing a bronchoscopic examination for diagnostic purposes. MDA-DNA adducts were higher in current smokers than in never smokers (frequency ratio (FR) = 1.51, 95% confidence interval (CI) 1.01-2.26). MDA-DNA adducts were also increased in lung cancer cases with respect to controls, but only in smokers (FR = 1.70, 95% CI 1.16-2.51). Subjects with GA and AA cyclin D1 (CCND1) genotypes showed higher levels of MDA-DNA adducts than those with the wild-type genotype (FR = 1.51 (1.04-2.20) and 1.45 (1.02-2.07)). Lung cancer cases with levels of MDA-DNA adducts over the median showed a worse, but not statistically significant, survival, after adjusting for age, gender, and packyears (hazard ratio = 2.48, 95% CI 0.65-9.44). Our findings reinforce the role of smoking in lung carcinogenesis through oxidative stress. Subjects who carry at least one variant allele of the CCND1 gene could accumulate DNA damage for altered cell-cycle control and reduced DNA repair proficiency.

Can risk of radiotherapy-induced normal tissue complications be predicted from genetic profiles?

Over the last decade, increasing efforts have been taken to establish associations between various genetic germline alterations and risk of normal tissue complications after radiotherapy. Though the studies have been relatively small and methodologically heterogeneous, preliminary indications have been provided that single nucleotide polymorphisms in the genes TGFB1 and ATM may modulate risk of particularly late toxicity. In addition, rare ATM alterations may enhance complication susceptibility. Nevertheless, we are still far from having an exhaustive understanding of the genetics that may underlie differences in clinical normal tissue radiosensitivity. Recent technical advances and emerging insights to the structure of inter-individual genetic variation open up unprecedented opportunities to dissect the molecular and genetic basis of normal tissue radiosensitivity. However, to fully exploit these new possibilities well-planed large-scale clinical studies are mandatory. Currently, international initiatives are taken to establish the bio banks and databases needed for this task.

The influence of HER2 genotypes as molecular markers in ovarian cancer outcome

A relevant clinical problem in the treatment of ovarian cancer (OC) is the development of resistance to chemotherapy, frequently due to genetic variations in enzymes and receptors. Changes in the HER2 receptor have been associated with breast and ovarian cancers. The role of a polymorphism in the HER2 gene in the clinical outcome of OC patients was investigated in this study. We characterized DNA samples from 111 patients with OC treated with cisplatin and paclitaxel, using PCR-RFLP. Our results indicate that patients carrying the valine homozygotic genotype present a lower overall survival mean, suggesting a role for this polymorphism in the outcome of ovarian cancer patients. The G allele has been implicated in the formation of active HER2 receptors, with a more aggressive phenotype. We hypothesize that HER2 genotypes can be predictive biomarkers in ovarian cancer, contributing to a genetic individual profile of great interest in clinical oncology.

ERCC1 and ERCC2 polymorphisms and adult glioma

ERCC2 and ERCC1 are important in DNA nucleotide excision repair and lie on chromosome 19q13.3 near a putative glioma suppressor region. We genotyped constitutive variants ERCC1 C8092A and ERCC2 K751Q and R156R in approximately 450 adults with glioma and 500 controls from two independent population-based series, uniformly reviewed patients' tumors to determine histopathologic category, and determined a variety of tumor markers among astrocytic tumors. Odds ratios (ORs) for glioblastoma for those carrying two ERCC1 A alleles versus none or one were 1.67 in series 1 and 1.64 in series 2, which yielded a combined OR of 1.67 (95% CI, 0.93-3.02; P = 0.09), adjusted for age, gender, ethnicity, and series. Odds ratios for the ERCC2 variants were not consistently elevated or reduced for the two series in all cases versus controls. However, among whites, for those with ERCC2 K751Q genotype QQ versus QK/KK, the OR for nonglioblastoma histologies versus controls was 1.82 (95% CI, 0.97-3.44; P = 0.06). Also, among whites, glioma patients were significantly more likely than controls to be homozygous for variants in both ERCC1 C8092A and ERCC2 K751Q (OR, 3.2; 95% CI, 1.1-9.3). Given the numbers of comparisons made, these findings could be due to chance. However, the results might warrant clarification in additional series in conjunction with the nearby putative glioma suppressor genes (GLTSCR1 and GLTSCR2).

Personalized exposure assessment: promising approaches for human environmental health research

New technologies and methods for assessing human exposure to chemicals, dietary and lifestyle factors, infectious agents, and other stressors provide an opportunity to extend the range of human health investigations and advance our understanding of the relationship between environmental exposure and disease. An ad hoc Committee on Environmental Exposure Technology Development was convened to identify new technologies and methods for deriving personalized exposure measurements for application to environmental health studies. The committee identified a "toolbox" of methods for measuring external (environmental) and internal (biologic) exposure and assessing human behaviors that influence the likelihood of exposure to environmental agents. The methods use environmental sensors, geographic information systems, biologic sensors, toxicogenomics, and body burden (biologic) measurements. We discuss each of the methods in relation to current use in human health research; specific gaps in the development, validation, and application of the methods are highlighted. We also present a conceptual framework for moving these technologies into use and acceptance by the scientific community. The framework focuses on understanding complex human diseases using an integrated approach to exposure assessment to define particular exposure-disease relationships and the interaction of genetic and environmental factors in disease occurrence. Improved methods for exposure assessment will result in better means of monitoring and targeting intervention and prevention programs.