Karen Kopciuk

Prospective cohort study of lifetime physical activity and breast cancer survival

Few studies have examined the association between physical activity and disease outcomes in breast cancer survivors. Here, we report the association between lifetime total physical activity performed prior to diagnosis and disease outcomes in a population‐based sample of breast cancer survivors. A cohort of 1,231 women diagnosed with breast cancer between 1995 and 1997 was followed for a minimum of 8.3 years for any cancer progressions, recurrences and new primaries; and a minimum of 10.3 years for deaths. All treatment and follow‐up care received was abstracted from medical records. Data on physical activity including type (occupational, household, recreational) and dose (frequency, intensity and duration) performed during the entire lifetime until diagnosis were examined in Cox proportional hazards models as well as with cumulative incidence curves. An average of 126 MET‐hr/week were reported for total physical activity (of which 13.9, 46.9 and 65.3 MET‐hr/week were, respectively, for recreational, occupational and household activity). A decreased risk of breast cancer death and all deaths was observed among women in the highest versus the lowest quartiles of recreational activity (MET‐hr/week/year) (HR = 0.54, 95% CI = 0.36–0.79). Both moderate (0.56, 95% CI = 0.38–0.82) and vigorous intensity recreational activity (0.74, 95% CI = 0.56–0.98) decreased the risk of breast cancer death. Moderate intensity recreational activity decreased the risk of a recurrence, progression or new primary cancer (0.66, 95% CI = 0.48–0.91). No other association with breast cancer survival was observed for other types of physical activity. Prediagnosis recreational activity conferred a benefit for survival after breast cancer. Moderate intensity recreational activity was particularly protective.

Feasibility of Identifying Pancreatic Cancer based on Serum Metabolomics

Background: We postulated that the abundance of various metabolites in blood would facilitate the diagnosis of pancreatic and biliary lesions, which could potentially prevent unnecessary surgery. Methods: Serum samples from patients with benign hepatobiliary disease (n = 43) and from patients with pancreatic cancer (n = 56) were examined by 1H NMR spectroscopy to quantify 58 unique metabolites. Data were analyzed by “targeted profiling” followed by supervised pattern recognition and orthogonal partial least-squares discriminant analysis (O-PLS-DA) of the most significant metabolites, which enables comparison of the whole sample spectrum between groups. Results: The metabolomic profile of patients with pancreatic cancer was significantly different from that of patients with benign disease (AUROC, area under the ROC curve, = 0.8372). Overt diabetes mellitus (DM) was identified as a possible confounding factor in the pancreatic cancer group. Thus, diabetics were excluded from further analysis. In this more homogeneous pancreatic cancer group, compared with benign cases, serum concentrations of glutamate and glucose were most elevated on multivariate analysis. In benign cases, creatine and glutamine were most abundant. To examine the usefulness of this test, a comparison was made to age- and gender-matched controls with benign lesions that mimic cancer, controlling also for presence of jaundice and diabetes (n = 14 per group). The metabolic profile in patients with pancreatic cancer remained distinguishable from patients with benign pancreatic lesions (AUROC = 0.8308). Conclusions: The serum metabolomic profile may be useful for distinguishing benign from malignant pancreatic lesions. Impact: Further studies will be required to study the effects of jaundice and diabetes. A more comprehensive metabolomic profile will be evaluated using mass spectrometry. Cancer Epidemiol Biomarkers Prev; 20(1); 140–7. ©2010 AACR.

Physical Activity and Survival After Prostate Cancer

BACKGROUND Despite the high global prevalence of prostate cancer (PCa), few epidemiologic studies have assessed physical activity in relation to PCa survival. OBJECTIVE To evaluate different types, intensities, and timing of physical activity relative to PCa survival. DESIGN, SETTING, AND PARTICIPANTS A prospective study was conducted in Alberta, Canada, in a cohort of 830 stage II-IV incident PCa cases diagnosed between 1997 and 2000 with follow-up to 2014 (up to 17 yr). Prediagnosis lifetime activity was self-reported at diagnosis. Postdiagnosis activity was self-reported up to three times during follow-up. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS Cox proportional hazards models related physical activity to all-cause and PCa-specific deaths and to first recurrence/progression of PCa. RESULTS AND LIMITATIONS A total of 458 deaths, 170 PCa-specific deaths, and, after first follow-up, 239 first recurrences/progressions occurred. Postdiagnosis total activity (>119 vs ≤42 metabolic equivalent [MET]-hours/week per year) was associated with a significantly lower all-cause mortality risk (hazard ratio [HR]: 0.58; 95% confidence interval [CI], 0.42-0.79; p value for trend <0.01). Postdiagnosis recreational activity (>26 vs ≤4 MET-hours/week per year) was associated with a significantly lower PCa-specific mortality risk (HR: 0.56; 95% CI, 0.35-0.90; p value for trend = 0.01). Sustained recreational activity before and after diagnosis (>18-20 vs <7-8 MET-hours/week per year) was associated with a lower risk of all-cause mortality (HR: 0.66; 95% CI, 0.49-0.88). Limitations included generalisability to healthier cases and an observational study design. CONCLUSIONS These findings support emerging recommendations to increase physical activity after the diagnosis of PCa and would inform a future exercise intervention trial examining PCa outcomes. PATIENT SUMMARY In a 17-yr prostate cancer (PCa) survival study, men who survived at least 2 yr who were more physically active postdiagnosis or performed more recreational physical activity before and after diagnosis survived longer. Recreational physical activity after diagnosis was associated with a lower risk of PCa death.

Serum metabolomic profile as a means to distinguish stage of colorectal cancer

BackgroundPresently, colorectal cancer (CRC) is staged preoperatively by radiographic tests, and postoperatively by pathological evaluation of available surgical specimens. However, present staging methods do not accurately identify occult metastases. This has a direct effect on clinical management. Early identification of metastases isolated to the liver may enable surgical resection, whereas more disseminated disease may be best treated with palliative chemotherapy.MethodsSera from 103 patients with colorectal adenocarcinoma treated at the same tertiary cancer center were analyzed by proton nuclear magnetic resonance (1H NMR) spectroscopy and gas chromatography-mass spectroscopy (GC-MS). Metabolic profiling was done using both supervised pattern recognition and orthogonal partial least squares-discriminant analysis (O-PLS-DA) of the most significant metabolites, which enables comparison of the whole sample spectrum between groups. The metabolomic profiles generated from each platform were compared between the following groups: locoregional CRC (N = 42); liver-only metastases (N = 45); and extrahepatic metastases (N = 25).ResultsThe serum metabolomic profile associated with locoregional CRC was distinct from that associated with liver-only metastases, based on 1H NMR spectroscopy (P = 5.10 × 10-7) and GC-MS (P = 1.79 × 10-7). Similarly, the serum metabolomic profile differed significantly between patients with liver-only metastases and with extrahepatic metastases. The change in metabolomic profile was most markedly demonstrated on GC-MS (P = 4.75 × 10-5).ConclusionsIn CRC, the serum metabolomic profile changes markedly with metastasis, and site of disease also appears to affect the pattern of circulating metabolites. This novel observation may have clinical utility in enhancing staging accuracy and selecting patients for surgical or medical management. Additional studies are required to determine the sensitivity of this approach to detect subtle or occult metastatic disease.

CXCR4 Overexpression Is Associated with Poor Outcome in Females Diagnosed with Stage IV Non-small Cell Lung Cancer

Background: It has been proposed that the chemokine receptor, CXCR4, and its ligand, stromal cell-derived factor-1 (SDF-1), play a critical role in organ-specific tumor metastasis. High CXCR4 expression in resected non-small cell lung cancer (NSCLC) tumors is associated with poorer outcome; however, its effect on patient outcome in advanced NSCLC has not been explored. Methods: After institutional ethical approval was obtained, demographic details, clinical variables, and outcome data were collected on consecutive NSCLC patients diagnosed at the Tom Baker Cancer Centre from 2003 to 2006 (Glans-Look Lung Cancer Database). Formalin-fixed paraffin-embedded diagnostic biopsies from stage IV patients were obtained and tissue microarrays generated. CXCR4 expression within NSCLC cells was analyzed by quantitative fluorescent immunohistochemistry using the HistoRx PM-2000 platform and then correlated with clinical outcome. Results: Of 832 patients, 170 had samples suitable for tissue microarray generation and analysis. Automated immunohistochemistry for CXCR4 was successfully completed on all 170 patients. High expressors had a significantly poorer median overall survival of 2.7 months versus 5.6 months for the low expressors (p = 0.0468). This difference is driven by high-expressing females who have a median overall survival of 1.6 months versus 6.4 months for the low expressors (p = 0.006). Conclusions: CXCR4 is expressed in the majority of NSCLC tumors, and overexpression is associated with significantly poorer survival in stage IV NSCLC patients. Interestingly, this poor outcome is disproportionately represented in the female population. Our results suggest a gender-dependent difference in clinical outcome based on CXCR4 overexpression in stage IV NSCLC.

Reovirus as a Viable Therapeutic Option for the Treatment of Multiple Myeloma

Purpose: Despite the recent advances made in the treatment of multiple myeloma, the disease still remains incurable. The oncolytic potential of reovirus has previously been shown and is currently in phase III clinical trials for solid tumors. We tested the hypothesis that reovirus can successfully target human multiple myeloma in vitro, ex vivo, and in vivo without affecting human hematopoietic stem cell (HHSC) re-population/differentiation in a murine model that partially recapitulates human multiple myeloma. Experimental Design: Human myeloma cell lines and ex vivo tumor specimens were exposed to reovirus and oncolysis and mechanisms of cell death were assessed. RPMI 8226GFP+ cells were injected intravenously to non-obese diabetic/severe combined immune deficient (NOD/SCID) mice and treated with live reovirus (LV) or dead virus (DV). Multiple myeloma disease progression was evaluated via whole-body fluorescence and bone marrow infiltration. HHSCs exposed to LV/DV were injected to NOD/SCID mice and re-population/differentiation was monitored. Results: A total of six of seven myeloma cell lines and five of seven patient tumor specimens exposed to reovirus showed significant in vitro sensitivity. Tumor response of multiple myeloma by LV, but not DV, was confirmed by comparison of total tumor weights (P = 0.05), and bone marrow infiltration (1/6, LV; 5/6, DV). Mice injected with LV- or DV-exposed HHSCs maintained in vivo re-population/lineage differentiation showing a lack of viral effect on the stem cell compartment. Reovirus oncolysis was mediated primarily by activation of the apoptotic pathways. Conclusions: The unique ability of reovirus to selectively kill multiple myeloma while sparing HHSCs places it as a promising systemic multiple myeloma therapeutic for clinical testing. Clin Cancer Res; 18(18); 4962–72. ©2012 AACR.

Assessing SNP-SNP Interactions among DNA Repair, Modification and Metabolism Related Pathway Genes in Breast Cancer Susceptibility

Genome-wide association studies (GWASs) have identified low-penetrance common variants (i.e., single nucleotide polymorphisms, SNPs) associated with breast cancer susceptibility. Although GWASs are primarily focused on single-locus effects, gene-gene interactions (i.e., epistasis) are also assumed to contribute to the genetic risks for complex diseases including breast cancer. While it has been hypothesized that moderately ranked (P value based) weak single-locus effects in GWASs could potentially harbor valuable information for evaluating epistasis, we lack systematic efforts to investigate SNPs showing consistent associations with weak statistical significance across independent discovery and replication stages. The objectives of this study were i) to select SNPs showing single-locus effects with weak statistical significance for breast cancer in a GWAS and/or candidate-gene studies; ii) to replicate these SNPs in an independent set of breast cancer cases and controls; and iii) to explore their potential SNP-SNP interactions contributing to breast cancer susceptibility. A total of 17 SNPs related to DNA repair, modification and metabolism pathway genes were selected since these pathways offer a priori knowledge for potential epistatic interactions and an overall role in breast carcinogenesis. The study design included predominantly Caucasian women (2,795 cases and 4,505 controls) from Alberta, Canada. We observed two two-way SNP-SNP interactions (APEX1-rs1130409 and RPAP1-rs2297381; MLH1-rs1799977 and MDM2-rs769412) in logistic regression that conferred elevated risks for breast cancer (P interaction<7.3×10−3). Logic regression identified an interaction involving four SNPs (MBD2-rs4041245, MLH1-rs1799977, MDM2-rs769412, BRCA2-rs1799943) (P permutation = 2.4×10−3). SNPs involved in SNP-SNP interactions also showed single-locus effects with weak statistical significance, while BRCA2-rs1799943 showed stronger statistical significance (P correlation/trend = 3.2×10−4) than the others. These single-locus effects were independent of body mass index. Our results provide a framework for evaluating SNPs showing statistically weak but reproducible single-locus effects for epistatic effects contributing to disease susceptibility.

Reovirus modulates autophagy during oncolysis of multiple myeloma

Multiple myeloma (MM) is a clonal plasma cell malignancy that accounts for 10–15% of newly diagnosed hematological cancers. Although significant advances have been made in the treatment of MM the disease still remains incurable. The oncolytic potential of reovirus has previously been demonstrated by others and us and is currently in phase III clinical trials for solid tumors. In addition a phase I clinical trial has recently been initiated for MM. Despite the clinical activity, the mechanism(s) of cell death caused by reovirus in MM is yet not well elucidated. A comprehensive understanding of reovirus-mediated histology-specific cell death mechanisms is imperative if this therapeutic is to become a standard of care for patients. Previously we have shown that reovirus-mediated cell death of breast and prostate cancer is orchestrated via apoptosis. The present study demonstrates for the first time that in addition to inducing apoptosis reovirus also upregulates autophagy during oncolysis of MM.

Polynomial spline estimation of partially linear single-index proportional hazards regression models

The Cox proportional hazards (PH) model usually assumes linearity of the covariates on the log hazard function, which may be violated because linearity cannot always be guaranteed. We propose a partially linear single-index proportional hazards regression model, which can model both linear and nonlinear covariate effects on the log hazard in the proportional hazards model. We adopt a polynomial spline smoothing technique to model the structured nonparametric single-index component for the nonlinear covariate effects. This method can reduce the dimensionality of the covariates being modeled, while, at the same time, can provide efficient estimates of the covariate effects. A two-step iterative algorithm to estimate the nonparametric component and the covariate effects is used for facilitating implementation. Asymptotic properties of the estimators are derived. Monte Carlo simulation studies are presented to compare the new method with the standard Cox linear PH model and some other comparable models. A case study with clinical trial data is presented for illustration.

A validated metabolomic signature for colorectal cancer: exploration of the clinical value of metabolomics.

Background:Timely diagnosis and classification of colorectal cancer (CRC) are hindered by unsatisfactory clinical assays. Our aim was to construct a blood-based biomarker series using a single assay, suitable for CRC detection, prognostication and staging.Methods:Serum metabolomic profiles of adenoma (N=31), various stages of CRC (N=320) and healthy matched controls (N=254) were analysed by gas chromatography-mass spectrometry (GC-MS). A diagnostic model for CRC was derived by orthogonal partial least squares-discriminant analysis (OPLS-DA) on a training set, and then validated on an independent data set. Metabolomic models suitable for identifying adenoma, poor prognosis stage II CRC and discriminating various stages were generated.Results:A diagnostic signature for CRC with remarkable multivariate performance (R2Y=0.46, Q2Y=0.39) was constructed, and then validated (sensitivity 85%; specificity 86%). Area under the receiver-operating characteristic curve was 0.91 (95% CI, 0.87–0.96). Adenomas were also detectable (R2Y=0.35, Q2Y=0.26, internal AUROC=0.81, 95% CI, 0.70–0.92). Also of particular interest, we identified models that stratified stage II by prognosis, and classified cases by stage.Conclusions:Using a single assay system, a suite of CRC biomarkers based on circulating metabolites enables early detection, prognostication and preliminary staging information. External population-based studies are required to evaluate the repeatability of our findings and to assess the clinical benefits of these biomarkers.