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N. Van Zandwijk
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MS07 - Epidemiology and Prevention (ID 24)
- Event: WCLC 2013
- Type: Mini Symposia
- Track: Prevention & Epidemiology
- Presentations: 4
- Moderators:K. Park, N. Van Zandwijk
- Coordinates: 10/28/2013, 14:00 - 15:30, Bayside Auditorium B, Level 1
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MS07.1 - Successful Tobacco Control Approaches in the 21st Century (ID 486)
14:05 - 14:25 | Author(s): M.A. Steliga
- Abstract
- Presentation
Abstract
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MS07.2 - Comorbidity & Competing Causes of Death in Lung Cancer Patients (ID 487)
14:25 - 14:45 | Author(s): M. Janssen-Heijnen
- Abstract
- Presentation
Abstract
Background Over fifty percent of all newly diagnosed lung cancer patients are aged over 65 years at the time of lung cancer diagnosis, and about 30% are aged over 70. Since lung cancer is a disease that mainly occurs in elderly, and smoking is the most important risk factor [1], many patients have (smoking-related) comorbidity at the time of lung cancer diagnosis. This may complicate the management of lung cancer and may also serve as a competing cause of death. Methods An overview of literature concerning the prevalence and prognostic influence of comorbidity in lung cancer patients as well as competing causes of death. ResultsPrevalence of comorbidity Previous studies have shown that over 70% of patients suffered from at least one serious comorbid condition at the time of lung cancer diagnosis [2, 3]. The prevalence of (especially tobacco-related) comorbidity was higher among lung cancer patients as compared to patients with other major tumour types or the general population [2, 4]. The most frequent concomitant diseases among lung cancer patients were tobacco-related, such as cardiovascular diseases (25-30%), chronic obstructive pulmonary diseases (COPD, 25-30%) and previous malignancies (about 20%) [2, 3]. Prognostic influence of comorbidity Since in most cancer trials significant comorbidity is an exclusion criteria, limited information is available on the prognostic influence of comorbidity (which is important information for everyday clinical practice). Previous studies have shown that comorbidity only had a significant influence on survival in case of a localized lung tumour or in case of severe comorbidity [2, 3, 5-7]. A poorer overall survival in patients with comorbidity might be explained by death due to complications of treatment, death from cancer due to less aggressive treatment, or an increased risk of mortality due to comorbid conditions (competing causes of death). Comorbidity may increase the risk of peroperative and postoperative complications, especially those of the cardiorespiratory system [8]. A previous population-based publication has also shown that up to 75% of elderly SCLC patients receiving chemotherapy developed grade 3-5 toxicity, and two thirds of these patients receiving chemotherapy were unable to complete the treatment [9]. Elderly patients with localized non-small cell lung cancer (NSCLC) underwent less surgery than younger patients, older patients with non-localized NSCLC received less chemotherapy or chemoradiation, and elderly with small cell lung cancer (SCLC) received less chemotherapy and chemoradiation [5, 9, 10]. Competing causes of death Increased mortality due to comorbidity is probably of less importance in case of a lethal disease as non-localized NSCLC or SCLC [2, 10, 11]. Most patients probably die of lung cancer before they become at risk of dying of the comorbid condition. Previous studies have shown that 80-90% of all lung cancer patients died of lung cancer. The most common other causes of death were other tobacco-related conditions as cancers and cardiovascular causes [12-14]. Respiratory failure is the most common immediate cause of death for patients with lung cancer, probably because most of them have lung disease besides cancer and therapy for lung cancer may also add to impairment of lung function [15]. The finding that over 90% of lung cancer patients have contributing causes of death, suggests the possibility that saving a patient from one cause may only allow another disease process to become the immediate cause of death [15]. Conclusions The majority of patients with lung cancer also have serious comorbidity, especially other smoking-related diseases as cardiovascular diseases and COPD. Besides making treatment complex, comorbid conditions may also serve as competing causes of death. References 1. Doll R, Peto R, Wheatley K et al. Mortality in relation to smoking: 40 years' observations on male British doctors. Bmj 1994; 309: 901-911. 2. Piccirillo JF, Tierney RM, Costas I et al. Prognostic importance of comorbidity in a hospital-based cancer registry. Jama 2004; 291: 2441-2447. 3. Janssen-Heijnen ML, Schipper RM, Razenberg PP et al. Prevalence of co-morbidity in lung cancer patients and its relationship with treatment: a population-based study. Lung Cancer 1998; 21: 105-113. 4. Janssen-Heijnen ML, Houterman S, Lemmens VE et al. Prognostic impact of increasing age and co-morbidity in cancer patients: a population-based approach. Crit Rev Oncol Hematol 2005; 55: 231-240. 5. Luchtenborg M, Jakobsen E, Krasnik M et al. The effect of comorbidity on stage-specific survival in resected non-small cell lung cancer patients. Eur J Cancer 2012; 48: 3386-3395. 6. Jorgensen TL, Hallas J, Friis S, Herrstedt J. Comorbidity in elderly cancer patients in relation to overall and cancer-specific mortality. Br J Cancer 2012; 106: 1353-1360. 7. Birim O, Kappetein AP, Bogers AJ. Charlson comorbidity index as a predictor of long-term outcome after surgery for nonsmall cell lung cancer. Eur J Cardiothorac Surg 2005; 28: 759-762. 8. Wang S, Wong ML, Hamilton N et al. Impact of age and comorbidity on non-small-cell lung cancer treatment in older veterans. J Clin Oncol 2012; 30: 1447-1455. 9. Janssen-Heijnen ML, Maas HA, van de Schans SA et al. Chemotherapy in elderly small-cell lung cancer patients: yes we can, but should we do it? Ann Oncol 2011; 22: 821-826. 10. Janssen-Heijnen ML, Smulders S, Lemmens VE et al. Effect of comorbidity on the treatment and prognosis of elderly patients with non-small cell lung cancer. Thorax 2004; 59: 602-607. 11. Phernambucq EC, Spoelstra FO, Verbakel WF et al. Outcomes of concurrent chemoradiotherapy in patients with stage III non-small-cell lung cancer and significant comorbidity. Ann Oncol 2011; 22: 132-138. 12. Janssen-Heijnen ML, Maas HA, Siesling S et al. Treatment and survival of patients with small-cell lung cancer: small steps forward, but not for patients >80. Ann Oncol 2012; 23: 954–960. 13. Pirie K, Peto R, Reeves GK et al. The 21st century hazards of smoking and benefits of stopping: a prospective study of one million women in the UK. Lancet 2013; 381: 133-141. 14. Thun MJ, Carter BD, Feskanich D et al. 50-year trends in smoking-related mortality in the United States. N Engl J Med 2013; 368: 351-364. 15. Nichols L, Saunders R, Knollmann FD. Causes of death of patients with lung cancer. Arch Pathol Lab Med 2012; 136: 1552-1557.Only Members that have purchased this event or have registered via an access code will be able to view this content. To view this presentation, please login, select "Add to Cart" and proceed to checkout. If you would like to become a member of IASLC, please click here.
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MS07.3 - Genetic Susceptibility (ID 488)
14:45 - 15:05 | Author(s): C. Amos
- Abstract
- Presentation
Abstract not provided
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MS07.4 - Risk Prediction Models (ID 489)
15:05 - 15:25 | Author(s): M.R. Spitz
- Abstract
- Presentation
Abstract
Results from the National Lung Screening Trial (NLST) showing a 20% reduction in lung cancer mortality in the screened arm have heightened awareness of the need for reliable risk prediction tools for estimating the probability of lung cancer. A key issue of uncertainty is which smokers should be targeted for low-dose computed tomography (LDCT) screening. The NLST used 55 - 74 years, ≥30 pack-years of smoking and up to 15 years since quitting as selection criteria. 7 million U.S. adults meet these entry criteria, and an estimated 94 million U.S. adults are current or former smokers. Validated risk prediction models could improve the outcomes of screening efforts. Such models have substantial public health implications and value in clinical decision making as well. Further, risk prediction tools could be incorporated into the design of smaller, more powerful, and “smarter” prevention trials. The first lung cancer risk prediction model was developed by Bach et al. using data from the Carotene and Retinol Efficacy Trial (CARET) of 14,000 heavy smokers and over 4,000 asbestos-exposed men. Variables included in the final model were age, gender, asbestos exposure, smoking history, cigarettes per day, duration of smoking and duration of cessation. Cronin et al. externally validated the Bach model in the Alpha-Tocopherol, Beta-Carotene Cancer Prevention Study control arm (c statistic of 0.69). Spitz et al. expanded on this model adding epidemiologic and clinical data derived from an ongoing lung cancer case-control study. Their model included environmental tobacco smoke (for never and former smokers), family cancer history, asbestos and dust exposures, prior respiratory disease, history of hay fever, and smoking history variables. These variables have strong biologically plausibility and are relatively easy to ascertain through patient interview. However, the validated area under the curve (AUC) statistics for former and current smoker models were modest (0.63 and 0.58, respectively), although consistent with those from other risk prediction models. The LLP model based on data from the Liverpool Lung Project included age, sex and smoking, as well as family history of lung cancer, exposure to asbestos, prior diagnosis of pneumonia and of a malignancy other than lung cancer. Prior diagnoses of emphysema and lung cancer lost significance in the multivariate model. Young et al. developed a risk model using a 20-single nucleotide polymorphism (SNP) panel including cell-cycle control, oxidant response, apoptosis, and inflammation genes, as well as age, history of COPD, family history of lung cancer, and gender. When numeric scores were assigned to both the SNP and demographic data, and sequentially combined by a simple algorithm in a risk model, the composite score was linearly related to risk with a bimodal distribution. These data have not been well replicated. In 2011,Tammemagi published a carefully constructed risk prediction model based on data from 70,962 control subjects in the Prostate, Lung, Colorectal, Ovarian cancer screening trial (PLCO). Model 1 included age, education, body mass index (BMI), family history of lung cancer, chronic obstructive pulmonary disease (COPD), recent chest x-ray, smoking status (never, former, current), pack-years smoked, and smoking duration. Model 2 also included time in years since ever-smokers permanently quit smoking. In external validation, performed with 44,223 PLCO intervention arm participants, Models 1 and 2 had area under the curves of 0.84 and 0.78, respectively. Tammemagi and colleagues also showed that their risk prediction model for lung cancer incidence was a more sensitive indicator of pre-screening risk of developing lung cancer than were NLST eligibility criteria. Kovalchik et al. subsequently showed that 88% of LDCT-prevented lung cancer deaths occurred among the 60% of NLST participants with highest pre-screening risk, while just 1% occurred among the 20% at lowest risk. This finding reinforces the role for risk-based screening. Maisonneuve et al. incorporated lung nodule characteristics and CT diagnosed emphysema into the Bach model. Presence of nonsolid nodules (RR = 10.1), nodule size > 8 mm (RR = 9.89), and emphysema (RR = 2.36) at baseline CT were all significant predictors of subsequent lung cancers. Incorporation of these variables into the Bach model increased the predictive value of the model (c-index = 0.759). Hoggart et al used prospective data from the European EPIC cohort. Using smoking information alone gave good predictive accuracy: the AUC and 95% CI in ever smokers was 0.843 (0.810-0.875). Adding other risk factors (10 occupational/environmental exposures previously implicated with lung cancer, and SNPs at two loci identified by GWAS of lung cancer) had a negligible effect on the AUC. An extended model was constructed incorporating two markers of DNA repair capacity that have been shown in case-control analyses to be associated with increased lung cancer risk. Addition of the biomarker assays improved the sensitivity of the models over epidemiologic and clinical data alone. These in vitro lymphocyte culture assays, however, are time-consuming and require technical expertise, and are not applicable for widespread population-based implementation. Spitz et al. added 3 SNPS that were most significant in their GWAS data – rs1051730 from 15q25 and two SNPs from the 5p15.33 locus (rs2736100 and rs401681 that were not in strong LD) to the baseline model. The AUC for the baseline epidemiologic/clinical model including 1016 cases and 1111 controls (all ever smokers) was 0.59. There was evidence of a gene dosage effect with an odds ratio over threefold elevated in the highest genetic risk score (GRS) stratum. With addition of the GRS to the model, the AUC showed modest improvement, to 0.61, although this was significantly improved over the baseline model, (P< 0.001). Current lung cancer risk prediction models are hampered by a restricted number of potential predictors, generally low overall predictive performance, and methodological limitations. To date, one can argue that the Tammemagi 2013 model exhibits the highest AUC among all the prediction models. It is important to conduct additional external validations of all models in diverse populations.Only Members that have purchased this event or have registered via an access code will be able to view this content. To view this presentation, please login, select "Add to Cart" and proceed to checkout. If you would like to become a member of IASLC, please click here.
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O05 - Cancer Control (ID 130)
- Event: WCLC 2013
- Type: Oral Abstract Session
- Track: Prevention & Epidemiology
- Presentations: 8
- Moderators:N. Van Zandwijk, A. McWilliams
- Coordinates: 10/28/2013, 10:30 - 12:00, Bayside Auditorium A, Level 1
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O05.01 - The DANTE trial, a randomized study of lung cancer screening with spiral CT: 7-year results (ID 1428)
10:30 - 10:40 | Author(s): M.V. Infante, S. Cavuto, F.R. Lutman, E. Passera, G. Chiesa, G. Brambilla, E. Angeli, M. Chiarenza, G. Aranzulla, M. Andresi, V. Errico, E. Bottoni, E. Voulaz, A. Santoro, M. Alloisio
- Abstract
- Presentation
Background
The purpose of this study was to explore the effect of screening with spiral CT on lung cancer mortality in comparison with no screening in a high-risk population. Secondary endpoints were incidence, stage and resectability.Methods
Male subjects, aged 60-75, smokers of 20+ pack-years were randomized to screening with low-dose spiral CT or control. Prospective participants were pre-assessed for eligibility and randomized during a telephone interview, while formal enrolment took place at a later date. All enrolled participants underwent a structured medical interview and physical examination, a baseline, once-only chest X-ray (CXR) and sputum cytology examination. Screening-arm subjects had a LDCT upon accrual, which was repeated every year for four additional years (5 rounds), while controls had a yearly clinical review only, with further testing only if needed.Results
Between March 2001 and February 2006, 2811 subjects were pre-assessed and randomized (CT arm: 1403, control arm:1408). 20 cases of double registration and two test records have been identified in the database, and 2540 subjects actually appeared for assessment (1229 CTR arm, 1299 CT arm), of whom 2450 (1264 CT arm and 1186 Controls) were eligible and enrolled. The two study groups are comparable for age, smoking exposure, and comorbid conditions. As per inclusion criteria, all subjects are males and 99.8 % are 60 or older. As of December 2012, median follow-up was 73.1 months in the control arm and 75.5 months in the screening arm. Altogether, 152 patients were detected during active follow-up with 161 lung cancers: 92 CT-arm subjects (7.27%) versus 60 controls (5.05%), p< 0,0237. 82% of CT-arm lung cancers were detected at scheduled CT examinations, and 55% were stage I disease at the time of diagnosis compared with 27% in the Control arm. The absolute number of lung cancer cases with stage II-IV disease was virtually the same as in the control arm. Resectability rate was similar in the two groups. After linkage with population registries, vital status information is now available for 2528 subjects (99.5%). Overall, 370 subjects have died, for 104 of whom we are currently investigating mortality causes.Conclusion
While the number of participants is relatively small, smoking exposure and average age of participants are higher than in similar trials. A comparatively high number of events has been observed. To date, 28% of such events cannot yet be attributed to a specific cause. Health registry data necessary to complete mortality comparisons is expected to become available in the next few weeks. Merging of all European trials may yield robust data about this strategy in the future.Only Members that have purchased this event or have registered via an access code will be able to view this content. To view this presentation, please login, select "Add to Cart" and proceed to checkout. If you would like to become a member of IASLC, please click here.
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O05.02 - Local, Surrounding and Global Features for Improved Computer Aided Diagnosis of Lung Cancer (ID 318)
10:40 - 10:50 | Author(s): J.C. Sieren, S. Dilger
- Abstract
- Presentation
Background
The National Lung Screening Trial reported a 20% reduction in lung cancer mortality achieved through low dose computed tomography (CT) screening of the at risk population, compared to screening with chest x-ray. Challenges with clinical implementation of CT screening for lung cancer include the high number of lesions detected that require further follow-up, approximately 97% of which are ultimately diagnosed as benign. A computer-aided diagnosis (CAD) tool can be designed to determine the probability of malignancy of a lung nodule based on objective measurements. While current CAD tools examine the pulmonary nodule’s shape, density, and border, analyzing the lung parenchyma surrounding the nodule is an area that has been minimally explored. By quantifying characteristics, or features, of the surrounding tissue, this study explores the hypothesis that textural differences in both the nodule and surrounding parenchyma exist between malignant and benign cases, which can be utilized to improve CAD performance.Methods
From CT data, several novel feature extraction techniques were developed, including a three-dimensional application of Laws’ Texture Energy Measures to quantify the textures of the parenchyma as well as the nodule. In addition, the densities of the nodule and parenchyma were summarized through metrics such as mean, variance, and entropy of the intensities. The margins of the nodule were characterized following ray casting and rubber-band straightening to analyze mean and variance of border irregularity. Basic demographics and risk factor data were also included. The large feature set was reduced by statistical testing and stepwise forward selection to a few independent features that best summarize the dataset. A neural network was used to classify the cases in a leave-one-out method.Results
To illustrate proof of concept, the CAD tool was applied to 27 lung nodule cases: 10 malignant and 17 benign. These data were diverse with regards to data acquisition protocol, reconstruction kernel and slice thickness – all of which can pose challenges to CAD. Through statistical testing, 36 features were found to be significant predictors of malignancy (p < 0.05), including many textural and parenchymal features. Two of these significant features, selected through stepwise forward selection, were utilized to classify the data: nodule variance (p = 0.0003) and parenchyma median intensity (p = 0.0028). CAD performance achieved a sensitivity of 90%, specificity of 100%, and an accuracy of 96.3%.Conclusion
Preliminary findings indicate features from both the nodule and the surrounding parenchyma have value in distinguishing benign and malignant lesions. This is particularly valuable in the analysis of early detected, small pulmonary lesions (<10mm). In these small lesions, standard CAD approaches are hindered by few CT data voxels contained within the lesion. By incorporating local, surrounding and global features, more information is included and augmented CAD performance may be achieved. Finally, many significant features were identified despite diversity in the CT data acquisition parameters which indicates the suitability of the approach to broad clinical application. We are currently working on applying the CAD tool to a larger dataset.Only Members that have purchased this event or have registered via an access code will be able to view this content. To view this presentation, please login, select "Add to Cart" and proceed to checkout. If you would like to become a member of IASLC, please click here.
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O05.03 - Screening of Lung Cancer by Low-Dose CT (LDCT), Digital Tomosynthesis (DT) and Chest Radiography (CR) in a High Risk Population: A Comparison of Detection Methods (ID 3018)
10:50 - 11:00 | Author(s): N. Triphuridet, S. Singharuksa, T. Sricharunrat
- Abstract
- Presentation
Background
LDCT has recently been recommended as a screening tool for lung cancer in a high risk population, provided a 20% reduction in lung-cancer specific mortality. Nevertheless, LDCT has some limitations with respect to its high false positive rate, accumulated radiation exposure and relatively high cost. Digital tomosynthesis (DT) is a multisection imaging technique which can improve detection ability of small lung nodules and renders much lower radiation dosage and operation costs.Methods
Thai heavy smokers (>30 pack-years) were enrolled in a prospective study starting from July 2012 to April 2013 (n=580). LDCT, DT and CR were utilized as a screening tool for lung cancer screening. All participants underwent imaging studies on the same day and the results were independently reviewed within a 1-week interval. Abnormal findings were categorized into 3 groups: negative, indeterminate (maximum diameter of pulmonary nodule >5- 9.9 mm), and suspicious for malignancy (maximum diameter of pulmonary nodule > 10 mm, consolidation, obstructive atelectasis, pleural effusion or mediastinal lymphadenopathy).Results
At baseline, LDCT and DT classified 16/580 cases as suspicious for primary lung cancer while CR detected 15/580 cases. Seven cases with positive LDCT and DT findings were tissue-proven primary lung cancer including 3 - stage I cancers, 1 - stage III cancer and 3 - stage IV cancers. CR detected only 3 proven cases of primary lung cancer and all of them were stage IV cancer. The lung cancer detection rate for pulmonary nodule > 10 mm and other suspicious findings was 1.2%, 1.2%, and 0.5% by LDCT, DT, and CR, respectively. LDCT classified 67 cases as indeterminate while DT and CR classified 21 and 11 as such cases, respectively. Two additional primary lung cancer cases were detected at a 3-month follow-up LDCT of the indeterminate group by LDCT (2 cases), DT (1 case) and CR (0 case), respectively. The lung cancer detection rate for pulmonary nodule > 5 mm and other suspicious findings was 1.6%, 1.4%, and 0.5% by LDCT, DT, and CR, respectively. The positive predictive value (PPV) for pulmonary nodule >10 mm and other suspicious findings by LDCT, DT and CR was 43.8%, 43.8%, and 20.0%, respectively, while the PPV for pulmonary nodules of> 5 mm and other suspicious for malignancy findings by LDCT, DT and CR were 10.8%, 21.6%, and 11.5%, respectively. The sensitivity and specificity was 100% and 87%, respectively, for LDCT, and 88.9% and 94.9%, respectively, for DT, and 33.3% and 96%, respectively, for CR.Conclusion
DT is a lung cancer screening modality that is comparable to LDCT, particularly for pulmonary lesions that are larger than 10 mm. and other suspicious for malignancy findings while CR was far inferior to DT and LDCT.Only Members that have purchased this event or have registered via an access code will be able to view this content. To view this presentation, please login, select "Add to Cart" and proceed to checkout. If you would like to become a member of IASLC, please click here.
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O05.04 - DISCUSSANT (ID 3991)
11:00 - 11:15 | Author(s): S. Lam
- Abstract
- Presentation
Abstract not provided
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O05.05 - Biennial lung cancer screening by low-dose CT scan - a simulation of cost effectiveness in Canada (ID 2313)
11:15 - 11:25 | Author(s): J.R. Goffin, W.M. Flanagan, A.B. Miller, F.F. Liu, S. Cressman, N. Fitzgerald, S. Fung, M.C. Wolfson, W. Evans
- Abstract
- Presentation
Background
Randomized data support annual screening for lung cancer among smokers using low-dose CT scans. To compare the resource implications of annual versus biennial screening, a cost-effectiveness analysis was undertaken using the Cancer Risk Management Model (CRMM version 2.0.1) in the context of the Canadian publicly funded healthcare system.Methods
The CRMM performs simulations at an individual level and incorporates demographic data, cancer risk factors, cancer registry data, diagnostic and treatment algorithms and health utilities. Outputs are aggregated and costs (in 2008 Cdn dollars) and life-years are discounted at 3% annually. Simulations were performed with a cohort 55-74 years and a ≥30 pack-year (p-y) smoking history recruited from 2012-2032. CT scan sensitivity (Sens) and specificity (Spec) and cohort outcomes were based on NLST and Canadian data. It was assumed 60% of the eligible population participates by 10 years, 70% adhere to the screening regimen, and smoking cessation rates are unchanged. Sensitivity analysis was undertaken.Results
An annual screening program incurs net costs of $2.97 billion and saves 55,000 quality-adjusted life-years (QALYs) at an incremental cost-effectiveness ratio (ICER) of $53,700 per QALY. Under default biennial screening assumptions (Table 1, scenario 3), biennial screening costs are $1.81 billion, saving 32,000 QALYs and producing an ICER of $56,200. In the least favourable stage shift scenario (1) tested, the ICER is $275,000, whereas the most favourable shift (4) results in $49,300. Using Sens/Spec 0.90/0.73 for all scans in scenario 3 produces an ICER of $61,400, whereas changing all incidence scan Sens/Spec to 0.87/0.73 gives an ICER of $60,900. Increasing age of eligibility to 55-79 cost $2.25 billion at an ICER of $58,700 per QALY while requiring a 40 p-y smoking history reduced cost to $1.3 billion at an ICER of $49,800 per QALY. Table 1.
T0, T1 refer to the NLST stage shift at specified time, where T0 equals shift at time zero screen, T1 shift at 12 month screen. T0/T1 indicates an average. CD: the unscreened Canadian stage distribution. PS: NLST post-screening stage shift. *Represents 3[rd] year and all future odd years. **Represents 4[th] year and all future even years. Hyphens indicate years without screening.Year Stage Shift Scenario Sens/ Spec 1 2 3 4 5 0 T0 T0 T0 T0 T0 0.9/0.73 1 CD PS PS PS CD - 2 T0 T0 T0/T1 T1 T1 0.89/0.84 3* CD PS PS PS CD - 4** T0 T0 T0/T1 T1 T1 0.89/0.84 ICER $275,000 $65,000 $56,200 $49,300 $104,00 Conclusion
Compared to annual lung cancer screening, biennial screening reduces net cost but may have a similar ICER. Stage shift assumptions have a significant impact on ICER values. Minor adjustments in Sens/Spec modestly change the ICER. Widening the age range increases but increasing the p-y requirement reduces system costs.Only Members that have purchased this event or have registered via an access code will be able to view this content. To view this presentation, please login, select "Add to Cart" and proceed to checkout. If you would like to become a member of IASLC, please click here.
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O05.06 - Resource utilization and costs of screening high-risk individuals for lung cancer in Canada (ID 1520)
11:25 - 11:35 | Author(s): S. Cressman, S.J. Peacock, I. Cromwell
- Abstract
- Presentation
Background
In September 2008 the Pan-Canadian early lung detection of lung cancer study recruited 2537 current or former smokers who were determined to have a high risk of developing lung cancer. An economic analysis was conducted to estimate the potential costs and benefits of screening with the aim of knowledge translation and decision aid for provincial screening programs. An analysis of prospectively collected resource utilization and cost data is presented.Methods
Screening costs have been determined, accounting for the cost of all resources utilized to confirm true negative and false positive screen tests as well as early stage treatment costs for resources applied to obtain diagnostic confirmation of true positive and false negative results for screened individuals, treat the primary disease and any subsequent lung cancer within three years. All costs have been calculated from the Canadian public payer’s perspective. The average CT-screening cost over a fixed period of 18 months for the pan-Canadian study participants who did not have cancer was determined and compared with the phase specific costs of true positive and false negative lung cancer screening participants who had a lung cancer diagnosis proven prior to Dec. 31, 2012. The costs for early-detected lung cancer were determined and presented by diagnosis, treatment and surveillance phases of care.Results
The average cost per screened individuals who did not end up having cancer in the first two years of the study was $456 (95%CI: $385-$570) per-person. The average rate of non-invasive investigations to pursue suspicious CT findings was 49% (CI: 45%-54%); depending significantly on the follow-up protocol observed in different participating sites. The rate of invasive investigations for individuals who had true negative or false positive results was low (<0.4%) as was the rate of complication (<0.004%). 85 individuals had lung cancer detected and diagnosed prior to December 31, 2012. The average cost of screening and the subsequent diagnostic workup for the most common detected lung cancer (stage IA and IB non-small cell lung cancer) was $4,233 (95%CI: $3,643-$4,822) per person. Per-person treatment and surveillance costs are presented by stage and mode of treatment for 84 lung cancers found in the early detection study.Conclusion
This information indicates that screening costs are low on average, as are the rates of complications in the screened individuals that do not receive a cancer diagnosis in the first two years of screening. These numbers arrive while Canadian and other national healthcare systems must manage the impacts of several private, opportunistic, lung-screening clinics that are already operational. This study is sponsored by the Terry Fox Research Institute and the Canadian Partnership against CancerOnly Members that have purchased this event or have registered via an access code will be able to view this content. To view this presentation, please login, select "Add to Cart" and proceed to checkout. If you would like to become a member of IASLC, please click here.
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O05.07 - COPD-based eligibility increases lung cancer detection rate and lowers over-diagnosis in CT screening studies (ID 1721)
11:35 - 11:45 | Author(s): R.P. Young, F. Duan, R.J. Hopkins, X. Deng, C. Chiles, G.D. Gamble, C. Gatsonis, D. Aberle
- Abstract
- Presentation
Background
Based on a 20% reduction in lung cancer deaths in the CT screening arm of the National Lung Screening Trial (NLST), yearly CT screening for lung cancer is now widely recommended. Eligibility for the NLST was based on age and smoking history only. However, we and others propose that multivariate risk models of lung cancer that incorporate variables for chronic obstructive pulmonary disease (COPD), improve risk prediction for lung cancer. The aim of this study was to examine recently published CT screening studies for lung cancer and the effect of having COPD on outcome.Methods
We searched the literature for CT screening studies of lung cancer where spirometry had been done at baseline to assess the effects of spirometry-defined COPD on outcomes. We identified six studies where there was published data reporting spirometry results in lung cancer screening studies. Using this data we objectively measured outcomes stratified or pre-selected on spirometry-defined COPD.Results
By comparing outcomes in these single arm and randomized studies we found the following lung cancer detection rates were between 1.5 to 6 fold higher in current and former smokers eligible for screening with spirometry-defined COPD compared to those with no airflow limitation or normal lungs (Table 1). Only 15% of those screened had advanced stage COPD (GOLD 3-4) The proportion of eligible current or former smokers with COPD had less indolent lung cancers with long doubling times (Table 2), and Survival after surgical resection of early stage CT-detected lung cancers was no different between those with or without COPD at baseline screening. Figure 1 Figure 2Conclusion
We conclude that a COPD-centric approach to lung cancer screening offers a more efficient means of identifying lung cancer (higher lung cancer detection rate), with less over-diagnosis and comparable outcomes to screening those without COPD.Only Members that have purchased this event or have registered via an access code will be able to view this content. To view this presentation, please login, select "Add to Cart" and proceed to checkout. If you would like to become a member of IASLC, please click here.
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O05.08 - DISCUSSANT (ID 3992)
11:45 - 12:00 | Author(s): H.M. Marshall
- Abstract
- Presentation
Abstract not provided
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O24 - Cancer Control and Epidemiology III (ID 134)
- Event: WCLC 2013
- Type: Oral Abstract Session
- Track: Prevention & Epidemiology
- Presentations: 6
- Moderators:N. Van Zandwijk, P. Yang
- Coordinates: 10/29/2013, 16:15 - 17:45, Bayside 103, Level 1
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O24.01 - Lung cancer risk attributable to occupation: in a case control study in black South Africans 2001-2008 (ID 3421)
16:15 - 16:25 | Author(s): C. Nattey
- Abstract
- Presentation
Background
Worldwide, lung cancer is the leading cause of death by cancer and most common cancer among occupational related cancers. Approximately 90% of men and 60% of women. developing lung cancer are smokers. Cancer Morbidity and the increase in cancer mortality in South Africa is well documented and has been attributed to different factors, including tobacco consumption, occupational exposures, infections, changing lifestyles, ageing population and environmental pollution The International Agency for Research on Cancer (IARC) has estimated that almost 40 000 deaths from cancer (58 000 cases) occur annually in South Africa. In men the leading causes of deaths were lung cancer (comprising 16% of all cancer deaths). Environmental and occupational risk factors contribute to the burden of lung cancer, but the extent of this contribution is still unclear in most settings especially in Africa, confirmed in a review by McCormack and Schuz Estimating the attributable fraction for specific risk factors helps to assess the potential impact the preventive interventions could have on the population. The proposed study will estimate lung cancer risk attributable to the different occupations and types of workplaces in black South African population represented in the data base while controlling for smoking and domestic fuel use. Identification of the role of occupation on the risk of lung cancer may enhance the ability to prevent the disease by permitting better focused occupational health and other preventive strategies in the fight against non-communicable diseases in black South Africans. There is very limited research on cancers and occupations in Africa; hence findings will contribute to the knowledge of lung cancer in relation to occupations in South Africa.Methods
Data from the on-going Johannesburg Cancer Case-Control Study (JCCCS) of black African adult cancer patients (2001-2008) was used. Information from 579 lung cancer cases and 1120 frequency matched controls was analysed. Controls were randomly selected from cancers not known to be associated with the effects of tobacco, matched by sex and age (±5years). Usual occupation and/or workplace stated at interview were used as an indicator of occupational exposure. Odds ratios (OR) and 95% confidence intervals (CI) were estimated using unconditional logistic regression and attributable fraction (AF) by Miettinen’s formula, adjusted for smoking pack years, HIV status and domestic fuel type use.Results
The mean age of cases and controls was 56.0 and 57.1 respectively. Among men the adjusted OR for lung cancer was 3.0 (95% CI 1.4-6.4) in miners and 1.7 (95% CI 1.3-3.2) in those working in transport occupations. In women working as domestic worker (maids, child minders etc) the adjusted OR was 7.3 (95% CI 1.7-11.3) whereas working in the food & beverage industry, the adjusted OR was 4.9 (95% CI 1.4-26.8). Occupation / workplace resulted in an AF of 14% in men and 26% in women.Conclusion
Occupational risk factors for lung cancer in South Africa are gender-specific, having more impact in women than in men. Further studies are needed to assess possible specific exposures in the mining and transport industries for men, and food industry and private homes for women.Only Members that have purchased this event or have registered via an access code will be able to view this content. To view this presentation, please login, select "Add to Cart" and proceed to checkout. If you would like to become a member of IASLC, please click here.
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O24.02 - Lung cancer in South East Scotland, are we still making progress? (ID 1320)
16:25 - 16:35 | Author(s): S.C. Erridge, G. Kerr, C. Dodds, S. Campbell, J. Ironside, F. Little, M. Mackean, A. Price, J. Gysin, L. Bhatti, C. Selby
- Abstract
- Presentation
Background
South-East Scotland Cancer Network (SCAN) serves 1.4 million people using unified protocols collecting prospective data. We published population-based data from 1995 and 2002 (J Thorac Oncol. 2008;3(5):491-8) demonstrating increased cancer treatment and improved overall survival. This review investigates whether this has been sustained.Methods
Patients were identified from Scottish Cancer Registry (SCR), SCAN audit and Edinburgh Cancer Centre databases to extract tumour characteristics, initial management (usually ≤6 months of diagnosis) and overall survival (OS). Missing data was sought from patients’ health records. Multivariate analysis (MVA) examined sex, age(<60,60-69,70-79,80+), deprivation, Healthboard of residence, performance status (PS), pathology and stage (localised, regional, metastatic) affecting use of any treatment, potentially curative treatment (PCT) defined as surgery (S) or potentially curative radiotherapy (PC-RT - ≥50Gy for NSCLC or ≥40Gy+chemo for SCLC) using Cox’s proportional hazards model to obtain factors affecting survival.Results
1117 patients were identified in the audit. 51.5% were men, median age 72 (range 31-98) years. 47.3% were from the two most deprived quintiles. 49.5% had WHO PS 0-1, 23.5% WHO2, 24.2% WHO3-4. 58.5% NSCLC (23.5% Stage I-II, 25.7% III, 48.8% IV), 13% SCLC (37.9% stage I-III, 61.4 stage IV) and 28.5% radiology-only diagnosis (24.5% Stage I-II, 19.5% III, 52.8% IV). 59.9% received some form of treatment; 28.4% with PCT ((126 S+/-chemo(C) = 19% of NSCLC), 190 PC-RT +/- C), and 31.5% palliatively. 467 (41.8%) received any RT, 268 (24%) any C. MVA showed age >70, PS≥2, metastatic disease, ‘not-SCLC’, but not sex, deprivation or Healthboard, were associated (all p<0.01) with lower treatment delivery, and only age > 80, PS≥2, radiology-only diagnosis and non-localised disease (all p<0.01) with reduced PCT. Median survival was 5.03 months (95%CI 4.3-5.8) with 46.8% alive at 6 months, 32.0% 12 and 17.7% 24 months following diagnosis. Male sex, PS≥2 and non-localised disease were associated with increased HR for death (all p<0.01). Comparison with the 2002 cohort (n= 971, Dumfries excluded from both cohorts) showed similar age and pathology profile, but increased women, residents from most deprived quintile and metastatic disease. Uni-variate analysis showed a similar proportion received treatment (62.3% 2002 v. 59.9% 2010 p=0.14) but more received PCT (23.6% v. 28.2% p=0.02) principally through increased use of PC-RT (13.1% v. 17.1% p=0.01). On MVA (without PS) the use of any treatment reduced (OR 0.73 (0.59-0.92) however, use of PCT increased (OR 1.84 (1.37-2.47) due to more PC-RT (1.57 (1.18-2.08)), but not surgery. Median (5.16 v. 4.90 months p=0.65), 1 year (29.0% (31.9-26.1) v. 31.4% (34.3-28.5) and 2 year (14.9% (17.3-12.5) v. 17.4% (19.8-15.0) survival were unchanged.Conclusion
In the last 8 years in SCAN, there has been an increase in the number of women with lung cancer along with a worsening deprivation profile and increased identification of stage IV disease, possibly through improved staging. There has been an increase in potentially curative, but reduction in all therapy delivered without any apparent impact on survival. This analysis demonstrates the challenges of improving population-based outcomes in a disease where most present with advanced disease and are often unfit for treatment .Only Members that have purchased this event or have registered via an access code will be able to view this content. To view this presentation, please login, select "Add to Cart" and proceed to checkout. If you would like to become a member of IASLC, please click here.
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O24.03 - Lung cancer incidence trends among Asian-American ethnic populations in the United States, 1990-2010 (ID 1969)
16:35 - 16:45 | Author(s): S. Lin Gomez, I. Cheng, K. Gali, M.I. Patel, R. Haile, A. Noone, H. Wakelee
- Abstract
- Presentation
Background
In the United States (US), anti-smoking policies have resulted in a population-wide decline in lung cancer rates over the past decade. However, little is known about how lung cancer incidence trends vary among Asian-American ethnic populations, the largest growing population in the US.Methods
For the first time, annual population estimates for Asian-American ethnic populations were developed for the regions in the Surveillance, Epidemiology, and End Results program, comprising half of the total U.S. Asian-American population. From 1990-2010, incidence rates and average annual percentage change (APC) were computed for each racial/ethnic group for lung cancer overall and by gender and histology.Results
Among Asian-American males, trends were either stable or declining in all groups (Figure 1). The declines were statistically significant among Koreans (APC = -3.0), Hawaiians (APC = -2.3), Vietnamese (APC = -1.4), Filipino (APC = -1.9 from 1996-2010), and Chinese (APC = -1.5). Among Asian-American females, declining trends were seen among Hawaiians (APC = -5.9 from 2002-2010) and Vietnamese (APC = -1.5). In contrast, increasing trends were seen among Japanese (APC = 1.7) and Filipinas (APC = 1.5). Among Asian-American males, all histologies exhibited stable or declining trends with the exception adenocarcinoma, which increased among Chinese males from 1997-2010, appearing independent of the decrease in NOS, which occurred much later in this group. Among Asian-American females, declining or stable trends were seen for most histologies, with the exception of adenocarcinoma among Filipina and Korean females (APC = 2.5 and 3.0, respectively), and squamous cell carcinoma among Japanese females (APC = 2.4). Figure 1Conclusion
To the extent that Asian-Americans have distinct primary and second-hand smoking profiles, unique environmental exposures , and population-specific genetic predisposition, analysis of incidence trends by histology suggests that, among Asian-American females, additional risk factors beyond primary and perhaps secondary smoking may be important for lung cancer etiology. The continued increase of lung cancer incidence among Filipina, Korean, and Japanese American females, especially in adenocarcinomas and squamous cell carcinomas, warrants further attention.Only Members that have purchased this event or have registered via an access code will be able to view this content. To view this presentation, please login, select "Add to Cart" and proceed to checkout. If you would like to become a member of IASLC, please click here.
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O24.04 - Risk of second primary lung cancer (SPLC) in patients (pts) with previously treated lung cancer: Analysis of the Surveillance, Epidemiology and End Results (SEER) data (ID 2204)
16:45 - 16:55 | Author(s): A.J. Wozniak, A. Schwartz, F.D. Vigneau, R.D. Shore, M.K. Islam, S. Gadgeel
- Abstract
- Presentation
Background
BACKGROUND: Second primary lung cancer (SPLC) in patients who have been treated for a prior lung cancer is a recognized phenomenon. There has been an improvement in the staging and treatment of lung cancer in the last several decades resulting in longer survival for pts and affording an opportunity for the development of SPLCs. The objective of this study was to establish the frequency of SPLCs and to characterize the demographics, histology and stage at presentation, time interval between diagnoses, and cumulative risks of developing a SPLC in this pt population.Methods
METHODS: The pts were identified from population-based SEER-9 Registries Data Base. All pts with a primary lung cancer between 1973 and 2004 were included with follow-up to 2009. The histology and stage of the SPLCs were evaluated in comparison to the initial primary lung cancer (IPLC). The incidence of SPLCs was compared to the expected incidence by calculating multiple primary-standardized incidence ratios (MP-SIRs) using the SEER Stat program. Selected cohorts were stratified by sex, race, age at diagnosis, and date of diagnosis. Sex-specific cumulative risks of developing SPLCs were calculated using the Kaplan-Meier method.Results
RESULTS: 208,486 pts had an IPLC diagnosed from 1973-2004. No smoking history was available. Patient Characteristics at time of IPLC: 60.4% male; 84.3% white; 8.5% (20-49 yr), 55.9% (50-69 yr), 35.6% (≥ 70 yr); 84% non-small cell lung cancer (NSCLC); 33.8% distant disease, 23.5% regional, 29.9% local. 5,302 pts developed SPLC. The majority were male (56.6%), white (84.9%), and in the 50-69 yr age group (68%). Females had the highest SIR values across all ethnicities and age groups particularly in the youngest cohort (20-49 yr) where the SIR was 8.58. The SIR values were ≥ 2 for all cohorts expect for males ≥ 70 yr (SIR=1.65). The predominant histologic types for IPLCs were adenocarcinoma (ADC) and squamous cell cancer and the associated SPLCs were usually of the same histology. IPLC ADC and BAC pts were most likely to develop a SPLC. Most SPLCs (50%) presented with regional or distant disease, while only 37% were localized at diagnosis. The median time to development of SPLCs was 68 mo for males and 74 mo for females. The risk of developing a SPLC continually increased as a function of time for both sexes.Conclusion
CONCLUSION: Patients with a history of IPLC are at high risk for developing SPLC and this risk increases over time. This is especially true of females who are diagnosed at an early age with their initial lung cancer. The majority of SPLCs present late and at a more advanced stage. These findings could have major implications with regard to the length and type of surveillance in pts who survive their initial lung cancer diagnosis.Only Members that have purchased this event or have registered via an access code will be able to view this content. To view this presentation, please login, select "Add to Cart" and proceed to checkout. If you would like to become a member of IASLC, please click here.
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O24.05 - The impact of body mass index on survival in stage 3 and 4 lung cancer (ID 663)
16:55 - 17:05 | Author(s): K.M. Wong, S. Cuffe, L. Coate, O. Espin-Garcia, K. Boyd, R. Feld, N. Leighl, F.A. Shepherd, W. Xu, G. Liu
- Abstract
- Presentation
Background
Obesity has been shown to be an adverse prognostic factor in several cancers, including breast, colorectal, endometrial, ovarian, pancreatic and prostate. However, studies of body mass index (BMI) and outcomes in lung cancer are lacking. Understanding the clinical impact of body weight on cancer outcomes is important given the high prevalence of obesity globally. We retrospectively evaluated the distribution of BMI at diagnosis and its effects on survival in stage 3 and 4 lung cancer patients.Methods
1,121 patients with stage 3 or 4 lung cancer from a single institution were analyzed. Clinicopathologic data were collected retrospectively. Adjusted hazard ratios (aHR) for overall survival (OS) and progression-free survival (PFS) were generated by Cox regression for each BMI (kg/m[2]) category (underweight: <18.5, normal: 18.5-24.9, overweight: 25.0-29.9, obese: ≥30), after adjusting for age, gender, Charlson Comorbidity Index, performance status (PS), clinical stage and treatment regimen.Results
In this cohort (n=1,121), the frequencies of stage 3A, 3B and 4 lung cancers were 35%, 32% and 33%, respectively. There were 633 (57%) adenocarcinomas, 238 (21%) squamous cell carcinomas, 38 (3%) small cell lung cancers, and 210 (19%) other histologies. Patients had variable BMI: 82 (7%) underweight, 550 (49%) normal weight, 333 (30%) overweight, 156 (14%) obese. Being overweight/obese was associated with older age (p=0.002) and stage 3A disease (p=0.001); underweight patients were more likely current smokers (p<0.001). OS was significantly decreased with age ≥65, males, PS 2-3, stage 4, and lack of systemic treatment (p<0.001). Median OS in underweight, normal weight, overweight and obese patients were 14, 23, 24 and 26 months, respectively. Compared with BMI ≥18.5, being underweight was associated with significantly poorer OS (aHR 1.33, 95% CI 1.01-1.77, p=0.045), but not PFS (aHR 1.12, 95% CI 0.86-1.46, p=0.414). The magnitude of this association was greatest among those aged less than 65 years (aHR 1.57, 95% CI 1.11-2.22, p=0.011).Conclusion
In stage 3 and 4 lung cancer, being underweight at diagnosis is associated with significantly poorer OS, especially in patients younger than 65 years of age. Lower BMI is mostly observed in current smokers, while above normal BMI is seen in older patients and stage 3A disease. Unlike other malignancies, obesity does not increase mortality in this population. The BMI-survival relationship in lung cancer requires further study.Only Members that have purchased this event or have registered via an access code will be able to view this content. To view this presentation, please login, select "Add to Cart" and proceed to checkout. If you would like to become a member of IASLC, please click here.
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O24.06 - DISCUSSANT (ID 4001)
17:05 - 17:20 | Author(s): I.N. Olver
- Abstract
- Presentation
Abstract not provided
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Author of
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P2.06 - Poster Session 2 - Prognostic and Predictive Biomarkers (ID 165)
- Event: WCLC 2013
- Type: Poster Session
- Track: Biology
- Presentations: 1
- Moderators:
- Coordinates: 10/29/2013, 09:30 - 16:30, Exhibit Hall, Ground Level
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P2.06-015 - Novel plasma proteins associated with prognosis in malignant pleural mesothelioma (ID 1337)
09:30 - 09:30 | Author(s): N. Van Zandwijk
- Abstract
Background
The search for novel biomarkers to define more successful and individual treatment approaches represent an important challenge for those involved in the care for patients with malignant pleural mesothelioma (MPM). In this exploratory study, we have systematically investigated the proteins present in plasma of MPM patients and correlated their levels with disease outcomes.Methods
Plasma samples from twelve MPM patients (6 ‘short-’ and 6 ‘long-term’ survivors from parallel phase II studies investigating thalidomide) were used for proteomic analyses. Our series included samples from 9 patients with epithelial MPM and 3 patients with biphasic MPM. Plasma samples were immuno-depleted of the 14 most abundant proteins prior to labelling for isobaric tag for relative and absolute quantitation (iTRAQ) analysis using mass spectrometry. The most promising candidates and mesothelin were chosen for selected reaction monitoring mass spectroscopy (SRM-MS) quantification and enzyme-linked immunosorbent assay (ELISA) validation. Statistical analyses using T-Test of peak areas were used to identify proteins that were differentially expressed between the short- and long-term survivor groups.Results
Median survival of short- and long-term survivors (1.2 and 38.3 months, respectively) differed significantly (p = 0.001). This was also the case for the neutrophil-to-lymphocyte ratio (NLR) that was significantly higher in the group of short-term survivors (p=0.03). Other baseline characteristics did not reveal major differences between the short- and long-term survivors. The total number of proteins identified was 226 (1% false discovery rate) in iTRAQ. A number of those were found to be differentially expressed between short- and long-term survivors (≥1.2-fold change; p≤0.05) by iTRAQ: selenoprotein P; tetranectin; insulin-like growth factor-binding protein 2 (IBP2); osteonectin (SPARC); platelet basic protein (CXCL7); and attractin. Mesothelin was assessed to validate the proteomic methodology: SRM-MS quantification was highly correlated with the MESOMARK ELISA values with a Pearson correlation of 0.82 (p=0.001). SRM-MS quantification revealed that the concentrations of attractin (p=0.02), tetranectin (p=0.003) and selenoprotein P (p=0.001) were higher in long-term survivors. In contrast, there was a trend for an increase in the concentration of SPARC (p=0.32), IBP2 (p=0.12) and CXCL7 (p=0.19) to be correlated with shorter survival. Furthermore, quantification by ELISA demonstrated an association between long survival and low concentration of SPARC (p=0.07) as well as high tetranectin (p=0.13).Conclusion
We have demonstrated the feasibility of using the iTRAQ and SRM-MS proteomic techniques to investigate potential prognostic protein markers in plasma of MPM patients. Potential prognostic biomarkers worthy of further studies include SPARC and tetranectin and we plan to validate these in a larger clinical cohort.
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P3.01 - Poster Session 3 - Cancer Biology (ID 147)
- Event: WCLC 2013
- Type: Poster Session
- Track: Biology
- Presentations: 1
- Moderators:
- Coordinates: 10/30/2013, 09:30 - 16:30, Exhibit Hall, Ground Level
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P3.01-019 - Analysis of Integrins in Malignant Mesothelioma (MM). (ID 1147)
09:30 - 09:30 | Author(s): N. Van Zandwijk
- Abstract
Background
Malignant mesothelioma (MM), strongly associated with exposure to asbestos, is a growing worldwide problem (1). This aggressive tumour is largely resistant to oncological treatments and new approaches to therapy are urgently needed. Integrins are a class of adhesion molecules composed of an α and a β chain. Combinations of 18 α and 8 β subunits form the 24 members of the integrin family. The αv subunit can dimerize with β1, β3, β5, β6 and β8. Aberrant expression of αv integrins was reported in MM, and the integrins αv β3 and αv β5 have been implicated in tumour progression and metastasis. We have investigated the expression and function of αv integrins in MM cell lines and the effect of gene knockdown on cell invasion.Methods
Expression of the integrin (ITG) genes was analysed by qPCR in 7 MM cell lines. Expression of the heterodimers was determined by Western blot, immunofluorescence and immunocytometry (monoclonal antibodies kindly provided by Simon Goodman, 2). In addition, we knocked down the genes potentially involved in tumour progression (ITGB3 and ITGB5) and analysed the in vitro 2D and 3D invasiveness with an agarose spot invasion assay (3) and MM spheroids.Results
All 7 MM cell lines showed high ITGB1 expression, moderate ITGB5 expression, and a general low ITGB6 and ITGB8 expression. ITGB3 was expressed in one cell line, which accordingly had high αv β3 expression. ITGB3 knockdown of this cell line resulted in suppression of invasion both in 2D and 3D cultures.Conclusion
We have found evidence that integrin αv β3 may play a role in MM invasion. Presently, we are testing cilengitide, a peptide antagonist of integrin αv, in MM cell lines. References: 1. Delgermaa F, Takahashi K, Park EK, Le GV, Hara T, Sorahan T. Global mesothelioma deaths reported to the World Health Organization between 1994 and 2008. Bull World Health Organ. 2011, 89:716-724. 2. Goodman SL, Grote HJ, Wilm C. Matched rabbit monoclonal antibodies against αv-series integrins reveal a novel αvβ3-LIBS epitope, and permit routine staining of archival paraffin samples of human tumors. Biol Open. 2012, 1:329-340. 3. Wiggins H and Rappoport J. An agarose spot assay for chemotactic invasion. Biotechniques. 2010, 48:121-124.
