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Luis M Seijo

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    MS18 - Role of Biomarkers in Lung Cancer Screening (ID 81)

    • Event: WCLC 2019
    • Type: Mini Symposium
    • Track: Screening and Early Detection
    • Presentations: 6
    • Now Available
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      MS18.01 - Exhaled Breath Biomarkers (Now Available) (ID 3544)

      14:30 - 16:00  |  Presenting Author(s): Nir Peled

      • Abstract
      • Presentation
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      Abstract

      The evoloving field of early detection of lung cancer is being implemented around the globe. Low Dose CT scans are standard of care in all guidelines, however real world implementation is stil lacking.

      Biomarker to support early detection is the current UNMET need, as well as non-invasive biomarkers to follow early disease recurrence and monitoring response to therapy.

      The exhaled breath approach is a growing field of interest, where several groups have contributed significant abount of data. There are numerous technologies available while clinical validation is varies between groups.

      This talk will score the current knoledge associated with the exhaled breath analysis associated with lung cancer. Surprizingly, the volatille signature is associated with disesae existance, disesae burden, response to therapy, disease profile and even the related mutatoins.

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      MS18.02 - Circulating Nucleic Acid Biomarkers (Now Available) (ID 3545)

      14:30 - 16:00  |  Presenting Author(s): Gabriella Sozzi  |  Author(s): Mattia Boeri, Ugo Pastorino

      • Abstract
      • Presentation
      • Slides

      Abstract

      Encouraging results in lung cancer (LC) mortality reduction were obtained by the introduction of low dose computed tomography (LDCT) for lung cancer screening. The results of Nelson screening trial showed a 26% reduction in lung cancer mortality in the LDCT arm thus confirming the benefit of LC screening with LDCT already published by the NLST group (1).

      In MILD trial we showed that at 10 years follow up the mortality reduction was even higher (-39%) proving that extended LDCT screening is effective in reducing lung cancer mortality (2).

      Nonetheless, the development of non-invasive complementary biomarkers could be helpful to improve the efficacy of LDCT screening by improving LC risk prediction and defining personalised LDCT screening intervals as well as to decrease false positives identified by LDCT and monitor disease evolution in patients after curative resection.

      The value of circulating tumor DNA (ctDNA) as a biomarker in advanced tumor stages is well established. However, its role in early lung cancer detection is still uncertain. The biggest technical challenge is sensitivity. Current efforts to develop next-generation sequencing (NGS) technologies to study ctDNA in the context of early detection might improve sensitivity in this context.

      The scientific community is awaiting the results of the Circulating Cell-free Genome Atlas (CCGA) Study for early cancer detection, enrolling 15,000 participants in the United States and Canada. Plasma samples collected at baseline and during 5 years of follow-up will be analyzed by whole genome sequencing(WGS) for copy number variation(CNV), targeted DNA sequencing (a 507-gene panel), and whole genome methylome profiling. Preliminary results in an observational case-control setting include 95% specificity, high sensitivity for advanced lung cancer in 54 patients (85% for targeted sequencing, 91% for CNV WGS, and 93% for methylome profiling), and modest sensitivity for 63 patients with stage I to III lung cancer (48% for targeted NGS, 54% for CNV WGS, and 56% for methylome profiling)(3). Therefore, the generalizability of these findings to the screening setting is uncertain.

      In order to implement lung cancer screening programs, we focused on circulating microRNAs which may reflect the contribution not only of the tumor but also of its microenvironment and the host. We developed a plasma miRNA Classifier (MSC) composed of 24 miRNAs which showed high performance in terms of sensitivity (87%) and specificity (81%) in 940 subjects enrolled in the MILD screening trial. The classifier was able to identify, in longitudinal plasma samples of the patients, a risk profile to develop LC up to two years before a significant tumor burden was visible at LDCT(4). These results prompted us to launch in 2013 a prospective screening trial, called bioMILD, to test the efficacy of a combined LDCT-MSC approach as forefront screening tests in a large cohort of 4119 smokers, 50 yrs or older. We succesfully completed the baseline of all the volunteers and executed a LDCT in 11,012 and miRNA test in 9,156 subjects. BioMILD has now reached the 3 yrs follow up for all subjects and 4.2 year median follow up for the all cohort. Analyses of the results are ongoing and will be presented.

      Concerning the origin of the 24 miRNA, since the classifier was able to identify a risk profile to develop lung cancer up to two years before the radiological diagnosis, we hypothesized that that such circulating miRNAs could be released not merely by cancer cells but rather by the damaged lung microenvironment and the host response that may sustain tumor development. Using in vitro models and clinical samples we showed that c-miRNAs originated mostly from blood cells, with activated neutrophils showing modulation of the 24 miRNAs overlapping that observed in plasma of MSC positive subjects(5).

      The role of immunity in modulating the risk of disease development remains to be elucidated, while it could have enormous impact in terms of prevention and early intervention. Therefore we characterized peripheral blood immune cell profiles as possible complementary biomarkers for risk assessment and analyzed their relationship with MSC. In a case control study of 40 lung cancer patients and 20 controls we found immune cell subpopulations differentially expressed between screening detected lung cancer patients and controls. Of interest an MSC high risk profile in patients was associated with specific circulating immune cell subsets including higher numbers of exausted T cells and monocytes/MDSC and lower cytotoxic T and NK cells. These findings suggest that MSC high risk profile might reflect an immunosuppressive status and prompted us to study the possible utility of MSC in lung cancer immunotherapy settings. Using a prospective cohort of 140 consecutive advanced NSCLC patients treated with immune checkpoints inhibitors we found that MSC either alone or in combination with PD-L1 expression in the tumor was associated with patients survival(6). Therefore, plasma MSC, reflecting an impaired tumor immune contexture, could supplement PD-L1 tumor expression to identify a subgroup of patients who do not benefit from immunotherapy.

      References:

      D.R. Aberle, A.M. Adams, C.D. Berg, et al.Reduced lung-cancer mortality with low-dose computed tomographic screening. N Engl J Med, 365 (2011), pp. 395-409

      Pastorino U, Silva M, Sestini S. et al. Prolonged Lung Cancer Screening Reduced 10-year Mortality in the MILD Trial. Ann Oncol. 2019 Apr 1.

      GR. Oxnard T. Maddala E. Hubbell et al. Genome-widesequencing for early stage lung cancer detection fromplasma cell-free DNA (cfDNA): the Circulating CancerGenome Atlas (CCGA) study. Paper presented at: 2018 American Society of Clinical Oncology Annual Meeting.June 1–5, 2018; Chicago, IL

      Sozzi G, Boeri M, Rossi M.et al. Clinical Utility of a Plasma-based microRNA Signature Classifier within Computed Tomography Lung Cancer Screening: A Correlative MILD Trial Study. J Clin Oncol. 2014 Mar 10;32(8):768-73.

      Fortunato O, Borzi C, Milione M, et al.Circulating mir-320a promotes immunosuppressive macrophages M2 phenotype associated with lung cancer risk. Int J Cancer. 2019 Jun 1;144(11):2746-2761. doi: 10.1002/ijc.31988. Epub 2019 Jan 6.

      Boeri M, Milione M, Proto C. et al. Circulating miRNAs and PD-L1 Tumor Expression Are Associated with Survival in Advanced NSCLC Patients Treated with Immunotherapy: a Prospective Study. Clin Cancer Res. 2019 Apr 1;25(7):2166-2173. doi: 10.1158/1078-0432.CCR-18-1981. Epub 2019 Jan 7.

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      MS18.03 - Amolecular Diagnostics, Incorporating GWAS and Risk Models: Future Approaches to the Identification of High-Risk Individuals (Now Available) (ID 3546)

      14:30 - 16:00  |  Presenting Author(s): Paul Brennan  |  Author(s): Christopher Ian Amos

      • Abstract
      • Presentation
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      Abstract

      Role of Biomarkers in Lung Cancer Screening

      As a part of ongoing research to understand the etiology and early detection of lung cancer, the Integrative Analysis of Lung Cancer Etiology and Risk (INTEGRAL) consortium has been genotyping large numbers of lung cancer cases and controls and analyzing biomarkers from case cohort members prior to their diagnosis with lung cancer and matched controls. We are also assembling knowledge about predictors of lung cancer risk to identify biomarkers that will be applied along with radiomic features to select individuals at highest risk for lung cancer to enroll in screening studies and to assist in resolution of cancer risk among those found to have small nodules. To date we have analyzed genetic data from 29,266 patients and 56,450 controls of European descent(1) and curated genotyping information from 20 studies conducted in European descent, 14 from Asian descent and 1 study in African-American Populations(2). Ongoing imputation is allowing us to integrate most of these data for a further analysis that brings together world populations for genetic discovery. Results of these studies have identified 12 strongly replicated loci and an additional 38 loci that are highly significant in some studies but less well replicated. Among the variants that we identified, a variant in BRCA2 (1) is remarkable for conferring over 2 fold increased risk for lung cancer development independent of smoking behavior and thereby indicating a small subset of high risk individuals based on genotype. Further studies to identify rare variants that confer a high risk of lung cancer have identified mutations in ATM and KIAA0930 with odds ratios well over 2. The ATM variant is associated with loss of heterozygosity in tumors but does not cause Ataxia Telangiectasia in homozygotes. We have used genetic information to develop polygenic risk scores and a model that included 221 variants yielded the most improvement in accuracy. Results comparing models to identify individuals at high risk for lung cancer development based on risk scores compared with models based on demographic, clinical and smoking information show a modest increase in prediction accuracy, but identify selected individuals who are at high risk and for whom lung screening would be particularly indicated.

      The genetic information we have developed and curated can also be used with additional approaches to identify predictors of lung cancer risk using shared heritability and Mendelian randomization analyses. Shared heritability analysis identifies strong genetic correlations with all measures of smoking behavior and also with primary biliary cirrhosis and schizophrenia. Mendelian randomization, which removes concerns about change in BMI during cancer development, shows that increased BMI is associated with squamous and small cell lung cancer and not associated with adenocarcinoma(3). Mendelian randomization studies found association of increased lung cancer risk with longer germline telomere length and increased risk associated with higher levels of vitamin B12(4). Further Mendelian randomization studies are underway to evaluate other biochemical factors that may associate with increased lung cancer risk.

      Cohort studies to identify biomarker signatures of risk have identified a reliable panel(5) comprising CEA125, CEA, CYFRA 21-1 and pro-SFTB that along with smoking behavior provide an area under the receiver operator curve of 83%, indicating that a strategy that seeks to identify high risk individuals using data from questionnaires about smoking along with biomarker analysis could substantially improve the yield of low dose spiral CT screening. Further studies of panels of biomarkers including microRNA and circulating cell-free DNA are underway to evaluate the utility of adding additional biomarkers to further identify higher risk individuals.

      1. McKay JD, et al. (2017) Large-scale association analysis identifies new lung cancer susceptibility loci and heterogeneity in genetic susceptibility across histological subtypes. Nature genetics 49(7):1126-1132.

      2. Bosse Y & Amos CI (2018) A Decade of GWAS Results in Lung Cancer. Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology 27(4):363-379.

      3. Carreras-Torres R, et al. (2017) Obesity, metabolic factors and risk of different histological types of lung cancer: A Mendelian randomization study. PloS one 12(6):e0177875.

      4. Fanidi A, et al. (2018) Is high vitamin B12 status a cause of lung cancer? International journal of cancer. Journal international du cancer.

      5. Integrative Analysis of Lung Cancer E, et al. (2018) Assessment of Lung Cancer Risk on the Basis of a Biomarker Panel of Circulating Proteins. JAMA oncology 4(10):e182078.

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      MS18.04 - Alternative and Promising Biomarkers (Now Available) (ID 3547)

      14:30 - 16:00  |  Presenting Author(s): Ruben Pio

      • Abstract
      • Presentation
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      Abstract

      Randomized controlled trials have demonstrated that lung cancer screening with low-dose computed tomography (LDCT) in subjects at risk is associated with a decrease in mortality (1-3). However, concerns regarding false positive findings, overdiagnosis, or selection criteria may limit their implementation and sustainability. The use of molecular biomarkers that help to overcome some of these limitations offers great potential. Biomarkers should be non-invasive, reproducible and improve the current standard of care for their intended use. Biomarkers could complement image-based screening in two different ways. First, they may allow refinement of screening selection criteria, independent of age and smoking habits, reducing the numbers of individuals exposed to screening and follow-up interventions. Worldwide collaborative efforts have been implemented to gain insights into the association between SNPs and common cancers (4). Lung cancer-associated single nucleotide polymorphisms (SNPs) identified in these studies may be integrated in risk models to limit the costs of lung cancer screening. Secondly, the combination of radiological findings with molecular biomarkers may facilitate the management of indeterminate pulmonary nodules (IPNs). The implementation of LDCT screening programs is rapidly increasing the detection of IPNs, which too often leads to unnecessary follow-up CTs, or even invasive procedures. Molecular markers may help to differentiate patients with malignant IPNs from the larger number of subjects with benign nodules.

      At present, no molecular biomarker of lung cancer is being used in routine clinical practice. The tremendous research efforts regarding the development and use of molecular biomarkers in lung cancer screening have recently been reviewed (5). Biomarkers can derive from cancer cells, the tumor microenvironment, or the immune response to cancer. They can be sampled from many different bodily sources, including whole blood, serum, plasma, airway epithelium, sputum, exhaled breath, or urine. Promising molecular candidates include proteins (e.g. cancer-associated antigens, autoantibodies or other immune-related markers), metabolites, microRNAs, epigenetic markers, DNA mutations or RNA signatures. Markers of this kind are at different phases of development, ranging from their analytical validation to the evaluation of their performance in the intended use population. Ultimately, evaluation of the biomarker in real clinical settings will determine its improvement of current standards and cost. Few biomarkers have reached the clinical testing phase. The application of an RNA-based signature in bronchial epithelial cell samples from the AEGIS-1 and AEGIS-2 prospective multicenter observational trials (NCT01309087 and NCT00746759) improved the diagnostic performance of bronchoscopy for the detection of lung cancer (6). In PANOPTIC (NCT01752114), a prospective multicenter observational study, plasma levels of two proteins, LG3BP and C163A, were used to discriminate benign from malignant nodules (7). The bioMILD study (NCT02247453) is prospectively evaluating the efficacy of a plasma microRNA profiling as a first line-screening test for lung cancer detection. The clinical utility of another microRNA-based signature is been validated in blood samples prospectively collected in the COSMOS-II lung cancer screening trial (8). ECLS (NCT01700257) is a randomized study aimed to assess the clinical and cost effectiveness of a test that measures a panel of seven tumor-associated autoantibodies in blood (9). The study has reached its 12,000-participant target, and initial results are expected soon. The DECAMP consortium is conducting two multicenter prospective observational trials (NCT01785342 and NCT02504697) designed to develop an integrated panel of airway and blood-based molecular markers. DECAMP-1 seeks to improve the discrimination between benign and malignant IPNs, whereas DECAMP-2 will test biomarkers to predict the development of lung cancer in screened asymptomatic high-risk individuals. Novel approaches to overcome sensitivity/specificity limitations are also being tested. Host responses to cancer based on activation of the immune system have proved to provide promising diagnostic and prognostic markers applicable in the context of lung cancer screening (10). A diagnostic signature based on the combined determination of complement-activation fragments and cancer-associated proteins has shown a notable capacity to discriminate those patients with malignant IPNs. Next-generation sequencing technologies are also starting to be applied. The CCGA study (NCT02889978) has recently concluded the enrollment of 15,000 participants (more than 10,000 of them with a diagnosis of cancer) from whom longitudinal plasma samples are being collected and analyzed by DNA sequencing and methylation profiling. This study will provide valuable information about the potential application of deep sequencing technologies in circulating cell-free DNA for the early detection of lung cancer. Finally, deep learning approaches will allow the integration of several levels of information (e.g. radiographic features, clinical characteristics and molecular biomarkers) for the generation of more accurate predictive models.

      In conclusion, molecular biomarkers are potentially useful adjuncts to LDCT screening for lung cancer, either by refining risk prior to LDCT or by assessing malignancy. A remarkable amount of discovery and clinical validation work is ongoing. However, more evidence is still needed to support the implementation of any of the proposed biomarkers in the routine clinical practice. Further development of emerging biomarkers, new technological and integrated approaches, better metrics of clinical utility, and innovative trial designs will be required to speed up the development of lung cancer early detection biomarkers.

      References:

      1. Aberle DR et al. N Engl J Med 2011; 365: 395-409.

      2. De Koning HJ et al. IASLC 19th WCLC 2018; Abstract PL02.05.

      3. Pastorino U et al. Ann Oncol 2019 [Epub ahead of print].

      4. McKay et al. Nat Genet 2017; 49: 1126-1132.

      5. Seijo et al. J Thorac Oncol 2019; 14: 343-357.

      6. Silvestri GA et al. N Engl J Med 2015; 373: 243-251.

      7. Silvestri GA et al. Chest 2018; 154: 491-500.

      8. Marzi M et al. Clin Chem 2016; 62: 743-754.

      9. Sullivan FM et al. BMC Cancer 2017; 17: 187.

      10. Ajona D et al. J Natl Cancer Inst 2013; 105: 1385-1393.

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      MS18.05 - Sputum Biomarkers, Dysplasia and Chemoprevention (Now Available) (ID 3548)

      14:30 - 16:00  |  Presenting Author(s): Robert L. Keith

      • Abstract
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      Abstract

      The most dramatic improvements in lung cancer survival will emerge from both early detection and the prevention of disease development. Low dose CT screening trials (NLST and NELSON) have shown significant improvements in survival and advances in lung cancer screening will rely on our ability to better define at risk populations and to more personalize the management of indeterminate pulmonary nodules. This includes identifying and validating biomarkers of risk. The NIH defines biomarkers as ‘characteristics that are objectively measured and evaluated as indicators of normal biologic processes, pathologic processes, or pharmacologic responses to therapeutic interventions’1. The ideal biomarker has excellent sensitivity and specificity and applications to lung cancer screening will mostly focus on two specific areas. The first is improving the selection of at-risk subjects to be screened, and the second is to guide the management of screening detected pulmonary nodules.

      Biomarkers of lung cancer risk can include a variety of potential biospecimens, ranging from sputum and exhaled breath condensates to endobronchial and peripheral lung biopsies. Expectorated sputum has long been viewed as a ‘window to the central airways’ and cytologic changes have been observed in sputum samples to predict the presence of lung cancer2. While sputum cytology can also predict the presence of pre-malignant central airway lesions, sputum collection has largely fallen out of favor due to perceived difficulties in collecting and interpreting specimens, and advances in analyzing other specimens like blood, urine and exhaled breath. Sputum is a readily available resource, and recent methodological advances, most notably automated 3-dimensional morphologic analysis of sputum3, are currently being studied to determine the presence of cancer or pre-malignant lesions. It may also help risk stratify subjects with suspicious LDCT findings. Additional studies have also focused on sputum samples. For example, selected gene promoter methylation in exfoliated cells from sputum has been shown to predict cancer up to 18 months prior to diagnosis4. Other groups have examined sputum miRNA, and their stability make them potentially attractive biomarkers. One study conducted qRT-PCR studies of sputum from subjects with indeterminate pulmonary nodules and found a panel of 3 miRNAs (miRs 21, 31, and 210) with good sensitivity and specificity for identifying malignant nodules5. More recently, a pilot study using metagenetic sequencing of the sputum microbiome suggests there may be bacterial biomarkers indicating the presence of lung cancer6. Exhaled breath condensate is an additional biospecimen that has been studied as an adjunct to screening protocols, and the subject is extensively reviewed in a recent publication7.

      For NSCLC, specific pre-malignant histologic lesions have been used as biomarkers of risk and modifiable endpoints in chemoprevention trials. For adenocarcinoma, atypical adenomatous hyperplasia (AAH, a lesion more commonly found now that more ground glass opacities are noted during LDCT screening) can progress to adenocarcinoma in situ and eventually adenocarcinoma. Multiple studies are currently profiling AAH lesions with a goal of better understanding those that progress to invasive cancer. Lung squamous cell carcinoma (SCC) develops in the central airways where pre-malignant lesions progress through advancing levels of dysplasia (mild, moderate, and severe), followed by carcinoma in situ and ultimately invasive SCC. Change in endobronchial histology has been the primary endpoint in multiple SCC chemoprevention trials8, and longitudinal research has revealed an increased cancer risk in subjects with multiple lesions that persist or progress over time9. Endobronchial dysplasia that regresses (i.e. fails to become invasive cancer) is associated with specific immune responses and ongoing studies are characterizing the lesional immune microenvironment of bronchial dysplasia. This will allow for a better understanding of progressive lesions and advance the field of precision chemoprevention.

      1. Biomarkers and surrogate endpoints: preferred definitions and conceptual framework. Clinical pharmacology and therapeutics 2001;69:89-95.

      2. Saccomanno G, Archer VE, Auerbach O, Saunders RP, Brennan LM. Development of carcinoma of the lung as reflected in exfoliated cells. Cancer 1974;33:256-70.

      3. Wilbur DC, Meyer MG, Presley C, et al. Automated 3-dimensional morphologic analysis of sputum specimens for lung cancer detection: Performance characteristics support use in lung cancer screening. Cancer cytopathology 2015;123:548-56.

      4. Leng S, Do K, Yingling CM, et al. Defining a gene promoter methylation signature in sputum for lung cancer risk assessment. Clin Cancer Res 2012.

      5. Xing L, Su J, Guarnera MA, et al. Sputum microRNA biomarkers for identifying lung cancer in indeterminate solitary pulmonary nodules. Clinical cancer research : an official journal of the American Association for Cancer Research 2015;21:484-9.

      6. Cameron SJS, Lewis KE, Huws SA, et al. A pilot study using metagenomic sequencing of the sputum microbiome suggests potential bacterial biomarkers for lung cancer. PloS one 2017;12:e0177062.

      7. Marzorati D, Mainardi L, Sedda G, Gasparri R, Spaggiari L, Cerveri P. A review of exhaled breath: a key role in lung cancer diagnosis. Journal of breath research 2019;13:034001.

      8. Keith RL, Miller YE. Lung cancer chemoprevention: current status and future prospects. Nat Rev Clin Oncol 2013;10:334-43.

      9. Merrick DT, Gao D, Miller YE, et al. Persistence of Bronchial Dysplasia Is Associated with Development of Invasive Squamous Cell Carcinoma. Cancer Prev Res (Phila) 2016;9:96-104.

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      MS18.06 - Captive Audience, Teachable Moment - Integrating Tobacco Cessation in Lung Cancer Screening (Now Available) (ID 3549)

      14:30 - 16:00  |  Presenting Author(s): Martin Tammemagi

      • Abstract
      • Presentation
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      Abstract

      Cigarette smoking causes more than 480,000 deaths each year in the United States.1Smoking has been causally linked to cancers of the oropharynx, larynx, esophagus, trachea, bronchus, lung, stomach, liver, pancreas, kidney, ureter, cervix, bladder and colorectum and acute myeloid leukemia, as well as to stroke, blindness, cataracts, age-related macular degeneration, periodontitis, aortic aneurysm, early abdominal aortic atherosclerosis, coronary heart disease, pneumonia, atherosclerotic peripheral vascular disease, chronic obstructive pulmonary disease, tuberculosis, asthma, diabetes, reproductive disorders, ectopic pregnancies, erectile dysfunction, hip fractures, rheumatoid arthritis and immune dysfunction.1Lung cancer screening is most effective when applied to individuals at high risk.2Using NLST data, Figure 1 describes how the number of competing-causes deaths, primarily smoking related, increases with lung cancer risk, primarily driven by smoking, and how competing-causes deaths exceeds lung cancer deaths. Successful smoking interventions have the potential to greatly reduce morbidity and mortality in lung cancer screenees. It is likely that smoking cessation interventions in lung cancer screening programs will be cost-effective and may lead to health benefits that exceed those of the lung cancer mortality reduction benefits. Current, U.S. guidelines recommend providing smoking cessation interventions for current smokers in lung cancer screening programs. However, which type of smoking cessation program in the lung cancer screening setting is most effective is unknown.

      Lung cancer screenees generally have longer and more intense smoking histories so they may be more intractable to cessation interventions. On the other hand, screening may provide a teachable moment, which may lead to greater rates of cessation.3The proportion of current smokers selected for screening is greater when selected by risk prediction model, than when selected by NLST-like criteria. The proportion of current smokers in the NLST was 48.2%, in PLCO NLST-eligible participants was 40.4%, and in the Pan-Canadian Early Detection of Lung Cancer Study and Cancer Care Ontario (CCO) pilot, both of which have eligibility criteria of PLCOm2012 6-year risks ≥2%, were 62.8% and 65.4%, respectively.

      Two recent reviews concluded that evidence is lacking to recommend specific tailored smoking cessation approach in the lung cancer screening setting and recommend more research.4,5Currently, in the U.S., 8 trials in the SCALE (Smoking Cessation within the Context of Lung Cancer Screening) collaboration are underway that are investigating different smoking cessation interventions within lung cancer screening programs.6Some of the factor under study in SCALE include the following6:participant eligibility criteria, baseline versus annual screen, participant’s interest in stopping smoking, treatment delivery method and dose, incorporation of positive and negative screening results, perceived risk of lung cancer, and costs of treatments.Results of SCALE are expected after 2021.

      Recently, Cadham and colleagues conducted a meta-analysis of smoking cessation interventions in samples that were similar to those in lung cancer screening programs.7At 6-month follow-up, smoking cessation had the following associations with interventions:

      Electronic/web-based (odds ratio [OR] 1.14, 95% CI 1.03-1.25)

      Telephone counseling (OR 1.21, 95% CI 0.98-1.50)

      In-person counseling (OR 1.46, 95% CI 1.25-1.70)

      Pharmacotherapy (OR 1.53, 95% CI 1.33-1.77).

      CCO’s Lung Cancer Screening Pilot for People at High Riskstarted low dose computed tomography screening in three sites on June 1, 2017. In the first year of screening, 1624 individuals received LDCT scans and current smokers were enrolled in an “opt-out” in-hospital smoking cessation programs. Of scanned participants 88.8% attended in-hospital smoking cessation counselling, and 95.2% were satisfied with their cessation services.

      In conclusion, several intervention approaches appear to be associated with smoking cessation. Multiple approaches appear better than single approaches. Pharmacotherapy and in-person counseling interventions appear to be superior to electronic/web-based or telephone counseling. Successful enrollment into in-person cessation programs is achievable.

      References

      1. United States. Public Health Service. Office of the Surgeon General., National Center for Chronic Disease Prevention and Health Promotion (U.S.). Office on Smoking and Health. The health consequences of smoking--50 years of progress : a report of the Surgeon General.Atlanta, GA: U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health; 2014.

      2. Tammemagi MC, Katki HA, Hocking WG, et al. Selection criteria for lung-cancer screening. The New England journal of medicine. 2013;368(8):728-736.

      3. Taylor KL, Cox LS, Zincke N, Mehta L, McGuire C, Gelmann E. Lung cancer screening as a teachable moment for smoking cessation. Lung cancer (Amsterdam, Netherlands). 2007;56(1):125-134.

      4. Iaccarino JM, Duran C, Slatore CG, Wiener RS, Kathuria H. Combining smoking cessation interventions with LDCT lung cancer screening: A systematic review. Preventive medicine. 2019;121:24-32.

      5. Pineiro B, Simmons VN, Palmer AM, Correa JB, Brandon TH. Smoking cessation interventions within the context of Low-Dose Computed Tomography lung cancer screening: A systematic review. Lung cancer (Amsterdam, Netherlands). 2016;98:91-98.

      6. Joseph AM, Rothman AJ, Almirall D, et al. Lung Cancer Screening and Smoking Cessation Clinical Trials. SCALE (Smoking Cessation within the Context of Lung Cancer Screening) Collaboration. American journal of respiratory and critical care medicine. 2018;197(2):172-182.

      7. Cadham C. Systematic Review and Meta-Analysis of Smoking Cessation Interventions for Potential Use in Lung Cancer Screening Settings: 6- and 12-Month Outcomes. . American Society of Preventive Oncology Annual Meeting ASPO 2019; Monday, March 11, 2019, 2019; Tampa, Florida.

      8. Tammemagi MC, Church TR, Hocking WG, et al. Evaluation of the Lung Cancer Risks at Which to Screen Ever- and Never-Smokers: Screening Rules Applied to the PLCO and NLST Cohorts. PLoS medicine. 2014;11(12):e1001764.

      Figure 1. Lung cancer and competing causes deaths in the National Lung Screening Trial by PLCOm2012 model risk level (taken from 8)

      nlstdeathsbyintervention.png

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Author of

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    MA15 - Usage of Computer and Molecular Analysis in Treatment Selection and Disease Prognostication (ID 141)

    • Event: WCLC 2019
    • Type: Mini Oral Session
    • Track: Pathology
    • Presentations: 1
    • Now Available
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      MA15.10 - Stromal Markers of Activated Tumor Associated Fibroblasts Predict Poor Survival and Are Associated with Necrosis in Non-Small Cell Lung Cancer (Now Available) (ID 2212)

      15:45 - 17:15  |  Author(s): Luis M Seijo

      • Abstract
      • Presentation
      • Slides

      Background

      Tumor associated fibroblasts (TAFs) are essential contributors of the progression of non-small cell lung cancer (NSCLC). Most lung TAFs exhibit an activated phenotype characterized by the expression of α-SMA and fibrillar collagens. However, the prognostic value of these activation markers in NSCLC remains unclear.

      Method

      We conducted a retrospective multicentric study of the prognostic value of the standard markers of activated fibroblasts. For this purpose, we conducted a quantitative image analysis of α-SMA immunostaining and picrosirius red staining of fibrillar collagens imaged by bright-field and polarized microscopy, respectively, using tissue microarrays with samples from 220 surgical patients, which elicited a percentage of positive staining area for each marker and patient.

      Result

      Kaplan-Meier curves showed that all TAF activation markers were significantly associated with poor survival, and their prognostic value was independent of TNM staging as revealed by multivariate analysis, which elicited an adjusted increased risk of death after 3 years of 129% and 94% for fibrillar collagens imaged with bright-field (p = 0.004) and polarized light (p = 0.003), respectively, and of 89% for α-SMA (p = 0.009). We also found a significant association between all TAF activation markers and tumor necrosis, which is often indicative of hypoxia, supporting a pathologic link between tumor desmoplasia and necrosis/hypoxia.

      Conclusion

      Our findings identify patients with large histologic coverage of fibrillar collagens and α-SMA+ TAFs to be at higher risk of recurrence and death, supporting that they could be considered for adjuvant therapy. Moreover it supports that antifibrotic drugs aiming to target tumor fibrosis may be an effective therapeutic approach to improve survival in NSCLC.

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