Virtual Library

Abstract:
Screening of high risk individuals for lung cancer was shown to reduce lung cancer mortality by 20% in the National Lung Screening Trial (NLST) comparing low-dose helical computerized tomography (LDCT) to chest x-ray [1]. Implementation of lung cancer screening will be a serious challenge. Since the time of the IASLC meeting in Sydney in 2013 additional information from the NLST has provided guidance on many aspects of screening and informed public health policy in the United States. The United States Preventive Services Task Force (USPSTF) in December 2013 and the Centers for Medicare and Medicaid Services in February 2015 released decisions favorable to lung cancer screening [2, 3]. The USPSTF recommended it at a Grade B level which means under the terms of the Affordable Care Act (ACA), many insurance companies must reimburse without a deductible. The recommendations followed the NLST criteria but extended the age for screening to cover 55 to 80. CMS also followed NLST extending screening to age 77. The coverage includes a counseling and shared decision making visit with a written order for the procedure. Requirements also included radiologist credentials, image acquisition standards and participation in a CMS registry. The American College of Radiology Lung Cancer Screening Registry has been approved. Coverage decisions acknowledged the known drawbacks of high false-positive rates, overdiagnosis potential, radiation risk, psychosocial consequences, effect on smoking behavior and incidental findings. More efficient screening strategies may use different criteria than the NLST excluding those at lower risk while including those outside NLST criteria that are at identifiable high risk. Several risk prediction models exist. The PLCO~m2012~ model is the best-validated. Selected risk factors included age, race, ethnicity, education, body mass index, self-reported chronic obstructive pulmonary disease, personal and family history of lung cancer, and smoking variables. A risk threshold of 1.5% over 6 years was chosen as below this threshold there was no reliable evidence of screening benefit and much higher numbers needed to screen. Comparing this risk model threshold to the USPSTF criteria in the PLCO CXR arm demonstrates that the PLCO~m2012~ risk model approach is more efficient [4]. Table The American College of Radiology developed the Lung-RADS nodule classification system [5]. When applied retrospectively to NLST data (26,455 baseline scans and 48,671 incidence scans), Lung-RADS 1.0 substantially reduced the false-positive rate (12.8% versus 26.6% at baseline and 5.3% versus 21.8% at incidence scans respectively). However, the trade-off was reduced sensitivity compared to NLST criteria: 84.9% vs. 93.5% at baseline and 78.6% versus 93.8% for incidence scans [6]. Retrospective subset analyses while imperfect are useful, providing some information about potential variations in effectiveness in subgroups. Analysis of performance within the NLST was conducted by age, gender and smoking status with additional detail comparing those less than 65 and ≥ 65 [7]. The mortality risk ratios by age, < 65 and ≥ 65, were 0.82 and 0.87; gender, males and females, 0.92 and 0.73, and by smoking status, current versus former, 0.81 and 0.91. Reassuringly, ninety day postsurgical mortality rates in those less than and ≥ 65 were 1.8% and 1.0% respectively. An estimate of overdiagnosis within the NLST has been done [8]. Using follow-up data extended from that in the primary manuscript, a total of 1089 lung cancers occurred in the LDCT arm compared with 969 in the CXR arm, resulting in 120 additional lung cancer cases in the LDCT arm. Two estimates of the upper bound of overdiagnosis were calculated, 18.5% of the cases detected during screening and 11% of the cases overall. More follow-up would be helpful to determine the extent of continued catch-up in cases in the CXR arm. Current smokers in the Lung Screening Study portion of the NLST were evaluated for smoking cessation and results also analyzed by findings on LDCT [9]. Those with normal scans did show a decline in smoking prevalence that continued for the seven years of assessment. Those with abnormal scans had higher cessations rates; the more abnormal the scan the higher the rates. All lung cancer screening programs should incorporate proven smoking cessation strategies. The cost-effectiveness analysis from the NLST utilized data from medical record abstraction covering in exhaustive detail medical interventions delivered as a consequence of screening [10]. As compared with no screening, screening with low-dose CT cost an additional $1,631 per person and provided an additional 0.0316 life-years per person and 0.0201 Quality Adjusted Live Years (QALY) per person. The corresponding Incremental Cost Effectiveness Ratios were $52,000 per life-year gained and $81,000 per QALY gained but varied widely by underlying risk group. Information from the NLST continues to refine our understanding of lung cancer screening. This should prove invaluable in ensuring that screening is done at a high level to achieve optimal mortality reductions as programs are expanded. References 1. The National Lung Screening Trial Research Team. Reduced Lung-Cancer Mortality with Low-Dose Computed Tomographic Screening. N Engl J Med 2011; 365: 395-409. 2. Moyer VA. Screening for lung cancer: U.S. Preventive Services Task Force recommendation statement. Ann Int Med 2014; 160: 330-338. 3. Centers for Medicare and Medicaid Services. Decision Memo for Screening for Lung Cancer with Low Dose Computed Tomography (LDCT) (CAG-00439N). http://www.cms.gov/medicare-coverage-database/details/nca-decision-memo.aspx?NCAId=274 (accessed February 22, 2015). 4.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: e10001764. 5. American College of Radiology ACR-STR Practice Guideline for the Performance and Reporting of Lung Cancer Screening Thoracic Computed Tomography http://www.acr.org/~/media/ACR/Documents/PGTS/guidelines/LungScreening.pdf (accessed February 22, 2015). 6. Pinsky PF, Gierada DS, Black W et al. Performance of Lung-RADS in the National Lung Screening Trial. Ann Intern Med [Epub ahead of print 10 February 2015] doi:10.7326/M14-2086. 7. Pinsky PF, Gierada DS, Hocking W et al. National Lung Screening Trial Findings by Age: Medicare-Eligible Versus Under-65 Population. Ann Intern Med 2014; 161: 627-633. 8. Patz EF, Pinsky P, Gatsonis CG et al. Overdiagnosis in Low-Dose Computed Tomography Screening for Lung Cancer. JAMA Intern Med 2014: 174: 269-274. 9. Tammemagi MC, Berg CD, Riley TL et al. Impact of Lung Cancer Screening Results on Smoking Cessation. J Natl Cancer Inst 2014;106: dju084. 10. Black WC, Gareen IF, Soneji SS et al. Cost-Effectiveness of CT Screening in the National Lung Screening Trial. N Engl J Med 2014; 371: 1793-1802. TABLE Comparison of PLCO~M2012~, NLST and USPSTF [4]

	PLCO~M2012 ~vs. NLST		PLCO~M2012~ vs. USPTF
	PLCO~M2012~	NLST	PLCO~M2012 ~	USPSTF
Selection criteria	>1.3455%[1]	Age 55-74, current/former smoker ≥30 PY	≥ 1.51%1	Age 55-80, current/former smoker ≥30 PY
Validation cohort	14,144 PLCO trial screening arm smokers	14,144 PLCO trial screening arm smokers who met NLST criteria	37,327 PLCO trial screening arm smokers	37,327 PLCO trial screening arm smokers who met USPSTF criteria
Sensitivity, % (95% CI)	83.0	71.1	80.1 (76.8–83.0)	71.2 (67.6–74.6)
Specificity, % (95% CI)	62.9	62.7	66.2 (65.7–66.7)	62.7 (62.2–63.1)
Positive Predictive Value, % (95% CI)	4.0	3.4	4.2 (3.9–4.6)	3.4 (3.1–3.7)

[1] Estimated lung cancer risk over six years

Abstract:
Lung cancer remains the most common cancer in the world. Worldwide, the leading cause of cancer mortality in men and the second leading cause in women. 1.8 million new cases were diagnosed in 2012. About 58% of lung cancer cases occurred in low and middle income countries. Although by far not the only known or suspected lung carcinogen, cigarette smoking remains the principal cause of lung cancer and is estimated to be responsible for 85% of all types of this cancer. The major risk factors and risk modifiers for lung cancer include: Cigarette Smoking Secondhand Smoke (SHS) Air Pollution Radon Occupational Exposures (e.g., asbestos, silica, Chromium, radon) Lung Cancer Susceptibility Genes Aspirin/NSAIDs Use (protective) Dietary vitamin D (protective) HRT – possibly protective. I will cover updates on our understanding of the major risk factors for lung cancer in the USA and globally. Smoking Smoking causes an estimated 170,000 cancer deaths in the U.S. every year (American Cancer Society) and the incidence among women is rising. Lung cancer now surpasses breast cancer as the number one cause of death among women. Globally, cigarette consumption has changed over the decades, with China now the number one consumer (44%) of cigarettes in the world, while the USA is consumes about 5%. In the USA, “Second Hand Smoke” is the third leading cause of lung cancer and responsible for an estimated 3,000 lung cancer deaths every year. Globally, the number of SHS related cancer deaths is unknown, but surely rising. SHS is also referred as ‘environmental tobacco smoke (ETS)’, ‘passive smoking’ or ‘involuntary smoking’. IARC has deemed SHS is “carcinogenic to humans”, with an increased risk of 20% for women and of 30% for men among never smokers who are exposed to SHS (i.e., environmental tobacco smoke) from their spouse. Ambient Air Pollution IARC has classified outdoor air pollution - as a whole - as “carcinogenic to humans (Group 1)”. Outdoor air pollution has been shown to cause lung cancer and bladder cancer, pointing to the role of overlapping carcinogen exposure to compounds such as polycylic aromatic compounds (PAC). The most recent data from the Global Burden of Disease (GBD) Project indicate that in 2010, 3.2 million deaths worldwide resulted from air pollution alone, including 223,000 from lung cancer. Radon Radon is an odorless, colorless, radioactive gas that causes lung cancer. IARC classifies radon and its progeny as “carcinogenic to humans” (Class I), and the US EPA lists radon as the second leading cause of lung cancer in the US and the number one cause of lung cancer among non-smokers. Originally described as a risk factor in underground miners (among both smokers and non-smokers, with synergistic interaction with smoking), the U.S. EPA estimates that 1 of 15 homes in the US (as many as 1 of 3 homes in some states)-about 7 million homes-have high radon levels. Occupational Exposures: Asbestos In North America, and most other high income countries, asbestos has been the most prevalent occupational lung carcinogen exposure. All forms of asbestos have been classified as a known human carcinogen (by the U.S. Department of Health and Human Services, EPA, and the IARC). About 125 million people in the world are exposed to asbestos at the workplace. According to WHO estimates, more than 107,000 deaths each year are attributable to occupational exposure to asbestos. Exposure to asbestos, including chrysotile, causes cancer of the lung, larynx and ovaries, and also mesothelioma. Co-exposure to tobacco smoke and asbestos fibers substantially increases the risk for lung cancer (multiplicative interaction). Heritable Factors: Common Genetic Variants GWAS provide novel insights into the development of LC. Genetic factors are increasingly recognized to be important in the etiology of LC: 15q25.1 (CHRNA5-CHRNA3-CHRNB4) 5p15.33 (TERT-CLPTM1) 6p21.33 (BAT3-MSH5) Follow up studies that pool data international as part of a large consortium (International Lung Cancer Consortium - ILCCO) have identified other common variants at multiple loci influencing LC risk, and these include BRACA1. Studies of pleiotropy are well underway. Additionally, GWAS studies globally, such as one from China, have identified unique, population-specific, risk loci. COPD and Lung Cancer risk COPD and LC are the 4[the] and 7[th] leading causes of death worldwide. The coexistence of COPD is an important marker of future risk of LC among smokers. Epidemiologic studies have shown that 50-70% of LC patients have co-existing impaired lung function or COPD. And, not surprisingly, 90% of combined LC and COPD cases are attributable to cigarette smoking. Recently, we have found that the co-existence of COPD with lung cancer also negatively influences survival among patients with all stages. Conclusion Lung cancer remains the number one cancer threat to the world’s populations. Lung cancer epidemiology continues to evolve and as we understand more about the origins and behavior of lung cancer, the more opportunities we will have for prevention and control of this deadly disease.

Abstract:
Smoking is the largest preventable risk factor for the development of lung cancer. Continued smoking by cancer patients and survivors causes adverse outcomes including an increase in overall mortality, cancer specific mortality, risk for second primary cancer, and associated increases in cancer treatment toxicity. Significant evidence demonstrates the biologic mechanisms of cancer initiation and progression caused by cigarette smoke, but relatively few studies have evaluated the effects of smoking on cancer biology and therapeutic response to cytotoxic agents. Most oncologists believe smoking causes adverse outcomes and that smoking cessation treatment should be a standard part of cancer care. However, most oncologists do not regularly provide cessation support to cancer patients. Moreover, tobacco assessments and cessation support are not regularly incorporated into clinical trials design or analysis. Recently released guidelines from several national and international organizations advocate for addressing tobacco use by cancer patients. This session will discuss the clinical and biologic effects of smoking on cancer, present the current state of tobacco assessments and cessation in clinical practice and research, and discuss methods to improve access to cessation support for cancer patients. Discussion will further detail deficits in the current understanding of the effects of smoking on cancer treatment outcomes and highlight areas of needed improvement.

Abstract:
The 2015 WHO Classification of Tumors of the Lung, Pleura, Thymus and Heart has just been published with numerous important changes from the 2004 WHO classification, due in part to remarkable advances in lung cancer genetics and therapy.[1] Multiple major changes for the common lung cancers mostly follow the 2011 lung adenocarcinoma classification sponsored by the International Association for the Study of Lung Cancer (IASLC), American Thoracic Society (ATS) and European Respiratory Society (ERS).[2 ] This 2015 edition follows previous WHO Classifications of Lung Tumors in 1967 and 1981, of Lung and Pleural Tumors in 1999 and Tumors of the Lung, Pleura, Thymus and Heart in 2004.[3, 4] Through support of its Pathology Committee, the IASLC has played a key role in the last three WHO Classifications.[5] With each subsequent classification, new techniques were introduced resulting in increased complexity, but greater ability to personalize therapeutic strategies that are now frequently dependent on histology and genetics. The most significant changes in the 2015 Classification involve: 1) Use of immunohistochemistry throughout the classification, when possible, not only for small biopsies/cytology, but also for resected specimens in certain settings such as solid adenocarcinoma, nonkeratinizing squamous cell carcinoma, large cell carcinoma, neuroendocrine tumors and sarcomatoid carcinomas. 2) A new emphasis on genetic studies, in particular integration of molecular testing to help personalize treatment strategies for advanced lung cancer patients. Due to the therapeutic implications, molecular testing for EGFR mutation and ALK rearrangement is today recommended in tumors classified as adenocarcinoma and in cases where an adenocarcinoma component cannot be excluded.[2, 6] 3) A new classification for small biopsies and cytology similar to that proposed in the 2011 IASLC/ATS/ERS Classification[2] proposes that tumors that have clear morphologic patterns of adenocarcinoma or squamous cell can be diagnosed as adenocarcinoma or squamous cell carcinoma, respectively, without immuhistochemistry, unless a pneumocyte marker such as TTF-1 is desired to address primary versus metastatic adenocarcinoma. However, in the setting of poorly differentiated tumors that do not show clear differentiation by routine microscopy, a limited immunohistochemical workup is recommended to allow for an accurate diagnosis and also to preserve as much tissue for molecular testing as possible. Most tumors can be classified using a single adenocarcinoma marker (e.g. TTF-1) and a single squamous marker (e.g. p40 or p63). Nonsmall cell carcinomas (NSCC) that show no clear adenocarcinoma or squamous cell carcinoma morphology or immunohistochemical markers are regarded as NSCC not otherwise specified (NOS). If a tumor with this morphology stains with pneumocyte markers (i.e. TTF-1), it is classified as NSCC, favor adenocarcinoma and if it stains only with squamous markers (i.e. p40) it is classified as NSCC, favor squamous cell carcinoma. Using this approach, a diagnosis of NSCC-NOS can be avoided in up to 90% of cases.[7, 8 ] 4) According to the 2011 IASLC/ATS/ERS Classification of lung adenocarcinoma, adenocarcinoma in situ (AIS) and minimally invasive adenocarcinoma (MIA) were defined as entities to have 100% or near 100% disease free survival if completely resected, respectively. Also, invasive adenocarcinomas are classified according to the predominant pattern using comprehensive histologic subtyping (CHS). Multiple studies have shown prognostic significance to this approach with favorable outcome for lepidic adenocarcinomas and poor outcome for solid and micropapillary adenocarcinomas. CHS can be helpful in staging as well: 1) along with other morphologic features, it can be useful in comparing multiple lung adenocarcinomas in a single patient in order to distinguish multiple primary tumors from intrapulmonary metastases and 2) it can also help in measuring invasive size in lepidic adenocarcinomas. Micropapillary or solid predominant subtyping also appears to predict improved responsiveness to adjuvant chemotherapy compared to acinar or papillary predominant tumors in surgically resected lug adenocarcinoma patients when analyzed by disease free survival and specific disease free survival.[9] 5) The diagnosis of large cell carcinoma is restricted only to resected tumors that lack any clear morphologic or immunohistochemical differentiation with reclassification of the remaining former large cell carcinoma subtypes into different categories. 6) Squamous cell carcinomas are reclassified into keratinizing, nonkeratinizing and basaloid subtypes with the non-keratinizing tumors requiring immunohistochemistry proof of squamous differentiation. 7) Neuroendocrine tumors are grouped together in one category, although new genetic data supports previous clinical, epidemiologic and pathologic data showing that low and intermediate grade typical (TC) and atypical carcinoids (AC) are distinct from the high grade small cell carcinoma (SCLC) and large cell neuroendocrine carcinoma (LCNEC). Ki-67 is useful to distinguish carcinoids from SCLC and LCNEC especially in small crushed biopsies. However, published data do not support incorporation into the classification, particularly in separating TC from AC. Spread through air spaces (STAS) is a newly recognized pattern of invasion which consists of micropapillary clusters, solid nests or single cells beyond the edge of the tumor into air spaces in the surrounding lung parenchyma, It probably contributes to the significantly increased recurrence rate for patients with small stage 1 adenocarcinomas who undergo limited resections.[10] Future clinical trials and large scale genetic studies such as The Cancer Genome Atlas (TCGA) need to incorporate the new pathologic criteria for both small biopsies and resection specimens which now require immunohistochemistry to precisely classify poorly differentiated tumors such as solid adenocarcinoma or nonkeratinizing squamous cell carcinoma. Despite promising preliminary data, additional work is needed to develop a histological grading system for lung cancer. Acknowledgement: This abstract is presented with gratitude on behalf of the WHO Panel and the IASLC Pathology Committee. References: 1. Travis WD, Brambilla E, Burke AP, Marx A, Nicholson AG. WHO Classification of Tumours of the Lung, Pleura, Thymus and Heart. Lyon: International Agency for Research on Cancer; 2015. 2. Travis WD, Brambilla E, Noguchi M, et al. The New IASLC/ATS/ERS international multidisciplinary lung adenocarcinoma classification. JThoracic Oncol 2011;6:244-85. 3. Travis WD, Colby TV, Corrin B, Shimosato Y, Brambilla E, in collaboration with LHS, Countries pf. Histological Typing of Lung and Pleural Tumors. Berlin: Springer; 1999. 4. Travis WD, Brambilla E, Mller-Hermelink HK, Harris CC. Pathology and Genetics: Tumours of the Lung, Pleura, Thymus and Heart. Lyon: IARC; 2004. 5. Tsao MS, Travis WD, Brambilla E, Nicholson AG, Noguchi M, Hirsch FR. Forty years of the international association for study of lung cancer pathology committee. J Thorac Oncol 2014;9:1740-9. 6. Lindeman NI, Cagle PT, Beasley MB, Chitale DA, Dacic S, Giaccone G, Jenkins RB, Kwiatkowski DJ, Saldivar JS, Squire J, Thunnissen E, Ladanyi M. Molecular Testing Guideline for Selection of Lung Cancer Patients for EGFR and ALK Tyrosine Kinase Inhibitors: Guideline from the College of American Pathologists, International Association for the Study of Lung Cancer, and Association for Molecular Pathology. J ThoracOncol 2013. 7. Nicholson AG, Gonzalez D, Shah P, Pynegar MJ, Deshmukh M, Rice A, Popat S. Refining the Diagnosis and EGFR Status of Non-small Cell Lung Carcinoma in Biopsy and Cytologic Material, Using a Panel of Mucin Staining, TTF-1, Cytokeratin 5/6, and P63, and EGFR Mutation Analysis. JThoracOncol 2010;5:436-41. 8. Loo PS, Thomas SC, Nicolson MC, Fyfe MN, Kerr KM. Subtyping of Undifferentiated Non-small Cell Carcinomas in Bronchial Biopsy Specimens. JThoracOncol 2010;5:442-7. 9. Tsao MS, Marguet S, Le Teuff G, Lantuejoul S, Shepherd FA, Seymour L, Kratzke R, Graziano SL, Popper HH, Rosell R, Douillard JY, Le-Chevalier T, Pignon JP, Soria JC, Brambilla EM. Subtype Classification of Lung Adenocarcinoma Predicts Benefit From Adjuvant Chemotherapy in Patients Undergoing Complete Resection. J Clin Oncol 2015. 10. Kadota K, Nitadori JI, Sima CS, Ujiie H, Rizk NP, Jones DR, Adusumilli PS, Travis WD. Tumor Spread Through Air Spaces is an Important Pattern of Invasion and Impacts the Frequency and Location of Recurrences Following Limited Resection for Small Stage I Lung Adenocarcinomas. J Thorac Oncol 2015;10:806-14.

WHO CLASSIFICATION

Adenocarcinoma

Lepidic adenocarcinoma

Acinar adenocarcinoma

Papillary adenocarcinoma

Micropapillary adenocarcinoma

Solid adenocarcinoma

Invasive mucinous adenocarcinoma Mixed invasive mucinous and non-mucinous adenocarcinoma

Colloid adenocarcinoma

Fetal adenocarcinoma

Enteric adenocarcinoma

Minimally invasive adenocarcinoma Non-mucinous Mucinous

Preinvasive lesions Atypical adenomatous hyperplasia Adenocarcinoma in situ Nonmucinous Mucinous

Squamous cell carcinoma

Keratinizing squamous cell carcinoma

Non-keratinizing squamous cell carcinoma

Basaloid squamous cell carcinoma

Preinvasive lesion Squamous cell carcinoma in situ

Neuroendocrine tumors

Small cell carcinoma Combined small cell carcinoma

Large cell neuroendocrine carcinoma Combined large cell neuroendocrine carcinoma

Carcinoid tumors Typical carcinoid Atypical carcinoid

Preinvasive lesion Diffuse idiopathic pulmpnary neuroendocrine cell hyperplasia

Large cell carcinoma

Abstract:
The changes introduced in the 7[th] edition of the tumour, node and metastasis (TNM) classification for lung cancer derived from the analyses of the International Association for the Study of Lung Cancer (IASLC) database. These analyses were conducted by the members of the IASLC Staging and Prognostic Factors Committee (SPFC) and the biostatisticians of Cancer Research And Biostatistics (CRAB). For the first time in the history of the TNM classification for lung cancer, the 7[th] edition was based on a truly international database of more than 80,000 evaluable patients collected in 45 different sources in 20 countries and treated with all treatment modalities from 1990 to 2000. (1) The changes recommended by the IASLC were accepted by the Union for International Cancer Control (UICC) and by the American Joint Committee on Cancer (AJCC) and were eventually published in their staging manuals. With this involvement of the IASLC in the revision of the TNM classification for lung cancer, the IASLC became the most important provider of data to the UICC and the AJCC for future editions of the classification. A similar process was used for the revision of the 7[th] edition into the 8[th] edition. The IASLC made an international call for submission of more data to the IASLC database. (2) The resulting international contribution amounted to more than 77,000 evaluable patients diagnosed with either non-small cell lung cancer (70,967 patients) or small cell lung cancer (6,189 patients) from 1990 to 2010. They were submitted from 35 different databases located in 16 countries in Europe, Asia, North and South America, and Australia. (3) The different subcommittees of the Lung Cancer Domain of the IASLC SPFC were in charge of analysing the data pertaining to the T, the N and the M component of the classification, as well as the stages and the small cell lung cancer. For the T component, the prognostic impact of the T descriptors was analysed in five different populations: pT1-4N0M0R0, pT1-4anyNM0R0, pT1-4anyNM0anyR, i.e., including incomplete resections, either microscopically incomplete, R1, or macroscopically incomplete, R2; and cT1-4N0M0 and cT1-4anyNM0. Survival analyses were completed with univariate and multivariate analyses adjusted by histological type, gender, region and age. The main results showed that the capacity of tumour size to separate tumours of different prognosis was greater than that shown in previous analyses, and that its influence could be spread to all T categories; the role of visceral pleura invasion as a T2 descriptor was confirmed; the prognostic impact of endobronchial location less than 2 cm from the carina (T3 in 7[th] edition) and of total atelectasis/pneumonitis (T3 in 7[th] edition) was found to be similar to that of their T2 counterparts; diaphragm invasion was found to have worse prognosis than that of other T3 descriptors; and mediastinal pleura invasion was found to be scarcely used as a T descriptor. (4) For the N component, the present N descriptors (N0, N1, N2 and N3) were found to separate tumours of different prognosis in clinically and pathologically (both in the R0 and any R populations) staged tumours. The impact of tumour burden in the lymph nodes could also be assessed when survival was analysed according to the number of nodal stations, but this could only be analysed in the population of patients who had undergone tumour resection and systematic nodal dissection, and could not be validated at clinical staging. (5) For the M component, the 7[th] edition M1a descriptors were validated, as all showed similar survival. However, when the M1b descriptors were analysed in detail, single metastasis (one metastasis in one organ) had better prognosis than multiple metastases in one or several organs. (6) Table 1 shows the changes recommended by the IASLC SPFC based on the analyses of the new IASLC database. The described changes implied some modifications in the stage grouping, creating more stages for early and advanced disease, (7) and were also applicable to small-cell lung cancer. (8) The IASLC recommendations emphasize the prognostic impact of tumour size; simplify the T descriptors by combining some of them; maintain the current N descriptors; separate tumours with single metastasis in a distinct group; and establish more stage groupings to refine prognosis based on anatomic extent of disease. They improve our capacity to indicate prognosis, which is one of the objectives of the TNM classification, and, therefore, they should be implemented in the 8[th] edition of the TNM classification. Table 1

Descriptor	7th edition	8th edition (recommended classification)
T component
	T1a	T1a
>1-2cm	T1a	T1b
>2-3cm	T1b	T1c
>3-4cm	T2a	T2a
>4-5cm	T2a	T2b
>5-7cm	T2b	T3
>7cm	T3	T4
Bronchus <2cm from carina	T3	T2
Total atelectasis/pneumonitis	T3	T2
Invasion of diaphragm	T3	T4
Invasion of mediastinal pleura	T3	-
N component
No involvement or involvement of regional lymph nodes	N0, N1, N2, N3	N0, N1, N2, N3
M component
Metastases within the thoracic cavity	M1a	M1a
Single extrathoracic metastasis	M1b	M1b
Multiple extrathoracic metastases	M1b	M1c

References 1. Goldstraw P, Crowley JJ. The International Association for the Study of Lung Cancer international staging project on lung cancer. J Thorac Oncol 2006; 1: 281-286. 2. Giroux DJ, Rami-Porta R, Chansky K et al. The IASLC Lung Cancer Staging Project: data elements for the prospective project. J Thorac Oncol 2009; 4: 679-683. 3. Rami-Porta R, Bolejack V, Giroux DJ et al. The IASLC Lung Cancer Staging Project: the new database to inform the 8[th] edition of the TNM classification of lung cancer. J Thorac Oncol 2014; 9: 1618-1624. 4. Rami-Porta R, Bolejack V, Crowley J et al. The IASLC Lung Cancer Staging Project: proposals for the revisions of the T descriptors in the forthcoming eighth edition of the TNM classification for lung cancer. J Thorac Oncol 2015;10:990-1003. 5. Asamura H et al. J Thorac Oncol 2015; in preparation. 6. Eberhardt WEE et al. J Thorac Oncol 2015; in preparation. 7. Golstraw P et al. J Thorac Oncol 2015; in preparation. 8. Nicholson AG et al. J Thorac Oncol 2015; in preparation.

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Abstract:
Platinum-based doublet chemotherapy is the standard first-line treatment for non-selected patients with advanced non-small cell lung cancer (NSCLC) who have a good performance status . However, some tumors are highly dependent on the function of specific oncogenes for proliferation and survival. This “oncogenic addiction” has leaded the development of targeted anticancer therapies and their ad hoc biomarkers as predictors of their efficacy. This fact has changed the diagnostic and treatment approach in NSCLC . Moreover, this ‘‘personalized medicine’’ approach, in which tumors might potentially benefit from a biology-guided treatment, has an impact in patients’ outcome . Personalized medicine is also feasible in other malignancies such as metastatic breast cancer, even for patients with rare genomic alterations (SAFIR01 trial) , and in other refractory malignancies (SHIVA trial) , reinforcing that the establishment of a comprehensive tumour molecular profile is feasible and compatible with clinical practice. Unlike “basket trials”, where researchers test the effect of a single drug on a single mutation in a variety of cancer types, “umbrella” trials are designed to test the impact of personalized medicine with different drugs on different mutations in a single type of cancer on the basis of a centralized molecular portrait . The phase II BATTLE (Biomarker-integrated Approaches of Targeted Therapy for lung Cancer) trial was the first prospective, biopsy-mandated, biomarker-based study, that adaptively randomised 255 pre-treated NSCLC patients to erlotinib, sorafenib, erlotinib plus bexarotene, or vandetanib, based on molecular biomarker analysed in fresh core needle biopsy specimens. Overall results included a 46% 8-week disease control rate (primary endpoint). This trial established the feasibility of “real-time” biopsies and personalized treatment in lung cancer. BATTLE-2 (NCT01248247), a phase II, randomised, multi-arm study in advanced pre-treated EGFR wild type and ALK non-rearranged NSCLC patients is currently ongoing. The SPECTA-lung (NCT02214134), included within the SPECTA-platform, is a program aiming at Screening Patients with thoracic tumors (lung cancer, malignant pleural mesothelioma, thymoma or thymic carcinoma at any stage) to identify the molecular characteristics of their disease for Efficient Clinical Trial Access. Second-generation trials encompass within the trial design to access to targeted therapies and usually incorporate a randomization process. SAFIR02-Lung (NCT02117167) is an open-label, multicentric randomised, phase II trial. Advanced no EGFR-activating mutation or ALK translocation NSCLC patients are biopsied during the two initial platinum-based chemotherapy cycles. A comparative genomic hybridisation (CGH) array and a next-generation sequencing are performed and analysed during the two subsequent cycles as a therapeutic decision tool. Only patients with a molecular alteration are randomized to maintenance targeted drug arm (AZD8931, Vandetanib, Selemutinib, AZD5363, AZD4547, AZD2014); or standard maintenance treatment (pemetrexed or erlotinib) after completion of four cycles of chemotherapy to test an improvement in progression free survival (PFS). Lung-MAP (NCT02154490) trial is a phase II/III multidrug, multi-sub-study, and biomarker-driven clinical trial in advanced second-line squamous lung cancer patients. Patients are randomized to standard second-line treatment (docetaxel / erlotinib) or five experimental drugs (four targeted therapies according NGS results and an anti-PDL1 immunotherapy based on immunochemistry results). The primary end-point of the trial is PFS. Approximately 500 and 1000 patients will be screened per year for over 200 cancer-related genes for genomic alterations. ALChEMIST trial (Adjuvant Lung Cancer Enrichment Marker Identification and Sequencing Trials) is designed to assess whether adjuvant therapy with erlotinib (ALCHEMIST-erlotinib, NCT02193282) or crizotinib (ALCHEMIST-crizotinib, NCT02201992) for 2 years will improve survival over placebo for patients with completely resected stage IB-IIIA EGFR-mutant or ALK-rearranged NSCLC tumors following standard post-operative therapy. ALCHEMIST-screening trial (NCT02194738) will screen about 6,000 to 8,000 participants over 5 to 6 years, with 400 patients enrolled per arm. The RTOG1306 is a phase II trial in EGFR-mutant or ALK-rearranged unresectable stage IIIA (pN2) or IIIB (pN3) NSCLC patients. The aim of the study is to asses whether induction therapy with erlotinib or crizotinib for 12 weeks prior to chemo-radiotherapy improves PFS compared to those treated with standard care therapy alone. Molecular screening is also tested across prospective trials in different malignancies. The MOSCATO trial (NCT01566019) includes metastatic solid tumors and the primary objective is to use high throughput molecular analysis (CGH Array and sequencing) to guide treatment of patients with targeted therapeutics in order to improve the PFS compared to the previous treatment line. IMPACT trial (Initiative for Molecular Profiling in Advanced Cancer Therapy Trial, NCT00851032), is an umbrella protocol in 5,000 patients with advanced malignancies. The goal is to correlate the molecular profile with response to phase I therapies. The NCI-MATCH trial (Molecular Analysis for Therapy CHoice) trial is an umbrella protocol for multiple single-arm, phase II trials. Biopsies from as many as 3,000 patients will be screened by next-generation DNA sequencing to identify 100 actionable mutations, with 1000 participants being enrolled (25% of whom will have rare cancers). Co-primary end-points are overall response rate and PFS rate at 6 months. Finally, for advanced and refractory cancer patients who do not have recognised genetic abnormalities WINTHER trial (NCT01856296) aims at selecting rational therapeutics based on the analysis of matched tumors and normal biopsies according to micro arrays and gene expression profiling results. The main objective is to compare the PFS of the current treatment versus the previously prescribed treatment. Models of personalized medicine implementation (no organized compared with organized framework) , optimal technology for molecular profile , and the optimal patients’ selection are some of challenges to be overcome in personalized medicine. Moreover, the actual model of personalized medicine does not take in account secondary events, which will be involved in cancer resistance. A major challenge in molecular medicine will be to target these secondary events early enough, in order to avoid treatment resistance . Intratumoral heterogeneity plays a critical role in tumor evolution. However, molecular characterization of the tumor is provided from a single biopsy and at single time point. Multiregional evaluations to determine geographical heterogeneity, and molecular characterization of different samples collected over space and time to ascertain clonal evolution are not routinely carried out . The prospective TRACERx trial (TRAcking non-small cell lung Cancer Evolution through therapy [Rx], NCT01888601) in NSCLC patients, aims to define the evolutionary trajectories of lung cancer in both space and time through multi-region and longitudinal tumor sampling and genetic analysis by following cancer from diagnosis to relapse. The study aims to recruit 842 patients . Incorporating an analysis of the tumor immune contexture is also a key challenge and need for the design of new precision medicine trials . In the near future most patients with metastatic tumors will receive targeted therapies or immune modualtors delineated by tumor genotyping and analysis of immune contexture and all of these trials will help to validate current biomarkers facilitating rapid access to innovative therapies.

Abstract:
Lung cancer and mesotheliomas belong to the most lethal human malignancies with poor prognosis. The majority of these tumors is associated with carcinogen exposure (smoking and asbestos). Small cell lung cancer (SCLC) and mesothelioma patients show very poor survival statistics due to their late detection, invasive and high metastatic potential, and chemo-resistance. Using the Rbf/f;p53f/f mouse model for SCLC, we found that the tumors are often composed of phenotypically different cells, characterized by mesenchymal and neuroendocrine markers. These cells often share a common origin. Crosstalk between these cells can endow the neuroendocrine component with metastatic capacity, illustrating the potential relevance of tumor cell heterogeneity in dictating functional tumor properties. Also specific genetic lesions appear to be associated with metastatic potential. We have studied the nature of this crosstalk and identified the components responsible for paracrine signaling and the downstream effector pathway critical for promoting metastatic spread. We have also evaluated the relevance of additional lesions that were frequently acquired in the mouse SCLC, such as amplification of Myc and Nfib. Therefore, we have derived ES cells from Rbf/f;p53f/f, equipped these cells with an exchange cassette in the ColA1 locus, and shuttled a conditional L-Myc and Nfib under a strong promoter into this locus. This accelerated tumorigenesis and resulted also in a shift in the metastatic phenotype. To investigate the cell-of-origin of thoracic tumors, we have inactivated a number of tumor suppressor/oncogene combinations (Trp53, Rb1, Nf2, Cdkn2ab-p19Arf, mutant Kras) in distinct cell types by targeting Cre-recombinase expression specifically to Clara cells, to neuroendocrine cells, alveolar type II cells and cells of the mesothelial lining (origin of malignant mesothelioma) using adenoviral or lentiviral vectors with Cre recombinase driven from specific promoters. Dependent on the induced lesions and the cell-type specific targeting, SCLC, NSCLC, or mesothelioma could be induced. We show that multiple cell types can give rise to these tumors but that the cell-of-origin is an important factor in determining tumor phenotype. Our data indicate that both cell type specific features and the nature of the oncogenic lesion(s) are critical factors in determining the tumor initiating capacity of lung (progenitor) cells. Furthermore, the cell-of-origin appears to influence the malignant properties of the resulting tumors. Sutherland, K., Song, J-Y., Kwon, M-C, Prooost and Berns A. (2014). Multiple cells-of-origin in K-RasG12D induced mous lung adenocarcinoma. Proc. Natl. Acad. SCi. USA, 111, 4952-4957. Kwon, M-C, and Berns, A. (2013) mouse models of Lung Cancer. Mol. Oncol. 7, 65-177. Sutherland, K.D., Proost, N., Brouns, I., Adriaensen, D., Song, J-Y., and Berns, A. (2011). Cell of Origin of Small Cell Lung Cancer: Inactivation of Trp53 and Rb1 in Distinct Cell Types of Adult Mouse Lung. Cancer Cell 19, 754-64. Calbo, J., van Montfort, E., Proost, N., van Drunen, E., Beverloo, H., Meuwissen, R., and Berns, A. (2011) A functional role for tumor cell heterogeneity in a mouse model of Small Cell Lung Cancer. Cancer Cell, 19, 244-56.

Background:
This abstract is under embargo until September 9, 2015 and will be distributed onsite on September 9 in a Late Breaking Abstract Supplement.

Methods:


Results:


Conclusion:

Abstract not provided

Background:
Adjuvant chemotherapy for resected early stage NSCLC provides modest survival benefit. Bevacizumab, a monoclonal antibody directed against vascular endothelial growth factor, improves outcomes when added to platinum-based chemotherapy in advanced stage non-squamous NSCLC. We conducted a phase 3 study to evaluate the addition of bevacizumab to adjuvant chemotherapy in early stage resected NSCLC. The primary endpoint was overall survival and secondary endpoints included disease-free survival and toxicity assessment.

Methods:
Patients with resected stage IB (>4 centimeters) to IIIA (AJCC 6th edition) NSCLC were enrolled within 6-12 weeks of surgery and stratified by chemotherapy regimen, stage, histology and sex. All patients were to receive adjuvant chemotherapy consisting of a planned 4 cycles of every 3 week cisplatin at 75 mg/m[2] with either vinorelbine, docetaxel, gemcitabine or pemetrexed. Patients were randomized 1:1 to arm A (chemotherapy alone) or arm B, adding bevacizumab at 15 mg/kg every 3 weeks starting with cycle 1 of chemotherapy and continuing for 1 year. Post-operative radiation therapy was not allowed. The study had 85% power to detect a 21% reduction in the overall survival (OS) hazard rate with a one-sided 0.025-level test.

Results:
From July 2007 to September 2013, 1501 patients were enrolled. Patients were 49.8% male, predominantly white (87.9%) with a median age of 61 years. Patients enrolled had tumors that were 26.2% stage IB, 43.8% stage II and 30.0% stage IIIA and 28.2% of patients had squamous cell histology. Chemotherapy options were utilized with the following distribution: vinorelbine 25.0%, docetaxel 22.9%, gemcitabine 18.9% and pemetrexed 33.2%. At a planned interim analysis, with 412 of 676 overall survival events needed for full information (60.9%), though the pre-planned futility boundary was not crossed, the Data Safety Monitoring Committee recommended releasing the trial results based on the conditional power of the logrank test. At the time of interim analysis, with a median follow-up time of 41 months, the OS hazard ratio comparing the bevacizumab containing arm (Arm B) to chemotherapy alone (Arm A) was 0.99 (95% CI: 0.81-1.21, p=0.93). The DFS hazard ratio was 0.98 (95% CI: 0.84-1.14, p=0.75). Completion of treatment per protocol was 80% on Arm A and 36% on Arm B. Statistically significantly increased grade 3-5 toxicities of note (all attributions) included: overall worst grade (67% versus 84%); hypertension (8% versus 30%), and neutropenia (33% versus 38%) on Arms A and B, respectively. There was no significant difference in grade 5 adverse events per arm with 16 (2%) on arm A and 19 (3%) on arm B.

Conclusion:
The addition of bevacizumab to adjuvant chemotherapy failed to improve survival for patients with surgically resected early stage NSCLC.

Abstract not provided

Background:
EGFR mutant (M+) NSCLC is an archetypical oncogene-driven solid tumor, typified by high response rates when treated with a tyrosine kinase inhibitor (TKI), and median progression free survival of 10 months, commonly due to emergence of T790M. The genomic architecture and spectra of EGFR M+ tumours may provide insights to mechanisms of treatment failure and has not been well described to date.

Methods:
Paired tumor-normal exome/ transcriptome sequencing and SNP array was performed on 30 tbiopsies from 25 patients with TKI resistance (TKI-R) as well as multiple regions (n=46) of 8 treatment naïve (TKI-N), never smoker East Asian EGFR M+ NSCLC (L858R, n=5; exon 19 del, n=2; exon 20 ins, n=1). Genomic alterations were validated with targeted re-sequencing at a mean depth of 2000x. Alterations were identified and annotated using established pipelines.

Results:
Exome sequencing of 46 sectors (4-11 sectors/tumor) from 8 resected NSCLC (Stage IA, n=5; Stage IB, n=3), revealed a median of 52.5 validated mutations (Range: 15-112) per tumor. Primary EGFR mutations (including exon 20 ins) were identified as truncal events in all cases, with the notable absence of T790M even at sequencing depths of 2000x. Private mutations comprised 10-33% of all mutations per tumor, and in some cases harbored potential drivers of subclonal diversity including p53, AKT1 and ATXN1. For the 30 TKI-R tumors (T790M+, n=16; T790M-, n=14), exome sequencing revealed a higher mutation burden (median 80 vs 49 in TKI-N), while SNP array and expression data confirmed ERBB2 and MET as common co-existing resistance mechanisms. We next inferred the relevance of alterations and their hierarchical order (trunk, T; branch, B; private, P). In a TKI-N tumor where 11 sectors were subject to exome-sequencing, 39 of 112 mutations were truncal events – with MAP3K19 and PTEN splice site mutations co-existing with EGFR L858R mutation. Strikingly, when comparing the transcriptomic profiles of TKI-N and TKI-R tumors, all 8 evaluated sectors in this tumor clustered together with the TKI-R signature, suggesting that truncal co-mutations can contribute to primary TKI resistance. Finally, we attempted to curate novel genes in the 46 TKI-N sectors that may be implicated in TKI resistance by identifying genes in common with those altered in TKI-R samples with allele frequency > 0.25. We shortlisted approximately 150 recurrent genes or putative drivers – 85% of which were either trunk or branch mutations including TP53 (T,P), PTEN (B), LRP1B (B), GPRIN3 (B), MAP3K19 (T), ARID3A (P) and MED12 (P).

Conclusion:
Multi-region sequencing of 8 never smoker EGFR M+ NSCLC revealed a low mutation burden, with a significant proportion of alterations occurring as trunk or branch events. The different activating EGFR mutations were ubiquitous truncal events and T790M was not found in ultra-deep sequencing across 46 sectors. Mutation hierarchy provides a basis for patterns of TKI treatment failure: with co-occurring truncal events (e.g. MAP3K19, PTEN) potentially contributing to primary resistance, and the low incidence of private subclonal drivers consistent with the relatively high prevalence of T790M mutation in the setting of secondary resistance.

Abstract not provided

Background:
The National Lung Screening Trial (NLST) has achieved a 7% reduction in mortality from any cause with low-dose computed tomography (LDCT) screening, as compared with the chest radiography arm. Other randomized trials are under way, comparing LDCT screening with no intervention in heavy smokers populations. None of these studies is designed to investigate the impact of smoking habits on screening outcome. In the present study, we have tested the effect of stopping smoking on the overall mortality of volunteers undergoing LDCT screening.

Methods:
Between 2000 and 2010, 3381 heavy smokers aged more than 50 years were enrolled in two LDCT screening programmes. Sixty-nine percent were males with median age of 58 years and median smoking exposure of 40 pack-years. Based on the last follow-up information, subjects were divided in two groups: current smokers throughout the screening period, and former smokers. The latter group included ex-smokers at the time of baseline screening (early quitters), and those who stopped smoking during the screening period (late quitters).The effect of smoking on mortality was adjusted according to the following covariates: gender, age, body-mass index (BMI), lung function (FEV1 %) and pack years at baseline.

Results:
With a median follow-up time of 9.7 years, and a total of 32,857 person/years (P/Y) follow-up, a total of 151 deaths were observed in the group of 1797 current smokers (17,846 P/Y) and 109 in 1584 former smokers (15,011 P/Y). As compared to current smokers, the Relative Risk (RR) of death of former smokers was 0.77 (95% CI, 0.60 to 0.99, p = 0.0416), corresponding to a 23% reduction of total mortality. Excluding 239 subjects who had stopped smoking from less than 2 years from the end-point of follow-up, RR was 0.64 (95% CI, 0.48 to 0.84, p = 0.0016), with a 36% mortality reduction. A similar risk reduction was observed in the subset of 476 late quitters (27 deaths, 4,777 P/Y), with a RR of 0.60 (95% CI, 0.40 to 0.91, p = 0.0158).

Conclusion:
Stopping smoking is associated with a significant reduction of the overall mortality of heavy smokers enrolled in LDCT screening programs. The benefit of stopping smoking appears to be 3 to 5-fold greater than the one achieved by earlier detection in the NLST trial.

Abstract not provided

Abstract not provided