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A. Nicholson
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SC18 - Precision Screening for Lung Cancer (ID 342)
- Event: WCLC 2016
- Type: Science Session
- Track: Radiology/Staging/Screening
- Presentations: 5
- Moderators:A. Nicholson, G. Ostoros
- Coordinates: 12/06/2016, 16:00 - 17:30, Lehar 1-2
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SC18.01 - Field Cancerization in the Airways and its Application to Lung Cancer Early Detection (ID 6671)
16:00 - 16:20 | Author(s): I. Wistuba
- Abstract
- Presentation
Abstract:
Molecular alterations that are characteristic of lung tumors have been shown to be present in normal-appearing airway epithelium adjacent to lung tumors suggestive of an airway field cancerization phenomenon (1, 2). These field effects include altered gene expression, loss of heterozygosity (LOH), gene mutation and methylation and microsatellite instability (3-7). Microarray studies have pointed to expression profiles that are dissimilar between airways in smokers with and without lung cancer (8, 9). It has been recently demonstrated gene expression profiles that are shared between normal-appearing airway cells and nearby NSCLCs and that can distinguish airways of smokers with lung cancer from those without the malignancy (8). Studies from several groups suggest that the field cancerization provides biological insights into non-small cell lung carcinoma (NSCLC) ad small cell lung carcinoma (SCLC) pathogenesis and clinical opportunities for lung cancer detection (6, 8). It is important to note that smoking perpetuates inflammation throughout the exposed airway epithelium (10). This effect is pronounced in patients with Chronic Obstructive Pulmonary Disease (COPD) (10). Notably, among smokers, even after smoking cessation, airway inflammation persists while the risk of lung cancer continues to increase (10). It is not known which tumor promoting profiles in the airway field cancerization may drive lung cancer development in COPD patients. Using microarray profiling, studies have pointed to expression profiles that are dissimilar between airways in smokers with lung cancer and airways in smokers without cancer (11-13). Importantly, these gene-expression changes within the “field of injury” have been leveraged for development and validation of a clinically-relevant biomarker that can improve the diagnostic performance of bronchoscopy for detection of lung cancer (predominantly NSCLC) among smokers with suspect disease (8, 12). In addition, gene expression array analysis pointed to airway field expression profiles that are spatially and temporally modulated in early stage patients following surgery and that may be associated with disease relapse (13). Further, we have recently demonstrated that there is significant enrichment in gene expression profiles measured in both small (adjacent to tumor) and large (mainstem bronchus) airway compartments of the airway field of injury, suggesting that gene-expression changes in the large airway can serve as a surrogate for the molecular changes occurring in the airway epithelium adjacent to the tumor (9). Taken together, studies from our group and others suggest that, by sampling “normal” and relatively accessible tissue (e.g., bronchial airway), the airway field of injury provides biological insights into the earliest phases in the development of lung malignancy and potential valuable clinical opportunities such as early detection (1, 2). Identifying molecular aberrations that precede cellular morphological changes will provide biological insights into why some smokers develop lung cancer and, thus, clinical opportunities for improved lung cancer detection. References: 1. Kadara H, Wistuba, II. Field cancerization in non-small cell lung cancer: implications in disease pathogenesis. Proceedings of the American Thoracic Society. 2012;9(2):38-42. 2. Steiling K, Ryan J, Brody JS, Spira A. The field of tissue injury in the lung and airway. Cancer Prev Res. 2008;1(6):396-403. 3. Belinsky SA, Nikula KJ, Palmisano WA, Michels R, Saccomanno G, Gabrielson E, Baylin SB, Herman JG. Aberrant methylation of p16(INK4a) is an early event in lung cancer and a potential biomarker for early diagnosis. Proc Natl Acad Sci U S A. 1998;95(20):11891-6. 4. Mao L, Lee JS, Kurie JM, Fan YH, Lippman SM, Lee JJ, Ro JY, Broxson A, Yu R, Morice RC, Kemp BL, Khuri FR, Walsh GL, Hittelman WN, Hong WK. Clonal genetic alterations in the lungs of current and former smokers. J Natl Cancer Inst. 1997;89(12):857-62. 5. Tang X, Shigematsu H, Bekele BN, Roth JA, Minna JD, Hong WK, Gazdar AF, Wistuba, II. EGFR tyrosine kinase domain mutations are detected in histologically normal respiratory epithelium in lung cancer patients. Cancer research. 2005;65(17):7568-72. 6. Wistuba, II, Behrens C, Milchgrub S, Bryant D, Hung J, Minna JD, Gazdar AF. Sequential molecular abnormalities are involved in the multistage development of squamous cell lung carcinoma. Oncogene. 1999;18(3):643-50. 7. Wistuba, II, Lam S, Behrens C, Virmani AK, Fong KM, LeRiche J, Samet JM, Srivastava S, Minna JD, Gazdar AF. Molecular damage in the bronchial epithelium of current and former smokers. J Natl Cancer Inst. 1997;89(18):1366-73. 8. Spira A, Beane JE, Shah V, Steiling K, Liu G, Schembri F, Gilman S, Dumas YM, Calner P, Sebastiani P, Sridhar S, Beamis J, Lamb C, Anderson T, Gerry N, Keane J, Lenburg ME, Brody JS. Airway epithelial gene expression in the diagnostic evaluation of smokers with suspect lung cancer. Nat Med. 2007;13(3):361-6. 9. Kadara H, Fujimoto J, Yoo SY, Maki Y, Gower AC, Kabbout M, Garcia MM, Chow CW, Chu Z, Mendoza G, Shen L, Kalhor N, Hong WK, Moran C, Wang J, Spira A, Coombes KR, Wistuba, II. Transcriptomic architecture of the adjacent airway field cancerization in non-small cell lung cancer. J Natl Cancer Inst. 2014;106(3):dju004. 10. Punturieri A, Szabo E, Croxton TL, Shapiro SD, Dubinett SM. Lung cancer and chronic obstructive pulmonary disease: needs and opportunities for integrated research. J Natl Cancer Inst. 2009;101(8):554-9. 11. Gustafson AM, Soldi R, Anderlind C, Scholand MB, Qian J, Zhang X, Cooper K, Walker D, McWilliams A, Liu G, Szabo E, Brody J, Massion PP, Lenburg ME, Lam S, Bild AH, Spira A. Airway PI3K pathway activation is an early and reversible event in lung cancer development. Sci Transl Med.2(26):26ra5. 12. Silvestri GA, Vachani A, Whitney D, Elashoff M, Porta Smith K, Ferguson JS, Parsons E, Mitra N, Brody J, Lenburg ME, Spira A, Team AS. A Bronchial Genomic Classifier for the Diagnostic Evaluation of Lung Cancer. N Engl J Med. 2015;373(3):243-51. 13. Kadara H, Shen L, Fujimoto J, Saintigny P, Chow CW, Lang W, Chu Z, Garcia M, Kabbout M, Fan YH, Behrens C, Liu DA, Mao L, Lee JJ, Gold KA, Wang J, Coombes KR, Kim ES, Hong WK, Wistuba, II. Characterizing the molecular spatial and temporal field of injury in early-stage smoker non-small cell lung cancer patients after definitive surgery by expression profiling. Cancer prevention research. 2013;6(1):8-17.
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SC18.02 - Integrating Lung Cancer Biomarkers into Future Screening Programs (ID 6672)
16:20 - 16:40 | Author(s): P.P. Massion
- Abstract
- Presentation
Abstract:
Low-dose computed tomography for high-risk individuals has for the first time demonstrated unequivocally that early detection save lives. The currently accepted screening strategy comes at the cost of a high rate of false positive findings while still missing a large percentage of the cases. Therefore, there is increasing interest in developing strategies to better estimate the risk of an individual to develop lung cancer, to increase the sensitivity of the screening process, to reduce screening costs and to reduce the numbers of individuals harmed by screening and follow-up interventions. New molecular biomarkers candidates show promise to improve lung cancer outcomes. This review discusses the current state of biomarker research in lung cancer screening with the primary focus on risk assessment. The rationale for developing biomarkers for the early detection of lung cancer is very strong and well established. It stems from the fact that, at the population level, the earlier we detect the disease, the better the outcome and the lower the health care cost. The impetus for biomarker development has grown stronger since the NLST trial demonstrated that early detection via chest CT screening reduced the relative risk for lung cancer death in the high risk individuals. Low dose chest CT in this group alone may save up to 12,000 lives a year, but it represents only about 8 % of individuals dying of this disease every year. Thus, much is to be done to capture these lung cancers that escape chest CT screening as currently recommended despite its high sensitivity and specificity. The reason for limited detection relates to how many at-risk individuals are studied with CT and to how we best define this risk. Detection and careful management of indeterminate pulmonary nodules are integral parts of this effort. Lung cancer screening using chest CT also raises many questions, some of which could be addressed with well poised biomarkers. For example, who is at utmost risk for lung cancer? How do we expand the screening criteria from the NLST without causing more harm than good? Once the CT screening studies are done, how do we approach a non-invasive diagnosis of lung cancer? How do we prevent the overdiagnosis bias? Here we focus on biomarkers that could be used in a risk assessment evaluation for screening programs. We will discuss current molecular biomarkers of risk assessment in those without measurable disease and before a chest CT has been done. Consideration of the use of such biomarkers should trigger a discussion with the patient before ordering it to address the intent of the test and the implications of the possible results. Many biomarkers have been developed over the years to predict tumor development. Let us consider the characteristics of such a biomarker to assess the risk of lung cancer. For screening purposes, given the low prevalence of disease, a strong negative predictive value (NPV) of a test is a very attractive feature. High specificity on the other hand is always desirable so we do not overcall cancers (false positive). Should such a test be positive, it would push individuals into a higher risk group to consider appropriate surveillance. The biomarker could measure a genetic risk (e.g. altered metabolism of carcinogens, DNA repair machinery abnormalities, predisposition to inflammation, or germline mutations) or the influence of the environment on tumor development (exposure to carcinogens or surrogates of risk such as epigenetic changes in the airway epithelium or the prevalence of preinvasive lesions). There has been recent interest in the potential for genetic variants to give insight into the pathogenesis of lung cancer. These variants indicate that there is great heterogeneity in mechanisms of disease development that is modulated by inherited genetic variation. With these come the opportunity to improve models predicting lung cancer risk. A larger question of timeliness of biomarker use in clinical practice will be discussed during the presentation. What are the risk and benefits of precision screening? Are current risk prediction models safe to use or robust to guarantee an advantage over current standard of care? There is a clear need to evaluate the benefit of risk assessment biomarkers with repeated measures over time. The assumption is that as risk increases, molecular moieties should be more readily available (e.g. in the circulation) over time. This may be true for tumor specific antigens and ctDNA, but would not apply to genetic risk. Statistical models could test the ability of different biomarkers to complement each other in a single population, in order to eventually determine those that could be tested prospectively. Given biomarkers' non-specificity and commonality in predicting diseases, modeling multiple markers of the same clinical diagnostic criteria can be used to develop more accurate individual and cumulative risk estimates for specific diseases. We should therefore consider a joint effects approach to determine individual biomarker associations as well as to ascertain the impact of simultaneous increases in multiple biomarker concentrations on the diagnosis of lung cancer. Biomarkers of risk would ideally be tested prospectively in a randomized clinical trial. However, given the relatively low prevalence of this disease, the number needed to screen may be prohibitive; therefore the development of registries is most appropriate. Registries are longitudinal cohort prospective studies where a biomarker is introduced but does not force providers to change their management. The lead time to diagnosis may be sufficient to cause a stage shift and therefore improve outcome. Finally, it is through better understanding of the biology of cancer development and of preinvasive lesions that we will shed further light into the field of biomarker research.
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SC18.03 - Lung Cancer Screening, COPD and Cardiovascular Diseases (ID 6673)
16:40 - 17:00 | Author(s): R. Huber
- Abstract
- Presentation
Abstract not provided
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SC18.04 - Exhaled Biomarker Fingerprints for Early Detection (ID 6674)
17:00 - 17:15 | Author(s): I. Horvath
- Abstract
- Presentation
Abstract not provided
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SC18.05 - UK Lung Screening Trial Cost Effectiveness and Current Planning Status of International Lung Cancer Screening Programs (ID 6675)
17:15 - 17:30 | Author(s): J.K. Field
- Abstract
- Presentation
Abstract:
The UKLS Trial and cost effectiveness The pilot UKLS lung cancer RCT screening trial recruited 4,000 individuals [1], using the LLP~v2~ risk model (5% risk over 5 years) [2]. The lessons learnt from the UKLS CT pilot screening trial are: UKLS – A Population based trial – all IMD’s (socioeconomic groups) included [1]. Risk Stratification (LLP~v2~ 5 % risk over 5 years) [2] Volumetric assessment of CT detected nodules [3]. Care Pathway – Management pathway implemented [3]. Early Stage Disease (Stage 1 68%: Stage I&II 86%) [4] High Proportion suitable for Surgery (83%) [4] 1.7% lung cancers identified at baseline scan [1] Benign Resection rate – 10.3% (NLST 27%)[1] Psychological impact – transient not significant [5, 6] Cost effectiveness modelling within NICE parameters [1] The cost effectiveness of the UKLS trial has been modelled and compared with that of the US National Lung Screening Trial (NLST), which has published an estimate of $81,000 per quality-adjusted life-year (QALY) as its mean incremental cost-effectiveness ratio (ICER) [7]. All UKLS cost estimates were based on 2011-12 NHS tariffs (Costs provided in $: £1=$1.5 on 30-11-15). Owing to the brief duration of the trial, observations relevant to economic evaluation were limited to cost-incurring events associated with screening and the initial management of screen-detected cancers. Expected outcomes of the cancers detected were simulated on the basis of both life tables and published survival data from other studies. The costs incurred from UKLS are those of baseline and repeat screens ($424,072), diagnostic workup ($113,478), and treatment ($449,243), which totaled $1,036794 (95% CI, $719,332 to $1,350,766). Recruitment costs ($15) per person for invitation and selection) were modelled from the UK colorectal screening programme and we assumed a participation rate of 30% of those invited. The gross current costs of the programme amounted to $1,133,217 (CI $817,887 to $1,450,610). Summary of findings: The ICER of screen-detection compared with symptomatic detection was estimated at $9495 per life-year gained. Using data from previous studies, we associated quality of life weights with the estimated survival gains, enabling us to report outcomes as QALYs. On this basis, the ICER equaled $12,709 per QALY gained (CI $ 8280 to $18966). The difference in cost effectiveness between NLST and UKLS as suggested by the estimated ICERs is more apparent than real. Most of the discrepancy can be explained by differences between settings in (i) local unit costs, (ii) intensity of resource use, (iii) number of screening rounds and (iv) disease prevalence in the target population. Thus, UKLS selected high-risk subjects only whereas NLST screened a general population, yet the latter reported an ICER as low as $32,000 for its highest-risk quintile. Expected QALY gains from screen-detection were similar in both trials. Figure 1
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Author of
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MA12 - Miscellaneous Biology/Pathology (ID 476)
- Event: WCLC 2016
- Type: Mini Oral Session
- Track: Biology/Pathology
- Presentations: 1
- Moderators:B. Dome, W.D. Travis
- Coordinates: 12/06/2016, 14:20 - 15:50, Schubert 1
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MA12.04 - Mitochondrial-Related Proteins, PGAM5 and FUNDC1, in COPD-Associated Non-Small Cell Lung Carcinoma (ID 5646)
14:44 - 14:50 | Author(s): A. Nicholson
- Abstract
- Presentation
Background:
Patients with COPD and/or emphysema have an increased risk of non-small cell lung cancer (NSCLC). COPD and lung cancer are both characterised by increased oxidative stress associated with mitochondrial dysfunction. We hypothesise that mitochondrial dysfunction is a driving mechanism for the increased risk of NSCLC in COPD. We determined whether there is dysregulated expression of mitochondrial-related proteins in NSCLC arising in COPD, and if so, their clinical significance.
Methods:
To determine the clinical relevance of mitochondrial related gene expression, we examined a database containing transcriptomic data of more than 1, 000 human NSCLC samples and with survival outcomes (https://precog.stanford.edu/). Immunohistochemistry for PGAM5 and FUNDC1 was performed on cancer and background (‘normal’) tissue from lung cancer resections from non-smokers, healthy smokers (without COPD) and COPD/ emphysema patients. Protein expression was assessed using a semi-quantitative immunohistochemical scoring system (H score). Specific gene expression was further correlated with outcome in dataset GSE 72194, containing transcriptomic data of NSCLC cases and patient survival.
Results:
25 mitochondrial-related genes were linked to survival in NSCLC. Of those 25, we chose to study further the expression of PGAM5 and FUNDC1, which are regulators of mitochondrial degradation (mitophagy). In background lung tissue, PGAM5 and FUNDC1, only expressed in alveolar macrophages, were most highly expressed in COPD (H score: 180 ± 58 and 23 ± 9, respectively) compared to healthy smokers (146 ± 58 and 20 ± 8) and non-smokers (68 ± 48 and 3.3 ± 1.4) (p<0.05). In cancerous tissue, only the malignant epithelial cells and associated macrophages, at the periphery of the cancer, expressed PGAM5 and FUNDC1. PGAM5 was also expressed in pre-neoplastic epithelium (squamous dysplasia and carcinoma in situ). There was no difference in expression across the 3 groups, although the macrophages, at the edge of cancer, from COPD patients tended to show higher expression of PGAM5 and FUNDC1, compared to those from the other groups. When the expression of PGAM5 was compared with that of 50 known macrophage transcriptomic signatures within NSCLC samples, there was a positive correlation between PGAM5 and 9 macrophage signatures (r= 0.27 - 0.44, p<0.05), with one a determinant of patient survival.
Conclusion:
PGAM5 expression in pre-neoplastic tissue and NSCLC, but not in normal epithelium, suggests it plays a role in the transformation of malignant epithelial cells. PGAM5 and FUNDC1 may contribute to the pathogenesis of both COPD and NSCLC, possibly through mitophagic processes.
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MTE11 - The Clinical Impact of the 2015 WHO Classification of Lung Tumors (Ticketed Session) (ID 305)
- Event: WCLC 2016
- Type: Meet the Expert Session (Ticketed Session)
- Track: Biology/Pathology
- Presentations: 1
- Moderators:
- Coordinates: 12/06/2016, 07:30 - 08:30, Schubert 2
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MTE11.01 - The Clinical Impact of the 2015 WHO Classification of Lung Tumors (ID 6558)
07:30 - 08:00 | Author(s): A. Nicholson
- Abstract
- Presentation
Abstract:
There are many important changes in the 2015 WHO classification of lung tumours, reflecting the numerous advances in tumour genetics and therapy over the past decade.[1] Many have been in the field of adenocarcinoma, with discontinuation of the term bronchioloalveolar carcinoma and the concept of stepwise progression accepted for adenocarcinoma.[1] Adenocarcinoma in situ (AIS) is a small (less than 3 cm in diameter), pure lepidic adenocarcinoma; minimally invasive adenocarcinoma (MIA) is also a small lepidic adenocarcinoma but has small invasive areas less than 5 mm across. As both entities have a very favorable outcome, with an expected 5-year survival rate of 100%, AIS and MIA are targets for reduction surgery, and are frequently detected by low-dose CT screening. High-resolution (HR)-CT demonstrates these tumours as a pure ground glass nodule (GGN) or a part-solid nodule (PSN), being closely correlated with their pathological features.[2] Therefore, AIS and MIA can be assessed by HR-CT. However, the size of the solid component in HR-CT images does not necessarily correspond to the extent of histological invasion, since features such as alveolar collapse and fibrosis are also included in the solid part demonstrated by HR-CT.[1] Although the new WHO classification defines the histological criteria for MIA invasion, the degree of inter-observer agreement regarding the histological definition of invasion in MIA has still not been fully studied, and a consensus trial will be needed in the near future. More advanced adenocarcinoma is subdivided into five categories: lepidic, papillary, acinar, solid and micropapillary. These subtypes are diagnosed according to the predominant component and the group comprising lepidic, papillary and acinar adenocarcinomas shows a better prognosis than those with solid and micropapillary patterns. Therefore the presence of solid and/or micropapillary adenocarcinoma should be reported, even if the predominant component is lepidic, papillary or acinar adenocarcinoma. These patterns also predict response to adjuvant chemotherapy,[3] and the above changes overall have also led new proposals for both clinical and pathologic staging in the 8[th] TNM revision in terms of multiple primary tumours and measurement of tumour invasive size.[4,5] For the other three major tumour types (large cell carcinoma (LCC), squamous cell carcinoma (SQCC) and neuroendocrine (NE) tumours), the classification has evolved from mainly morphological to a more biologically based system, which allows more appropriate decisions in relation to adjuvant therapy and better defined subgroups for studies into molecular characterisation and the search for potentially treatable targets. LCC is now restricted to resected tumours that lack clear morphologic and immunohistochemical differentiation, with reclassification of those that do to solid adenocarcinoma (TTF-1 positive) and non-keratinising SQCC (P40 and/or CK5/6 positive). This has already been shown to correlate with molecular data.[6] For SQCC, classification is simplified to keratinizing, nonkeratinizing and basaloid subtypes, with the non-keratinizing tumours ideally requiring immunohistochemical confirmation. Criteria for diagnosing NE tumours remain essentially unchanged but these tumours are now grouped in one category, with further subdivision into carcinoids, and large cell neuroendocrine carcinoma and small cell carcinoma. Molecular studies based on these definitions are already identifying interesting subgroups.[7] In relation to rarer entities, the definition of pleomorphic carcinomas is also being shown to have clinical relevance in terms of correlating with potential therapies, both in relation to specific molecular abnormalities (exon 14 skipping mutations)[8] and immunoodulatory therapy with high levels of PD-L1 expression.[9] Molecular characterisation is also increasingly important in the accurate diagnosis and potential treatment of other rare tumours, such as NUT-carcinoma and inflammatory myofibroblastic tumours (ALK and ROS1/RET gene rearrangements).[10] A classification system for small biopsies and cytology is provided for the first time, with emphasis on integration of molecular testing and usage of a limited panel of immunohistochemistry when needed (table 1). The presence of such a system for the first time provides a system for consistent classification of the majority (unresectable) of lung cancer cases, both in terms of clinical management, assignment to pathways for molecular and immunomodulatory characterisations, and for assessment of the results of clinical trials that have sometimes been confounded by inaccurate subgrouping. The book also emphasises how to obtain the greatest value from small sample via efficient usage and avoidance of inappropriate testing.[1] Table 1: Classification of non-small cell lung carcinoma in small biopsies and cytology specimens when there is no morphologic evidence of differentiation
REFERENCES 1. WHO Classification of Tumours of the Lung, Pleura, Thymus and Heart. Lyons, France.: International Agency for Research on Cancer (IARC); 2015. 2. Kakinuma R, Noguchi M, Ashizawa K, et al. Natural History of Pulmonary Subsolid Nodules: A Prospective Multicenter Study. J Thorac Oncol. Jul 2016;11(7):1012-1028. 3. Tsao MS, Marguet S, Le Teuff G, et al. Subtype Classification of Lung Adenocarcinoma Predicts Benefit From Adjuvant Chemotherapy in Patients Undergoing Complete Resection. J Clin Oncol. Oct 20 2015;33(30):3439-3446. 4. Detterbeck FC, Nicholson AG, Franklin WA, et al. The IASLC Lung Cancer Staging Project: Summary of Proposals for Revisions of the Classification of Lung Cancers with Multiple Pulmonary Sites of Involvement in the Forthcoming Eighth Edition of the TNM Classification. J Thorac Oncol. Feb 29 2016. 5. Travis WD, Asamura H, Bankier AA, et al. The IASLC Lung Cancer Staging Project: Proposals for Coding T Categories for Subsolid Nodules and Assessment of Tumor Size in Part-Solid Tumors in the Forthcoming Eighth Edition of the TNM Classification of Lung Cancer. J Thorac Oncol. Aug 2016;11(8):1204-1223. 6. Clinical Lung Cancer Genome P, Network Genomic M. A genomics-based classification of human lung tumors. Sci Transl Med. Oct 30 2013;5(209):209ra153. 7. Rekhtman N, Pietanza MC, Hellmann MD, et al. Next-Generation Sequencing of Pulmonary Large Cell Neuroendocrine Carcinoma Reveals Small Cell Carcinoma-like and Non-Small Cell Carcinoma-like Subsets. Clin Cancer Res. Jul 15 2016;22(14):3618-3629. 8. Schrock AB, Frampton GM, Suh J, et al. Characterization of 298 Patients with Lung Cancer Harboring MET Exon 14 Skipping Alterations. J Thorac Oncol. Sep 2016;11(9):1493-1502. 9. Chang YL, Yang CY, Lin MW, Wu CT, Yang PC. High co-expression of PD-L1 and HIF-1alpha correlates with tumour necrosis in pulmonary pleomorphic carcinoma. Eur J Cancer. Jun 2016;60:125-135. 10. Antonescu CR, Suurmeijer AJ, Zhang L, et al. Molecular characterization of inflammatory myofibroblastic tumors with frequent ALK and ROS1 gene fusions and rare novel RET rearrangement. Am J Surg Pathol. Jul 2015;39(7):957-967.2015 WHO Small Biopsy/Cytology Terminology Morphology/Stains 2015 WHO Classification in resection specimens Non-small cell carcinoma, favour adenocarcinoma using IHC Morphologic adenocarcinoma patterns (lepidic, acinar, papillary, micropapillary) not present, but supported by special stains (+TTF-1) Adenocarcinoma, solid pattern (may only be a component) Non-small cell carcinoma, favour squamous cell carcinoma using IHC Morphologic squamoid features (keratinization and/or clear intercellular bridging) not present, but supported by stains ( +p40) Squamous cell carcinoma, (non-keratinizing pattern may be just one component) Non-small cell carcinoma, not otherwise specified NSCLC-NOS using IHC No clear adenocarcinoma, squamous or neuroendocrine morphology or staining pattern (IHC or mucin stains). Large cell carcinoma
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P2.03b - Poster Session with Presenters Present (ID 465)
- Event: WCLC 2016
- Type: Poster Presenters Present
- Track: Advanced NSCLC
- Presentations: 1
- Moderators:
- Coordinates: 12/06/2016, 14:30 - 15:45, Hall B (Poster Area)
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P2.03b-086 - High Expression of PDL-1 Correlates with Pleomorphic Features in Non-Small Cell Lung Carcinomas (ID 5761)
14:30 - 14:30 | Author(s): A. Nicholson
- Abstract
Background:
With immunomodulatory therapy being integrated into treatment regimes for non-small cell carcinoma (NSCLC), we have reviewed our initial experience within the UK in relation to potential access to treatment with pembrolizumab, in order to assess correlation between tumour morphology and staining patterns.
Methods:
Immunohistochemistry for PD-L1 (IHC/PD-L1) was performed with the PD-L1 IHC 22C3 pharmDxTM assay (Dako) on cases being considered for treatment. The test was considered adequate when more than 100 tumour cells were seen microscopically. When adequate, PD-L1 staining was scored as 0%, <1%, ≥ 1-49% or ≥ 50% positive membrane staining within tumour cells only. PD-L1 staining was considered positive when the score was >50%. In initial cases, it was noticed that there was increased staining in cases with pleomorphic features, so a separate cohort of 9 resections of pleomorphic carcinomas was additionally assessed.
Results:
PD-L1 expression was assessed in 72 NSCLC test cases which comprised 19 lung resections, 31 lung biopsies, 11 lymph node biopsies (5 of which were TBNAs), 4 pleural/pericardial tissue (2 from effusions), and 7 other metastatic sites (cores). There were 52 ADC (8 of which were NSCLC-ADC on IHC and 3 of which were invasive mucinous ADC), 7 SQCC (2 of which were NSCLC-SQCC on IHC), one LCC, 2 NSCLC-NE and 4 NSCLC-NOS. 6 cases were inadequate. Of the 65 cases with adequate tissue, 9 cases had pleomorphic features. A score of >50% was found in 78% (7/9) of cases with pleomorphic features with the remainder being 1-49%, compared to 27% (15/56) in those without pleomorphic features (p<0.05) (1-49% = 22 ,<1% = 19). 8 of 9 (89%) additional resected pleomorphic carcinomas showed >50% positivity with one case showing 10% positive staining concentrated in the pleomorphic area.
Conclusion:
Initial data show a correlation between PD-L1 staining and pleomorphic features in non-small cell lung carcinomas. Assessment on cell blocks obtained from TBNAs and effusions also provide assessable material.
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P3.01 - Poster Session with Presenters Present (ID 469)
- Event: WCLC 2016
- Type: Poster Presenters Present
- Track: Biology/Pathology
- Presentations: 1
- Moderators:
- Coordinates: 12/07/2016, 14:30 - 15:45, Hall B (Poster Area)
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P3.01-021 - Reproducibility of Comprehensive Histologic Assessment and Refining Histologic Criteria in P Staging of Multiple Tumour Nodules (ID 5365)
14:30 - 14:30 | Author(s): A. Nicholson
- Abstract
Background:
Multiple tumor nodules (MTNs) are being encountered, with increasing frequency with the 8[th] TNM staging system recommending classification as separate primary lung cancers (SPLC) or intrapulmonary metastases (IM). Pathological staging requires assessment of morphological features, with criteria of Martini and Melamed supplanted by comprehensive histologic assessment of tumour type, predominant pattern, other histologic patterns and cytologic features. With publication of the 2015 WHO classification of lung tumours, we assessed the reproducibility of comprehensive histologic assessment and also sought to identify the most useful histological features.
Methods:
We conducted an online survey in which pathologists reviewed a sequential cohort of resected multifocal tumours to determine whether they were SPLC, IM, or a combination. Specific histological features for each nodule were entered into the database by the observing pathologist (tumour type, predominant adenocarcinoma pattern, and histological features including presence of lepidic growth, intra-alveolar cell clusters, cell size, mitotic rate, nuclear pleomorphism, nucleolar size and pleomorphism, nuclear inclusions, necrosis pattern, vascular invasion, mucin content, keratinization, clear cell change, cytoplasmic granules¸ lymphocytosis, macrophage response, acute inflammation and emperipolesis). Results were statistically analyzed for concordance with submitting diagnosis (gold standard) and among pathologists. Consistency of each feature was correlated with final determination of SPLC vs. IM status (p staging) by chi square analysis and Fisher exact test.
Results:
Seventeen pathologists evaluated 126 tumors from 48 patients. Kappa score on overall assessment of primary v. metastatic status was 0.60. There was good agreement as measured by Cohen’s Kappa (0.64, p<0.0001) between WHO histological patterns in individual cases with SPLC or IM status but proportions for histology and SPT or IM status were not identical (McNemar's test, p<0.0001) and additional histological features were assessed. There was marked variation in p values among the specific histological features. The strongest correlations (<0.05) between p staging status and histological features were with nuclear pleomorphism, cell size, acinus formation, nucleolar size, mitotic rate, nuclear inclusions, intra-alveolar clusters and necrosis pattern. Correlation between lymphocytosis, mucin content, lepidic growth, vascular invasion, macrophage response, clear cell change, acute inflammation keratinization and emperipolesis did not reach a p value of 0.05.
Conclusion:
Comprehensive histologic assessment shows good reproducibility between practicing lung pathologists. In addition to main tumour type and predominant patterns, nuclear pleomorphism, cell size, acinus formation, nucleolar size, and mitotic rate appear to be useful in distinguishing between SPLC and IM.
