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John Kirkpatrick Field



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    MA06 - PDL1, TMB and DNA Repair (ID 903)

    • Event: WCLC 2018
    • Type: Mini Oral Abstract Session
    • Track: Biology
    • Presentations: 1
    • Now Available
    • Moderators:
    • Coordinates: 9/24/2018, 13:30 - 15:00, Room 206 AC
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      MA06.10 - Germline Mutation in ATM Affect Lung Cancer Risk with High Effect (Now Available) (ID 12792)

      14:35 - 14:40  |  Author(s): John Kirkpatrick Field

      • Abstract
      • Presentation
      • Slides

      Background

      Genome wide association studies have identified several lung cancer susceptibility regions and common variants influencing lung cancer risk. However, few previous studies investigated the association between germline mutations and lung cancer risk.

      Method

      We analyzed data from a case-control study with 19053 lung cancer cases and 15446 healthy controls of European ancestry in a discovery phase and performed a validation analysis using a case-control study comprising 4261 lung cancer cases and 4152 healthy controls of European ancestry for replication. Logistic regression was used to identify germline mutations with high effect within exome regions associated with lung cancer risk.

      Result

      We found rs56009889 in ATM was statistically associated with lung cancer risk in the discovery set (OR = 3.05, P = 3.68 × 10−8) and was nonsignificantly associated with lung cancer risk in the validation set (OR = 1.83, P = 0.16). Stratified analyses by gender with adjustment for age and smoking status showed that females carrying at least one mutated allele of rs56009889 (T/C + T/T) had an increased risk of lung cancer with ORs being 7.77 (95% CI 3.45 - 17.47) in discovery and 6.73 (95% CI 1.46–30.98) in replication, compared to C/C homozygotes among females. Individuals carrying at least one T allele showed a significant 6.9-fold increased risk for lung adenocarcinoma in discovery (adjusted OR = 6.85; 95% CI 4.37 – 10.75) and approximately a 4.9-fold increased risk in replication (adjusted OR = 4.89; 95% CI 2.01 – 11.91). Never smokers with combined genotypes (T/C + T/T) had a greater than 8-fold increased risk of lung cancer in discovery (adjusted OR = 8.03, 95% CI 4.00 – 16.13), while smokers only showed a 2.13-fold increased risk (adjusted OR = 2.13, 95% CI 1.25 – 3.65). In replication, however, the risks from this variant were comparable between smokers and nonsmokers, although the sample size is small for nonsmokers (adjusted OR = 2.16; 95% CI 0.48 – 9.79 for never-smokers and adjusted OR = 2.07; 95% CI 0.66 – 6.52 for smokers). All the T/T homozygotes of rs56009889 developed lung adenocarcinoma in discovery (P = 0.036). The association exhibited a dose-response relationship between the number of T allele of rs56009889 and lung cancer risk in discovery (Ptrend = 1.07 x 10 -9).

      Conclusion

      rs56009889 highly affected the risk of lung cancer, mainly of lung adenocarcinoma, primarily in women and never smokers. These germline mutations provide important insights for the prevention of lung cancer.

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    MS29 - Selection into Screening Programs: Interplay of Risk Algorithms, Genetic Markers and Biomarkers (ID 807)

    • Event: WCLC 2018
    • Type: Mini Symposium
    • Track: Screening and Early Detection
    • Presentations: 1
    • Now Available
    • Moderators:
    • Coordinates: 9/26/2018, 13:30 - 15:00, Room 206 F
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      MS29.03 - Polygenic Risk Score for Risk Assessment (Now Available) (ID 11527)

      14:05 - 14:20  |  Author(s): John Kirkpatrick Field

      • Abstract
      • Presentation
      • Slides

      Abstract

      Background: Genome-wide association studies uncovered multiple lung cancer susceptibility genes, and consortium efforts greatly increased our ability to investigate the genetic architecture of histological subtypes. However the clinical utility of these genomic discoveries remains unclear. Method: We therefore constructed a risk prediction model with polygenic risk score (PRS) based on 18,316 lung cancer patients and 14,025 controls with European ancestry, via 10-fold cross-validation with elastic net penalized regression. Model calibration was assessed, and was validated with UK biobank data (N=336,911 unrelated participants with European ancestry). To evaluate its potential clinical utility, the PRS distribution was simulated in the National Lung Screening Trial (NLST, N=50,772 participants). Absolute risk was estimated based on age-specific lung cancer incidence and all-cause mortality as competing risk. Added value of PRS to the risk prediction model was assessed by Net Reclassification Index. Results: A PRS was constructed based on 128 independent lung cancer variants using regularized penalized regression. The lung cancer ORs for individuals at the bottom 5% and top 5% of the PRS distribution were 0.49 (95%CI=0.43-0.56, P=2.7e-26) and 2.23 (95%CI=1.93-2.58, P=2.3e-27) in the training set, and 0.46 (95%CI=0.34-0.64, P=2.50e-6) and 1.33 (95%CI=1.08-1.64, P=7.10e-3) in the testing set, versus those at 40 to 60% as the referent group. The OR per standard deviation of PRS was 1.43 (95%CI=1.39-1.47. P=7.8e-138) for overall lung cancer risk in the training set and 1.24 (95%CI=1.18-1.30, P=2.59-e19) in the testing set. When considering age as the time scale, PRS separated out the curve of 5-year absolute risk and cumulative risk. When simulating the PRS distribution in the NLST population, we estimated 47.4% of cases occurred in the top 20% of the individuals with highest lifetime cumulative risk. Discussion: Including well-established genomic information in the risk model can contribute to the risk stratification of the population.

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    P1.04 - Immunooncology (Not CME Accredited Session) (ID 936)

    • Event: WCLC 2018
    • Type: Poster Viewing in the Exhibit Hall
    • Track:
    • Presentations: 1
    • Moderators:
    • Coordinates: 9/24/2018, 16:45 - 18:00, Exhibit Hall
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      P1.04-24 - Digital Core Needle-Biopsy to Assess PD-L1 Expression in Non-Small Cell Lung Cancer: Optimal Sampling and Need for Re-Biopsy (ID 12059)

      16:45 - 18:00  |  Author(s): John Kirkpatrick Field

      • Abstract
      • Slides

      Background

      Assessing expression of PD-L1 on tumour cell membranes by immunochemistry is an important complementary or crucial companion diagnostic test to guide the use of immune modulating checkpoint inhibitors in the treatment of non-small cell lung cancer (NSCLC). Unfortunately, the known temporal and spatial heterogeneity of PD-L1 expression raises the important question of how to ensure that the small biopsy specimens with which this assessment is usually made are adequately representative of PD-L1 expression by the whole tumour.

      Method

      Expression of PD-L1 was assessed in sections of 94 tissue blocks from 50 primary pulmonary adenocarcinomas using the Ventana SP263 antibody and a validated protocol. Scoring was performed by two appropriately-trained pathologists with extensive experience in its interpretation. After conventional assessment, slides were digitally scanned and divided into squares of 1mm² area to form a digital database (mean of 150 data-points per tumour), which were assigned co-ordinates and re-scored. By these means, multiple, “digital core biopsies” (DCBx) approximating a 17 gauge needle were simulated in sequential fashion, and expression in these was compared to that in the whole tumour and categorised by current UK prescribing guidelines*

      Result

      PD-L1 score (%)

      Total number of cases

      Cases where PD-L1% from single DCBx changed scoring category vs whole tumour*

      Cases where PD-L1% from two DCBx changed scoring category vs whole tumour*

      Cases where PD-L1% from three DCBx changed scoring category vs whole tumour*

      Cases where PD-L1% from four DCBx changed scoring category vs whole tumour*

      Cases where PD-L1% from five DCBx changed scoring category vs whole tumour*

      Focal expression primary pattern in non-correlative cases

      <1

      14

      2

      2

      2

      2

      2

      Y

      1-10

      13

      6

      3

      1

      1

      0

      Y

      11-49

      10

      1

      1

      0

      0

      0

      Y

      50-100

      13

      0

      0

      0

      0

      0

      n/a

      All

      50

      9 (18%)

      6 (12%)

      3 (6%)

      3 (6%)

      2 (4%)

      PD-L1, programmed death ligand 1; DCBx, Digital Core Biopsy

      *Based on pembrolizumab categories as: 1st line ≥50%, 2nd line 1-49%; nivolumab categories as: ≥1% (for adenocarcinoma)

      Conclusion

      In the majority of cases, three digital core biopsies achieved closest correlation with the whole tumour, with little greater accuracy achieved by assessing four cores or more. Correlation was weakest when expression was low and very focal, an important consideration in view of the importance of the ‘1% cut-off’ used commonly to guide immune checkpoint therapy. Using this model as a guide, a single good quality biopsy (2x10mm² area) is sufficient for most tumours scoring 11% or greater PD-L1 expression. However, in the lower range of expression, re-biopsy might be routinely considered if there is doubt about specimen adequacy.

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    P2.09 - Pathology (Not CME Accredited Session) (ID 958)

    • Event: WCLC 2018
    • Type: Poster Viewing in the Exhibit Hall
    • Track:
    • Presentations: 1
    • Moderators:
    • Coordinates: 9/25/2018, 16:45 - 18:00, Exhibit Hall
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      P2.09-19 - Utilising Heterogeneity: Using a Digital Database of Lung Cancers and Immune Profile to Complement Subjective Assessment (ID 12594)

      16:45 - 18:00  |  Author(s): John Kirkpatrick Field

      • Abstract
      • Slides

      Background

      Traditional pathological assessment of tissue sections involves subjective analysis of complex and heterogeneous features, typified by the challenge of ‘measuring’ PD-L1 expression in non-small cell lung cancer (NSCLC) as a guide to its treatment with immune checkpoint inhibitors. Such heterogeneity is generally perceived as a problem but might, in fact, reflect not only biologically important epitope variation, but also important features of the tumour microenvironment and, by extension, be a tool for predicting behaviour. In-depth analysis of a single slide of a tumour by digital pathology, image analysis and machine learning makes more accurate and meaningful analysis a possibility.

      Method

      Expression of PD-L1 was assessed by immunochemistry in 250 sections from 137 resected NSCLCs using the Ventana SP263 antibody and a validated protocol and its distribution compared with morphology as revealed by corresponding H&E-stained sections. Slides were scanned to create a digital image using Aperio Scanscope with division of images into 1mm² squares using QuPath opensource software, each of which was assigned x and y co-ordinates. Squares were assessed subjectively by two pathologists for morphological features and PD-L1 expression and also subject to automatic image analysis including cell counting and membrane detection. Co-ordinates and values were stored in Microsoft Excel and a digital database was generated for every slide. In-depth analysis of digital data points was achieved using “R” software custom algorithms that included simulating biopsy sampling and applying spatial analysis packages.

      Result

      The resulting database, comprising approximately 30,000 data points from the 137 tumours, is being used to simulate needle-core biopsies, assess heterogeneity of PD-L1 expression and relate this to the tumour micro-environment including immune cell populations, immune signature and tumour mutational burden.

      Conclusion

      The vast amount of information in every NSCLC cannot be extracted by conventional histopathological analysis. By utilising new technologies and considering alternative paradigms for data acquisition, powerful new approaches may be developed that give information pertaining to not just diagnostic and prognostic features of a tumour, but behavioural traits including likely responses and resistances to novel drugs such as immune checkpoint inhibitors. The methodology described here is an attempt to extract these data in a more objective way and complement the still crucial subjective analysis that is traditionally the prerogative of the histopathologist.

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    P3.11 - Screening and Early Detection (Not CME Accredited Session) (ID 977)

    • Event: WCLC 2018
    • Type: Poster Viewing in the Exhibit Hall
    • Track:
    • Presentations: 1
    • Now Available
    • Moderators:
    • Coordinates: 9/26/2018, 12:00 - 13:30, Exhibit Hall
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      P3.11-13 - Liverpool Identifies the Hard to Reach Population at Risk of Developing Lung Cancer. (Now Available) (ID 13173)

      12:00 - 13:30  |  Author(s): John Kirkpatrick Field

      • Abstract
      • Slides

      Background

      The Liverpool Healthy Lung Programme (LHLP) is an initiative aimed at improving respiratory health and diagnosing respiratory disease at a more treatable stage, taken by the Liverpool Clinical Commissioning Group (CCG) working with communities across Liverpool. Liverpool has one of the highest respiratory morbidity rates in England, with double the national lung cancer incidence, particularly in lower socioeconomic groups. The Liverpool Healthy Lung Programme was initiated in response to both the clinical problem and the health inequality.

      Method

      General practice records targeted ever-smokers and subjects with chronic obstructive pulmonary disease (COPD), 58-70y and were invited for 45-minute lung health check. Positive lifestyle messages were promoted; 5-year personal lung cancer risk calculated (www.MyLungRisk.org using LLPv2 risk model). Those who trigger the 5% threshold were offered a LDCT-scan. Spirometry was used to assess lung function (FEV1/FVC); those with abnormal results referred for potentially definitive diagnosis of COPD. Smoking advice and referrals to smoking cessation clinics were provided. Patients CT detected nodules were managed, based on BTS guidelines; referred to MDT for work-up and significant other findings (SoF) were analysed in detail.

      Result

      3,591 Healthy Lung Programme consultations (consented). 11,526 people were invited, 4,566 (40%) attended. 1,853 (52%) were male, 2,897 (81%) in the most deprived IMD quintile. 832 (23%) subjects had an existing diagnosis of COPD and 527 (15%) had a previous diagnosis of cancer. 1,173 (33%) subjects had a family history of cancer.

      1,548 (99.3% meeting LLPv2 5% risk criterion) were offered CT scan. 119 (9%) patients required further investigations (follow-up CT scan at 3 or 12 months, or immediate MDT referral), 25 (1.9% undergoing CT scan) were diagnosed with lung cancer (11 have suspected lung cancer, undergoing further investigations). Analysis of a sub-set of the SoF findings were followed up and indicated benefit to participants.

      Conclusion

      The results suggest that it is feasible to achieve similar clinical outcome benefits to those observed in the US trial of LDCT screening for lung cancer, with lesser harms in terms of unnecessary diagnostic activity. However, this needs confirmation with extended follow-up, larger numbers of lung cancers diagnosed, and the addition of mortality data. Additional randomised trial results would also add to the precision of estimation of benefits and harms, in particular mortality results from the large European trial, NELSON. In the meantime, the results of LHLP suggest that it is succeeding in early detection of both COPD and lung cancer.

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    PL02 - Presidential Symposium - Top 5 Abstracts (ID 850)

    • Event: WCLC 2018
    • Type: Plenary Session
    • Track: Advanced NSCLC
    • Presentations: 1
    • Now Available
    • Moderators:
    • Coordinates: 9/25/2018, 08:15 - 09:45, Plenary Hall
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      PL02.06 - Discussant - PL02.05 (Now Available) (ID 14738)

      08:55 - 09:00  |  Presenting Author(s): John Kirkpatrick Field

      • Abstract
      • Presentation
      • Slides

      Abstract not provided

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    S01 - IASLC CT Screening Symposium: Forefront Advances in Lung Cancer Screening (Ticketed Session) (ID 853)

    • Event: WCLC 2018
    • Type: Symposium
    • Track: Screening and Early Detection
    • Presentations: 1
    • Now Available
    • Moderators:
    • Coordinates: 9/23/2018, 07:00 - 12:00, Room 203 BD
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      S01.18 - IASLC Leads the International Collaboration on Data Sharing (IASLC- ELIC-CCTRR) (Now Available) (ID 11899)

      11:30 - 11:50  |  Presenting Author(s): John Kirkpatrick Field

      • Abstract
      • Presentation
      • Slides

      Abstract

      The IASLC ELIC-CCTR vision is to create a globally-accessible, privacy-secured environment to enable the analysis and study of extremely large collections of quality-controlled internationally assembled CT lung cancer images and associated biomedical data for research and healthcare delivery. This initiative will rapidly accelerate improvements to the multi-disciplinary management of early curable, lung cancer and other major thoracic diseases. This new research environment will be deployed and used to conduct global studies within the first two years of this project and is designed to one day scale to enabling coherent analysis across millions of cases.

      The current problem is that the implementation and advancement of lung cancer low dose CT screening (LDCT) screening requires large and high-quality collections of data obtained from global populations with currently deployed scanning equipment 1-5. Furthermore, there are new opportunities to develop deep learning methods for lung cancer imaging, which requires large quality-controlled datasets. As a community we have to very aware of the privacy challenges around data sharing. Lack of high quality data has been a barrier to LDCT screening progress.

      The way forward has been developed at the recent IASLC Confederation of CT Screened Patients Registry & Resource (CCTRR) Roundtable Workshop, as outlined in figure 1.

      figure 1.jpg

      IASLC will develop and run a new international collaborative (the ELIC framework) building on the processes established in the successful TNM Staging project. An internationally-federated Hub and Spoke system will be deployed to permit analysis of CT images and associated data in a secure environment, without any requirement to reveal data itself (i.e. privacy-protecting). No identifiable data ever leaves sources under local governance (PI) control. Existing imaging collections remain in the geographic regions where they were collected, so the resulting environment remains consistent with local regulations without privacy or data disclosure risk. In addition to connecting the world’s largest lung cancer screening registries, which is necessary for exploiting advanced computing capabilities with trustworthy security, enabling the rapid ramp up and participation of new global screening groups.

      The structure will provide the ability to interrogate large, high-quality, and internationally sourced image data sets will allow the lung cancer screening community to identify key insights, publish studies, and make lung cancer recommendations based on potentially millions of screening participants. By validating and distributing common data standards for CT imaging as well as for additional clinical follow-up information, the framework can be applied to the collaborative study of related intrathoracic disease processes.

      1. Henschke CI, McCauley DI, Yankelevitz DF, et al. Early Lung Cancer Action Project: overall design and findings from baseline screening. Lancet 1999; 354(9173): 99-105.

      2. National Lung Screening Trial Research T, Aberle DR, Adams AM, et al. Reduced lung-cancer mortality with low-dose computed tomographic screening. N Engl J Med 2011; 365(5): 395-409.

      3. van Klaveren RJ, Oudkerk M, Prokop M, et al. Management of lung nodules detected by volume CT scanning. N Engl J Med 2009; 361(23): 2221-9.

      4. Tammemagi MC, Schmidt H, Martel S, et al. Participant selection for lung cancer screening by risk modelling (the Pan-Canadian Early Detection of Lung Cancer [PanCan] study): a single-arm, prospective study. Lancet Oncol 2017; 18(11): 1523-31.

      5. Field JK, Duffy SW, Baldwin DR, et al. The UK Lung Cancer Screening Trial: a pilot randomised controlled trial of low-dose computed tomography screening for the early detection of lung cancer. Health Technol Assess 2016; 20(40): 1-146.

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